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.
Face recognition based attendance management system
Core Problem: Traditional attendance systems in educational institutions rely on manual roll calls, sign-in sheets, or card-based methods that are time-consuming, prone to proxy attendance (students marking attendance for absent peers), and difficult to maintain accurately over time. Faculty spend valuable lecture time on attendance, and administrative staff struggle with compiling and analyzing attendance records. Core Position: The Smart Attendance System leverages face recognition technology to automate the attendance marking process in educational institutions. By capturing and identifying student faces through a webcam or uploaded image, the system eliminates proxy attendance, reduces manual effort, saves classroom time, and provides real-time, accurate attendance records accessible to both students and administrators through a web-based dashboard.
Intrusion Guard: A Hybrid Machine Learning System for Network Intrusion Detection
Modern computer networks face continuous threats from malware, unauthorized access, and zero-day attacks that traditional signature-based security tools often fail to detect. These systems depend heavily on known attack patterns, which makes them less effective against new or evolving intrusions. The growing scale and complexity of network traffic also create a need for intelligent security solutions that can analyze traffic in real time and detect suspicious activity with high accuracy. This project proposes Intrusion Guard, a real-time intrusion detection system that uses machine learning to classify network traffic as normal or malicious. The system is designed for cybersecurity monitoring in environments where fast and accurate threat detection is critical, such as enterprise networks, laboratories, and institutional systems. It combines supervised and unsupervised learning to improve both known-attack detection and anomaly detection, making it more adaptable than conventional rule-based systems. The technical approach uses a hybrid model built around Random Forest for supervised classification and Isolation Forest for anomaly detection. The system processes network traffic data, extracts relevant flow-based features, and applies trained models to generate predictions in real time. To improve transparency and trust, the system also includes explainable AI output so users can understand why traffic is flagged as suspicious. The expected outcome is a practical and scalable intrusion detection solution that improves threat visibility, supports early warning, and strengthens network defense against both known and unknown attacks.
ZAPNEST: AI-Enabled SaaS E-Commerce Platform for SMEs (MERN Stack Based
ZAPNEST is a web-based Software as a Service (SaaS) e-commerce platform developed to help small and medium-sized enterprises (SMEs) transition from traditional physical businesses to modern digital marketplaces. In today’s rapidly evolving ...
AI-Based Student E-Learning Assistant
AI-Based Student E-Learning Assistant: The AI-Based Student E-Learning Assistant is a smart web-based learning platform designed to help students improve their studies through artificial intelligence. The system acts as a virtual tutor tha...
MediTrust : AI Driven doctor recommendation and Fake Review Detection Platform
In recent years, the demand for efficient and intelligent systems in the field of healthcare has significantly increased. However, the existing systems currently in use suffer from several limitations and inefficiencies. These systems are often limited to providing basic search functionality and fail to support disease-based doctor recommendations. Moreover, the presence of fake or unverified reviews reduces the reliability of these platforms. According to the literature review, many systems lack advanced filtering options, real-time doctor availability, and proper integration of appointment scheduling, which makes the overall process inefficient and time-consuming.As a result, users face difficulties in making informed decisions when selecting appropriate doctors, especially due to limited medical knowledge and unreliable feedback systems. This not only reduces the effectiveness of the system but also negatively impacts user satisfaction and decision-making.Although some solutions attempt to address these challenges, they fail to provide intelligent recommendation systems, fake review detection mechanisms, real-time scheduling, and comprehensive doctor information with advanced filtering features.Therefore, there is a strong need for a robust and intelligent system that can overcome these limitations and provide efficient, accurate, and user-friendly solutions.
Gesture control virtual mouse platform
Functional Requirements (What the system DOES) These describe the features of the system. 1. Hand Gesture Detection The system uses a camera to detect your hand. It recognizes different hand gestures. 2. Cursor Movement You can move t...
Meet hub
Functional Requirements of Meet Hub 1. User Registration and Authentication The system shall allow users to create accounts, log in securely, and recover forgotten passwords using email verification and authentication mechanisms. 2. User...
Neux remote control system and fake voice recognition
A Neux remote control system lets users control devices using smart signals instead of buttons. Fake voice recognition is when systems are fooled by copied or AI-generated voices. These technologies are advanced but need strong security t...
Campus event management system
Functional Requirements The Campus Event Management System will allow Admin, Students, and Organizers to manage campus events through a web-based platform. Admin can create, update, approve, and delete events, manage users, view registrati...
| Project Information | Status | Batch | Technologies | Action |
|---|---|---|---|---|
|
Face recognition based attendance management system
Core Problem:
Traditional attendance systems in educational institutions rely on manual ...
|
Active | FA23 (2026) |
MongoDB
Express.js
React
+3
|
Details |
|
Intrusion Guard: A Hybrid Machine Learning System for Network Intrusion Detection
Modern computer networks face continuous threats from malware, unauthorized access, and ze...
|
Active | FA23 (2026) |
Python
Flask
|
Details |
|
ZAPNEST: AI-Enabled SaaS E-Commerce Platform for SMEs (MERN Stack Based
ZAPNEST is a web-based Software as a Service (SaaS) e-commerce platform developed to help ...
|
Active | FA23 (2026) |
JavaScript
React
Express.js
+3
|
Details |
|
AI-Based Student E-Learning Assistant
AI-Based Student E-Learning Assistant:
The AI-Based Student E-Learning Assistant is a sma...
|
Active | FA23 (2026) |
JavaScript
React
Express.js
+6
|
Details |
|
MediTrust : AI Driven doctor recommendation and Fake Review Detection Platform
In recent years, the demand for efficient and intelligent systems in the field of healthca...
|
Active | FA23 (2026) |
JavaScript
Python
Next.js
+6
|
Details |
|
Gesture control virtual mouse platform
Functional Requirements (What the system DOES)
These describe the features of the system....
|
Active | FA23 (2026) |
MongoDB
Express.js
React
+1
|
Details |
|
Meet hub
Functional Requirements of Meet Hub
1. User Registration and Authentication
The system s...
|
Active | FA23 (2026) |
MongoDB
Express.js
React
+1
|
Details |
|
Neux remote control system and fake voice recognition
A Neux remote control system lets users control devices using smart signals instead of but...
|
Active | FA23 (2026) |
Python
Django
|
Details |
|
Campus event management system
Functional Requirements
The Campus Event Management System will allow Admin, Students, an...
|
Active | FA23 (2026) |
JavaScript
HTML/CSS
Bootstrap
+2
|
Details |
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AI-Based Student E-Learning Assistant
The AI-Based Student E-Learning Assistant is a smart web-based learning platform designed to help students improve their studies through artificial intelligence. The system acts as a virtual tutor tha...