[{"id":1266,"title":"Study Sphere - Where Knowledge Meets Collaboration","prob":"In today\u2019s academic landscape, students struggle to prepare effectively for exams due to fragmented study resources, lack of personalized learning tools, and limited opportunities for real-time collaboration. Traditional platforms do not integrate dynamic content creation with advanced AI capabilities, leaving learners with static, isolated materials. Study Sphere addresses these challenges by unifying community-driven learning with AI-powered functionalities, enabling efficient note sharing, intelligent content generation, and interactive peer collaboration that collectively enhance academic outcomes.","description":"StudySphere is an Android-based mobile application that merges advanced AI techniques with a collaborative learning ecosystem. The platform allows users to upload, share, and organize study materials while engaging in discussion forums and real-time chats. Its AI modules\u2014designed for text summarization, quiz generation, and context-aware Q&A\u2014dynamically convert user content into effective study aids. Additionally, personalized study groups, gamified learning features, and comprehensive analytics foster an interactive, data-driven study environment, ultimately streamlining exam preparation and improving performance.$$\n1.\tAccess Guard (User Profile & Authentication Module):\r\no\tEnsures secure access to Study Sphere by managing user identities through robust account creation, login\/logout, and profile management using Firebase Authentication.\r\no\tIncorporates privacy controls that allow users to determine which content may be used for AI processing.\r\n2.\tStudy Connect (Discussion Threads & Group Chat Module):\r\no\tProvides a dynamic forum-style platform for users to pose questions and share ideas in structured discussions.\r\no\tFacilitates real-time group chats with file-sharing capabilities and supports the creation of both public and private study groups.\r\n3.\tKnowledge Vault (Notes Sharing Module):\r\no\tEnables users to upload, share, and download study materials in various formats such as PDFs and images.\r\no\tImplements tagging and categorization for efficient search and quick access to specific study notes.\r\n4.\tInsight Track (Study Insights & Progress Tracker Module):\r\no\tMonitors and logs user activities (e.g., time spent on summaries and quizzes) and generates visual progress reports with charts.\r\no\tProvides data-driven insights to help users identify their strengths and areas for improvement.\r\n5.\tAdmin Sphere (User Management Module):\r\no\tEmpowers administrators to view and manage user data, monitor activity logs, and control permissions such as role assignments and account status.\r\no\tFacilitates actions like suspending or deleting accounts, thereby ensuring a secure and well-moderated platform.\r\n6.\tSmart Digest (AI-Powered Summarization Module):\r\no\tProcesses uploaded textual content using advanced NLP models to generate concise and context-aware summaries.\r\no\tOffers customization options, allowing users to select between brief, medium, or detailed summaries based on their needs.\r\n7.\tAuto Quiz (Quiz Generator Module):\r\no\tAutomatically analyses study materials to generate diverse quiz formats, including multiple-choice, True\/False, and fill-in-the-blank questions.\r\no\tEnsures contextual relevance and adjusts the difficulty level based on user performance metrics.\r\n8.\tLearn Quest (Gamified Learning Module):\r\no\tIncentivizes learning by rewarding users with points, badges for engaging in activities such as sharing notes, creating quizzes, and participating in discussions.\r\no\tActively promotes consistent participation and fosters a motivational environment through gamification.\r\n9.\tAsk Edu (Q&A Module):\r\no\tAllows users to interactively ask questions based on uploaded text or images, leveraging a Retrieval-Augmented Generation (RAG) framework for accurate, context-aware responses.\r\no\tSupports follow-up inquiries and clarifications to enhance learning.\r\n10.\tUser Echo (Feedback Module):\r\no\tProvides a mechanism for users to rate and review platform features, content, and overall experience through surveys, polls, and a suggestion box.\r\no\tEnables administrators to review feedback and implement improvements, ensuring continuous refinement of the platform.$$\nIn Study Sphere I shall develop following modules: \r\n\r\n(i) Access Guard (User Profile & Authentication Module)\r\n(ii) Study Connect (Discussion Threads & Group Chat Module)\r\n(iii) Knowledge Vault (Notes Sharing Module)\r\n(iv) Insight Track (Study Insights & Progress Tracker Module)\r\n(v) Admin Sphere (User Management Module)$$\nIn Study Sphere I shall develop following modules: \r\n(i) Smart Digest (AI-Powered Summarization Module)\r\n(ii) Auto Quiz (Quiz Generator Module)\r\n(iii) Learn Quest (Gamified Learning Module)\r\n(iv) Ask Edu (Q&A Module)\r\n(v) User Echo (Feedback Module)$$\n$$\n(i) Educational Hub\r\n(ii) AI-Based Intelligent Learning System for CS$$\n1.\tIntegration of AI-powered tools (SmartDigest, AutoQuiz, AskEdu) with collaborative features (KnowledgeVault, StudyConnect, AdminSphere).$$\n2.\tA collaborative platform enabling users to share notes, engage in real-time discussions, and join personalized study groups, fostering an interactive learning environment.$$\n3.\tA gamified learning experience (LearnQuest) that promotes engagement and productivity while providing actionable study insights.","user_id":69,"comments":" $$ Approved","isDraft":0,"status":4,"created_at":"2025-02-25 12:10:09","updated_at":"2025-12-11 13:46:51","isReviewDraft":0,"isInternalDraft":0,"isExternalDraft":0,"isAssign":1,"reviewedDate":"2025-03-10 10:58:14","markedDate":null,"academic_session_id":20,"deleted_at":null,"is_assign_internal_sev":1,"is_assign_internal_eight":1,"is_assign_external_eight":1,"is_evaluated_internal_7th":1,"is_evaluated_internal_8th":1,"is_evaluated_external_8th":null,"member_count":3,"allow_7th_evolution":1,"allow8thEvaluation":1,"external_examiner_id":208,"start_date_time":null,"team_id":186},{"id":1267,"title":"SoulSketch: Revolutionizing Psychological Tests with AI","prob":"The mental health sector often faces challenges in managing patient data, conducting\r\npsychological tests, and generating reports efficiently. Therapists and administrators need a\r\ncentralized platform to manage patient history, conduct tests like HTP (House-Tree-Person) and TAT\r\n(Thematic Apperception Test), and generate detailed reports. This project aims to solve these\r\nproblems by providing a user-friendly mobile application that allows therapists to conduct tests,\r\nmanage patient data, and generate reports, while administrators can oversee the entire system,\r\nincluding therapist details, test details, patient records, and blogs.","description":"The \"SoulSketch\" project is a mobile application designed to assist therapists in conducting\r\nand managing psychological tests. The app has two primary user roles: Admin and Therapist. The Admin will have complete access to manage therapists, tests, patients, reports, and blogs. Therapists will be able to conduct two specific psychological tests (HTP and TAT), manage patient, history, generate reports, create blogs, chatbot for therapist assistance and manage their profiles. Additionally, the app will incorporate a custom dataset to train models that assist in test analysis. The application aims to enhance efficiency in psychological test administration, ensure proper patient data management, and provide insightful test analysis through AI-powered models. Firebase will be used for authentication, database management, and storage, with optional backend support using Node.js and Express.$$\nIn SoulSketch app the modules are : Therapist Module: 1. Test Conducting:\r\no Purpose: Conduct psychological tests (HTP and TAT).\r\no Key Features: Provide drawing tools, capture responses, and store results.\r\n2. Patient History:\r\no Purpose: Manage and view patient history.\r\no Key Features: Access past test results and track progress.\r\n3.Report Generation:\r\no Purpose: Generate detailed reports based on test results.\r\no Key Features: Use AI-assisted analysis to generate reports.\r\n4. Blog Creation:\r\no Purpose: Allow therapists to share insights and knowledge.\r\no Key Features: Write, edit, and publish blogs.\r\n5. Profile Management:\r\no Purpose: Enable therapists to manage their personal information.\r\no Key Features: Update personal details, qualifications, and expertise\r\n6. Chatbot for Therapist Assistance:\r\no AI-powered chatbot to provide instant guidance and resources.\r\no Help with therapy techniques and best practices.\r\n\r\nAdmin Module:\r\n1. User Management:\r\no Purpose: Manage therapist and admin accounts.\r\no Key Features: Add, update, and delete therapist details.\r\n2. Test Management:\r\no Purpose: Manage psychological tests (HTP and TAT).\r\no Key Features: Update test parameters and test details.\r\n3. Patient Management:\r\no Purpose: Oversee patient records and history.\r\no Key Features: View patient details, test history, and reports.\r\n4. Report Management:\r\no Purpose: Manage and review reports generated by therapists.\r\no Key Features: Store, update, and analyze reports.\r\n5. Blog Management:\r\no Purpose: Manage mental health-related blogs.\r\no Key Features: Create, update, and delete blogs.\r\n\r\nDataset and Model Module\r\n1. Data Collection:\r\no Purpose: Gather and preprocess data for AI training.\r\no Key Features: Collect patient test responses (HTP and TAT) to build a dataset for\r\nmodel training.\r\n2. Data Preparation:\r\no Purpose: Clean, preprocess, and structure data for optimal model performance.\r\no Key Features: Normalize images, remove noise, annotate responses, and format\r\ndata for AI model input.\r\n3. Model Building:\r\no Purpose: Develop and train AI models for psychological test analysis.\r\no Key Features: Implement CNN-based architectures (ResNet, VGG, Inception, etc.) and transformer which includes ViT, CLIP, BLIP to analyze test drawings and responses.\r\n4. Model Evaluation:\r\no Purpose: Assess model performance using standard AI metrics.\r\no Key Features: Use accuracy, precision, recall, and F1-score to determine model\r\neffectiveness.\r\n5. Model Selection:\r\no Purpose: Choose the most suitable AI model based on evaluation metrics.\r\no Key Features: Compare multiple architectures and select the best-performing one\r\nfor deployment\r\n6. Model Deployment:\r\no Purpose: Integrate the selected AI model into the application for real-time analysis.\r\no Key Features: Deploy the model in Firebase or a cloud-based API to provide instant\r\npsychological test analysis$$\nIn SoulSketch, I shall develop Therapist and Model which includes: 1. Develop Therapist features, including test conducting, patient history, report generation, blog creation, and profile management.\r\n2. Implement Firebase integration for data storage and retrieval.\r\n3. Develop dataset collection, model evaluation, and optimal model selection\r\nfunctionalities.\r\n4. Compare various AI architectures for test analysis.$$\nIn SoulSketch, I shall develop Admin and Model which includes: 1. Develop Admin features, including therapist management, test management, patient management, report management, and blog management.\r\n2. Implement Firebase integration for data storage and retrieval.\r\n3. Develop dataset collection, model evaluation, and optimal model selection\r\nfunctionalities.\r\n4. Compare various AI architectures for test analysis$$\nIn SoulSketch, I shall develop Therapist which includes: 1. Develop Therapist features, including test conducting, patient history, report generation, blog creation, and profile management.\r\n2. Implement Firebase integration for data storage and retrieval.$$\n$$\n$$\n$$\n","user_id":76,"comments":" $$ Use the available data set. And add more tests. $$ Increase number of tests. Use existing datasets.","isDraft":0,"status":4,"created_at":"2025-02-25 12:28:13","updated_at":"2025-12-11 13:46:51","isReviewDraft":0,"isInternalDraft":0,"isExternalDraft":0,"isAssign":1,"reviewedDate":"2025-03-17 11:03:46","markedDate":null,"academic_session_id":20,"deleted_at":null,"is_assign_internal_sev":1,"is_assign_internal_eight":1,"is_assign_external_eight":1,"is_evaluated_internal_7th":1,"is_evaluated_internal_8th":1,"is_evaluated_external_8th":null,"member_count":3,"allow_7th_evolution":1,"allow8thEvaluation":0,"external_examiner_id":208,"start_date_time":null,"team_id":null},{"id":1272,"title":"AI-Powered Automated Resume Screening and Job Matching System with LLM Integration for Efficient Recruitment","prob":"This FYP solves the real-world problem of slow and inefficient hiring processes. In many companies, HR teams spend a lot of time on reading and analyzing resumes manually, which can lead to delays, human errors, and missed opportunities to find the best candidates. Sometimes, qualified candidates are overlooked because their skills are not matched properly with job requirements. \r\n\r\nThe AI-Powered Automated Resume Screener solves this by quickly analyzing resumes, identifying key skills, and matching candidates to suitable jobs using LLM integration. It reduces the time spent on manual screening, ensures accurate job matches, and highlights top candidates. The system also schedules interviews automatically and sends timely email notifications, saving time for both employers and job seekers. \r\n\r\nThis project makes the hiring process faster, smarter, and more efficient, helping companies find the right talent easily while improving the overall experience for candidates.","description":"AI-Powered Automated Resume Screening and Job Matching System with LLM Integration, is designed to make the hiring process faster and smarter. The system uses AI and Large Language Models (LLMs) to analyze resumes, match candidates to suitable jobs, schedule interviews, and send automated emails.\r\nThe process starts with user registration, where candidates create an account. After signing up, candidates can upload their resumes. The system then parses the resumes, extracting important details like skills, education, and work experience.\r\nNext, the LLM-powered profile analysis comes into action. The AI carefully reviews each resume, highlighting strengths and weaknesses based on job requirements. The job-candidate matching module compares candidate profiles with available job descriptions. Using LLMs, they ranked candidates according to how well they fit a particular role.\r\n\r\nAdmin dashboard provides a clear view of scheduled interviews and generates a report of selected candidates. The interview scheduling system automatically arranges interviews for top candidates, saving time for employers.\r\nTo keep candidates updated, the system sends automated email notifications for interview invitations. However it also sends an apology\/rejection email to users for future instructions & improvement. \r\nOverall, this system reduces the time and effort required in hiring by automating resume screening, job matching, and communication. It ensures that the right candidates are matched with the right jobs, making the hiring process smooth and efficient for both employers and job seekers.$$\n1\ufe0f\u20e3 User Registration & Dashboard \r\n Candidates can sign up, log in, and manage their profiles.\r\n2\ufe0f\u20e3 Resume Upload & Parsing\r\n Users can upload resumes & the system extracts key information for efficient parsing.\r\n3\ufe0f\u20e3 LLM-Powered Profile Analysis\r\n This module uses LLM models to analyze resumes. \r\n4\ufe0f\u20e3 Job-Candidate Matching\r\n The system compares candidate profiles with job descriptions. \r\n5\ufe0f\u20e3 Interactive Dashboards\r\n Allows admins to generate reports.\r\n Allow users to submit their resumes without any misinterpretation. \r\n6\ufe0f\u20e3 Interview Scheduling System\r\n Automatically schedules interviews for top candidates\r\n7\ufe0f\u20e3 Automated Email Notifications\r\n Sends personalized emails regarding interview invitations \r\n8\ufe0f\u20e3 Candidate Feedback\r\n Get the feedback from the users and give suggestions to rejected users.$$\n1\ufe0f\u20e3 Job-Candidate Matching\r\n LLM logic for job-candidate matching.\r\n2\ufe0f\u20e3 Interactive Dashboards (Admin & User)\r\n Admin panel development for report generation.\r\n3\ufe0f\u20e3 Interview Scheduling System\r\n Use Libraries for auto-scheduling interviews.\r\n4\ufe0f\u20e3 Automated Email Notifications\r\n Send email to notify users for their interview invitations.$$\n1\ufe0f\u20e3 User Registration & Dashboard\r\n Candidates can sign up, log in, and manage their profiles.\r\n2\ufe0f\u20e3 Resume Upload & Parsing\r\n Users can upload resumes & the system extracts key information for efficient parsing.\r\n3\ufe0f\u20e3 LLM-Powered Profile Analysis\r\n This module uses LLM models to analyze resumes. \r\n4\ufe0f\u20e3 Candidate Feedback \r\n Get the feedback from the users and give suggestions to rejected users.$$\n$$\n$$\n$$\n$$\n","user_id":23,"comments":" $$ Approved with following scope. (1). Company profiling on your product (2).Resume must be shortlisted by uploading the doc, pdf and image of the CV. $$ Submit the revision according to the comments above.","isDraft":0,"status":4,"created_at":"2025-02-25 20:36:54","updated_at":"2025-12-11 13:46:51","isReviewDraft":0,"isInternalDraft":0,"isExternalDraft":0,"isAssign":1,"reviewedDate":"2025-03-25 11:08:23","markedDate":null,"academic_session_id":20,"deleted_at":null,"is_assign_internal_sev":1,"is_assign_internal_eight":1,"is_assign_external_eight":1,"is_evaluated_internal_7th":1,"is_evaluated_internal_8th":1,"is_evaluated_external_8th":null,"member_count":3,"allow_7th_evolution":1,"allow8thEvaluation":1,"external_examiner_id":208,"start_date_time":null,"team_id":186},{"id":1273,"title":"Lost and found hub","prob":"Every day people lose important items like mobile phones, wallets, keys and bags etc. It can be very frustrating when there is no central place to report lost items, making it nearly impossible to recover them. Our platform addresses this issue by providing a digital space where users can easily report lost and found items. The system helps match lost and found items, increasing the chances of recovery. By using this portal user can quickly connect with others who may have found their missing belongings. It is a simple but effective way of solving a common problem","description":"Lost & Found Portal is a simple web platform that helps people recover lost items quickly. Users can report items they've lost or found by uploading details and photos. The system uses AI image recognition to automatically match lost and found posts. Secure messaging lets users communicate safely without sharing personal information. An admin dashboard monitors all activities, while automatic notifications keep everyone updated. Additionally, item categorization and a trust & reward system ensure an organized and reliable experience for all users$$\n1.\tLost Portal: \r\n A section where users can easily report and describe items they have lost.\r\n2.\tFound Portal:\r\n A space for users to post details and photos of items they have found.\r\n3.\tAI-Image Recognition: \r\n Uses artificial intelligence to compare images and help match lost and found items.\r\n The system must effectively match lost and found items based on descriptions and images.\r\n4.\tSecure Messaging System (Chat Bot): \r\nEnables safe communication between users without sharing personal contact details.\r\n5.\tAdmin Dashboard:\r\n A control panel for administrators to monitor and manage posts, users, and system \r\n activities\r\n6.\tAutomatic Notification System: \r\n Sends instant alerts to users about new posts, matches.\r\n7.\tTrust and Reward System: \r\n Rewards honest users with points for successfully returning lost items.\r\n8.\tItem Categorization: \r\n Organizes items into categories for easier searching and browsing.\r\n9.\tLocation Map integration:\r\n Displays a map showing where lost and found items are reported, helping users easily$$\n\u2022 found portal\r\nA space for users to post details and photos of items they have found.\r\n\u2022\tSecure messaging system \r\nEnables safe communication between users without sharing personal contact details.\r\n\u2022\tAutomatic Notification System\r\nSends instant alerts to users about new posts, matches.\r\n\u2022\titem categorization \r\nOrganizes items into categories for easier searching and browsing.\r\n\u2022\tlocation mapping\r\nDisplays a map showing where lost and found items are reported, helping users easily$$\nLost portal\r\n A section where users can easily report and describe items they have lost.\r\n\u2022\tAi image recognition\r\nUses artificial intelligence to compare images and help match lost and found items.\r\n The system must effectively match lost and found items based on descriptions and images.\r\n\u2022\tAdmin Dashboard\r\n A control panel for administrators to monitor and manage posts, users, and system \r\n activities\r\n\u2022\tTrust and reward system \r\nRewards honest users with points for successfully returning lost items.$$\n$$\n$$\n$$\n$$\n","user_id":66,"comments":" $$ Approved $$ Approved","isDraft":0,"status":4,"created_at":"2025-02-25 20:53:57","updated_at":"2025-12-11 13:46:51","isReviewDraft":0,"isInternalDraft":0,"isExternalDraft":0,"isAssign":1,"reviewedDate":"2025-03-14 08:46:34","markedDate":null,"academic_session_id":20,"deleted_at":null,"is_assign_internal_sev":1,"is_assign_internal_eight":1,"is_assign_external_eight":1,"is_evaluated_internal_7th":1,"is_evaluated_internal_8th":1,"is_evaluated_external_8th":null,"member_count":3,"allow_7th_evolution":1,"allow8thEvaluation":0,"external_examiner_id":208,"start_date_time":null,"team_id":null},{"id":1277,"title":"Shadow Archer: Survival Quest ( 3rd Person Open world 3d Game )","prob":"Shadow Archer 3D: Survival Quest is a third-person open-world adventure game designed to provide a stress-relieving and immersive gaming experience. Players will take on the role of an archer tasked with navigating through diverse environments while battling enemies using their archery skills","description":"Under the guidance of their master, a skilled archer embarks on a journey through multiple perilous environments, filled with creatures and adversaries that pose a threat. The archer must rely on their agility, strategy, and precision with the bow to overcome challenges and reach the destination. As the Game operation starts, game is divided into three Levels Based on Locational Changes.\r\n\r\nLevel 1 \uf0e0 City Environment\r\nLevel 2 \uf0e0 Jungle Environment\r\nLevel 3 \uf0e0 Mountain terrains environment.\r\n\r\nAll levels have detailed 3d surroundings according to their type.\r\nIncluding 3d objects and animations.\r\n\r\nFeatures and Functionalities :\r\n\r\n1.\tRunning (The character can run freely as it will be open world game)\r\n2.\tAvoiding enemies (Enemies can be animals or other beings that can hurt the archer )\r\n3.\tTo kill other animals coming in their way (By using the arrows and arch).\r\n4.\tEnemies will have the power bars.(special effects for their death)\r\n 5.\tWith every passing level game would get more complex by adding more details and number of enemies will increase.\r\n6.\tEvery level has a different location. Successfully completing 3 levels the archer will cross all the environments successfully.$$\nThe Project is related to 3rd Person Game.\r\n\r\nModules:\r\n\r\n1. Story Mode\r\n2. Character\/Game Object\r\n3. Animations(According to Character)\r\n4. AI behavioral Enemies\r\n5. Bow\/Arrow working\r\n6. Three different Environments for each level.$$\nIn this Project i shall develop following three modules, \r\nCharacter and different Game Object design \r\nAnimations(According to Character)\r\nBow\/Arrow working according to the character defense strategy$$\nIn this Project i shall develop following three modules :\r\nStory Mode and demo of the theme\r\nArtificial Intelligent based behavioral variations in the charcters of Enemies\r\nThree different Environments for each level.$$\n$$\nD.A.R.K :Survival (VR) (Decide-Accomplish-Run-Kill)$$\nBow and Arrow System for Defending against the enemies$$\nAi behavioral Enemies$$\nCustom city environment","user_id":28,"comments":" $$ Starting point of the game should be different every time. $$ Develop local environment for your game $$ include story line as well. $$ 3 Levels. City, jungle, mountain. Also add rewards in the game. Cut scene and story mode. Localized envirnoment. $$ Make your own local environment. $$ Include story line in game. $$ Add localized custom assets.","isDraft":0,"status":4,"created_at":"2025-02-26 14:33:04","updated_at":"2025-12-11 13:46:51","isReviewDraft":0,"isInternalDraft":0,"isExternalDraft":0,"isAssign":1,"reviewedDate":"2025-03-14 08:49:30","markedDate":null,"academic_session_id":20,"deleted_at":null,"is_assign_internal_sev":1,"is_assign_internal_eight":1,"is_assign_external_eight":1,"is_evaluated_internal_7th":1,"is_evaluated_internal_8th":1,"is_evaluated_external_8th":null,"member_count":3,"allow_7th_evolution":1,"allow8thEvaluation":1,"external_examiner_id":208,"start_date_time":null,"team_id":null},{"id":1279,"title":"ACELT \u2013 IELTS & TOEFL Trainer","prob":"Many students aspiring for master\u2019s and PhD programs abroad must take English proficiency tests like IELTS and TOEFL. However, they often face challenges such as unstructured study plans, limited feedback, and costly learning resources. Existing platforms are either expensive, lack detailed evaluations, or fail to offer a supportive learning environment. This project solves these issues by integrating IELTS and TOEFL preparation into one platform. It provides structured study modules, mock tests with performance assessments, and a community for sharing responses and feedback, ensuring effective and accessible test preparation.","description":"ACElT is a mobile application designed to provide a structured and interactive\r\nplatform for IELTS and TOEFL preparation. The app offers comprehensive study modules\r\ncovering all test sections, including Reading, Writing, Listening, and Speaking. Users\r\ncan take mock tests, receive detailed performance assessments, and improve through\r\ncommunity-driven learning, where they can share responses, receive peer feedback,\r\nand engage in discussions. Additionally, the platform includes an interview feature,\r\nwhere an instructor will evaluate users through interviews and provide feedback to\r\nenhance their preparation. By combining well-organized study resources, interactive\r\npractice sessions, expert guidance, and a supportive learning community, Test Glide\r\nensures an engaging and effective test preparation experience.$$\n1. User Profile & Authentication Module:\r\ni. The User Profile & Authentication Module ensures secure access to\r\nTest Glide and manages user identities.\r\nii. It provides account creation, login\/logout, profile management, and\r\nauthentication security using Firebase Authentication.\r\n\r\n2. Preparation & Practice Module:\r\ni. Users can prepare and practice all four sections:\r\n\u2022 Listening\r\n\u2022 Reading\r\n\u2022 Writing\r\n\u2022 Speaking\r\nii. Each section includes practice exercises, sample questions, and study\r\nmaterials.\r\niii. While practicing, users receive correct answers to help them understand\r\nmistakes and improve their performance. \r\n\r\n3. Community Module:\r\ni. Users can create their own communities or join existing ones to engage in\r\ndiscussions and share insights.\r\nii. Includes discussion forums where users can get reviews, feedback,\r\nand follow expert tutor communities, like Reddit.\r\n\r\n4. Listening Mock Test Modules:\r\ni. Users take listening mock tests with real exam-style audio and\r\nquestions.\r\nii. After completion, the test is evaluated based on accuracy, and users\r\nreceive feedback on their performance.\r\n\r\n5. Reading Mock Test Module:\r\ni. Users attempt reading mock tests with passages and comprehension\r\nquestions.\r\nii. The system evaluates answers, provides scores, and highlights\r\nincorrect responses with explanations.\r\n\r\n6. Writing Mock Test Module:\r\ni. Users complete writing tasks based on IELTS\/TOEFL formats.\r\nii. The system analyzes structure, grammar, and coherence, providing a\r\ndetailed evaluation.\r\n\r\n7. Speaking Mock Test Module:\r\ni. Users record their responses for speaking tasks.\r\nii. The test evaluates based on fluency, pronunciation, and coherence, by\r\nexpert\/instructor feedback and they will scores.\r\n\r\n\r\n8. Evaluation & Performance Report Module:\r\ni. The dashboard displays progress graph and band scores to help users\r\ntrack their performance.\r\nii. The test history section keeps a record of all attempted mock tests for\r\nreview and analysis.\r\n\r\n9. Admin Panel Module:\r\ni. Allows admins to manage users, including account control and activity\r\nmonitoring.\r\nii. Enables adding, updating, and managing test content and practice\r\nmaterials.\r\niii. AI model management and reviewing test evaluations for accuracy.\r\niv. Includes community moderation features to oversee discussions and\r\nmaintain a healthy environment.\r\n\r\n10. Feedback Module:\r\ni. Users can rate and review features, content, and overall platform\r\nexperience.\r\nii. Includes surveys, polls, and a suggestion box for users to provide\r\nfeedback and propose improvements.$$\ni. User Profile & Authentication Module manages user accounts.\r\nii. Community Module enables discussions.\r\niii. Reading Mock Test Module.\r\niv. Speaking Mock Test Modules.\r\nv. Admin Panel Module.$$\ni. Preparation & Practice Module provides study materials.\r\nii. Listening Mock Test Module evaluate skills.\r\niii. Writing Mock Test Modules.\r\niv. Evaluation & Performance Report tracks progress.\r\nv. Feedback Module collects user reviews and suggestions.$$\n$$\n$$\n$$\n$$\n","user_id":68,"comments":" $$ Approved $$ The idea was good. Work on the accent of the users","isDraft":0,"status":4,"created_at":"2025-02-26 15:00:42","updated_at":"2025-12-11 13:46:51","isReviewDraft":0,"isInternalDraft":0,"isExternalDraft":0,"isAssign":1,"reviewedDate":"2025-03-14 08:52:32","markedDate":null,"academic_session_id":20,"deleted_at":null,"is_assign_internal_sev":1,"is_assign_internal_eight":1,"is_assign_external_eight":1,"is_evaluated_internal_7th":1,"is_evaluated_internal_8th":1,"is_evaluated_external_8th":null,"member_count":3,"allow_7th_evolution":1,"allow8thEvaluation":1,"external_examiner_id":208,"start_date_time":null,"team_id":null},{"id":1285,"title":"DoctorHelp Tool - A Decision Support System for Doctors","prob":"Doctors often struggle with managing patient data, tracking vitals over time, and predicting health risks due to the lack of digital decision-support tools. This project provides an AI-assisted system for doctors to record patient vitals, visualize trends in real-time, and predict risks for conditions like high-risk pregnancy. It also includes an admin-verified doctor signup system, a searchable drug risk database, and an AI chatbot to assist doctors with medical queries. This system enhances efficiency, accuracy, and accessibility in healthcare decision-making.","description":"DoctorHelp Tool is a web-based healthcare decision support system that allows doctors to monitor patient vitals, analyze trends using visual graphs, predict health risks (pregnancy complications), and access AI-assisted medical insights. Doctors will sign up for verification by the admin before gaining access. The system will also provide a searchable drug risk database and secure communication between doctors and an AI medical assistant.$$\n1\ufe0f\u20e3 Doctor Registration & Verification\r\n2\ufe0f\u20e3 Doctor Dashboard\r\n3\ufe0f\u20e3 Patient Data & Vitals Management\r\n4\ufe0f\u20e3 Graphical Visualization of Vitals\r\n5\ufe0f\u20e3 High Risk Pregnancy Prediction\r\n6\ufe0f\u20e3 Drug Risk Database\r\n7\ufe0f\u20e3 AI Chatbot for Doctor Assistance$$\nIn the Doctor Help Tool, I shall develop the Frontend & User Interaction & High-Risk Pregnancy Prediction module, which includes:\r\n(i) Doctor Panel (Signup\/Login UI, Dashboard, Patient List, Vitals Display)\r\n(ii) Patient Management UI (Add\/Update Patient History, Enter & View Vitals, Graphical Visualization)\r\n(iii) Admin Panel (Doctor Verification UI)\r\n(iv) Drug Risk UI (Search & View Drug Information)\r\n(v) AI Chat Assistant UI (Interface for chatbot interaction)\r\n(vi) High-Risk Pregnancy Prediction System (Machine Learning Model for Pregnancy Risk)$$\nIn the Doctor Help Tool, I shall develop the Backend, AI Chatbot & High-Risk Prediction integeration, which includes:\r\n(i) Authentication & Authorization (Doctor Registration, Admin Approval)\r\n(ii) Patient & Vitals Management (Database Design, API for Patient History & Vitals, Time-Series Data Storage)\r\n(iii) High-Risk Pregnancy Prediction Integration (Flask\/Django)\r\n(iv) Drug Risk Database Backend (Process Drug Data)\r\n(v) AI Chat Assistant (GPT-based Chatbot, Medical Query Processing, Secure API Responses)$$\n$$\n$$\n$$\n$$\n","user_id":5,"comments":" $$ Include generalized risk prediction $$ Study the existing systems for this project $$ seems like data entry only, the project is lagging AI concepts $$ Students are advised to conduct a thorough study of the idea, consult general physicians to understand the real nature of the problem, analyze existing systems, identify their limitations, and then resubmit the proposal.","isDraft":0,"status":4,"created_at":"2025-02-26 17:25:21","updated_at":"2025-12-11 13:46:51","isReviewDraft":0,"isInternalDraft":0,"isExternalDraft":0,"isAssign":1,"reviewedDate":"2025-03-25 11:11:22","markedDate":null,"academic_session_id":20,"deleted_at":null,"is_assign_internal_sev":1,"is_assign_internal_eight":1,"is_assign_external_eight":1,"is_evaluated_internal_7th":1,"is_evaluated_internal_8th":1,"is_evaluated_external_8th":null,"member_count":3,"allow_7th_evolution":1,"allow8thEvaluation":1,"external_examiner_id":208,"start_date_time":null,"team_id":190}] 0 [{"id":1286,"title":"GoggleVision AR","prob":"Bridging the Gap Between Online and Offline Shopping\r\nHigh Return Rates for Eyewear.\r\nLimited Accessibility to Physical Stores.\r\nDifficulty in Choosing the Right Style.\r\nWhen customers buy eyewear online, they often struggle to determine if the goggles will fit their face shape, size, or style preferences. This leads to dissatisfaction and high return rates.","description":"The \"GoggleVision AR\" is a mobile application designed for Android and iOS. It enables users to try on different eyewear styles virtually using AR technology. The application will utilize face-tracking technology to detect facial landmarks and position 3D glasses on the user\u2019s face in real-time. The app will feature a selection of eyewear models, the ability to switch between different frames, and a user-friendly interface. Users will also have the option to take screenshots of their try-on experience.$$\n1. Face Tracking & Detection Module - Uses ARKit (iOS) or ARCore (Android) to detect the user\u2019s face and adjust the positioning of virtual glasses accordingly.\r\n2. 3D Eyewear Rendering Module - Integrates 3D glasses designed in Blender into the Unity environment and ensures realistic rendering.\r\n3. UI & Glasses Selection Module - Provides an interface for users to browse and select different eyewear styles.\r\n4. Screenshot & Sharing Module (Optional) - Allows users to take snapshots and share their virtual try-on images.$$\nDevelops the Face Tracking & Detection Module by integrating ARKit for iOS and ARCore for Android within Unity. This involves setting up real-time face tracking, detecting facial landmarks, and ensuring accurate placement of virtual glasses on the user\u2019s face. Additional tasks include optimizing tracking performance and ensuring a seamless augmented reality experience across different mobile devices.$$\nWorks on 3D Eyewear Rendering and UI implementation in Unity, which includes designing and integrating high-quality 3D glasses models using Blender. The student ensures realistic material properties, reflections, and lighting effects for better visualization. Additionally, they will create a responsive and user-friendly UI that allows seamless navigation between different eyewear styles and customization options.$$\n$$\n$$\n$$\n$$\n","user_id":22,"comments":" $$ Discuss with your supervisor and resubmit $$ Scope of the project is very limited. Students are advised either enhance the project scope or changed the idea.","isDraft":0,"status":4,"created_at":"2025-02-26 17:46:18","updated_at":"2025-12-11 13:47:20","isReviewDraft":0,"isInternalDraft":0,"isExternalDraft":0,"isAssign":1,"reviewedDate":"2025-03-26 09:04:15","markedDate":null,"academic_session_id":20,"deleted_at":null,"is_assign_internal_sev":1,"is_assign_internal_eight":1,"is_assign_external_eight":1,"is_evaluated_internal_7th":1,"is_evaluated_internal_8th":1,"is_evaluated_external_8th":null,"member_count":3,"allow_7th_evolution":1,"allow8thEvaluation":0,"external_examiner_id":209,"start_date_time":null,"team_id":null},{"id":1292,"title":"DeepShield: Protecting Against Deepfake Manipulations","prob":"1. Protection Against Fake & Harmful Content\r\nDeepfake technology is used to create fake and inappropriate content without consent, violating privacy and causing harm.\r\nOur app helps users check suspicious photos and videos so they can report them to the right authorities.\r\n2. Detecting Fake Videos on Social Media\r\nFake deepfake videos spread quickly on platforms like YouTube, Instagram, and TikTok, misleading people with false information.\r\nWith our app, users can upload social media videos to check if they are deepfake and help stop misinformation.\r\n3. Preventing Cybercrime & Fraud\r\nScammers use deepfake videos and images to steal identities, blackmail people, or commit fraud.\r\nOur app helps verify if a video or image is real or fake before it can be misused.","description":"Through this Final Year Project (FYP), we will create an artificial intelligence system that accurately detects deep fake media content. This system utilizes cutting-edge deep learning approaches, including hybrid architectures or transformers, to examine both visual and temporal attributes within media (images and videos) presentations. Training the model will involve modern synthetic datasets with high-quality deep fakes created through advanced AI methods to ensure robustness against current deep fake generation techniques.\r\n\r\nThe initiative will feature a mobile application designed to be user-friendly while enabling users to upload images or videos and obtain immediate authenticity assessments. Additionally, the system will support real-time deepfake detection through the device camera, allowing users to instantly analyze live video frames without relying on pre-recorded content. The system's design optimization ensures real-time operation, which allows for fast and effective deep fake detection.\r\n\r\nThis project merges sophisticated AI models with a practical mobile interface to counter deep fake threats on social media and online platforms by offering a dependable solution for fighting misinformation.$$\nUI\/UX Design: Creating intuitive and user-friendly app interfaces using Figma for seamless user experience.\r\nFrontend Development: Implementing the designed UI in Flutter, ensuring smooth app interactions.\r\nReal-Time Detection (App Side): enabling live deepfake detection using the device camera for instant analysis.\r\nDataset Collection: Gathering real and deepfake images and videos from various datasets for model training.\r\nPreprocessing: Enhancing dataset quality by applying normalization, resizing, and noise reduction techniques.\r\nModel Development and Training: Implementing deepfake detection models using AI frameworks like TensorFlow, PyTorch, OpenCV, etc.\r\nIntegration: Merging the trained AI model with the mobile app for deepfake detection functionality\r\nBackend: Implementing authentication, media storage, and user data management to support app functionality.$$\nI will do the following modules from our project:\r\n1.\tUI\/UX Design (using Figma)\r\n2.\tFrontend Development\r\n3.\tReal-Time Detection (App side)\r\n4.\tDataset collection\r\n5.\tPreprocessing\r\n6.\tIntegration of app and deep learning models$$\nI will do the following modules from our project:\r\n1.\tData Collection\r\n2.\tModel Development and Training \r\n3.\tIntegration of app and deep learning models\r\n4.\tReal-Time Detection (model side)\r\n5.\tBackend$$\n$$\nDeep Fake Detection using Deep Neural Network Based Methods.$$\nAI-Generated Face Detection: Detects not only face-swapped deepfakes but also AI-generated faces created by GAN models, enhancing detection capabilities.$$\nReal-Time Detection: Users can instantly analyze live video frames using the device camera, ensuring fast and accurate deepfake detection.$$\nEnhanced Deepfake Detection Model: Combining CNNs for detail recognition and transformers for pattern analysis improves accuracy against advanced deepfakes.","user_id":74,"comments":"","isDraft":0,"status":4,"created_at":"2025-02-26 19:54:32","updated_at":"2025-12-11 13:47:20","isReviewDraft":0,"isInternalDraft":0,"isExternalDraft":0,"isAssign":1,"reviewedDate":"2025-03-14 08:59:22","markedDate":null,"academic_session_id":20,"deleted_at":null,"is_assign_internal_sev":1,"is_assign_internal_eight":1,"is_assign_external_eight":1,"is_evaluated_internal_7th":1,"is_evaluated_internal_8th":1,"is_evaluated_external_8th":null,"member_count":3,"allow_7th_evolution":1,"allow8thEvaluation":1,"external_examiner_id":209,"start_date_time":null,"team_id":null},{"id":1300,"title":"The Educators: A Smart Solution for Automated Learning & School Management","prob":"Our FYP solves the problem of inefficient school management and communication gaps between students, teachers, and parents. Currently, parents have to call the school for leave requests, check homework manually, and visit the school for fee payments. Teachers struggle with tracking attendance, sharing homework, and managing test reports. Admins face difficulties in handling fee challans, student promotions, and sending important notices. Our LMS will automate these tasks, making school operations smoother. Parents will receive updates via WhatsApp, students will access homework, recorded lectures, and study materials online, and admin tasks like fee management and exam results will be fully automated.","description":"The Educators LMS is a web-based application designed to automate and streamline school management tasks for students, teachers, parents, and administrators. The system allows parents to apply for student leave online, with automatic approval notifications via WhatsApp. Teachers can upload homework, which is sent to parents after school. Monthly test reports, holiday notices, and fee challans are automatically generated and shared with parents. The system also includes a smart fee management module, applying late fees and restricting access if payments are not made on time. A class leaderboard rewards top performers with fee waivers, and an automated student promotion system ensures smooth transitions between grades. Students can access recorded lectures, study notes, and engage in class discussions. The LMS simplifies school operations, improves communication, and enhances learning accessibility for students.$$\nIn the Educators LMS, the modules are (i) Automated Attendance & Absence Notifications, where teachers mark daily attendance, and if a student is absent, parents receive an immediate WhatsApp notification while attendance records remain visible in the portal; (ii) Student Leave Management System, allowing parents to request student leave online, which can be approved or rejected by admins or teachers, and once approved, attendance is automatically updated with a WhatsApp confirmation sent to parents; (iii) Digital Diary & Homework Notifications, where teachers upload homework on the LMS, parents receive notifications via WhatsApp, and students can access their daily homework online; (iv) Monthly Test Reports, enabling teachers to upload test results, notify parents via WhatsApp, and display performance trends such as improvement or decline; (v) Holiday & Important Notices System, which allows the admin to send school-wide notifications delivered via WhatsApp and the LMS dashboard; (vi) Smart Fee Challan & Late Fee Handling, which auto-generates monthly fee challans with due dates, applies a 5% late fee after the grace period, and enables the admin to track the fee status as paid, unpaid, or late; (vii) Automated Detention System for Late Fee, which restricts access to class materials and exams for students with unpaid fees while sending daily WhatsApp reminders until fees are cleared; (viii) Student Performance Leaderboard & Fee Waivers, displaying the top students in class and school-wide rankings while automatically granting fee waivers of 100%, 75%, or 50% to the top three performers; (ix) Auto-Generated Exam Results & Class Ranks, which calculates total marks, percentages, and class rankings, generating student performance reports; and (x) DLP & Scheme of Work Sharing System, where the principal can enter a Digital Lesson Plan (DLP) or Scheme of Work link into the system, which is then sent automatically to all teachers via WhatsApp, allowing them to access or view the shared document instantly.$$\nIn the LMS, I shall develop various modules, including (i) autogenerated exam results and class ranks to automate student assessments and rankings, (ii) a DLP and scheme of work sharing system to facilitate structured lesson planning and collaboration among teachers, (iii) a digital diary and homework notification module to enhance communication between teachers, students, and parents, (iv) a smart fee challan and late fee handling system to automate fee management and track late payments efficiently, and (v) a student performance leaderboard and fee waivers module to encourage academic excellence by rewarding top performers with financial assistance.$$\nIn the LMS, I shall develop various modules, including (i) a student leave management system to streamline the process of requesting and approving leaves, (ii) a monthly test reports module to generate and share student performance reports efficiently, (iii) a holiday and important notices system to keep students and staff informed about upcoming holidays and crucial announcements, (iv) an automated detention system for late fee management, ensuring timely payments by enforcing necessary actions, and (v) an automated attendance and absence notification module to track student attendance and send real-time alerts to parents and administrators.$$\n$$\n$$\n$$\n$$\n","user_id":23,"comments":" $$ review the Requirements and SMS Apis $$ Mobile application is recommended to be added $$ students are not clear about the main modules of the project. Twilio is not recommended, as its paid. $$ students are encouraged to develop mobile app for parents, instead of frequent alerts, so that parent can track evrything about children. $$ Project should be deployed at the end, with web portal and mobile app for parent","isDraft":0,"status":4,"created_at":"2025-02-28 19:57:31","updated_at":"2025-12-11 13:47:20","isReviewDraft":0,"isInternalDraft":0,"isExternalDraft":0,"isAssign":1,"reviewedDate":"2025-03-17 11:40:42","markedDate":null,"academic_session_id":20,"deleted_at":null,"is_assign_internal_sev":1,"is_assign_internal_eight":1,"is_assign_external_eight":1,"is_evaluated_internal_7th":1,"is_evaluated_internal_8th":1,"is_evaluated_external_8th":null,"member_count":3,"allow_7th_evolution":1,"allow8thEvaluation":1,"external_examiner_id":209,"start_date_time":null,"team_id":186},{"id":1301,"title":"AI-Powered Data Maintenance & Cleaning System with Reinforcement Learning for Real-Time Data Quality Enhancement","prob":"In today\u2019s data-driven world, organizations across industries such as finance, healthcare, and e-commerce struggle with poor data quality\u2014caused by missing values, duplicates, inconsistencies, and anomalies. Manual data cleaning is labor-intensive, error-prone, and inefficient, leading to inaccurate analytics and suboptimal decision-making. This FYP proposes to develop an AI-powered system that automates data validation, cleaning, and correction by integrating machine learning and reinforcement learning techniques. The solution will dynamically learn from user feedback, adapt to various data types, and provide real-time data quality assurance, thereby reducing manual effort and enhancing data reliability for downstream applications.","description":"This project develops an AI-powered Data Maintenance & Cleaning System designed to automatically detect and correct data quality issues in real-time. The system allows users to upload datasets (CSV, Excel, JSON, etc.) via a user-friendly web interface. Once uploaded, the backend uses Pandas and statistical methods to analyze the dataset for missing values, duplicates, outliers, and formatting errors. Advanced machine learning models, including anomaly detection algorithms (such as Isolation Forests and Autoencoders), identify problematic entries. A unique reinforcement learning (RL) module then learns from user feedback and historical corrections to suggest and automatically apply data corrections. The final, clean dataset is available for download or integration with external systems. The entire workflow\u2014from upload through cleaning to export\u2014is designed for scalability and adaptability across various industries, ensuring a robust solution for maintaining high data quality.$$\nIn AI-Powered Data Maintenance & Cleaning System with Reinforcement Learning for Real-Time Data Quality Enhancement, the modules are (i) Data Upload and Preprocessing Module, (ii) Anomaly Detection Module, (iii) Data Cleaning Module, (iv) Data Export and Integration Module, (v) User Interface and Dashboard Module.$$\nIn AI Data Maintenance, I shall develop the Backend and ML\/RL modules which include: (i) building secure file upload endpoints and data validation routines using Flask and Pandas; (ii) implementing data preprocessing and anomaly detection with ML models (e.g., Isolation Forest, Autoencoders); (iii) creating the RL environment with OpenAI Gym and Stable-Baselines3 to automatically learn and apply data corrections.$$\nIn AI Data Maintenance, I shall develop the Frontend and Integration modules which include: (i) designing an intuitive web dashboard using React.js for file uploads and data visualization; (ii) implementing interfaces to display analysis reports and correction suggestions; (iii) integrating frontend with backend REST APIs; (iv) developing features for data export and seamless integration with external systems.$$\n$$\n$$\n$$\n$$\n","user_id":74,"comments":" $$ Discuss with your supervisor and resubmit $$ Discuss with your supervisor and resubmit $$ Scope is limited. The word cleaning of data has very limited meaning. Add more modules as working on a textual data has very limited scope. $$ Scope of the project is very limited. Students are advised either enhance the project scope.","isDraft":0,"status":4,"created_at":"2025-02-28 22:40:51","updated_at":"2025-12-11 13:47:20","isReviewDraft":0,"isInternalDraft":0,"isExternalDraft":0,"isAssign":1,"reviewedDate":"2025-04-10 09:08:41","markedDate":null,"academic_session_id":20,"deleted_at":null,"is_assign_internal_sev":1,"is_assign_internal_eight":1,"is_assign_external_eight":1,"is_evaluated_internal_7th":1,"is_evaluated_internal_8th":1,"is_evaluated_external_8th":null,"member_count":3,"allow_7th_evolution":1,"allow8thEvaluation":1,"external_examiner_id":209,"start_date_time":null,"team_id":null},{"id":1303,"title":"AI-Powered Smart Finance Manager","prob":"Managing personal finances is a challenge for many individuals, especially with increasing expenses and complex financial goals. People often struggle to track their daily expenses,categorize and analyze their spending habits,set and achieve realistic financial goals and predict future expenses.\r\nThis FYP aims to solve these problems by providing an AI-powered mobile app that helps users:\r\n\uf06cTrack and categorize expenses.\r\n\uf06cGenerate personalized budgets.\r\n\uf06cPredict future expenses using historical data\r\n\uf06cSet and monitor financial goals.\r\n\uf06cReceive actionable insights and reminders to improve financial health.","description":"The app is a personal finance management system that leverages AI and machine learning to provide users with intelligent financial insights. The app will:\r\n1-Allow users to authenticate and set up their financial profile.\r\n2-Track expenses manually.\r\n3-Use AI to categorize expenses and generate spending insights.\r\n4-Predict future expenses using time-series forecasting.\r\n5-Help users set financial goals and track progress.\r\n6-Send smart notifications and reminders to keep users on track.\r\nThe AI-powered personal finance management app streamlines expense tracking, budgeting, and financial goal-setting through an intelligent workflow. Upon launch, users authenticate via Firebase and proceed to onboarding, where they input financial details like income, fixed expenses, and savings goals. AI then generates an initial budget plan and stores data in Firebase Firestore. Users can manually log expenses, while NLP-based AI categorizes transactions automatically. AI-driven budgeting analyzes spending patterns, suggests optimizations, and presents insights through charts and reports. Future expense prediction leverages LSTM and ARIMA models to forecast spending trends, helping users adjust budgets proactively. The app also includes goal-setting features, tracking progress with AI-generated recommendations. Smart notifications powered by Firebase Cloud Messaging provide reminders, spending alerts, and potential fraud detection. This project integrates machine learning, AI-driven analytics, and real-time user engagement to enhance financial decision-making.$$\nModule 1: User Authentication and Onboarding\r\nDescription: Handles user login\/signup and onboarding process.\r\nFeatures:\r\n1-Google\/Email authentication using Firebase.\r\n2-On boarding screens to explain app functionality.\r\n3-Initial financial setup (income, expenses, savings goal).\r\nTech Used: Flutter, Firebase Authentication.\r\nModule 2: Expense Tracking and Categorization\r\nDescription: Allows users to add expenses manually.\r\nFeatures:\r\n1-Manual expense entry with AI-based categorization.\r\n2-NLP-based text categorization (e.g., Na\u00efve Bayes, TF-IDF).\r\nTech Used: Flutter, NLP models.\r\nModule 3: AI-Based Budgeting and Spending Insights\r\n Description: Analyzes user spending patterns and provides budgeting recommendations.\r\nFeatures:\r\n1-AI-generated budget plans.\r\n2-Spending insights and visual reports (charts, graphs).\r\n3-Linear\/polynomial regression for budget adjustments.\r\nTech Used: Flutter, Firebase Firestore, Regression models.\r\n\r\nModule 4: Future Expense Prediction\r\nDescription: Predicts future expenses using historical data.\r\nFeatures:\r\n1-Time-series forecasting using LSTM and ARIMA models.\r\n2-Alerts for potential budget overruns.\r\nTech Used: LSTM, ARIMA, Firebase Firestore.\r\n\r\nModule 5: Financial Goal Setting and Progress Tracking\r\nDescription: Helps users set financial goals and track progress.\r\nFeatures:\r\n1-Goal setting (e.g., save Rs. 20,000 in 3 months).\r\n2-AI-based progress tracking and suggestions.\r\nTech Used: Flutter, Firebase Firestore, Regression analysis.\r\n\r\nModule 6: Smart Notifications and Reminders\r\nDescription: Sends timely notifications and reminders to users.\r\nFeatures:\r\n1-Daily\/weekly spending alerts.\r\n2-Goal progress reminders.\r\nTech Used: Firebase Cloud Messaging (FCM), Rule-based AI system.$$\nIn this project I shall develop modules which includes: User Authentication and Onboarding\r\nExpense Tracking and Categorization\r\nSmart Notifications and Reminders\r\nResponsibilities:\r\n\uf06cImplement Firebase Authentication.\r\n\uf06cDevelop onboarding screens and manual expense entry Screen.\r\n\uf06cImplement NLP-based expense categorization. Firebase Cloud Messaging (FCM), Rule-based AI system$$\nIn this project,I shall develop modules which includes: AI-Based Budgeting and Spending Insights\r\nFuture Expense Prediction\r\nFinancial Goal Setting and Progress Tracking\r\nResponsibilities:\r\n\uf06cImplement AI models for budgeting and expense prediction.\r\n\uf06cDevelop visual reports using Flutter Charts.\r\n\uf06cSet up Firebase Firestore for data storage.$$\n$$\n$$\n$$\n$$\n","user_id":78,"comments":" $$ it is recommended to use voice input instead of text input for useability $$ Check the available apps and add the advance functionality in your project $$ In 7th semester, you should have implemented at least one major use case other than user logins and user registrations along with the newly modified designed SRS document. In 8th semester, the FYP MUST be 90% complete in the 14th week. Your website, if any, MUST be online and your App, if any, MUST be in AppStore when you come for internal viva. Your hardware MUST be packed in such a way that it gives the look of a sellable product.","isDraft":0,"status":4,"created_at":"2025-03-01 09:32:05","updated_at":"2025-12-11 13:47:20","isReviewDraft":0,"isInternalDraft":0,"isExternalDraft":0,"isAssign":1,"reviewedDate":"2025-03-17 11:42:54","markedDate":null,"academic_session_id":20,"deleted_at":null,"is_assign_internal_sev":1,"is_assign_internal_eight":1,"is_assign_external_eight":1,"is_evaluated_internal_7th":1,"is_evaluated_internal_8th":1,"is_evaluated_external_8th":null,"member_count":3,"allow_7th_evolution":1,"allow8thEvaluation":0,"external_examiner_id":209,"start_date_time":null,"team_id":null},{"id":1304,"title":"RAG-Based Generative Story Writing: Merging Retrieval with AI-Driven Narrative Creation","prob":"Modern automated story writing tools often produce stories with broken plots, inconsistent characters, and missing background details. This project will solve these problems by creating a system that gathers useful story elements from a carefully chosen collection and uses an AI model to generate new stories. The system will pick up key details like common character types, popular themes, and story structures, then mix them with user ideas to create complete and engaging stories. This solution will help writers, teachers, and content creators improve digital story writing.","description":"This project develops an Android application that enhances automated story writing by combining a retrieval system with a generative AI model. Users simply enter a story prompt, and the AI generates a narrative based on that prompt, using additional story elements like common character types, popular themes, and proven plot ideas. By incorporating well-established literary components into the creative process, the application improves character development, plot coherence, and overall story quality. The result is an intuitive mobile tool that helps writers, educators, and content creators generate richer, more engaging stories while addressing common challenges in automated story writing.$$\n1.\tUser Input Module:\r\n\u2022\tAllows users to enter a story prompt.\r\n2.\tPrompt Analysis and Retrieval Module:\r\n\u2022\tRetrieves relevant literary cues to guide the narrative generation process.\r\n3.\tGenerative Module:\r\n\u2022\tIntegrates a fine-tuned generative AI model that processes the prompt along with the identified elements.\r\n4.\tStory Composition and Post-Processing Module:\r\n\u2022\tMerges and formats the output from the generative module to ensure coherence and readability.\r\n\u2022\tApplies post-processing tasks such as grammar checks and stylistic adjustments.\r\n5.\t User Interface Module:\r\n\u2022\tProvides an intuitive Android-based interface for input, output, and interaction.\r\n\u2022\tEnsures a smooth user experience with clear navigation and feedback display.\r\n6.\t Settings and Feedback Module:\r\n\u2022\tAllows users to customize parameters (e.g., story length, tone) and adjust preferences.\r\n\u2022\tCollects user feedback to improve story quality and overall application performance.\r\n7.\t Version Control Module:\r\n\u2022\tMaintain history and revisions of generated stories for user review and editing.\r\n8.\t Content Moderation Module:\r\n\u2022\tAutomatically screen generated content to enforce quality and safety guidelines.$$\nHe will develop the Prompt Analysis and Retrieval, Generative, Settings and Feedback, and Version Control modules. These modules enable the system to extract literary cues from the input, generate coherent narratives using AI, allow users to customize parameters and provide feedback, and maintain version histories for review and editing.$$\nHe will develop the Input, User Interface, Story Composition and Post-Processing, and Content Moderation Modules. These components will handle user inputs, provide an engaging Android interface, refine generated stories for coherence and quality, and enforce content safety standards.$$\n$$\nhttps:\/\/111.68.98.91\/rms\/student-console\/fyp\/proposal?_token=20STs63nR6iDHidQBHW3jEvF3bUyDuhAto80BLVW&fypSearch_length=-1&view=1110$$\nGenerative AI$$\nRetrieval Augmented Generation (RAG)$$\nContent Moderation","user_id":54,"comments":" $$ scope of the project is very limited. As students will use pre train models and API, it will deny the main objective of FYP (to code things and learn) $$ If AI can be the part your project, then we you can proceed, otherwise change of idea is suggested $$ There is no such module for development as already projects and build in libraries are available $$ make the script base video story modules","isDraft":0,"status":4,"created_at":"2025-03-01 11:55:54","updated_at":"2025-12-11 13:47:20","isReviewDraft":0,"isInternalDraft":0,"isExternalDraft":0,"isAssign":1,"reviewedDate":"2025-03-21 13:12:18","markedDate":null,"academic_session_id":20,"deleted_at":null,"is_assign_internal_sev":1,"is_assign_internal_eight":1,"is_assign_external_eight":1,"is_evaluated_internal_7th":1,"is_evaluated_internal_8th":1,"is_evaluated_external_8th":null,"member_count":3,"allow_7th_evolution":1,"allow8thEvaluation":0,"external_examiner_id":209,"start_date_time":null,"team_id":null},{"id":1310,"title":"Seeing the Unseen\r\nSmart Vision Assistant:AI-Powered Tool For Visually Impaired","prob":"For visually impaired individuals, even simple daily tasks can be overwhelming, leading\r\nto dependence on others and emotional distress. This reliance limits independence, makes\r\neducation difficult, restricts job opportunities, and instills fear of going out alone, often\r\nresulting in isolation and reduced quality of life.Our project aims to empower them through a mobile application with real-time object detection, text recognition, and currency identification via voice assistance by the help of\r\nAI. This app will restore confidence, reduce reliance on others, and promote dignity and\r\nfreedom","description":"The AI-Driven Smart Vision Assistant is a mobile application designed to assist\r\nvisually impaired individuals by providing real-time object detection, text reading,\r\nand currency recognition through voice assistance. The application allows users to\r\nchoose from three primary functionalities, offering them greater independence and\r\naccessibility in their daily lives.\r\nWith the Object Detection feature, the app will activate the camera to recognize\r\nand identify objects in front of the user, providing an audio description of what is\r\ndetected. This enables visually impaired individuals to understand their\r\nsurroundings without external help. The Text Reading functionality allows users\r\nto read a product description, letter, book, or any other text by simply placing the\r\nobject in front of the camera. The app will extract and read the text aloud, ensuring\r\nthat visually impaired individuals can access written content effortlessly.\r\nAdditionally, the Currency Recognition feature helps users identify money by\r\nholding currency notes in front of the camera, where the app will analyze and\r\nannounce the denomination via voice assistance.\r\nAll functionalities will be accessible through a user-friendly interface, ensuring\r\nseamless interaction. The app is designed to provide real-time voice assistance,\r\nallowing visually impaired individuals to perform essential tasks independently and\r\nefficiently. In the future, we will integrate all this functionality with smart\r\nglasses to make it even easier and more convenient for visually impaired users.$$\nObject Detection Module\r\nThis module will do real-time object detection. It captures images from the camera,\r\nprocesses them using AI models, and provides an audio description of the detected objects.\r\nThis helps visually impaired users understand what is in front of them.\r\nText Recognition Module\r\nThe text recognition module extracts printed text from books, letters, product descriptions,\r\nor any other documents. The extracted text is then processed and converted into speech for\r\nthe user.\r\nCurrency Recognition Module\r\nThis module is designed to detect and identify currency notes. It uses AI models trained to\r\nrecognize and announces the currency value through voice assistance, enabling visually\r\nimpaired users to handle money with confidence.\r\nSpeech Output Module\r\nThis module is responsible for converting detected objects, text, and currency details into\r\nspeech. It will generate clear and natural voice feedback, ensuring ease of use for visually\r\nimpaired individuals.$$\nIn Smart Vision Assistant Wahaj shall develop the Object Detection and Speech\r\nOutput modules, ensuring real-time identification and voice descriptions of detected\r\nobjects. He will optimize the AI models to enhance object recognition accuracy and\r\nintegrate a reliable voice output system. Wahaj will collaborate with Dania to\r\nensure seamless integration of all modules, refining detection techniques for optimal\r\nperformance. They will work together to align the overall app architecture, enhance\r\nthe user experience, and provide mutual support in AI development efforts.$$\nDania shall develop the Currency Recognition and Text Recognition modules, ensuring accurate text extraction from objects and identification of currency. She will work on text recognition accuracy and ensure reliable currency classification. Additionally, she will optimize preprocessing techniques to refine text readability and currency detection. Dania will collaborate with Wahaj to ensure seamless module integration, refine detection techniques for optimal performance, and align the overall system architecture. Together, they will enhance user experience and support each other in AI development efforts.$$\n$$\n$$\n$$\n$$\n","user_id":17,"comments":" $$ Approved with the above scope","isDraft":0,"status":4,"created_at":"2025-03-05 09:44:15","updated_at":"2025-12-11 13:47:20","isReviewDraft":0,"isInternalDraft":0,"isExternalDraft":0,"isAssign":1,"reviewedDate":"2025-03-17 11:10:22","markedDate":null,"academic_session_id":20,"deleted_at":null,"is_assign_internal_sev":1,"is_assign_internal_eight":1,"is_assign_external_eight":1,"is_evaluated_internal_7th":1,"is_evaluated_internal_8th":1,"is_evaluated_external_8th":null,"member_count":3,"allow_7th_evolution":1,"allow8thEvaluation":1,"external_examiner_id":209,"start_date_time":null,"team_id":188}] 0 [{"id":1196,"title":"Quran Verse Recognition","prob":"This Final Year Project (FYP) addresses a significant real-world problem by leveraging technology to enhance the learning and recitation experience of the Quran, the Holy scripture of Islam. The project aims to develop an AI-based system that assists users in improving their Quranic recitation by providing real-time feedback on their pronunciation and recitation accuracy.","description":"The \"AI Model for Recognition and Synchronization of Quranic Text with Audio\" project aims to automate the synchronization of Quranic text with audio. By integrating ASR with a Matching Algorithm, it streamlines transcription and synchronization, reducing manual efforts. Exploring traditional methods, ASR tech, and addressing Tajweed's role and database challenges, it seeks to revolutionize content creation, meeting the demand for accurately synchronized Quranic recitation efficiently$$\n1. Automatic Speech Recognition (ASR) Module: Converts audio recitations into text using ASR technology.\r\n 2. Text Processing Module: Prepares and formats transcribed text for further analysis.\r\n 3. Matching Algorithm Module: Synchronizes text with corresponding audio segments using advanced algorithms.\r\n 4. User Interface Module: Develops a user-friendly interface for easy interaction with the AI model.\r\n 5. Quality Assurance Module: Ensures accuracy and reliability of synchronized text with audio.\r\n 6. Integration and Deployment Module: Combines all components and deploys the model for practical usage.$$\nHe will develop the Automatic Speech Recognition (ASR) Module, tasked with converting audio recitations into text using ASR technology. This is crucial for accurately transcribing Quranic verses, a pivotal aspect of the project's functionality.$$\nHe will prepare and formatting transcribed text for analysis. This includes ensuring data quality through preprocessing and structuring the text appropriately for integration into the synchronization algorithm$$\n$$\n$$\n$$\n$$\n","user_id":17,"comments":" $$ In 7th semester, you should have implemented at least one major use case other than user logins and user registrations along with the newly modified designed SRS document.","isDraft":0,"status":4,"created_at":"2024-05-09 16:31:16","updated_at":"2025-12-12 17:50:58","isReviewDraft":0,"isInternalDraft":0,"isExternalDraft":0,"isAssign":1,"reviewedDate":"2024-05-22 15:09:26","markedDate":null,"academic_session_id":20,"deleted_at":null,"is_assign_internal_sev":1,"is_assign_internal_eight":1,"is_assign_external_eight":1,"is_evaluated_internal_7th":1,"is_evaluated_internal_8th":1,"is_evaluated_external_8th":null,"member_count":3,"allow_7th_evolution":1,"allow8thEvaluation":1,"external_examiner_id":210,"start_date_time":null,"team_id":null},{"id":1263,"title":"LifeDrop (life-saving blood donations)","prob":"LifeDrop tackles a very real issue we face today: an inefficient and disorganized blood donation system. As a student working on this project, we noticed that connecting donors, patients, hospitals, and volunteers often involves too many delays and miscommunications, so our solution is to create a secure, integrated, and data-driven platform that brings everyone together in one place. By incorporating AI and ML, LifeDrop can match donors to patients quickly and accurately, ensuring that the right blood reaches the right person at just the right time\u2014resulting in fewer delays, improved safety, and better management of blood resources overall. In essence, LifeDrop is about making the entire process smoother and more efficient, using modern technology and smart data analytics to significantly enhance the blood donation system, ultimately saving more lives and strengthening our healthcare infrastructure.","description":"LifeDrop is a comprehensive blood donation management system designed to efficiently connect donors, patients, hospitals, and volunteers while ensuring a seamless and secure experience. The platform begins with an authentication module for user sign-up and login, granting access to different roles. Donors can create and manage profiles, while patients can register and request blood donations. Hospitals maintain records of registered facilities, while an AI-powered recommendation system intelligently matches donors with patients based on blood type and availability. The system also includes an events module for organizing blood drives and an admin module to manage blood inventory and user records. Additionally, analytics and reporting provide insights into past donations and needs, while emergency response mechanisms handle urgent requests efficiently. To ensure donor safety, a blood testing information module manages screening processes. The platform also fosters engagement through success stories, volunteer staff management, and a feedback module for continuous improvement. Users can communicate via email, chat, or notifications, ensuring smooth coordination.$$\nIn LifeDrop the Modules are (1) Authentication (Sign In\/Sign Up) (2)Donor Module (Donor Profile with Details) (3)Patient Module (Patient Profile with Details) (4)Hospital Module (Registered Hospitals Details) (5) AI powered Recommendation (Donors matching with the required blood request) (6)Events Modules (7) Admin Module (Blood Inventory Details, Registered Donors and Patients Details) (8) Analytics and Reporting Module (past records of donation and blood needs) (9)Emergency Responses (10) Blood Testing Details (screening of the donors) (11) Feedback Module (Feedback from users will be taken) (12) Communication Module (13) Social Engagement (Success Stories) \r\n(14) Volunteer Staff Management$$\nStudent-1 will handle the Authentication Module, Donor Module, Patient Module, Blood Testing Details, Feedback Module, and Communication Module and volunteer staff management. They will focus on building the user authentication system, managing donor and patient profiles, recording blood test details, collecting user feedback, and enabling messaging between donors, patients, and hospitals.$$\nStudent-2 will handle the Hospital Module, AI-Powered Recommendation, Events Module, Admin Module, Analytics & Reporting Module, Emergency Responses Module, and Social Engagement Module. They will focus on managing registered hospitals, developing AI-driven donor recommendations, organizing donation events, handling blood inventory and patient records, tracking past donation trends, facilitating emergency blood requests, and showcasing success stories to encourage more donors.$$\n$$\n1)\tBlood Donation Application ( Save Life)\r\n2) Blood Donation Website (donateblood.pk)$$\n1. AI Powered Recommendation$$\n2. Analytics and Reporting$$\n3. Blood Testing Details.","user_id":13,"comments":" $$ Make a mobile app instead of website. $$ Add a feature to give user an option to activate the donation mode if he wants to donate the blood. $$ Use messages for communication instead of emails. Add referral system module in your system. $$ It will be a mobile application. Instead of email it is suggeted that they must integrate whatsapp API $$ Instead of Website, it should a mobile app. Members registration must be through referral system. Communication module should be changed (e.g. App messages, whatsapp).","isDraft":0,"status":4,"created_at":"2025-02-20 19:39:26","updated_at":"2025-12-12 22:06:59","isReviewDraft":0,"isInternalDraft":0,"isExternalDraft":0,"isAssign":1,"reviewedDate":"2025-03-17 11:02:27","markedDate":null,"academic_session_id":20,"deleted_at":null,"is_assign_internal_sev":1,"is_assign_internal_eight":1,"is_assign_external_eight":1,"is_evaluated_internal_7th":1,"is_evaluated_internal_8th":1,"is_evaluated_external_8th":null,"member_count":3,"allow_7th_evolution":1,"allow8thEvaluation":1,"external_examiner_id":210,"start_date_time":null,"team_id":190},{"id":1264,"title":"AI-Based X-ray Fracture Detection System with Voice-Assisted Reporting","prob":"Manual X-ray interpretation for fracture detection is time-consuming and prone to human error, leading to delayed diagnoses and potential misjudgments. This project aims to automate fracture detection using deep learning techniques, assisting radiologists in identifying fractures more accurately and efficiently. The system will include a voice-assisted reporting feature, allowing doctors to receive spoken reports of AI-generated diagnoses and provide feedback either by typing or speaking. This will improve accessibility, speed up patient diagnosis, and optimize hospital workflow.","description":"The AI-Based X-ray Fracture Detection System assists doctors in accurately identifying bone fractures using deep learning. The system will be trained on hospital-provided anonymized X-ray images, ensuring it adapts to real-world medical cases.\r\nThe process begins with doctors uploading X-ray scans, which are then preprocessed to enhance image quality. The AI model analyzes these images and detects fractures, providing a confidence score for its predictions. To ensure accuracy, doctors can review, confirm, or correct the AI-generated results through a feedback module, allowing the system to improve over time.\r\nA voice assistant will be integrated into the system, enabling hands-free interaction by reading reports aloud and accepting spoken feedback from doctors. Additionally, the system will generate automated reports in PDF format, securely store patient data, and include heatmap-based AI explanations to highlight detected fracture regions.\r\nThis AI-powered system will reduce diagnostic workload, assist radiologists in decision-making, and improve the speed and accuracy of fracture detection, ultimately leading to better patient outcomes and more efficient hospital operations in net shell.\r\n\r\nThis system will process X-ray images and analyze them using a deep learning-based fracture detection model. Doctors will upload X-ray scans, which will go through image preprocessing before being analyzed by the AI model. The model will then classify fractures and provide a confidence score for its prediction.\r\nDoctors will have the option to review, confirm, or correct AI predictions using a feedback module, ensuring continuous learning and accuracy improvements. Incorrect predictions will be logged for future retraining, allowing the system to evolve.\r\nThe system will also include a voice assistant that reads reports aloud and accepts spoken feedback, automated report generation, secure patient record-keeping, and heatmap-based AI explanations for transparency. This AI-powered solution will significantly reduce diagnostic workload, assist radiologists in decision-making, and improve the speed and accuracy of fracture detection.$$\n1.\tImage Upload & Preprocessing: Doctors upload X-ray images, which are enhanced \r\n using OpenCV.\r\n2.\tAI Fracture Detection: A deep learning model predicts whether a fracture is present.\r\n3.\tVoice-Assisted Reporting: The system reads AI-generated reports aloud for doctors.\r\n4.\tDoctor Feedback Integration: Doctors validate AI predictions either by typing or\r\n \r\n5.\tReport Generation: Automated reports in both text and voice formats for patient\r\n records.\r\n6.\tPatient Management & Record-Keeping: Secure storage of X-ray images, AI results, and\r\n patient history. \r\n7.\tHeatmap Visualization (Explainable AI - XAI): AI-generated Grad-CAM heatmaps\r\n highlight detected fracture regions.\r\n8.\tAutomated Severity Scoring: AI assigns severity levels (Mild, Moderate, Severe) to\r\n fractures$$\n1.\tX-ray Image Processing: Enhances images by adjusting contrast and reducing noise.\r\n2.\tAbnormality Detection & Classification: AI detects and classifies fractures, tumors, or infections.\r\n3.\tMedical Report Generation: Generates reports with severity assessment\r\n4. Image Upload & Preprocessing + AI Model Training$$\n4.\tReal-time AI Assistance: Chatbot answers patient queries regarding their X-ray results.\r\n5.\tExplainable AI (XAI): The system highlights affected areas, compares past cases, and provides text-based explanations for better understanding.\r\n6.\tMedical Imaging Storage Integration: Securely stores processed X-rays for hospitals and medical practitioners.\r\n7. Doctor Feedback Integration + Report Generation$$\n$$\n$$\n1.\tVoice-Assisted Reporting \u2013 AI-generated diagnoses are read aloud, making it easier for doctors to review reports.$$\n2.\tSpeech-to-Text Feedback \u2013 Doctors can give feedback either by typing or speaking, which is recorded for AI improvement$$\n3.\tExplainable AI (Heatmaps) \u2013 Visual representation of detected fracture regions for better understanding and trust in AI predictions.","user_id":26,"comments":" $$ Students are uncertain about the functioning of image enhancement. Likewise, they need clarity on their future course of action, including how they will train the model and how AI will operate and which model will be used for image processing. $$ They have no idea about report genration, how report will be generated for XRAYS $$ Development operation\/modules are limited $$ Student learning is very limited, Lack of Generalization of model","isDraft":0,"status":4,"created_at":"2025-02-24 17:49:29","updated_at":"2025-12-12 17:50:58","isReviewDraft":0,"isInternalDraft":0,"isExternalDraft":0,"isAssign":1,"reviewedDate":"2025-03-12 12:53:24","markedDate":null,"academic_session_id":20,"deleted_at":null,"is_assign_internal_sev":1,"is_assign_internal_eight":1,"is_assign_external_eight":1,"is_evaluated_internal_7th":1,"is_evaluated_internal_8th":1,"is_evaluated_external_8th":null,"member_count":3,"allow_7th_evolution":1,"allow8thEvaluation":0,"external_examiner_id":210,"start_date_time":null,"team_id":null},{"id":1265,"title":"Devhive","prob":"The traditional online learning platforms lack personalized learning paths and real-time AI assistance for web development learners. Many students struggle with understanding key concepts, structuring their learning, and preparing for job opportunities. This project aims to provide an AI-powered learning experience that dynamically adjusts to the learner\u2019s progress, offers coding challenges, and connects students with job opportunities. This solution bridges the gap between learning and employability by ensuring learners gain practical, job-ready skills in web development.","description":"This AI-driven web-based learning platform provides an interactive and structured environment for learning JavaScript, CSS, HTML, and React.js. The system assesses users\u2019 current skill levels through an initial coding test, then tailors a personalized learning path, interactive exercises, and coding-based tests. A dashboard allows learners to track progress, while AI assistance provides real-time support. Additionally, the platform integrates job placement assistance by connecting learners with job opportunities. The platform also features a community integration module linked with Discord, enabling users to engage in discussions, ask questions, and collaborate with other learners in real time.$$\n\u2022 Skill Assessment and Course Recommendation: CodeGemma AI conducts an initial coding test to determine proficiency (beginner, intermediate, or advanced) and assigns an appropriate learning path.\r\n\u2022 Personalized Learning Path: AI dynamically adjusts course content, quizzes, and exercises based on user performance.\r\n\u2022 Dashboard & Progress Tracking: Displays learning progress, completed lessons, and performance analytics.\r\n\u2022 AI Assistance: LLaMA AI provides real-time coding help and debugging support.\r\n\u2022 Final Assessment and Certification: Users take final tests, and certificates are generated based on performance\r\n\u2022 Job Placement Assistance: job listings based on user skills and coursework completion.\r\n\u2022 Community Integration: A Discord-linked community feature enables learners to interact, ask questions, and collaborate with peers.\r\n\u2022 Admin Portal: Admins can update course content, track platform analytics, and manage user interactions.$$\n\u2022 Skill Assessment & Course Recommendation: an CodeGemma AI-based coding test to assess users\u2019 proficiency and assign a learning path.\r\n\u2022 Dashboard & Progress Tracking: Displays completed lessons, progress analytics, and performance tracking.\r\n\u2022 Final Assessment and Certification: Manages final exams and generates certificates based on user performance.\r\n\u2022 Admin Portal: Admins can manage course content, platform analytics, and user interactions.$$\n\u2022 Personalized Learning Path: LLaMA AI dynamically adjusts course content, quizzes, and exercises based on user performance.\r\n\u2022 AI Assistance: LLaMA AI provides real-time coding help and debugging support.\r\n\u2022 Job Placement Assistance: Provide job listings based on user skills.\r\n\u2022 Community Integration: Implements the Discord API for learner collaboration and networking.$$\n$$\n$$\n$$\n$$\n","user_id":3,"comments":" $$ Approved","isDraft":0,"status":4,"created_at":"2025-02-24 23:47:09","updated_at":"2025-12-12 17:50:58","isReviewDraft":0,"isInternalDraft":0,"isExternalDraft":0,"isAssign":1,"reviewedDate":"2025-03-10 10:57:46","markedDate":null,"academic_session_id":20,"deleted_at":null,"is_assign_internal_sev":1,"is_assign_internal_eight":1,"is_assign_external_eight":1,"is_evaluated_internal_7th":1,"is_evaluated_internal_8th":1,"is_evaluated_external_8th":null,"member_count":3,"allow_7th_evolution":1,"allow8thEvaluation":1,"external_examiner_id":210,"start_date_time":null,"team_id":186},{"id":1268,"title":"Qisflex: Interactive Learning Platform for Quantum Computing","prob":"The lack of accessible, interactive quantum computing education hinders enthusiasts, students, and professionals from mastering this emerging field. Existing resources are often theoretical, fragmented, or overly complex, lacking hands-on tools and personalized guidance. This project addresses this by developing a comprehensive Quantum Computing Learning Platform. It offers structured courses with articles, videos, quizzes, and interactive exercises, alongside a custom Quantum Circuit Simulator for practical learning. A RAG-based chatbot provides instant, context-aware assistance, while blogs keep users updated on quantum advancements. By integrating these features, the platform simplifies quantum concepts, fosters practical skills, and tracks user progress, bridging the gap between theoretical knowledge and real-world application. Targeting learners globally, it democratizes quantum education, making it engaging and accessible via a web-based interface, ultimately empowering a broader audience to contribute to quantum innovation.","description":"The Quantum Computing Learning Platform is a web-based application designed to educate users on quantum computing through an interactive, all-in-one experience. It features a course module with articles, videos, quizzes, and interactive exercises to teach quantum concepts progressively. A custom Quantum Circuit Simulator, built with Javascript, mimics IBM Composer, allowing users to design and test quantum circuits visually. A RAG-based chatbot, powered by LangChain and Python, offers real-time, context-aware support by retrieving answers from external quantum resources stored in vector databases. Blogs, authored by admins provide updates and insights on quantum advancements. Admins manage content via a dedicated dashboard built with Laravel and Vue, leveraging Inertia for seamless frontend-backend integration. User progress is tracked by course completion, quiz scores, and exercise outcomes stored in MySQL for personalized feedback. Tailwind ensures a modern, responsive UI, while Tensorflow.js enhances simulator computations. The platform supports login\/logout and authentication as default functionalities, targeting learners worldwide via an online deployment.$$\nThe platform comprises six key modules:\r\n\r\n1. Course Management: Handles creation and delivery of educational content. Admins craft courses with four item types\u2014Articles (TipTap-authored text), Videos, Quizzes (MCQs for assessment), and Exercises (Vue-based interactive tasks teaching quantum concepts like superposition). Users access structured learning paths with progress tracking.\r\n2. Quantum Circuit Simulator: A Javascript-based tool mimicking IBM Composer. Users design quantum circuits using a drag-and-drop interface, apply gates (e.g., Hadamard, CNOT), and simulate results. Tensorflow.js optimizes computations, providing visual outputs like Bloch spheres or probability distributions for hands-on learning.\r\n3. RAG Chatbot: Powered by LangChain and Python, this module uses retrieval-augmented generation to answer user queries. It leverages vector databases storing quantum literature, offering precise, context-aware responses to enhance learning.\r\n4. Blog System: Admins create and publish quantum-related blogs via the TipTap headless editor. Users read updates, tutorials, or research insights, fostering community engagement and knowledge sharing within the platform.\r\n5. Admin Dashboard: Built with Laravel, Vue, and Inertia, this module enables content management (courses, blogs), user oversight, and progress analytics. MySQL stores all data, while Tailwind ensures a sleek, responsive interface for efficient administration.\r\n6. Student Activity Management: The system will manage the student activity including course enrollments, progress tracking, quizzes evaluation, etc.$$\nIn the Quantum Computing Learning Platform, I\u2019ll craft the Quantum Circuit Simulator module, featuring an intuitive drag-and-drop interface, plus the Admin Dashboard, empowering seamless course and blog creation and management with real-time oversight and dynamic content control.$$\nIn the Quantum Computing Learning Platform, I will develop the Student Course and Blog Management module. This provides a structured, engaging learning experience for users. Moreover, I\u2019ll develop the RAG system for this learning platform to let the model make informed responses.$$\n$$\n$$\n$$\n$$\n","user_id":18,"comments":" $$ The idea is new and innovative $$ the idea is new and innovative. And students MUST develop a complete simulator at the end of project and it should be deployed online","isDraft":0,"status":4,"created_at":"2025-02-25 12:51:21","updated_at":"2025-12-12 17:50:58","isReviewDraft":0,"isInternalDraft":0,"isExternalDraft":0,"isAssign":1,"reviewedDate":"2025-03-12 12:53:52","markedDate":null,"academic_session_id":20,"deleted_at":null,"is_assign_internal_sev":1,"is_assign_internal_eight":1,"is_assign_external_eight":1,"is_evaluated_internal_7th":1,"is_evaluated_internal_8th":1,"is_evaluated_external_8th":null,"member_count":3,"allow_7th_evolution":1,"allow8thEvaluation":1,"external_examiner_id":210,"start_date_time":null,"team_id":null},{"id":1269,"title":"Intelligent Clothing Search Engine","prob":"Many online shoppers struggle to find clothing that matches their preferences in fabric, color, price, and design across multiple brands. Currently, users usually visit different brand websites separately, making the process time-consuming and inefficient. No unified platform allows searching for specific clothing items using detailed queries like \u201corange-colored dress with cotton dupatta in the range of 2500 to 4500.\u201d Our solution is a centralized clothing search and comparison platform that enables users to enter queries and receive results from multiple brands in one place. The website presents search results in a structured table with product details, images, prices, and purchase links, saving time and improving shopping efficiency.","description":"Our platform functions as a centralized clothing search and comparison website that gathers real-time data from multiple clothing brands. Users enter specific queries such as fabric type, color, price range, occasion or clothing category. The system processes the query and retrieves relevant clothing options by extracting data from various brand websites. The results are displayed in the form of interactive cards, showing product details, images, prices, and direct purchase links. The frontend, built with Bootstrap, ensures a user-friendly and visually appealing experience, while the backend efficiently handles data extraction and query processing. Users can compare similar items across brands, helping them make informed decisions without switching between multiple websites, thus saving time and effort.$$\nIn Intelligent Clothing Search Engine, the modules are:\r\n(i) Clothing Search & Filtering\r\n(ii) Data Extraction & Management$$\n(i) Clothing Search & Filtering:\r\nThis module enables users to search for clothing items based on fabric, color, price range, category (men, women, kids), and clothing type (stitched\/unstitched). It includes: \r\n(i) A search bar for entering detailed queries. \r\n(ii) Filtering options to refine search results.\r\n(iii) Displaying results in interactive cards with images, descriptions, and prices.\r\n(iv) Providing direct links to brand websites for purchasing.$$\n(ii) Data Extraction & Management:\r\nThis module handles real-time data extraction from multiple brand websites and manages the backend system. It includes:\r\n(i) Web scraping\/crawling to collect product details like price, fabric, and availability.\r\n(ii) Storing and updating data in a structured database.\r\n(iii) Processing user queries to fetch and display relevant products.\r\n(iv) Ensuring data accuracy and synchronization with brand websites.$$\n$$\n$$\n$$\n$$\n","user_id":14,"comments":" $$ Include NLP model in your project $$ Work on feature extraction $$ Data duplication should be dealt with. $$ Question 1: What if the crawler is blocked by the target website? Question 2: By running crawler 2 times on a same website how will the duplicates be removed? Q3 When crawler takes the image then how will the image features will be extracted? Question 4: How will your system understand the prompt? What NLP techinques will be used to understand this.? $$ how duplicate issue will be handled? $$ how system will understand different types of queries. $$ Some functionalities (for example prompt understanding) requires the inclusion of AI in the project.","isDraft":0,"status":4,"created_at":"2025-02-25 14:52:29","updated_at":"2025-12-12 17:50:58","isReviewDraft":0,"isInternalDraft":0,"isExternalDraft":0,"isAssign":1,"reviewedDate":"2025-04-16 10:18:33","markedDate":null,"academic_session_id":20,"deleted_at":null,"is_assign_internal_sev":1,"is_assign_internal_eight":1,"is_assign_external_eight":1,"is_evaluated_internal_7th":1,"is_evaluated_internal_8th":1,"is_evaluated_external_8th":null,"member_count":3,"allow_7th_evolution":1,"allow8thEvaluation":0,"external_examiner_id":210,"start_date_time":null,"team_id":null},{"id":1271,"title":"Animal Selling Platform with Ai Breed Recognition System","prob":"This project makes it easier for people to buy and sell animals. It provides a simple and safe platform where users can look at animals, save favorites, and buy them easily. Sellers can list their animals and manage sales without trouble. An AI tool helps recognize animal breeds from pictures, making sure listings are correct and helping buyers choose wisely. Admins keep the platform safe by checking users and making sure all content follows the rules.","description":"The Animal Selling Platform with Ai Breed Recognition System is a web application that aims to connect animal buyers and sellers in a secure, easy-to-use platform. Buyers can search for animals based on various filters, contact sellers, and make secure purchases. Sellers can create detailed listings, manage them, and track their transactions. Middlemen can mediate deals to ensure secure transactions. The admin will oversee user activity, listings, and system functionality to maintain the platform's integrity.\r\nThe app enables animal buyers to search for animals by various filters, view detailed information, and purchase them securely. Sellers can create animal listings, manage their profiles, and track sales. The admin ensures smooth operation and handles user management, content moderation, and transaction oversight. A deal-making gateway, with the middleman acting as a mediator for deals requiring extra assurance. Additionally, an AI breed recognition module helps ensure the accuracy of animal breed information by analyzing uploaded images.$$\n\u2022\tBuyer Module: Allows buyers to search for animals, view details, add animals to their Wishlist, and make purchases. Includes review and rating functionalities post-purchase.\r\n\u2022\tSeller Module: Enables sellers to manage their profiles, create listings, and track transactions and sales.\r\n\u2022\tAdmin Module: Administers user accounts, manages content moderation, monitors transactions, and ensures system stability.$$\nSeller Module and Admin Module \r\n1. Seller Module\r\n\u2022\tProfile and Portfolio Management\r\n\u2022\tListing Management\r\n\u2022\tPurchasing History\r\n2. Admin Module\r\n\u2022\tContent Moderation\r\n\u2022\tSystem Maintenance\r\n\u2022\tDeal Monitoring\r\n\u2022\tNotification Management$$\nBuyer Module and Admin Module (User Management, Content Moderation)\r\n1.\tBUYER:\r\n\u2022\tHome Page\r\n\u2022\tAnimal Search\r\n\u2022\tAnimal Details\r\n\u2022\tWishlist\/Favorites\r\n\u2022\tAdd to Cart\r\n\u2022\tSales Record\r\n\u2022\tReview and Rating\r\n\u2022\tAI Breed Recognition\r\n2.\tAdmin Module\r\n\u2022\tUser Management$$\n$$\n$$\n$$\n$$\n","user_id":44,"comments":" $$ Make sure your product must list animal related features. like for example https:\/\/www.bakraonline.pk\/ does. $$ No need to add AI breed module. $$ Location based and city based searches must be available. $$ The scope of the project should be lemmatized. Focus on local market instead of international market. $$ AI breed identification should be excluded. $$ Secure transaction and fraudulent data should be handled by the buyer and seller. $$ Enhance features of project by studying existing similar websites. $$ Add an Advanced Search Filter (Filtering animals based on price range, animal name, etc.). $$ Implementing Seller Verification (Verifying sellers through phone number or email). $$ Introducing Seasonal Demand Feature (Highlighting demand during Qurbani Eid). Enhancing Communication (Allowing buyer-seller communication and enabling seller-to-admin contact for selling animals).","isDraft":0,"status":4,"created_at":"2025-02-25 16:51:21","updated_at":"2025-12-12 17:50:58","isReviewDraft":0,"isInternalDraft":0,"isExternalDraft":0,"isAssign":1,"reviewedDate":"2025-03-25 11:06:57","markedDate":null,"academic_session_id":20,"deleted_at":null,"is_assign_internal_sev":1,"is_assign_internal_eight":1,"is_assign_external_eight":1,"is_evaluated_internal_7th":1,"is_evaluated_internal_8th":1,"is_evaluated_external_8th":null,"member_count":3,"allow_7th_evolution":1,"allow8thEvaluation":0,"external_examiner_id":210,"start_date_time":null,"team_id":null}] 0 [{"id":1274,"title":"RoyalAura \u2013Luxury Wedding Fashion & Styling Platform","prob":"The wedding fashion industry doesn\u2019t have a single online platform where people can find luxury wedding dresses, styling, and beauty services all in one place. Brides and grooms often struggle to choose the right outfits, accessories, and beauty services for their big day. There\u2019s also no smart system to help with nail art designs or an easy way to rent wedding dresses and accessories. This project aims to solve these problems by creating a complete online marketplace that offers wedding fashion, beauty services, rental options, and order management\u2014all in one convenient system.","description":"RoyalAura is a web-based platform designed to offer a seamless experience in luxury wedding fashion, beauty services, and rentals. It aims to simplify the process for brides, grooms, and fashion enthusiasts by providing everything they need in one place. The system is built using the MERN stack (MongoDB, Express, React, Node.js) to ensure efficiency and smooth functionality.\r\n\r\nUsers can browse and purchase bridal, groom, and fancy dresses, along with matching accessories such as jewelry, handbags, and footwear. To make wedding fashion more affordable, the platform also offers rental services for dresses and accessories. In addition to fashion, beauty and styling services are a key feature, allowing users to book bridal and groom makeup, hairstyling, skincare treatments, and mehndi services through professional service providers.\r\n\r\nA unique feature of RoyalAura is its AI-powered nail art suggestion tool, which allows users to create or select nail designs based on pre-designed templates. This intelligent system enhances the beauty experience by offering personalized recommendations for nail art.\r\n\r\nFor convenience, the platform includes a shopping and order management system where users can add products to their cart, save items to a wishlist, and place orders with multiple payment options. They can also track their orders and bookings for a hassle-free experience. Bridal and groom packages further streamline wedding preparations by bundling dresses, makeup, and accessories into a single, customizable package.\r\n\r\nThe admin panel plays a crucial role in managing the platform, allowing administrators to oversee products, orders, beauty service bookings, and AI nail art templates. RoyalAura creates an all-in-one digital solution for luxury wedding fashion and styling, making wedding planning easier and more accessible with AI-enhanced beauty features.$$\n1. User Management Module\r\n\r\n User Registration & Login\r\n Profile Management\r\n Wishlist & Order History\r\n Appointment & Rental History\r\n\r\n2. Clothing Collection & Rentals Module\r\n\r\n Bridal & Groom Attire\r\n Party & Formal Wear\r\n Kids\u2019 Dresses\r\n Rental System for Clothing\r\n\r\n3. Parlor & Beauty Services Module\r\n\r\n Bridal & Groom Makeup Booking\r\n Hair & Skincare Treatments\r\n Mehndi (Henna) Services\r\n Appointment Scheduling System for Beauty Professionals\r\n\r\n4. Jewelry & Accessories Module\r\n\r\n Bridal & Casual Jewelry\r\n Fashion Accessories (Handbags, Watches, etc.)\r\n Rental System for Jewelry\r\n\r\n5. Shoes & Footwear Module\r\n\r\n Bridal & Groom Footwear\r\n Traditional & Casual Shoes\r\n\r\n6. AI-Powered Nail Art Suggestions Module\r\n\r\n AI-Generated Nail Art Recommendations\r\n Manual Nail Design Drawing\r\n Pre-Designed Nail Art Templates\r\n\r\n7. Online Shopping & Order Management Module\r\n\r\n Shopping Cart & Checkout\r\n Order Tracking\r\n Payment Gateway Integration (Cash on Delivery, Credit\/Debit Cards, etc.)\r\n Wishlist Management\r\n\r\n8. Bridal & Groom Packages Module\r\n\r\n Customizable Wedding Packages\r\n Combination of Dresses, Jewelry, Makeup, & Accessories\r\n\r\n9. Rental Services Module\r\n\r\n Dress & Jewelry Rental\r\n Rental Request & Approval System\r\n Rental Tracking & Return Management\r\n\r\n10. Flower Collection Module\r\n\r\n Bridal Bouquets & Floral Jewelry\r\n Fresh & Artificial Floral Accessories\r\n\r\n11. Admin Panel\r\n\r\n Product Management (Add, Update, Delete)\r\n Order Processing & Tracking\r\n Beauty Service & Rental Management\r\n AI Nail Art Template Management\r\n User & Vendor Management\r\n\r\n12. Vendor Management Module (if third-party vendors are involved)\r\n\r\n Vendor Registration & Login\r\n Product Listing & Order Fulfillment\r\n Service Provider Profile Management\r\n\r\n13. Review & Rating Module\r\n\r\n Product & Service Reviews\r\n Star Ratings for Vendors & Services\r\n\r\n14. Notification & Communication Module\r\n\r\n Email & SMS Notifications\r\n Order & Appointment Reminders\r\n Chat Support (Optional)\r\n\r\n15. Reports & Analytics Module\r\n\r\n Sales Reports & Revenue Tracking\r\n User Engagement Analytics\r\n Order & Rental Reports$$\nUser Management \u2013 Handles user registration, profiles, wishlist, and history.\r\nClothing Collection & Rentals \u2013 Manages wedding and fancy dress sales and rentals.\r\nParlor & Beauty Services \u2013 Enables booking for makeup, hair, and skincare services.\r\nJewelry & Accessories \u2013 Provides bridal and casual jewelry for purchase and rental.\r\nShoes & Footwear \u2013 Offers bridal, groom, and casual footwear.\r\nBridal & Groom Packages \u2013 Combines dresses, makeup, and accessories into packages.\r\nFlower Collection \u2013 Manages floral accessories, including bouquets and handmade jewelry.$$\nAI-Powered Nail Art Suggestions \u2013 Generates nail designs using AI.\r\nOnline Shopping & Order Management \u2013 Handles cart, checkout, payment, and order tracking.\r\nRental Services \u2013 Manages rental requests and returns for dresses and accessories.\r\nAdmin Panel \u2013 Controls product management, orders, and services.\r\nVendor Management \u2013 Allows vendors to manage their products and services.\r\nReview & Rating \u2013 Enables customers to review products and services.\r\nNotification & Communication \u2013 Sends order updates, reminders, and alerts.\r\nReports & Analytics \u2013 Tracks sales, engagement, and performance metrics.$$\n$$\n$$\n$$\n$$\n","user_id":63,"comments":" $$ There is no use of \"AI-Powered Nail Art Suggestions Module\", therefore, it is suggested to remove this module. $$ In 7th semester, you should have implemented at least one major use case other than user logins and user registrations along with the newly modified designed SRS document. In 8th semester, the FYP MUST be 90% complete in the 14th week. Your website, if any, MUST be online and your App, if any, MUST be in AppStore when you come for internal viva. Your hardware MUST be packed in such a way that it gives the look of a sellable product. $$ Nail suggestion module should be exclude as it goes out of scope. $$ System is very similar to online shopping store, students are not very clear about the difference between this system and online shopping system. $$ Students should deploy this full feldge system. $$ already system available ,Maximum system are online available $$ suggested to Recheck the existing system and add the required modules that are missing and differentiate it","isDraft":0,"status":4,"created_at":"2025-02-26 11:27:25","updated_at":"2025-12-12 17:51:32","isReviewDraft":0,"isInternalDraft":0,"isExternalDraft":0,"isAssign":1,"reviewedDate":"2025-03-19 10:53:36","markedDate":null,"academic_session_id":20,"deleted_at":null,"is_assign_internal_sev":1,"is_assign_internal_eight":1,"is_assign_external_eight":1,"is_evaluated_internal_7th":1,"is_evaluated_internal_8th":1,"is_evaluated_external_8th":null,"member_count":3,"allow_7th_evolution":0,"allow8thEvaluation":1,"external_examiner_id":211,"start_date_time":null,"team_id":null},{"id":1275,"title":"VisionAid: AI Glasses for Visually Impaired person","prob":"The independence of visually impaired people is limited by difficulties with reading, object recognition, and mobility. Conventional aids, such as guiding dogs and canes, offer little help and don't have real-time scene awareness. By combining text-to-speech (TTS), speech-to-text (STT), object detection (YOLOv8), and navigation, AI-powered smart glasses address these problems. Users can read text aloud from books or signs, identify 20 important things, and get auditory cues for difficulties. By directing people around obstacles, the navigation module guarantees safe mobility. These glasses improve accessibility by enabling hands-free interaction via voice commands, which lessens the need for human help and greatly enhances users' daily life","description":"AI-powered smart glasses for visually impaired individuals integrate object recognition, text-to-speech (TTS), speech-to-text (STT), and navigation to enhance mobility and accessibility. The system consists of a camera, processor (Jetson Nano\/Raspberry Pi), microphone, speaker, and optional LiDAR or ultrasonic sensors. The camera captures real-time visuals, enabling YOLOv8 to detect 20 essential objects like vehicles, doors, and traffic lights. The OCR module reads text from books or signs and converts it into speech using TTS, allowing users to access written content effortlessly. STT enables hands-free control, letting users issue voice commands like \"Read this\" or \"Guide me home.\" The navigation module uses GPS and depth sensors to detect obstacles and provide voice-guided movement assistance. The speaker or bone conduction headphones relay real-time feedback, allowing users to navigate, recognize objects, and interact with their surroundings, significantly improving independence and daily life$$\n1)\tDataset Collection 2) Data Preprocessing 3) Model Training 4) Optical character Recognition 5) Navigation 6) text to speech 7) speech to text 8) obstacle and object detection 9) hardware setup and integration$$\nAneeqa Kamran will do the following modules in the project\r\n1)\tDataset Preparation (multiple sources, i.e OpenImages, Kaggle etc)\r\n2)\tDataset Preprocessing\r\n3)\tOptical Character Recognition\r\n4)\tText to speech\/ Speech to Text\r\n5)\tHardware Setup$$\nMuhammad Umer Farooq will do the following modules in the project\r\n1)\tDataset Preparation (multiple sources, i.e OpenImages, Kaggle etc)\r\n2)\tModel Training (yolo v8 or any other version)\r\n3)\tNavigation\r\n4)\tHardware Setup$$\n$$\n$$\n$$\n$$\n","user_id":25,"comments":" $$ Approved $$ The concept is good. Students have well background knowledge. $$ Actions mode should be determined for better user interaction. $$ Approved.","isDraft":0,"status":4,"created_at":"2025-02-26 12:10:56","updated_at":"2025-12-12 17:51:32","isReviewDraft":0,"isInternalDraft":0,"isExternalDraft":0,"isAssign":1,"reviewedDate":"2025-03-14 08:47:42","markedDate":null,"academic_session_id":20,"deleted_at":null,"is_assign_internal_sev":1,"is_assign_internal_eight":1,"is_assign_external_eight":1,"is_evaluated_internal_7th":1,"is_evaluated_internal_8th":1,"is_evaluated_external_8th":null,"member_count":3,"allow_7th_evolution":1,"allow8thEvaluation":1,"external_examiner_id":211,"start_date_time":null,"team_id":null},{"id":1280,"title":"LittleGenius - AI Interactive Learning Hub","prob":"Many young children struggle with early learning due to a lack of interactive tools, while parents lack guidance on teaching foundational concepts.\r\n\r\nLittleGenius: AI Interactive Learning Hub addresses this by:\r\n\u2022 Using animations & interactive exercises to enhance engagement.\r\n\u2022 Providing real-time speech recognition for AI-driven pronunciation feedback.\r\n\u2022 Enabling handwriting recognition for guided writing practice.\r\n\u2022 Implementing AI-powered text-to-speech for reading assistance.\r\n\u2022 Introducing game-based learning activities to reinforce concepts.\r\n\u2022 Offering a parent dashboard to track learning progress.\r\n\r\nThis project ensures a personalized, engaging, and effective learning experience for early learners.","description":"LittleGenius: AI Interactive Learning Hub is a mobile application designed to help pre-school and early-school children develop fundamental learning skills through AI-powered tools and interactive content.\r\nHow It Works:\r\n\u2022 The child interacts with animated lessons covering alphabets, numbers, shapes, colors, and basic concepts.\r\n\u2022 AI-powered Speech Recognition listens to the child\u2019s spoken words and provides instant feedback on pronunciation.\r\n\u2022 AI-based Handwriting Recognition allows children to write letters\/numbers on-screen, providing real-time corrections.\r\n\u2022 Text-to-Speech (TTS) narrates lessons and built-in stories, making learning more engaging.\r\n\u2022 Parents receive guidance on early education and can track their child's progress through a Parent Dashboard.\r\n\u2022 Mini-games & fun activities reinforce learning concepts in an interactive way.\r\nThis project leverages AI & animations to provide a personalized, engaging, and effective learning experience, while also helping parents set a strong foundation for their child\u2019s education.$$\n(i) AI Speech Recognition (Voice Interaction):\r\nConverts speech to text using AI models and provides real-time feedback.\r\nDetects pronunciation errors, highlights mistakes, and suggests corrections.\r\n\r\n(ii) On-Screen Handwriting Recognition:\r\nDetects and recognizes letters\/numbers written on-screen using AI models.\r\nCompares handwriting with correct patterns and provides real-time feedback.\r\n\r\n(iii) AI Text-to-Speech (TTS):\r\nConverts text into natural-sounding speech using AI-powered TTS models.\r\nReads out lessons and stories in a kid-friendly voice with adjustable speed.\r\n\r\n(iv) Engaging Animations & Interactive Learning:\r\nUses animations and interactive exercises to make learning fun and engaging.\r\nReinforces concepts through visual storytelling, gamified lessons, and interactive quizzes.\r\n\r\n(v) Fun Learning Activities & Mini-Games:\r\nIncludes educational mini-games to reinforce concepts through play-based learning.\r\nAdapts difficulty levels based on the child\u2019s progress for a personalized experience.\r\n\r\n\r\n(vi) Parent Dashboard & Progress TrackingProvides basic tracking of the child\u2019s learning progress.$$\n(i) Handwriting Recognition System \u2013 Identifies letters\/numbers written on the screen.\r\n(ii) Real-Time Feedback \u2013 Compares handwriting with correct patterns and suggests improvements.\r\n(iii) Parent Dashboard \u2013 Allows parents to track their child\u2019s learning progress.\r\n(iv) Progress Reports \u2013 Displays learning statistics, including completed activities and accuracy.$$\n(i) AI-powered Speech Recognition \u2013 Converts speech into text and provides real-time feedback.\r\n(ii) Pronunciation Analysis \u2013 Detects errors in spoken words and suggests corrections.\r\n(iii) AI Text-to-Speech (TTS) \u2013 Reads out lessons and built-in stories in a kid-friendly voice.\r\n(iv) Feedback System \u2013 Provides auditory and visual feedback for better engagement.$$\n$$\n\"Little Learners\u201d: Focus on providing educational content, promoting safe and healthy screen time for kids.$$\n1. AI Speech Recognition for real-time pronunciation feedback.$$\n2. On-Screen Handwriting Recognition to help kids practice writing.$$\n3. AI-Powered Text-to-Speech for narrating lessons & stories.","user_id":34,"comments":" $$ Stdudents have very limited knowledge of the project and do not know how the taks will be achieved. $$ they must be familiar about next course of action, how text will be recognized and how system will handle user interction. $$ students must be vigilent for the progress and completion of the project $$ Idea is well ,cover all module $$ In 7th semester, you should have implemented at least one major use case other than user logins and user registrations along with the newly modified designed SRS document. In 8th semester, the FYP MUST be 90% complete in the 14th week. Your website, if any, MUST be online and your App, if any, MUST be in AppStore when you come for internal viva. Your hardware MUST be packed in such a way that it gives the look of a sellable product.","isDraft":0,"status":4,"created_at":"2025-02-26 15:17:19","updated_at":"2025-12-12 17:51:32","isReviewDraft":0,"isInternalDraft":0,"isExternalDraft":0,"isAssign":1,"reviewedDate":"2025-03-12 13:00:04","markedDate":null,"academic_session_id":20,"deleted_at":null,"is_assign_internal_sev":1,"is_assign_internal_eight":1,"is_assign_external_eight":1,"is_evaluated_internal_7th":1,"is_evaluated_internal_8th":1,"is_evaluated_external_8th":null,"member_count":3,"allow_7th_evolution":1,"allow8thEvaluation":0,"external_examiner_id":211,"start_date_time":null,"team_id":null},{"id":1281,"title":"Eye tracking based cursor control for hands free computer operation","prob":"This project addresses the accessibility challenges faced by individuals with hand mobility impairments. Traditional computer interaction methods rely on physical input devices like a mouse and keyboard, making it difficult for people with disabilities to perform essential computing tasks. Our system provides a hands-free solution by allowing users to control the cursor using eye movements, perform clicks through blinking, and type using an on-screen keyboard with gaze-based selection. This will enhance digital accessibility, independence, and efficiency for users with limited hand functionality.","description":"The proposed system enables hands-free computer operation using eye-tracking technology. It translates eye movements into cursor actions, allowing users to navigate interfaces, perform clicks via blinking, and use an on-screen keyboard for text input. Additional features include speech-to-text for efficient typing, voice commands for executing actions, and customized gesture recognition. The project aims to enhance accessibility and productivity for individuals with mobility limitations, particularly handymen who require digital assistance.$$\n\u2022\tComputer Navigation: Control the cursor using eye movement, click, scroll, and drag objects. The eye movement is detected through camera and cursor is moved accordingly. Clicking and scrolling will be done through blinking and eye gestures.\r\n\u2022\tApplication Usage: Open, close, switch between applications, and navigate web browsers, emails, and file explorers.\r\n\u2022\tText Input & Communication: Use an on-screen keyboard with gaze-based selection, speech-to-text for faster input, and compose\/send emails, messages, and documents.\r\n\u2022\tProductivity & Work Management: Edit documents and spreadsheets, manage task lists and work schedules, and interact with industry-specific software.\r\n\u2022\tCustomization & Accessibility Features: Adjust gaze sensitivity, integrate predictive text, and customize shortcut keys.\r\n\u2022\tLearning & Training Support: Access tutorials and learning materials via the eye-tracking interface.$$\n\u2022\tDeep learning-based eye-tracking model for cursor movement\r\n\u2022\tClick and scroll functionalities using blinking\r\n\u2022\tSensitivity adjustment and calibration module\r\n\u2022\tIntegration with system accessibility features$$\n\u2022\tOn-screen keyboard for gaze-based text input\r\n\u2022\tVoice command integration for additional controls\r\n\u2022\tPredictive text implementation using NLP models\r\n\u2022\tUI\/UX design for accessibility optimization$$\n$$\n$$\n$$\n$$\n","user_id":6,"comments":" $$ work on accessibility of the system $$ Take good background knowledge of the eye tracking with respect to the pixel locations $$ Please figure out which gestures should be used for which actions. $$ Finalize the technoligies which will be used to accomplish this. What API will be used for what purpose. $$ Also list the gestures which will be used to do different tasks. $$ Some accessibility option (for example, mobile phone gesture control) can be added in the project.","isDraft":0,"status":4,"created_at":"2025-02-26 15:21:52","updated_at":"2025-12-12 17:51:32","isReviewDraft":0,"isInternalDraft":0,"isExternalDraft":0,"isAssign":1,"reviewedDate":"2025-03-25 11:09:59","markedDate":null,"academic_session_id":20,"deleted_at":null,"is_assign_internal_sev":1,"is_assign_internal_eight":1,"is_assign_external_eight":1,"is_evaluated_internal_7th":1,"is_evaluated_internal_8th":1,"is_evaluated_external_8th":null,"member_count":3,"allow_7th_evolution":1,"allow8thEvaluation":0,"external_examiner_id":211,"start_date_time":null,"team_id":null},{"id":1282,"title":"AI-Powered Plant Disease Detection and Cure Recommendation System","prob":"Agriculture is the backbone of Pakistan\u2019s economy, yet many farmers, in rural areas, struggle with plant disease identification and treatment due to a lack of education and awareness of modern technologies. Traditionally, they rely on government agricultural offices for guidance, leading to delays and inconsistent advice. In many cases, by the time farmers receive expert recommendations, the damage is irreversible, leading to significant crop losses. To address this issue, our project introduces an AI-powered web application that enables farmers and plant enthusiasts to detect plants and diseases instantly by capturing and uploading images. The system will analyze the plant, detect potential diseases, and suggest appropriate treatments using a chatbot-driven knowledge base. This solution aims to empower farmers with accurate, timely, and accessible information, reducing dependence on external consultation and improving overall agricultural productivity.","description":"The AI-Powered Plant Disease Detection and Cure Recommendation System is a web-based application that uses Artificial Intelligence and Image Processing to detect plant diseases and provide real-time solutions. Users can upload or capture plant images, and the system will analyze them using an AI model to identify plant diseases. A chatbot-driven cure recommendation system will provide treatment options based on a predefined knowledge base.\r\nAdditionally, an admin panel will allow experts to update disease-related information, ensuring the system remains accurate and up to date. This project will act as a virtual agricultural assistant, helping farmers detect diseases early, reduce losses, and improve yield efficiency.$$\n1) User Registration & Authentication: Users can create an account and log in securely using email, phone number, or social media credentials. Authentication ensures personalized access to disease history, recommendations, and user preferences.\r\n2) Plant & Disease Detection: Users can upload plant images or capture real-time photos to detect plant diseases. The system identifies the plant species and matches symptoms using an AI-powered model.\r\n3) Chatbot for Disease Solutions: An AI-driven chatbot provides instant diagnostic results and treatment suggestions. It supports multiple languages to assist farmers with limited literacy in understanding solutions.\r\n4) Image Processing & AI Model Integration: The project integrates deep learning algorithms for analyzing plant images. Pre-trained AI models process leaf patterns, color variations, and texture differences to detect diseases.\r\n5) Cure Recommendation System: Based on detected diseases, the system suggests organic, chemical, and preventive treatments. Recommendations include fertilizers, pesticides, home remedies, and best farming practices.\r\n6) User Dashboard: Users can view their previous diagnoses, recommended treatments, and disease trends. Provides insights on plant health monitoring over time for better crop management.\r\n7) Admin Panel: Admins can update the AI model, manage user queries, and add new disease data. Includes analytics and reporting features to track disease trends and system performance.$$\nPlant & Disease Detection\r\n\r\nImplement image processing and AI Model Integration\r\n\r\nTrain and integrate the machine learning model\r\n\r\nChatbot & Cure Recommendation System\r\n\r\nDevelop cure recommendation database$$\nUser registration and authentication \r\nIntegrate login and registration for users and admin\r\nProfile management for both users\r\nDesign and implement the user dashboard and admin panel$$\n$$\n1.Plant detection system\r\n2.Plant disease detection$$\nAI-powered real-time plant disease detection$$\nChatbot-driven cure recommendations$$\nAdmin panel for continuous knowledge base updates","user_id":29,"comments":" $$ Instead of web application develop a mobile application $$ Scope of the project is limited. Add more modules in your system. $$ You should have experts in your contact for providing cures. $$ It suggested that this product will be a mobile application not the web. Also list the diseases and cure suggestion will from the local zarai markaz. $$ Cure Recommendation for the diseases should be followed by some authetic solution provider (e.g. Zari Markaz). Instead of Website, it should a mobile app.","isDraft":0,"status":4,"created_at":"2025-02-26 15:59:21","updated_at":"2025-12-12 17:51:32","isReviewDraft":0,"isInternalDraft":0,"isExternalDraft":0,"isAssign":1,"reviewedDate":"2025-03-25 11:10:30","markedDate":null,"academic_session_id":20,"deleted_at":null,"is_assign_internal_sev":1,"is_assign_internal_eight":1,"is_assign_external_eight":1,"is_evaluated_internal_7th":1,"is_evaluated_internal_8th":1,"is_evaluated_external_8th":null,"member_count":3,"allow_7th_evolution":0,"allow8thEvaluation":0,"external_examiner_id":211,"start_date_time":null,"team_id":null},{"id":1283,"title":"RoadRescue: Smart Helmet for Bikers Safety","prob":"Motorcycle accidents are a leading cause of traffic-related fatalities worldwide. Many lives are lost due to delayed medical assistance, lack of preventive measures, and rider negligence. Additionally, riders often neglect helmet usage, increasing the risk of severe injuries. Parents also face concerns regarding the safety of children riding motorcycles. Our Final Year Project (FYP) aims to address these issues by developing an AI-based smart helmet that enforces helmet compliance, detects accidents, prevents potential hazards, and ensures timely communication with emergency contacts and services.","description":"The proposed solution, RoadRescue, is a comprehensive safety system integrating hardware sensors and AI-based software solutions to enhance motorcycle rider safety. The system ensures that the bike will not start unless the rider is wearing the helmet.\r\n\r\nIn case of an emergency, RoadRescue automatically shares the rider\u2019s GPS location with emergency contacts and enables a voice-enabled chatbot to call an ambulance through VoIP integration. For child safety, the system allows parents to monitor their child\u2019s route in real-time using GPS tracking and route anomaly detection with LSTM models, ensuring that unauthorized rides are detected and prevented.$$\nIn Our RoadRescue Mobile App following are the Modules:\r\n1. Accident Detection\r\n2. Emergency Communication\r\n3. Calling Ambulance\r\n4. Helmet Compliance\r\n5. Route Tracking \r\n6. Gesture-Based Call Management\r\n7. Speed limiter$$\nIn RoadRescue APP, I shall develop:\r\n1. Accident Detection (Using an impact sensor, accelerometer, and gyroscope).\r\n2. Emergency Communication (Rider's location to family members).\r\n3. Route Tracking (Route Monitoring).\r\n4. Speed limiter (Alert Rider incase of Over Speeding).$$\nIn RoadRescue APP, I shall develop:\r\n1. Ambulance Calling (Using AI voice agent and GPS)\r\n2. Helmet Compliance (Helmet Detection through AI to Start Bike Ignition)\r\n3. Gesture-Based Call Management (Attend, hangup call and Volume control without actually taking Phone out).$$\n$$\n$$\n$$\n$$\n","user_id":15,"comments":"","isDraft":0,"status":4,"created_at":"2025-02-26 16:26:18","updated_at":"2025-12-12 17:51:32","isReviewDraft":0,"isInternalDraft":0,"isExternalDraft":0,"isAssign":1,"reviewedDate":"2025-03-14 08:53:01","markedDate":null,"academic_session_id":20,"deleted_at":null,"is_assign_internal_sev":1,"is_assign_internal_eight":1,"is_assign_external_eight":1,"is_evaluated_internal_7th":1,"is_evaluated_internal_8th":1,"is_evaluated_external_8th":null,"member_count":3,"allow_7th_evolution":1,"allow8thEvaluation":0,"external_examiner_id":211,"start_date_time":null,"team_id":null},{"id":1287,"title":"Automated Multilanguage Invoice OCR System","prob":"The fintech industry is making a lot of progress and providing solutions for different problems. Different sectors still relies on the manual invoice reimbursements. This requires trained human resources along with time for processing. It is highly important to design an automated system that can automatically understand the invoices and make reimbursements online. However, this fintech solution has many challenges as these invoices are from different sectors and in different formats. These invoices not only have variations in format but also in typed computerized text and handwritten text. To handle all these variations to design an automated solution remains a challenging task. In this system, the objective is to automate the process of reading and extracting invoice data (Typed and handwritten text) from images or PDFs using latest deep learning techniques. This will significantly reduce the manual effort and time required to process large volumes of invoices.","description":"The Automated Invoice Processing System is a web-based fintech solution designed to address the challenges of manual invoice reimbursements by automating the extraction and processing of invoice data from images and PDFs using advanced deep learning techniques. Many industries still rely on human effort for invoice validation and reimbursement, which is both time-consuming and resource-intensive. This system aims to reduce manual workload, improve processing efficiency, and accelerate reimbursements by automatically extracting key invoice details from diverse invoice formats, including both typed and handwritten text.\r\nUsers can upload invoices in image or PDF format, and the system utilizes AI-driven OCR technology to analyze and extract essential details such as invoice number, date, item descriptions, prices, taxes, and total amounts. Since invoices vary significantly across industries in structure and format, the system is trained to handle these variations effectively, ensuring high precision in recognizing and organizing invoice data.\r\nOnce extracted, the invoice data is displayed on a user-friendly web interface, allowing users to review and validate the information before processing reimbursements. Additionally, the system enables businesses to export extracted data in Excel format, facilitating easy storage, retrieval, and financial analysis.\r\nTo further enhance accuracy, the system integrates a continuous learning mechanism, allowing the AI model to adapt to different invoice styles over time. By leveraging deep learning and OCR advancements, the system improves its ability to correctly interpret invoices, reducing errors and enhancing automation in financial workflows.\r\nAs a web-based application, the system is accessible from any device with an internet browser, eliminating the need for specialized software installations. This ensures flexibility and ease of use, making it a valuable tool for businesses handling large volumes of invoices. Overall, this project aims to streamline invoice management, minimize human intervention, and enhance financial automation in the fintech sector.$$\n1. Invoice Upload Module:\r\n\u2022\tFile Handling: Enables users to upload invoices in different formats such as PDF, JPEG, and PNG.\r\n\u2022\tPreprocessing: Applies image enhancement techniques, noise reduction, and skew correction to improve OCR accuracy.\r\n2. Data Annotation Module:\r\n\u2022\tData Labeling for English: Annotates typed and handwritten English invoices to train the AI model.\r\n\u2022\tData Labeling for Arabic: Annotates typed Arabic invoices to enable multi-language support.\r\n3. Text Detection Module:\r\n\u2022\tText Detection for English and Arabic: Identifies text regions within the invoice image to locate key fields.\r\n\u2022\tBounding Box Generation: Highlights detected text areas for recognition and validation.\r\n4. Text Recognition Module:\r\n\u2022\tText Recognition for English and Arabic: Extracts both printed and handwritten text from invoices in multiple languages.\r\nDeep Learning Model Training Module:\r\n\u2022\tTraining for Typed English: Develops AI models to extract text from typed English invoices.\r\n\u2022\tTraining for Handwritten English: Trains models to recognize handwritten text in invoices.\r\n\u2022\tTraining for Typed Arabic: Trains models to process computer-typed Arabic invoices.\r\nModel Testing Module:\r\n\u2022\tTesting for Typed English: Evaluates the accuracy of text recognition for typed English invoices.\r\n\u2022\tTesting for Handwritten English: Measures the model\u2019s effectiveness in extracting handwritten English text.\r\n\u2022\tTesting for Typed Arabic: Tests recognition capabilities for typed Arabic invoices.\r\n5. Data Analytics:\r\n\r\n\u2022\tAlgorithm Design: Develop an algorithm for data analytics.\r\n\u2022\tInsights & Visualizations: Generate reports on invoice trends.\r\n\u2022\tKey Metrics: Track total invoice amounts, frequently invoiced products\/services, and payment cycles.\r\n\u2022\t Dashboards: Provide interactive visualizations with filters for date range, company, and invoice type.\r\n6. Data Display Module:\r\n\u2022\tWeb Interface: Provides a user-friendly dashboard to display extracted invoice data.\r\n7. API Integration Module:\r\n\u2022\tInvoice Upload API: Allows external applications to submit invoices for processing.\r\n\u2022\tData Processing API: Handles the extraction and transformation of invoice data.\r\n\u2022\tResult Display API: Provides structured invoice data for third-party system integration.\r\n8. Data Export Module:\r\n\u2022\tExcel, PDF & CSV Export: Enables users to save extracted data in multiple formats for accounting integration.\r\n\u2022\tStructured Report Generation: Produces detailed invoice reports in structured formats for business use.$$\n\u2022\tData Labeling for Arabic: Handles annotation of typed Arabic invoices.\r\n\u2022\tText Detection : Implements text detection algorithms for invoices.\r\n\u2022\tDeep Learning Model Training (Typed Arabic & English Detection): Develops AI models for Arabic invoices and English detection improvements.\r\n\u2022\tModel Testing for Arabic (Typed): Evaluates and improves recognition performance for Arabic invoices.\r\n\u2022\tData Analytics: Implements Data analytics, reports, trends.\r\n\u2022\tAPI Development for Data Processing & Result Display: Implements structured API endpoints for data handling.\r\n\u2022\tUser Authentication & Security: Implements role-based access control and encryption.$$\nAbdul Basit:\r\n\u2022\tInvoice Upload & Preprocessing: Implements file handling and image preprocessing.\r\n\u2022\tData Labeling for English: Annotates typed and handwritten English invoices.\r\n\u2022\tText Detection : Implements text detection algorithms.\r\n\u2022\tDeep Learning Model Training (Typed English & Handwritten English): Develops AI models for typed and handwritten English invoices.\r\n\u2022\tModel Testing for English (Typed & Handwritten): Evaluates text recognition accuracy for English invoices.\r\n\u2022\tAPI Development for Invoice Processing: Implements REST APIs for invoice extraction and integration.\r\n\u2022\tExport Module & Structured Report Generation: Develops functionalities for Excel, PDF, and CSV export.$$\n$$\n$$\n$$\n$$\n","user_id":52,"comments":" $$ Students have limited knowledge about the future course of action, including how OCR will function and how handwritten invoices will be identified. Since this is a crucial aspect, they have not yet worked on datasets or identified potential datasets for training. $$ Can use arabic tokenizers for this purpose. $$ Students MUST upload the industry letter to RMS $$ Modules are recommended to be implement directly without conversion to English $$ Review the project modules","isDraft":0,"status":4,"created_at":"2025-02-26 18:06:04","updated_at":"2025-12-12 17:51:32","isReviewDraft":0,"isInternalDraft":0,"isExternalDraft":0,"isAssign":1,"reviewedDate":"2025-03-27 12:52:48","markedDate":null,"academic_session_id":20,"deleted_at":null,"is_assign_internal_sev":1,"is_assign_internal_eight":1,"is_assign_external_eight":1,"is_evaluated_internal_7th":1,"is_evaluated_internal_8th":1,"is_evaluated_external_8th":null,"member_count":3,"allow_7th_evolution":1,"allow8thEvaluation":1,"external_examiner_id":211,"start_date_time":null,"team_id":null}] 0 [{"id":1289,"title":"MediPredict system (Volunteer Doctor & Disease Prediction System)","prob":"Millions worldwide, especially in remote areas, lack access to timely medical care due to doctor shortages, overcrowded hospitals, and high costs, leading to delayed diagnoses and severe complications. Even in urban areas, identifying symptoms before consulting a doctor can cause unnecessary panic or delays. The MediPredict system bridges this gap by offering a web-based platform where patients connect with volunteer doctors for free or low-cost consultations. It features AI-driven disease prediction, live chat and video consultations, secure medical record management, appointment scheduling, and data encryption, ensuring accessible, efficient, and secure healthcare for all.","description":"The MediPredict system is a web-based healthcare platform that enables patients to connect with volunteer doctors for free or low-cost consultations. The system integrates AI-powered disease prediction based on symptoms and incorporates real-time message translation through NLP in live chat consultations to eliminate language barriers between doctors and patients.\r\nThe platform allows patients to input symptoms, which an AI model analyzes to predict potential diseases. It supports live chat and video consultations, with real-time NLP-based message translation ensuring effective doctor-patient communication across different languages. Additionally, the system provides secure medical record management, enabling users to store and access prescriptions, reports, and consultation history. Appointment scheduling ensures seamless doctor-patient interactions, while data encryption and security protocols protect patient privacy.\r\nObjectives:\r\n\u2022\tProvide accessible and affordable healthcare through volunteer doctors.\r\n\u2022\tEnable AI-powered disease prediction for early symptom-based diagnosis.\r\n\u2022\tFacilitate real-time message translation via NLP in live chat consultations.\r\n\u2022\tSupport secure video & chat consultations for remote healthcare access.\r\n\u2022\tOffer medical record management for prescriptions and reports.\r\n\u2022\tEnsure data privacy and security through encryption and access controls.\r\nBy combining AI-driven diagnosis, NLP translation, and telemedicine services, the system improves healthcare accessibility, early disease detection, and seamless multilingual doctor-patient interactions.$$\nIn the MediPredict system the modules are as follows:\r\n\r\n1: Doctor & Patient Dashboard\r\n2: Appointment Scheduling\r\n3: Live Chat & Video Consultation\r\n4: Message Translation (NLP)\r\n5: AI-Powered Disease Prediction\r\n6: Medical Records & Prescription Management\r\n7: User Profile Management\r\n8: Patient Feedback & Ratings$$\nIn the MediPredict system I shall develop the following modules\r\no\tAppointment Scheduling\r\no\tLive Chat & Video Consultation\r\no\tMessage Translation (NLP)\r\no\tAI-Powered Disease Prediction$$\nIn the MediPredict system I shall develop the following modules\r\no\tDoctor & Patient Dashboard\r\no\tMedical Records & Prescription Management\r\no\tAdmin Profile Management\r\no\tPatient Feedback & Ratings$$\n$$\nVolunteer online doctor system$$\nReal-time Message Translation (NLP):$$\nAI-Powered Disease Prediction$$\nMedical Records & Prescription Management","user_id":38,"comments":" $$ lack of understanding of Module, need more research of module $$ check dataset and identify the disease to be targeted $$ students have very limited knoweldge of the future course of action. $$ They must identify the targeted diseases and relevant datasets. Their limited understanding of the system could lead them to a dead end. $$ Scope of the project must be defined, Like which languages will be targetted by NLP, which disease dataset will be trained for model","isDraft":0,"status":4,"created_at":"2025-02-26 19:19:27","updated_at":"2025-12-12 17:52:04","isReviewDraft":0,"isInternalDraft":0,"isExternalDraft":0,"isAssign":1,"reviewedDate":"2025-03-27 12:53:47","markedDate":null,"academic_session_id":20,"deleted_at":null,"is_assign_internal_sev":1,"is_assign_internal_eight":1,"is_assign_external_eight":1,"is_evaluated_internal_7th":1,"is_evaluated_internal_8th":1,"is_evaluated_external_8th":null,"member_count":3,"allow_7th_evolution":0,"allow8thEvaluation":1,"external_examiner_id":212,"start_date_time":null,"team_id":null},{"id":1290,"title":"HealConnect : AI-Powered Anonymous Therapy & Mental Wellness Tracking","prob":"Mental health issues have been on the rise globally, yet many individuals struggle to seek help due to social stigma, lack of awareness, and accessibility constraints. Psychological disorders such as depression, anxiety, PTSD, and stress-related conditions are often left untreated because patients fear being judged or misunderstood. Our Final Year Project (FYP) aims to address these challenges by developing an innovative mobile application that facilitates private, secure, and professional interactions between patients and therapists. By incorporating Natural Language Processing (NLP), the app will analyze textual data from patients to monitor their progress and provide personalized support.","description":"Our Final Year Project (FYP) focuses on raising awareness about mental and psychological issues, especially for individuals who struggle to openly share their problems. We aim to develop a mobile application that connects patients with professional therapists while ensuring complete anonymity for both. This anonymity will encourage patients to share their thoughts, feelings, and past traumas without fear of judgment. The app will provide a secure platform where users can seek therapy and receive guidance from professionals. Additionally, we will integrate Natural Language Processing (NLP) to analyze the textual data of patients, tracking their emotional progress on a weekly basis. By implementing emotional and sentiment tracking, the app will assess the user's mood based on their interactions, allowing therapists to gain deeper insights into their mental well-being and provide personalized therapy sessions. Furthermore, we will introduce a community support feature, where users can join peer groups anonymously to share experiences, offer mutual support, and engage in guided discussions. AI moderation will ensure a safe and supportive environment by filtering harmful content and maintaining respectful conversations. This combination of technology and mental healthcare will create a comprehensive, accessible, and effective solution, fostering emotional healing, reducing isolation, and promoting overall mental well-being.$$\n1 : User Authentication & Anonymity Module\r\n2 : Patient-Therapist Matching Module\r\n3 : NLP based communication\r\n4: Providing resources to heal patient\r\n5 : Assessment of the patient on regular basis on text using NLP\r\n6 : Provide community support \r\n6 : Feedback & Review Module$$\nNLP based discussion with therapist , Analysing patient behavior through text using NLP,provide community support , feedback & review module will be developed by Fazal-ur-Rehman (SP22-BCS-062)$$\nUser authentication module ,Patient therapist matching module , security & anonymity of users , fetching data from different APIs will be developed by Huzaifa Sarfaraz ( SP22-BCS-064)$$\n$$\nPsychePal : Development of an AI-Powered Virtual Psychiatrist for Mental Health Support$$\n1.\tNLP based communication$$\n2. Analysing patient situation through text$$\n3. Assessing patient on timely basis and providing community support","user_id":79,"comments":" $$ Already existing website suggestion is to check the sites for comparison. $$ Idea change is suggested $$ The students are unclear about the future development of the project, as they lack prior knowledge of emotion datasets. And they dont know how they will train model with dataset. $$ A change of idea is recommended, or the students must have a clear course of action moving forward. $$ The modules listed are insufficient for the FYP. Please add authentic modules that also cover the custom development aspect. $$ Idea change is suggested as the modules are already implemented","isDraft":0,"status":4,"created_at":"2025-02-26 19:22:57","updated_at":"2025-12-12 17:52:04","isReviewDraft":0,"isInternalDraft":0,"isExternalDraft":0,"isAssign":1,"reviewedDate":"2025-04-07 13:10:52","markedDate":null,"academic_session_id":20,"deleted_at":null,"is_assign_internal_sev":1,"is_assign_internal_eight":1,"is_assign_external_eight":1,"is_evaluated_internal_7th":1,"is_evaluated_internal_8th":1,"is_evaluated_external_8th":null,"member_count":3,"allow_7th_evolution":1,"allow8thEvaluation":0,"external_examiner_id":212,"start_date_time":null,"team_id":null},{"id":1291,"title":"SheinReview","prob":"ReviewNext helps mobile and laptop buyers make informed purchasing decisions by providing reliable and verified reviews. Many customers rely on biased or insufficient reviews, leading to poor choices. This platform ensures that buyers get authentic user experiences before making a purchase, reducing fraud risks and increasing consumer confidence.","description":"ReviewNext is a web-based platform specifically designed for mobile and laptop buyers. It provides a space for users to read and write product reviews, share complaints, and offer suggestions. The platform ensures that buyers make informed decisions by offering unbiased and research-backed knowledge.\r\n\r\nCustomers prefer visiting our website before exploring other platforms because we provide generic product information along with detailed research insights. This helps users gain a well-rounded understanding of products before making a purchase decision. By offering a centralized source of unbiased information, buyers can compare different options before finalizing their purchase.\r\n\r\nUsers can search for mobile phones and laptops, read verified reviews, and share their own experiences. The platform is dedicated exclusively to these two product categories. Additionally, AI sentiment analysis will be integrated to assess review authenticity and overall sentiment trends, ensuring buyers receive reliable feedback.\r\n\r\nKey Functionalities:\r\n\r\nUser Reviews & Ratings (specific to mobile & laptop brands and models)\r\n\r\nComplaint & Dispute Management (focused on tech-related issues like performance, durability, service centers, etc.)\r\n\r\nProduct Suggestion System (helps users choose the best mobile or laptop based on their needs and budget)\r\n\r\nSearch & Filtering (filter by brand, specs, price, and reviews)\r\n\r\nReview Authentication (detecting fake reviews for laptops and mobiles specifically)\r\n\r\nAdmin Dashboard\r\n\r\nApproach to Seller$$\nReviewNext\r\n1.User Reviews & Ratings\r\n\r\n2.Complaint & Dispute Management\r\n\r\n3. Product Suggestion System\r\n\r\n4. User Profile & Management\r\n\r\n5. Review Authentication\r\n\r\n6. Admin Dashboard\r\n\r\n7. Approach to Seller$$\nAqsa Fayyaz shall develop the following modules:\r\n\r\nComplaint & Dispute Management\r\n\r\nProduct Suggestion System\r\n\r\nUser Profile & Management\r\n\r\nAdmin Dashboard\r\n\r\nAqsa Fayyaz will be responsible for implementing these modules, ensuring smooth user interaction, efficient product suggestions, and an organized complaint system. The admin dashboard will allow proper monitoring and management of platform activities.$$\nNazir Hussain shall develop the following modules:\r\n\r\nUser Reviews & Ratings\r\n\r\nReview Authentication\r\n\r\nApproach to Seller\r\n\r\nNazir Hussain will be responsible for implementing these modules, ensuring they function correctly and integrate well with the platform. These modules will help users provide reliable feedback, authenticate reviews, and connect with sellers efficiently.$$\n$$\n$$\n$$\n$$\n","user_id":40,"comments":" $$ The students have no understanding of the project yet; they don\u2019t even know what they\u2019re going to develop. They need to either come up with a clear idea or define the scope of the project more specifically. $$ The students are proposing to create a website focused solely on reviews, but this wouldn't be a valuable product to develop, as it\u2019s unlikely anyone would use it. $$ If they can gather data related to a product and then perform sentiment analysis on the reviews to identify fake ones, it could be a promising product. Students should either refine their idea or clearly define the scope of the product.","isDraft":0,"status":4,"created_at":"2025-02-26 19:24:37","updated_at":"2025-12-12 17:52:05","isReviewDraft":0,"isInternalDraft":0,"isExternalDraft":0,"isAssign":1,"reviewedDate":"2025-03-27 12:55:16","markedDate":null,"academic_session_id":20,"deleted_at":null,"is_assign_internal_sev":1,"is_assign_internal_eight":1,"is_assign_external_eight":1,"is_evaluated_internal_7th":1,"is_evaluated_internal_8th":1,"is_evaluated_external_8th":null,"member_count":3,"allow_7th_evolution":1,"allow8thEvaluation":0,"external_examiner_id":212,"start_date_time":null,"team_id":190},{"id":1293,"title":"OptiAI","prob":"OptiAI addresses real-world challenges by integrating AI, voice recognition, and computer vision into a wearable device, ensuring seamless and hands-free access to information.\r\nOne major issue it solves is accessibility for visually impaired individuals, who often struggle with recognizing objects or accessing real-time information. OptiAI features a voice-based AI assistant that describes objects, answers questions, and assists with navigation.\r\nIt also provides hands-free access to information, making it safer and more convenient in situations like driving, working, or cooking.\r\nOptiAI eliminates time wasted on minor searches by delivering instant, hands-free information, reducing distractions, and enhancing efficiency and focus.\r\nAdditionally, the glasses enable real-time object identification. If a user wants to identify an object, such as a car or product, the built-in camera captures an image, AI analyzes it, and the system provides relevant details through voice output.","description":"OptiAI is an AI-powered wearable device designed to provide real-time, hands-free assistance to users through voice commands and object recognition. The glasses are equipped with a microphone, speaker, and ESP32 camera and are connected to a Flutter-based mobile application that processes user queries using Speech-to-Text conversion, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG) systems, and Text-to-Speech conversion. The system enables users to access information instantly, without the need to use a mobile phone. \r\nWhen a user wears the OptiAI and issues a voice command, the built-in microphone captures the audio and sends it to the Flutter mobile app. The app converts speech to text and processes it using a custom LLM. If the query is general, the LLM forwards it to a pretrained external model via API, retrieves a response, converts it to speech, and plays it through the speaker.\r\nFor object-related queries, the ESP32 camera captures an image, which an AI-based detection model analyzes. A RAG system fetches additional data, and the LLM structures a response before converting it to speech. To improve efficiency, an SQLite database stores frequently asked questions and past interactions, enabling quick responses and personalization.$$\n1-Hardware Module: Includes ESP32-CAM for image capture, a microphone for voice input, a speaker for audio output, and connectivity components like Wi-Fi\/Bluetooth.\r\n2-Voice Processing Module: Captures and converts speech into text using speech-to-text algorithms for further analysis.\r\n3-LLM Query Processing Module: Analyzes the text query and determines if it requires general information retrieval or image-based processing.\r\n4-Multimodal LLM: The Multimodal LLM Module processes both text and image-based queries using AI models. For text queries, it uses a LLM using external APIs for response generation. For image-based queries, it employs AI-powered internally object recognition to extract relevant details. Additionally, a Retrieval-Augmented Generation (RAG) system enhances accuracy by fetching relevant data before generating the final response.\r\n5-Response Generation Module: Converts processed text into speech and plays it through the glasses\u2019 speaker for hands-free interaction.\r\n6-Mobile App & Database Module: The Flutter-based app manages device communication, stores frequently asked queries, and optimizes response time using SQLite.$$\n(i)-Hardware Module\r\nIncludes ESP32-CAM for image capture, a microphone for voice input, a speaker for audio output, and connectivity components like Wi-Fi\/Bluetooth\r\n(ii)-Voice Processing Module\r\nCaptures and converts speech into text using speech-to-text algorithms for further analysis.\r\n(iii)-Mobile App & Database Module\r\nThe Flutter-based app manages device communication, stores frequently asked queries, and optimizes response time using SQLite.$$\n(i)-LLM Query Processing Module\r\nAnalyzes the text query and determines if it requires general information retrieval or image-based processing.\r\n(ii)-Multimodal LLM\r\nThe Multimodal LLM Module processes both text and image-based queries using AI models. For text queries, it uses a LLM using external APIs for response generation. For image-based queries, it employs AI-powered internally object recognition to extract relevant details. Additionally, a Retrieval-Augmented Generation (RAG) system enhances accuracy by fetching relevant data before generating the final response.\r\n(iii)-Response Generation Module\r\nConverts processed text into speech and plays it through the glasses\u2019 speaker for hands-free interaction.$$\n$$\nSmart white Cane$$\nHardware Module: Includes ESP32-CAM for image capture, a microphone for voice input, a speaker for audio output, and connectivity components like Wi-Fi\/Bluetooth$$\nMultimodal LLM: Processes text and image queries using AI. Text queries use an LLM via APIs, while image queries leverage object recognition. RAG improves accuracy by retrieving relevant data.$$\nResponse Generation Module: Converts processed text into speech and plays it through the glasses\u2019 speaker for hands-free interaction.","user_id":80,"comments":" $$ Idea is good, students should have confirmation about the deployment of the model, either it will be deployed on Mobile app or on some edge server. $$ Review the project requirements, as students do not fully understand them.","isDraft":0,"status":4,"created_at":"2025-02-26 20:31:52","updated_at":"2025-12-12 17:52:05","isReviewDraft":0,"isInternalDraft":0,"isExternalDraft":0,"isAssign":1,"reviewedDate":"2025-03-12 13:49:42","markedDate":null,"academic_session_id":20,"deleted_at":null,"is_assign_internal_sev":1,"is_assign_internal_eight":1,"is_assign_external_eight":1,"is_evaluated_internal_7th":1,"is_evaluated_internal_8th":1,"is_evaluated_external_8th":null,"member_count":3,"allow_7th_evolution":1,"allow8thEvaluation":0,"external_examiner_id":212,"start_date_time":null,"team_id":null},{"id":1294,"title":"Sparta Academy","prob":"This project addresses key challenges faced by football clubs and academies, such as inefficient player registration processes, lack of centralized access to tournament schedules and match details, and difficulty in tracking player profiles. By introducing a digital platform, we aim to modernize club operations, enhance engagement with players and fans, and streamline administrative tasks. Our goal is to create a user-friendly and visually appealing web interface that simplifies interaction and fosters a stronger connection between the club and its community.","description":"This FYP revolves around designing and developing a specialized website builder for football clubs, enabling them to create professional and dynamic websites with ease. The platform serves as a centralized hub for managing club activities, showcasing its identity, and engaging with players and fans. A major focus is simplifying the player registration process, which often poses challenges for clubs. Additionally, the system provides features like real-time match updates, tournament schedules, and player profiles, addressing practical issues faced by clubs. By offering advanced functionalities beyond standard sports websites, this project aims to elevate the club\u2019s digital presence, improve operational efficiency, and foster greater community engagement.$$\nTournament Module\r\nThis module simplifies organizing, managing, and promoting club tournaments and competitions. It will allow administrators to easily create tournaments by specifying critical information like tournament name, date, venue, participating teams, and format\r\nAdmin Module\r\nAdmin Module will manage a number of very important functions:\r\n Player Management: Club administrators shall have complete control of player information such as registrations, profiles, contact details, medical information, and performance statistics. They will be capable of adding, modifying, and tracking players' development over time.\r\n-User Management: This functionality will enable administrators to create and manage user accounts, reset passwords, modify user information, assign roles and permissions, providing secure access control within the system.\r\n-Reporting and Analytics: The module will create analytical summaries in the form of reports and dashboards, based on key metrics such as player engagement, tournament turnout, web traffic, and user activity. Such data will enable informed decisions and club enhancements.\r\n\r\nMatch Highlights Module\r\nThis module aims to keep users aware of the club's recent events and activities:\r\n\r\n- Match Updates: Users will be provided with real-time updates on forthcoming matches, such as schedules, venues, and opponents, so they are kept up to date with club fixtures and can plan accordingly.\r\n- Match Highlights: The module will include recaps, highlights, and post-match analysis of finished games. This enables users to relive important highlights and get up to speed on match summaries if they missed the live match.\r\nClub Record Module\r\nThe Club Record Module is a vital module used to track and analyze the performance of the football club across different competitions and games.\r\n\r\n- Performance Tracking: This aspect systematically keeps a record of and maintains the major performance data such as wins, losses, draws, goals scored, and goals allowed, offering an overall perspective on the club's success.\r\n- Statistical Analysis: The module computes significant statistics like win rates, goal margins, win-loss rates, and aggregate points earned over time. Such information assists in evaluating the competitiveness and general performance of club.\r\n- Historical Data: It stores historical records of matches played and performance patterns and enables users to view and examine past results. This facilitates monitoring the club's performance across seasons and tournaments.\r\n\r\n-Email Integration Module\r\nEmail Integration facilitates communication through automated messaging in the system to provide smooth interactions between the members and the club.\r\n\r\n- Registration Confirmation: When a player is successfully registered, the system sends an auto-generated confirmation message to the email address registered for the player to confirm their entry and include the required information. \r\n\r\nPlayer Profiles Module\r\nThe Player Profiles Module enables users to create and maintain personalized profiles and therefore it is a critical component of the club's digital platform.\r\n\r\n- Options for Customization: Players have the option to personalize their profiles through uploading profile images, choosing display names, changing profile themes, and adding personal descriptions or bios.\r\n- Player Statistics: This module allows players to monitor their performance by logging important statistics like goals scored, clean sheets, passing accuracy, and other important gameplay data.$$\nSparta Football Club Modules:\r\n\r\nClub Record Module:\r\n\r\nLogs match outcomes, wins, losses, goals for, and goals against.\r\nExamines performance statistics such as win percentages, goal margins, and trends over time.\r\nEmail Integration Module:\r\n\r\nAutomatically issues confirmatory emails on player registration.\r\nPlayer Profiles Module:\r\n\r\nEnables users to personalize profiles with images, display names, and biographies.\r\nLogs individual statistics such as goals scored, clean sheets, and passing accuracy.\r\nThese modules improve performance tracking, user interaction, and communication in the club system.$$\nSparta Football Club Modules:\r\n\r\nTournament Module:\r\nAllows administrators to organize tournaments by defining name, date, place, teams, and type (knockout, round-robin). It handles team enrollments, match schedules, referees, and result logging.\r\n\r\nAdmin Module:\r\n\r\nPlayer Management: Manages player enrollments, profiles, medical data, and performance statistics.\r\nUser Management: Manages accounts, roles, and access control.\r\nReporting & Analytics: Gives insights regarding player play, tournament visit, and user activity.\r\nMatch Highlights Module:\r\n\r\nMatch Updates: Provides live schedules, venues, and opponent information.\r\nMatch Highlights: Includes recaps, highlights, and post-game analysis.\r\nThese modules simplify tournament management, player tracking, and fan engagement, making the club's digital experience better.$$\n$$\n$$\n$$\n$$\n","user_id":41,"comments":" $$ Review the project requirements, as students do not fully understand them. $$ Review the already build projects and add the functionality accordingly $$ students are not clear about use cases of the system. they must know what they will develop, as they have some confusions about use cases of each stake holder. $$ In 7th semester, you should have implemented at least one major use case other than user logins and user registrations along with the newly modified designed SRS document. In 8th semester, the FYP MUST be 90% complete in the 14th week. Your website, if any, MUST be online and your App, if any, MUST be in AppStore when you come for internal viva. Your hardware MUST be packed in such a way that it gives the look of a sellable product.","isDraft":0,"status":4,"created_at":"2025-02-26 21:39:06","updated_at":"2025-12-12 17:52:05","isReviewDraft":0,"isInternalDraft":0,"isExternalDraft":0,"isAssign":1,"reviewedDate":"2025-03-12 13:50:40","markedDate":null,"academic_session_id":20,"deleted_at":null,"is_assign_internal_sev":1,"is_assign_internal_eight":1,"is_assign_external_eight":1,"is_evaluated_internal_7th":1,"is_evaluated_internal_8th":1,"is_evaluated_external_8th":null,"member_count":3,"allow_7th_evolution":0,"allow8thEvaluation":0,"external_examiner_id":212,"start_date_time":null,"team_id":null},{"id":1298,"title":"Agentic AI for Automated Market Research and Trend Analysis","prob":"Market research is slow, expensive, and lacks real-time insights. Businesses struggle to track emerging trends, analyze consumer sentiment, and make informed decisions quickly. Traditional market research methods rely on static reports that become outdated, causing missed opportunities.\r\n\r\nThis project introduces an Agentic AI-powered system that automates market research, detects trends, and performs sentiment analysis from multiple sources such as news, social media, and business reports. By using Natural Language Processing (NLP) and AI models, the system can analyze market trends in real-time and provide actionable insights.\r\n\r\nInitially, the system will provide automated data collection, trend detection, and sentiment analysis. Later, it can be expanded with predictive forecasting, competitor analysis, and AI-generated business strategies. This project aims to revolutionize market research by making it fast, accurate, and fully autonomous.","description":"This project is an AI-powered market research system that automates data collection, trend analysis, and sentiment detection to help businesses make data-driven decisions.\r\n\r\nStep 1: Data Collection & Storage \u2013 The system scrapes data from news articles, Twitter, Google Trends, and business reports.\r\nStep 2: Data Processing & Storage \u2013 The collected data is cleaned, structured, and stored in a database.\r\nStep 3: Trend Detection & Sentiment Analysis \u2013 AI detects emerging trends and classifies them as positive, negative, or neutral.\r\nStep 4: Web Dashboard \u2013 Insights are displayed in a React.js-powered UI, allowing users to filter and explore trends.\r\n\r\nThis project will provide real-time market insights, reduce manual effort, and offer a scalable AI-powered market research solution.$$\nModules:\r\n1. Data Collection & Storage:\r\nFunction: Collects and stores data from news, social media (Twitter), Google Trends.\r\nTech Stack: Python, Scrapy, BeautifulSoup, APIs (Google News, Twitter)\r\nDatabase: MongoDB,PostgreSQL.\r\n\r\n2. Trend Detection & Sentiment Analysis:\r\nFunction: Identifies emerging market trends and analyzes sentiment (positive\/negative\/neutral).\r\nTech Stack: NLP (TF-IDF, BERT, VADER), Python (spaCy, Scikit-learn).\r\n\r\n3. Web Dashboard (Visualization Module):\r\nFunction: Displays real-time insights on a user-friendly React.js dashboard.\r\nTech Stack: React.js, FastAPI, Chart.js.$$\nResponsible for: Data Collection & Storage.\r\nTasks: Web scraping, APIs, data cleaning, and database integration.\r\nSkills Required: Python, BeautifulSoup\/Scrapy, MongoDB\/PostgreSQL.\r\nAdditional Details: Ensures smooth data retrieval, optimizes storage efficiency, and integrates multiple data sources.$$\nResponsible for: Trend Analysis, Sentiment Analysis, and Dashboard.\r\nTasks: Implement NLP models, sentiment classification, and design web UI.\r\nSkills Required: Python (NLP), React.js, FastAPI.\r\nAdditional Details: Develops AI models for trend\/sentiment analysis and integrates them into the dashboard for real-time visualization.$$\n$$\n$$\n$$\n$$\n","user_id":70,"comments":" $$ Review the existing websites and projects $$ Build in APIS are used, Students are not cleared about the implementation $$ Fetch data from multiple resources (How it will be fetch) $$ The students are unclear about the system. They should have a full understanding of the project\u2019s objective and how the data related to that objective will be collected. $$ Social platforms can't provide product trends, as they mainly focus on event trends. $$ The students have limited knowledge of the system, as they are targeting businesses and using social platforms.","isDraft":0,"status":4,"created_at":"2025-02-26 23:35:30","updated_at":"2025-12-12 17:52:05","isReviewDraft":0,"isInternalDraft":0,"isExternalDraft":0,"isAssign":1,"reviewedDate":"2025-04-17 12:55:14","markedDate":null,"academic_session_id":20,"deleted_at":null,"is_assign_internal_sev":1,"is_assign_internal_eight":1,"is_assign_external_eight":1,"is_evaluated_internal_7th":1,"is_evaluated_internal_8th":1,"is_evaluated_external_8th":null,"member_count":3,"allow_7th_evolution":0,"allow8thEvaluation":1,"external_examiner_id":212,"start_date_time":null,"team_id":null},{"id":1306,"title":"Smart Emergency Dispatch System (SEDS)","prob":"In critical emergencies, patients often face delays in ambulance response because the nearest available ambulance may not be assigned to them. Additionally, paramedics often arrive without prior knowledge of the patient's medical history, leading to delayed or incorrect treatment. Our system aims to solve these challenges by optimizing ambulance dispatch based on real-time route data and patient history.","description":"Every second counts in an emergency. Lives are lost due to delayed ambulance dispatch, miscommunication, and inefficient resource allocation. Our Smart Emergency Dispatch System (SEDS) is designed to revolutionize emergency response, ensuring faster, smarter, and more efficient ambulance coordination.\r\n\r\n\ud83d\udd39 Instant Emergency Alerts: Users in distress can trigger an alert, notifying affiliated contacts and nearby ambulances immediately.\r\n\ud83d\udd39 Real-Time Location-Based Dispatch: The system intelligently assigns the nearest ambulance, reducing response time significantly.\r\n\ud83d\udd39Auto-Handover System \u2013 If a closer ambulance becomes available, the system reroutes for faster response.\r\n\ud83d\udd39AI-Based Severity Prediction \u2013 Analyzes patient symptoms to categorize emergency levels and alert hospitals.\r\n\ud83d\udd39Blockchain for Medical Records \u2013 Ensures secure, tamper-proof storage of patient history and emergency data.\r\n\ud83d\udd39Hospital Dashboard \u2013 Provides real-time tracking of incoming ambulances and patient condition updates.\r\n\ud83d\udd39 Seamless Coordination with Hospitals: Emergency teams receive live updates on patient arrival, condition, and critical details to prepare in advance.\r\n\ud83d\udd39 Life-Saving Efficiency: By cutting down response and hospital preparation time, SEDS has the potential to save countless lives every year.$$\n1. System Modules\r\n\r\n1.1 Emergency Dispatch & Routing Module\r\nDynamic Ambulance Assignment \u2013 Assigns the nearest ambulance using traffic-aware routing.\r\nAuto-Handover to Another Ambulance \u2013 If a closer ambulance becomes available en route, the system will reroute for faster service.\r\nAmbulance Mobile App \u2013 Provides real-time route tracking, patient details, and doctor communication features.\r\n\r\n1.2 AI-Powered Patient Health Analysis Module\r\nAI-Based Severity Prediction \u2013 Users enter symptoms, and AI suggests triage levels (mild, moderate, critical).\r\nDisease Prediction from Medical History \u2013 AI detects patterns in previous records to predict possible conditions.\r\nSmart Treatment Suggestions \u2013 AI provides first-aid recommendations for paramedics and assisters based on patient symptoms.\r\n\r\n1.3 Hospital Dashboard & Medical Record Management Module\r\nReal-Time Monitoring Dashboard \u2013 Hospitals can track incoming ambulances, patient vitals, and estimated arrival time.\r\nElectronic Health Record (EHR) Integration \u2013 Syncs with hospital databases for faster access to patient records.\r\n\r\n1.4 Blockchain-Based Medical Data Security Module\r\nTamper-Proof Medical Records \u2013 Stores patient history securely using blockchain technology.\r\nBiometric Authentication for Medical Staff \u2013 Ensures only authorized paramedics and doctors can access emergency records.\r\nPatient-Owned Data Access \u2013 Patients control who can view their records for privacy and security.\r\n\r\n1.5 Route Optimization & Traffic Management Module\r\nDynamic Traffic-Based Routing \u2013 Uses Google Maps API + AI to find the fastest route considering traffic, roadblocks, etc.\r\nReal-Time GPS Ambulance Tracking \u2013 Allows hospitals and users to track ambulance movement in real-time.\r\n\r\n1.6 Cloud & Backend Infrastructure Module\r\nCloud-Based Hosting (AWS\/GCP) \u2013 Ensures scalability and real-time data processing.\r\nSocket.io for Real-Time Communication \u2013 Enables live updates between ambulances, hospitals, and users.\r\n\r\n1.7 User & Emergency Contact Management Module\r\nEmergency Contact Notifier \u2013 Users can assign emergency contacts who get notified during crises.\r\nUser Profile with Medical History \u2013 Allows users to store and update their medical history for quick access.\r\nMulti-User Role System \u2013 Supports patients, paramedics, and hospital staff with different access levels.$$\nAI-Powered Patient Health Analysis Module\r\nAI-Based Severity Prediction \u2013 Users enter symptoms, and AI suggests triage levels (mild, moderate, critical).\r\nDisease Prediction from Medical History \u2013 AI detects patterns in previous records to predict possible conditions.\r\nSmart Treatment Suggestions \u2013 AI provides first-aid recommendations for paramedics and assisters based on patient symptoms.\r\n\r\nCloud & Backend Infrastructure Module\r\nCloud-Based Hosting (AWS\/GCP) \u2013 Ensures scalability and real-time data processing.\r\nSocket.io for Real-Time Communication \u2013 Enables live updates between ambulances, hospitals, and users.\r\n\r\nHospital Dashboard & Medical Record Management Module\r\nReal-Time Monitoring Dashboard \u2013 Hospitals can track incoming ambulances, patient vitals, and estimated arrival time.\r\n\r\nUser & Emergency Contact Management Module\r\nEmergency Contact Notifier \u2013 Users can assign emergency contacts who get notified during crises.\r\nMulti-User Role System \u2013 Supports patients, paramedics, and hospital staff with different access levels.$$\nEmergency Dispatch & Routing Module\r\nDynamic Ambulance Assignment \u2013 Assigns the nearest ambulance using traffic-aware routing.\r\nAuto-Handover to Another Ambulance \u2013 If a closer ambulance becomes available en route, the system will reroute for faster service.\r\nAmbulance Mobile App \u2013 Provides real-time route tracking, patient details, and doctor communication features.\r\n\r\nBlockchain-Based Medical Data Security Module\r\nTamper-Proof Medical Records \u2013 Stores patient history securely using blockchain technology.\r\nBiometric Authentication for Medical Staff \u2013 Ensures only authorized paramedics and doctors can access emergency records.\r\nPatient-Owned Data Access \u2013 Patients control who can view their records for privacy and security.\r\n\r\nRoute Optimization & Traffic Management Module\r\nDynamic Traffic-Based Routing \u2013 Uses Google Maps API + AI to find the fastest route considering traffic, roadblocks, etc.\r\nReal-Time GPS Ambulance Tracking \u2013 Allows hospitals and users to track ambulance movement in real-time.$$\n$$\n$$\n$$\n$$\n","user_id":18,"comments":" $$ Approved with the above scope","isDraft":0,"status":4,"created_at":"2025-03-01 20:47:28","updated_at":"2025-12-12 17:52:05","isReviewDraft":0,"isInternalDraft":0,"isExternalDraft":0,"isAssign":1,"reviewedDate":"2025-03-17 11:11:33","markedDate":null,"academic_session_id":20,"deleted_at":null,"is_assign_internal_sev":1,"is_assign_internal_eight":1,"is_assign_external_eight":1,"is_evaluated_internal_7th":1,"is_evaluated_internal_8th":1,"is_evaluated_external_8th":null,"member_count":3,"allow_7th_evolution":1,"allow8thEvaluation":1,"external_examiner_id":212,"start_date_time":null,"team_id":null}] 0 [{"id":1270,"title":"AIForge: One-Click AI Model Deployment & Monetization Platform","prob":"Deploying AI models is complex, time-consuming, and expensive. Developers, researchers, and businesses struggle with setting up infrastructure, managing servers, scaling models, and monetizing AI solutions. Existing platforms require manual configuration, coding expertise, and cloud setup, making AI deployment inaccessible for many. Additionally, AI developers lack an efficient way to monetize their models. AIForge solves this by providing a one-click AI model deployment platform that automates hosting, API generation, scaling, and monetization, enabling fast, cost-effective AI adoption for everyone.","description":"AIForge is a web-based platform that enables users to deploy, manage, and monetize AI models in one click without requiring complex infrastructure setup. Users can upload their pre-trained AI models, and the system automatically hosts them on the cloud, generates an API endpoint, and provides a dashboard for usage monitoring. Developers can choose to keep models private, share publicly, or monetize them through API subscriptions. The platform supports scalable cloud deployment, allowing AI models to run efficiently with automatic scaling and GPU acceleration. Users can integrate their deployed models into web apps, mobile applications, or automation workflows through auto-generated SDKs and API keys. The system also includes payment processing for monetized models, enabling developers to earn from their AI solutions while businesses can quickly access and integrate powerful AI capabilities.$$\n1.\tUser Authentication & Profile Management\r\n\u2022\tUsers can sign up and log in using Email, Google, or GitHub. \r\n\u2022\tSecure authentication with API key management for developers. \r\n\u2022\tRole-based access for AI Developers, Businesses, and Researchers. \r\n\u2022\tTwo-factor authentication (2FA) for enhanced security. \r\n2.\tAI Model Upload & Deployment \r\n\u2022\tUsers upload pre-trained AI models (TensorFlow, PyTorch, ONNX, etc.). \r\n\u2022\tThe platform automatically hosts models on cloud infrastructure. \r\n\u2022\tModels are deployed in one click with containerized execution. \r\n\u2022\tDeployment status is displayed on a real-time dashboard. \r\n3.\tAPI Generation & Integration \r\n\u2022\tThe system auto-generates API endpoints for deployed models. \r\n\u2022\tDevelopers can send API requests to interact with their models. \r\n\u2022\tSupports REST API & WebSocket integration. \r\n\u2022\tAuto-generated SDKs (Python, JavaScript) for easy integration. \r\n4.\tAI Model Access Control \r\n\u2022\tUsers can choose between Public, Private, or Paid model access. \r\n\u2022\tPublic models are accessible to everyone via a shared API. \r\n\u2022\tPrivate models are restricted to the owner or selected users. \r\n\u2022\tPaid models require subscription or pay-per-use access. \r\n5.\tAI Model Monetization & Payment System \r\n\u2022\tDevelopers can charge users for API usage (pay-per-call or subscription). \r\n\u2022\tIntegrated Stripe and PayPal for payments. \r\n\u2022\tUsage and revenue tracking via a billing dashboard. \r\n\u2022\tRate limiting & request monitoring for API security. \r\n6.\tAI Model Management & Monitoring \r\n\u2022\tReal-time dashboard to monitor API usage and model performance. \r\n\u2022\tTracks number of API calls, response time, and errors. \r\n\u2022\tUsers can update and redeploy models with new versions. \r\n\u2022\tAutomatic scaling based on demand to optimize performance. \r\n7.\tWeb-Based AI Model Testing \r\n\u2022\tUsers can test AI models directly from the browser. \r\n\u2022\tDrag & drop file input (for image\/audio models). \r\n\u2022\tProvides real-time AI-generated responses. \r\n\u2022\tParameter tuning options for model customization. \r\n8.\tAI-Powered Search & Model Discovery \r\n\u2022\tSmart search and filter system for finding AI models. \r\n\u2022\tPersonalized recommendations based on user behavior. \r\n\u2022\tAI-driven model ranking based on performance and popularity. \r\n\u2022\tUsers can browse top-rated and trending AI models.$$\n1. AI Model Upload & Deployment: This module allows users to upload pre-trained AI models (TensorFlow, PyTorch). The system will handle cloud-based hosting, enabling one-click deployment with containerized execution. A real-time dashboard will show deployment status.\r\n\r\n2. API Generation & Integration: The platform will auto-generate API endpoints for deployed models, supporting REST API.\r\n\r\n3. AI Model Access Control: Users can set model access as Public, Private, or Paid. Private models will have authentication-based restrictions, while public models will be open for free use.\r\n\r\n4. AI Model Monetization & Payment System: Developers can monetize their AI models via pay-per-call or subscription. Stripe will handle transactions.$$\n1. User Authentication & Profile Management: This module will enable secure user authentication using Email, Google, and GitHub login. It will include API key management, role-based access control, and two-factor authentication (2FA) for enhanced security. \r\n\r\n2. Web-Based AI Model Testing: Users will be able to test AI models directly from the browser using a drag-and-drop interface for input files (e.g., images, audio). Real-time AI-generated responses and parameter tuning options will be provided. \r\n\r\n3. AI-Powered Search & Model Discovery: A smart search and filtering system will help users find AI models based on performance, category, and popularity. AI-driven recommendations and trending model rankings will enhance discoverability. \r\n\r\n4. AI Model Management & Monitoring: This module will provide a real-time dashboard to track API usage, performance, and errors. Users will be able to update and redeploy models, with automatic scaling based on demand to optimize efficiency.$$\n$$\n$$\n$$\n$$\n","user_id":76,"comments":" $$ Approved with above scope","isDraft":0,"status":4,"created_at":"2025-02-25 16:13:32","updated_at":"2025-12-12 17:52:46","isReviewDraft":0,"isInternalDraft":0,"isExternalDraft":0,"isAssign":1,"reviewedDate":"2025-03-17 11:08:29","markedDate":null,"academic_session_id":20,"deleted_at":null,"is_assign_internal_sev":1,"is_assign_internal_eight":1,"is_assign_external_eight":1,"is_evaluated_internal_7th":1,"is_evaluated_internal_8th":1,"is_evaluated_external_8th":null,"member_count":3,"allow_7th_evolution":0,"allow8thEvaluation":0,"external_examiner_id":213,"start_date_time":null,"team_id":null},{"id":1308,"title":"Assist Network Windows Service","prob":"Our decentralized Windows service enables Automated Application Synchronization & Event Handling, ensuring that when an application runs on one node, other nodes automatically detect and respond by launching the configured application. This eliminates manual coordination, making systems more efficient and responsive in multi-user environments.\r\nIn military and defense, secure and autonomous network management is critical. During combat operations or emergency scenarios, centralized servers are unreliable due to potential cyberattacks or communication failures. Your service allows military units to establish ad hoc peer-to-peer networks, ensuring real-time event-driven automation without internet dependency. For example, if an intelligence system activates on one device, all connected units receive synchronized updates, ensuring instant coordination.\r\nAdditionally, node validation using a shared key enhances security, preventing unauthorized access. This makes your solution ideal for battlefield networks, secure command centers, and disaster response, where real-time synchronization and decentralized operations are essential.","description":"Assist is a network management service which will be running in the background to assist a network. The service will be a part of a distributed de-centralized peer to peer ad hoc network in which it will be responsible for creating new sessions and application-level handshake between nodes. The objective of this service is automation of repetitive tasks across multiple nodes. Useful for deploying applications and services on several machines simultaneously. It also enhances internal network security by detecting and alerting intrusions.\r\n\r\nAssist Framework: Core Services and Console Overview:\r\nAssist will have 2 parts. The first one is Assist Service which will perform the following task:\r\n\u2022\tAutomatically running when a system boots up.\r\n\u2022\tValidates the neighboring nodes in the network.\r\n\u2022\tIt provides event detection capabilities. \r\n\u2022\tIt will make sure that if an application is started on one node, it must start up on other nodes in the network automatically.\r\n\u2022\tKeep record of sessions.\r\n\u2022\tResponsible for network security. \r\n\u2022\tChecks if whether unauthorized user or device tries to connect in a network. If yes then it will trigger configurations or alerts based on this event.\r\n\u2022\tIt can remotely power\u2019s up or down any other node on the network.\r\n\u2022\tReport link failures.\r\n\r\nThe second one is Assist Console which will be the interface for the user. It will enable user to perform the following:\r\n\u2022\tHandle tasks and configurations.\r\n\u2022\tCreating new sessions.\r\n\u2022\tSave logs.\r\n\u2022\tInteract with assist service.\r\n\u2022\tMonitoring all active sessions.$$\nAssist Service:\r\n\u2022 NodeConfig \u2013 Stores configuration details of a node, such as its name.\r\n\u2022 RuleConfig \u2013 Defines rules for triggering applications on specific target nodes.\r\n\u2022 TargetNode \u2013 Represents a target node where an application should be launched.\r\n\u2022 Peer \u2013 Represents a discovered peer in the network with an associated IP endpoint.\r\n\u2022 Service1 (Windows Service) \u2013 The core service that manages node discovery, communication, and application monitoring.\r\n\u2022 UDP Communication \u2013 Uses UdpClient to send and receive messages for peer discovery and inter-node communication.\r\n\u2022 Thread Management \u2013 Multiple threads handle message listening, application monitoring, and named pipe communication.\r\n\u2022 Named Pipe Server \u2013 Handles inter-process communication via named pipes to receive and process application launch requests.\r\n\u2022 Application Monitoring \u2013 Tracks running applications and triggers responses based on configured rules.\r\n\u2022 Peer Discovery \u2013 Implements multicast-based peer discovery to identify other nodes in the network.\r\n\u2022 Logging \u2013 Maintains logs to track service execution and errors.\r\n\u2022 Configuration Loading \u2013 Reads node and rule configurations from JSON files (NodeConfig.json and RulesConfig.json).\r\n\u2022 Application Launch Handling \u2013 Manages launching applications locally or forwarding requests to a console app via named pipes.\r\n\u2022 Service Start\/Stop Handlers \u2013 Implements Windows Service lifecycle methods (OnStart, OnStop).\r\n\r\nAssist TSR:\r\n1\ufe0f\u20e3 System Tray & UI Management \u2013 Manages system tray icon, UI interactions, and context menu options (Start, Stop, Exit).\r\n2\ufe0f\u20e3 Background Process & TSR Management \u2013 Ensures the application runs in the background and minimizes to the system tray.\r\n3\ufe0f\u20e3 Named Pipe Communication \u2013 Handles communication between the Windows Form application and the Windows Service.\r\n4\ufe0f\u20e3 Application Launch & Process Management \u2013 Receives commands to launch applications and ensures they run in Session 1.\r\n5\ufe0f\u20e3 Auto-Startup & Privilege Management \u2013 Configures the application to start automatically with admin privileges at system boot.\r\n6\ufe0f\u20e3 Logging & Event Handling \u2013 Tracks events, logs system actions, and monitors communication with the service.\r\n7\ufe0f\u20e3 Configuration & Settings \u2013 Allows users to modify settings like auto-start, application launch preferences, and pipe configurations.\r\n8\ufe0f\u20e3 Error Handling & Recovery \u2013 Detects failures, reconnects to the service, and restarts applications if they crash.$$\nAbdullah will develop the following modules:\r\n \r\nAssist TSR:\r\n\r\n1\ufe0f\u20e3 System Tray & UI Management\r\n2\ufe0f\u20e3 Background Process & TSR Management\r\n3\ufe0f\u20e3 Named Pipe Communication\r\n4\ufe0f\u20e3 Application Launch & Process Management\r\n5\ufe0f\u20e3 Auto-Startup & Privilege Management\r\n6\ufe0f\u20e3 Logging & Event Handling\r\n7\ufe0f\u20e3 Configuration & Settings\r\n8\ufe0f\u20e3 Error Handling & Recovery$$\nIbrahim Ali Shah will develop the following modules:\r\n\r\nAssist Service:\r\n\r\n1\ufe0f\u20e3 NodeConfig\r\n2\ufe0f\u20e3 RuleConfig\r\n3\ufe0f\u20e3 TargetNode\r\n4\ufe0f\u20e3 Peer\r\n5\ufe0f\u20e3 Service\r\n6\ufe0f\u20e3 UDP Communication\r\n7\ufe0f\u20e3 Thread Management\r\n8\ufe0f\u20e3 Named Pipe Server\r\n9\ufe0f\u20e3 Application Monitoring\r\n\ud83d\udd1f Peer Discovery\r\n1\ufe0f\u20e31\ufe0f\u20e3 Logging\r\n1\ufe0f\u20e32\ufe0f\u20e3 Configuration Loading\r\n1\ufe0f\u20e33\ufe0f\u20e3 Application Launch Handling\r\n1\ufe0f\u20e34\ufe0f\u20e3 Service Start\/Stop Handlers$$\n$$\n$$\n$$\n$$\n","user_id":17,"comments":" $$ Seems like students are not sure about complexity of the project, and they are not sure about the exact requirement of the project $$ It is recommended to use Ubuntu instead of Windows, as student might get issues with source code $$ And all the claimed things must be completed at the end of project $$ Too many modules are being claimed. Conduct research on the modules, as students are asserting that they are already familiar with the technology and content.","isDraft":0,"status":4,"created_at":"2025-03-01 21:39:09","updated_at":"2025-12-12 17:52:46","isReviewDraft":0,"isInternalDraft":0,"isExternalDraft":0,"isAssign":1,"reviewedDate":"2025-03-17 12:40:54","markedDate":null,"academic_session_id":20,"deleted_at":null,"is_assign_internal_sev":1,"is_assign_internal_eight":1,"is_assign_external_eight":1,"is_evaluated_internal_7th":1,"is_evaluated_internal_8th":1,"is_evaluated_external_8th":null,"member_count":3,"allow_7th_evolution":1,"allow8thEvaluation":1,"external_examiner_id":213,"start_date_time":null,"team_id":null},{"id":1311,"title":"OpportuNest \u2013 (A nest of opportunities)","prob":"Finding relevant and genuine internships is a major challenge for students, as they often struggle with scattered job postings, lack of guidance, and ineffective tracking of applications. A bigger issue is the rise of scam internships, where fake software houses demand money for placements. At the same time, real companies struggle to connect with qualified university students. Our Internship Portal provides a centralized and verified platform where students can find legitimate internships tailored to their skills, and companies can efficiently manage applications. With features like real-time application tracking, AI-based recommendations, and strict verification of internship postings, the portal ensures transparency and eliminates fraudulent listings. By bridging the gap between students and trusted companies, it creates a safe, accessible, and efficient internship-hunting experience.","description":"The Internship Portal is a web-based platform designed to bridge the gap between students and companies, making the internship-hunting process efficient, transparent, and scam-free. This MERN stack-based project provides a centralized solution where students can find verified internships based on their skills, and companies can easily post and manage internship applications.\r\nThe platform enables companies to post internships, specifying details like required skills, duration, stipend, and deadlines. Students can browse and filter internships based on their skill set, field of interest, and location. To ensure a fraud-free environment, all internship postings undergo a verification process by the admin before being visible to students.\r\nStudents can apply for internships directly through the platform by submitting their resumes and cover letters. Once applied, they can track their application status in real-time, receiving updates on whether they have been shortlisted, interviewed, or selected. Companies, on the other hand, get access to a dashboard where they can review applications, shortlist candidates, and send interview invites efficiently.\r\nTo enhance user experience, the portal includes an AI-powered recommendation system that suggests relevant internships based on a student\u2019s skills, past applications, and preferences. This feature saves time and helps students discover the best opportunities tailored to their profiles.\r\nThe system follows a secure and scalable architecture, utilizing MongoDB for database storage, Express.js for backend API handling, React.js for an interactive UI, and Node.js for backend logic. The platform will be deployed on Vercel (frontend), Render (backend), and MongoDB Atlas (database) for seamless scalability and performance.\r\nIn summary, this Internship Portal aims to streamline the hiring process for companies, prevent scam internships, and provide students with a secure, accessible, and efficient way to find the right opportunities, ultimately helping them build successful careers.$$\n1. Internship Management Module\r\nEnables companies to post and manage internships while students can search, filter, and apply easily.\r\n2. Student Profile & Application Module\r\nAllows students to create profiles, track applications, and receive AI-based internship recommendations.\r\n3. Company Dashboard Module\r\nProvides companies with tools to review applications, shortlist candidates, and manage internship postings.\r\n4. Admin Verification & Moderation Module\r\nEnsures platform security by verifying companies, approving internships, and preventing fraudulent listings.\r\n5. AI-Based Matching & Recommendation Module\r\nUses AI to suggest relevant internships to students and helps companies find the right candidates.\r\n6. Communication & Notification Module\r\nFacilitates interaction between students and companies through messaging and real-time notifications.$$\n4. Admin Verification & Moderation Module\r\nEnsures platform security by verifying companies, approving internships, and preventing fraudulent listings.\r\n5. AI-Based Matching & Recommendation Module\r\nUses AI to suggest relevant internships to students and helps companies find the right candidates.\r\n6. Communication & Notification Module\r\nFacilitates interaction between students and companies through messaging and real-time notifications.$$\n1. Internship Management Module\r\nEnables companies to post and manage internships while students can search, filter, and apply easily.\r\n2. Student Profile & Application Module\r\nAllows students to create profiles, track applications, and receive AI-based internship recommendations.\r\n3. Company Dashboard Module\r\nProvides companies with tools to review applications, shortlist candidates, and manage internship postings.$$\n$$\n$$\n$$\n$$\n","user_id":14,"comments":" $$ It is recommended to provide some templates for CV or a CV builder and CVs will be customized for each type of job. $$ How verficiation of the companies will be done? $$ Project need exetnsive work and at the end of the project these modules Must be devloped and deployed $$ Idea is well ,cover all module","isDraft":0,"status":4,"created_at":"2025-03-05 09:46:16","updated_at":"2025-12-12 17:52:46","isReviewDraft":0,"isInternalDraft":0,"isExternalDraft":0,"isAssign":1,"reviewedDate":"2025-03-17 13:01:26","markedDate":null,"academic_session_id":20,"deleted_at":null,"is_assign_internal_sev":1,"is_assign_internal_eight":1,"is_assign_external_eight":1,"is_evaluated_internal_7th":1,"is_evaluated_internal_8th":1,"is_evaluated_external_8th":null,"member_count":3,"allow_7th_evolution":1,"allow8thEvaluation":0,"external_examiner_id":213,"start_date_time":null,"team_id":null},{"id":1313,"title":"SmartVision: An AI-Powered Mobile Assistant for Visually Impaired \r\nIndividuals","prob":"The visually impaired individuals face significant challenges in their daily lives \r\ndue to the inability to recognize objects read printed text, and navigate their \r\nsurroundings without external assistance. This lack of independence affects \r\ntheir ability to perform essential tasks such as identifying household items, \r\nreading signboards, and seeking help in emergencies. While some assistive \r\ntechnologies exist, they rely on expensive hardware or require constant \r\nhuman intervention, making them impractical for real-time use. To address \r\nthis issue, our project aims to develop an AI-powered mobile application that \r\nprovides real-time object recognition, text-to-speech conversion for printed \r\ntext, and hands-free voice command navigation. Application will utilize \r\nadvanced AI techniques to process visual and textual information, ensuring a \r\nseamless and interactive user experience. Additionally, it will feature an \r\nautomatic flashlight activation system for low-light conditions. This solution will \r\nempower visually impaired individuals, promoting greater autonomy in their \r\neveryday activities while enhancing safety and accessibility.","description":"The Blind Vision App is an AI-driven mobile application designed to provide \r\nreal-time assistance to visually impaired individuals by helping them \r\nrecognize objects, read printed text, and navigate their surroundings \r\nindependently. \r\nThe application functions through an intuitive interface where users can \r\ninteract via voice commands, allowing for hands-free operation. Upon \r\nactivation, the camera captures the surrounding environment, and the AI\r\npowered object detection system identifies and announces the objects in \r\nview. \r\nThe integrated OCR module further enables users to scan and convert \r\nprinted text into speech, providing a seamless way to read signboards, \r\ndocuments, or labels. To ensure usability in various lighting conditions, the \r\napp includes an automatic flashlight feature that activates in low-light \r\nenvironments. \r\nThe Blind Vision App merges the power of Flutter for a user-friendly \r\nexperience with advanced AI for object recognition and text processing, \r\nultimately offering an accessible, reliable, and intelligent solution for \r\nvisually impaired users to navigate their daily lives with greater \r\nindependence and safety.$$\n1.Camera & Object Detection Module: \r\n\u2022 Image Processing: Captures and processes images from the camera. \r\n\u2022 Real-Time Object Recognition: Detects objects and announces them using AI. \r\n2. Voice Command Module: \r\n\u2022 Speech-to-Text Processing: Converts spoken commands into actions. \r\n\u2022 Hands-Free Navigation: Enables users to control the app using voice commands. \r\n3. Text Recognition (OCR) Module: \r\n\u2022 Text Extraction: Reads printed text from images (e.g., signboards, labels). \r\n\u2022 Text-to-Speech Conversion: Converts extracted text into audible speech output. \r\n4. Auto Flashlight Module: \r\n\u2022 Low-Light Detection: Detects ambient light levels. \r\n\u2022 Automatic Flashlight Activation: Turns on the flashlight in dark conditions. \r\n5. Mobile Application Interface Module: \r\n\u2022 User Authentication: Implements sign-in, sign-up, and profile management. \r\n\u2022 User-Friendly UI: Ensures accessibility for visually impaired users. \r\n\u2022 Navigation & Settings: Provides easy-to-use controls and app settings. \r\n6. AI Model Training & Optimization Module: \r\n\u2022 Custom AI Model Training: Develops an object detection model for better \r\naccuracy. \r\n\u2022 Performance Optimization: Ensures the AI model runs efficiently on mobile devices. \r\n7. Backend & Database Management Module: \r\n\u2022 Cloud Storage: Manages user data and preferences using Firebase Firestore. \r\n\u2022 Data Communication: Facilitates interaction between the mobile \r\napp and AI models.$$\nCamera & Object Detection Integration \u2013 Implement camera functionality and send images to \r\nAI model. \r\n User Authentication Module: Implements sign-up, login, and user profile management using \r\nFirebase\/Auth API. \r\n Voice Command & Speech Processing Module: Integrates speech-to-text functionality, \r\nallowing users to control the app using voice commands. \r\n Backend & API Development: Implements REST APIs to communicate between the mobile \r\napp and AI models. \r\nBackend & Database Management \u2013 Set up Firebase Firestore for data storage and \r\ncommunication. \r\nDeployment & Testing: Ensures the app is tested on multiple devices and \r\nplatforms before launch.$$\n1. Develop AI\/ML Models: \r\no Train object detection models (e.g., YOLO, TensorFlow Lite) for real-time object \r\nrecognition. \r\no Build an OCR model (e.g., Google ML Kit, Tesseract) for text extraction from \r\nimages. \r\n2. Optimize Models: \r\no Optimize models for mobile devices to ensure efficiency and low latency. \r\n3. Integrate with Flutter: \r\no Use tflite_flutter to integrate models into the app. \r\n4. Audio Feedback: \r\no Convert detected objects and text into audio using flutter_tts. \r\n5. Testing: \r\no Test models in real-world scenarios and evaluate performance.$$\n$$\nAn AI based mobile app working as a sight for blind and visually impaired$$\n1. Multi-Language Support: Recognises and speaks text in multiple languages.$$\n2. Voice-Controlled Navigation: Allows users to control the app entirely through \r\nvoice commands.$$\n3. Auto Flashlight in Low Light: The app will automatically turn on the flashlight \r\nin low-light conditions to ensure proper object detection.","user_id":75,"comments":" $$ students have very lmited knowledge of the project. and scope of the project is very limited, as they will use YOLO and already available API for text to voice conversion $$ In the same way, most of the technology needs online support. $$ It is recommended to change the idea or make this system module enrich, so it can be proceed as an FYP. $$ Review the project requirements, as students do not fully understand them.","isDraft":0,"status":4,"created_at":"2025-03-07 10:42:17","updated_at":"2025-12-12 17:52:46","isReviewDraft":0,"isInternalDraft":0,"isExternalDraft":0,"isAssign":1,"reviewedDate":"2025-04-07 13:09:31","markedDate":null,"academic_session_id":20,"deleted_at":null,"is_assign_internal_sev":1,"is_assign_internal_eight":1,"is_assign_external_eight":1,"is_evaluated_internal_7th":1,"is_evaluated_internal_8th":1,"is_evaluated_external_8th":null,"member_count":3,"allow_7th_evolution":1,"allow8thEvaluation":0,"external_examiner_id":213,"start_date_time":null,"team_id":null}] 0