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.
Multi-Tenant Agri-Retail with AI-Powered Supplier Price Intelligence
Many small agricultural-input shops in rural Pakistan manage customer credit (udhaar), supplier balances, daily sales, purchases, cashbooks, and inventory using handwritten registers and bill books. Dealer price lists are often received as PDFs from different companies, making product, pack-size, and purchase-price comparisons time-consuming and error-prone. These fragmented workflows can lead to inaccurate balances, poor stock visibility, missed expiry dates, and difficulty generating reliable business reports. Existing generic tools may not adequately address the specific workflows, local-language needs, and mobile-first usage of these shops. This project proposes AgriLedger, a mobile-first, multi-tenant agri-shop management system with Urdu-friendly interfaces and AI-assisted supplier price-list processing. The system will be evaluated for usability, data accuracy, and reliability using representative test data and pilot users where available.
EduVerse Atlas - A Complete 3D Smart Campus Platform
Students face difficulty in finding classrooms and understanding the correct timetable, because the campus is large and timetables have multiple confusing versions. There is no single platform for 3D campus view, timetable search, and navigation.
AI VoiceClone-X :Speech to Speech emotion Transfer
In this morden era there is no such perfect and practical tool for translate or understand the urdu to english .So ,this project will solve the issues while preserving the emotions of speaker whilr dubbing.
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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
Mathematics eduplay learning
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.
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.
| Project Information | Status | Batch | Technologies | Action |
|---|---|---|---|---|
|
Multi-Tenant Agri-Retail with AI-Powered Supplier Price Intelligence
Many small agricultural-input shops in rural Pakistan manage customer credit (udhaar), sup...
|
Active | FA23 (2026) |
React, Next.js, TypeScript, Tailwind CSS
Node.js, PostgreSQL, Prisma ORM, Auth.js
Progressive Web App (PWA), Service Workers, Workbox, Indexed
+2
|
Details |
|
EduVerse Atlas - A Complete 3D Smart Campus Platform
Students face difficulty in finding classrooms and understanding the correct timetable, be...
|
Active | FA26 (2026) |
Three.js
Python
SQLite
+1
|
Details |
|
AI VoiceClone-X :Speech to Speech emotion Transfer
In this morden era there is no such perfect and practical tool for translate or understand...
|
Active | FA26 (2026) |
Python
React
Next.js
+4
|
Details |
|
dddddddddddddddddddddddddd
jjjjjjjjjjjjjjjjjjjjj...
|
Active | FA23 (2026) |
MongoDB
Express.js
React
+1
|
Details |
|
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 |
|
Mathematics eduplay learning
In the digital age, social media and online platforms have made it extremely easy for fake...
|
Active | FA23 (2026) |
Python
JavaScript
React
+2
|
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 |
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Multi-Tenant Agri-Retail with AI-Powered Supplier Price Intelligence
• Multi-tenant shop management with strict shop-wise data isolation.
• Product and inventory management for seeds, pesticides, fertilizers, pack sizes, units, batches, expiry dates, purchase prices, and selling prices.
• Sales, purchases, sales returns, purchase returns, expenses, customer payments, and supplier payments.
• Customer and supplier ledgers with opening balances, credit transactions, payment history, outstanding balances, and account statements.
• Daily cashbook, stock movement history, low-stock and near-expiry alerts, and sales and purchase reports.
• Upload dealer price-list PDFs and extract candidate product names, pack sizes, prices, and dates for user review and confirmation.
• Compare matching products using normalized unit prices and maintain supplier purchase-price history where data is available.
• Mobile-first Progressive Web App (PWA) with Urdu/RTL support, English product names, and flexible product search.
• Search, invoice and receipt generation, and CSV/PDF report export.
• Audit history for important financial changes, plus secure backup and data restoration support.
• Clear validation and synchronization status for supported offline drafts, with duplicate-operation prevention where offline synchronization is implemented.
- • Agriculture-specific integration of customer udhaar, supplier ledgers, daily cashbook, inventory batches, expiry tracking, and business reports in one platform.
- • AI-assisted extraction of product names, pack sizes, prices, and dates from supplier price-list PDFs, with human verification to reduce incorrect financial entries.
- • Product matching and comparable unit-price analysis across supplier lists, including purchase-price history where sufficient data is available.
- • Urdu-friendly, RTL, mobile-first PWA designed around the workflows of local agricultural retailers.
- • Multi-tenant architecture that enables multiple independent shops to use one platform while keeping their business data isolated.
- • Reliability-focused design with auditable financial changes, data export, backup restoration, and carefully controlled offline synchronization for supported operations.
• Secure communication over HTTPS, protected authentication, server-side authorization, and strict tenant isolation.
• Financial and inventory transactions must remain consistent; use atomic database transactions, input validation, and appropriate numeric precision for monetary values.
• Target response time of under 2 seconds for common operations under defined test conditions and a representative test dataset.
• Automated tests for ledger calculations, partial payments, returns, stock movements, duplicate synchronization, and cross-tenant access prevention.
• Secure handling of uploaded PDFs and business records, with scheduled backups and a tested restoration procedure.
• Price extraction must allow manual review and correction before extracted data is used in confirmed financial records.
• Maintainable modular architecture, documented APIs, database migrations, and deployment instructions.