Active Final Year Projects Showcase
Explore verified, ongoing final year projects advancing across all academic batches. Filter by emerging tech stacks, discover architectures, and explore student innovation.
Learning management system
Traditional learning systems rely on manual processes for sharing course materials, assignments, attendance, and communication between teachers and students. This creates difficulties in managing academic activities efficiently, tracking student progress, and providing timely feedback. The proposed Learning Management System aims to provide a centralized digital platform that improves learning, communication, and academic management.
AI-Based Facial Recognition Attendance System for CUI Vehari CS Faculty
Traditional faculty attendance systems are manual, time-consuming, and prone to human errors and proxy attendance. These methods require significant administrative effort and often produce inaccurate attendance records. Existing systems generally lack automated identity verification and real-time attendance management. This project aims to develop an AI-Based Facial Recognition Attendance System that automatically identifies Computer Science faculty members using facial recognition technology and marks attendance in real time. The system will improve attendance accuracy, eliminate proxy attendance, reduce manual workload, and provide secure attendance management with reports and analytics.
AI-Powered Adaptive Diet & Fitness System
Current diet and fitness applications often provide static recommendations that do not sufficiently adapt to changes in a user's behavior, adherence, progress, and fitness goals. Users may skip meals or workouts, making fixed plans less effective. This project aims to develop an AI-powered adaptive system that generates personalized diet and exercise plans and continuously analyzes user behavior to automatically adjust recommendations according to their progress and adherence
Factlens: Fake News Detection Platform
In the digital age, social media and online platforms have made it extremely easy for fake news and misleading information to spread rapidly. Many users are unable to verify the authenticity of news before sharing it, which leads to misinformation, confusion, and sometimes social or political harm. There is a lack of an accessible and automated system that can quickly analyze news content and determine whether it is real or fake. Therefore, this project aims to develop a Fake News Detection Platform that uses machine learning techniques to analyze news content and help users verify information before trusting or sharing it.
Smart Lost & Found Management System for University
Students frequently lose items (ID cards, wallets, mobiles) on campus, and there is no centralized system to report or recover them efficiently.
GharFix – On-Demand Home Service Platform
In many areas, finding reliable and skilled home service professionals (e.g., electricians, plumbers, carpenters, masons) is difficult, time-consuming, and often unsafe. People rely on word-of-mouth or random contacts, which leads to: Unverified workers Unclear pricing Delays and poor service quality No accountability or complaint system There is a need for a centralized, trusted, and efficient digital platform that connects customers with verified service providers for home-related tasks.
Generic Automation for University
Universities rely heavily on manual and repetitive workflows such as admissions, attendance, transcript requests, and HR approvals. These manual processes reduce efficiency, increase paperwork, and cause delays for both students and staff.
AI-Based Multilingual Fake News and Propaganda Detection System
The rapid spread of fake news and propaganda on social media platforms has become a critical issue in Pakistan. Users frequently communicate in Urdu, Roman Urdu, and English, often mixing these languages (code-switching), which makes it difficult for existing fake news detection systems to accurately analyze such content. Most existing models are trained on English or standard Urdu datasets and fail to effectively process Roman Urdu and multilingual text. Additionally, identifying propaganda techniques such as emotional manipulation, fear appeal, and political bias remains a significant challenge. This project aims to develop an intelligent AI-based system capable of detecting fake news and propaganda in multilingual text (Urdu, Roman Urdu, and English), while addressing the limitations of existing systems by incorporating Pakistan-specific linguistic patterns.
PSM
Educational institutions (especially small academies and portfolio-based organizations) face challenges in managing and showcasing their digital presence efficiently. Most lack a centralized system to manage websites, portfolios, updates, and user interactions. Existing solutions are either too complex, expensive, or not tailored to their needs. There is also limited support for scalability, collaboration among developers, and recurring income generation through digital platforms.
| Project Information | Status | Batch | Technologies | Action |
|---|---|---|---|---|
|
Learning management system
Traditional learning systems rely on manual processes for sharing course materials, assign...
|
Active | FA23 (2026) |
JavaScript
TypeScript
Python
+4
|
Details |
|
AI-Based Facial Recognition Attendance System for CUI Vehari CS Faculty
Traditional faculty attendance systems are manual, time-consuming, and prone to human erro...
|
Active | FA23 (2026) |
MongoDB
Express.js
React
+2
|
Details |
|
AI-Powered Adaptive Diet & Fitness System
Current diet and fitness applications often provide static recommendations that do not suf...
|
Active | FA23 (2026) |
Dart
Flutter
JavaScript
+10
|
Details |
|
Factlens: Fake News Detection Platform
In the digital age, social media and online platforms have made it extremely easy for fake...
|
Active | FA23 (2026) |
Python
JavaScript
React
+2
|
Details |
|
Smart Lost & Found Management System for University
Students frequently lose items (ID cards, wallets, mobiles) on campus, and there is no cen...
|
Active | FA23 (2026) |
Flutter
Firebase
|
Details |
|
GharFix – On-Demand Home Service Platform
In many areas, finding reliable and skilled home service professionals (e.g., electricians...
|
Active | FA23 (2026) |
MongoDB
Express.js
React
+1
|
Details |
|
Generic Automation for University
Universities rely heavily on manual and repetitive workflows such as admissions, attendanc...
|
Active | FA23 (2026) |
|
Details |
|
AI-Based Multilingual Fake News and Propaganda Detection System
The rapid spread of fake news and propaganda on social media platforms has become a critic...
|
Active | FA23 (2026) |
Python
Bootstrap
Flask
|
Details |
|
PSM
Educational institutions (especially small academies and portfolio-based organizations) fa...
|
Active | FA23 (2026) |
MongoDB
Express.js
React
+3
|
Details |
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AI-Based Facial Recognition Attendance System for CUI Vehari CS Faculty
Department Administrator
HOD / Department Management (for attendance reports and monitoring)
FR-02: Faculty Management (Add, Update, Delete Faculty)
FR-03: Faculty Dataset Collection & Image Upload
FR-04: Manual Image Labeling & Class Management
FR-05: Image Preprocessing & Data Augmentation
FR-06: Training & Testing Multiple Machine Learning Models
FR-07: Model Performance Evaluation & Best Model Selection
FR-08: Real-Time Face Detection & Recognition using Webcam
FR-09: Automatic Attendance Marking
FR-10: Attendance History & Record Management
FR-11: Search & Filter Attendance Records
FR-12: Dashboard with Attendance Analytics
FR-13: Generate Attendance Reports (PDF/Excel)
FR-14: REST API Integration between MERN Stack and AI Module
- Secure Admin Login & Authentication
- Faculty Management (Add, Update, Delete)
- Faculty Image Dataset Collection
- Manual Image Labeling
- Image Preprocessing & Data Augmentation
- Multiple AI/ML Model Training & Evaluation
- Real-Time Face Detection & Recognition
- Automatic Attendance Marking
- Attendance History & Record Management
- Search & Filter Attendance Records
- Dashboard with Attendance Analytics
- Generate Attendance Reports (PDF/Excel)
- REST API Integration between MERN Stack and AI Module
Performance (Fast real-time face recognition and attendance marking)
Accuracy (High facial recognition accuracy with minimum false detections)
Reliability (Consistent attendance recording without data loss)
Scalability (Support adding more faculty members in the future)
Availability (System accessible whenever required)
Usability (Simple and user-friendly interface)
Maintainability (Easy to update AI models and system modules)
Data Integrity (Accurate and consistent attendance data)
Compatibility (Works with modern web browsers and standard webcams)