An Autonomous Institution
Accredited by NBA(CSE, ECE, EEE, MECH)
AICTE Sponsored Margdarshan Mentor Institution
DST-FIST Supported Institution | ISO 9001:2015 certified
Recognised Under Section 2(f) & 12(B) of the UGC Act,1956
103/G2, Bypass Road, Vannarpettai, Tirunelveli, Tamil Nadu, India - 627003.
Team Members:Barvin D S - IV CSBS
Mohamed Sirajul Muneer Z - IV CSBS
Dhanushkiren R - IV CSBS
The "Tree Enumeration and Forest Fire Prediction Using AI-Powered Drones" project harnesses the power of artificial intelligence and advanced drone technology to address critical environmental challenges. By utilizing AI algorithms and computer vision, drones are deployed to accurately count and monitor tree populations in forests, providing crucial data for sustainable forestry management. Additionally, the system incorporates real-time data analysis to predict forest fire risks by monitoring environmental conditions such as temperature, humidity, and wind patterns. This AI-powered solution enables early detection of fire hazards, offering a proactive approach to forest conservation and mitigating the devastating effects of wildfires.
Team Members:
Barvin D. S - IV CSBS
Muthu P - III CSBS
Syed Abbas Iqbal K - III CSBS
The "Smart Watch for Visually Impaired People" is a groundbreaking assistive technology designed to enhance the independence and quality of life for individuals with visual impairments. Equipped with advanced features such as voice commands, tactile feedback, and obstacle detection sensors, the smartwatch provides real-time navigation assistance and alerts users to nearby obstacles. It integrates AI-powered voice assistants to facilitate tasks such as making phone calls, setting reminders, and accessing essential information hands-free. By leveraging GPS, the watch can guide users through unfamiliar environments, while health monitoring features keep track of vital signs. This innovative device empowers visually impaired individuals to navigate daily activities with confidence and ease.
Team Members
Barvin D S - IV CSBS
Nowfil Ahamed T - II CSBS
Siva Balan G - II CSBS
The "AI-Powered Autonomous Tourist Rover Guide for Heritage Sites" is an innovative solution designed to enhance the visitor experience at historical and cultural landmarks. Equipped with AI-driven navigation and speech recognition, the autonomous rover guides tourists through heritage sites, providing detailed information about landmarks, historical events, and cultural significance in real-time. The rover uses advanced sensors and machine learning algorithms to navigate crowded areas, avoid obstacles, and offer personalized tour recommendations based on user preferences. With multilingual support and interactive features, this AI-powered guide offers an immersive and informative experience, making it an ideal companion for exploring heritage sites while preserving the authenticity and integrity of the location.
Team Members:
Mohamed Haji S - III CSBS
Mohamed Ibrahim M - III CSBS
Mathialagan T - III CSBS
Saravanan.V - III MECH
In Army, there is something called IPPT (Individual Physical Proficiency Test). The problem with this test is not how physically demanding it is, but instead the electronic machine that is used to count the number of Push-ups and Sit-ups done. Like most people out there, my Push-up form was always sub-par (according to the machine’s opinion). Furthermore, many NS Men (those that have already completed their 2 years of mandatory National Service) struggle to do well for the IPPT test due to the lack of practice with the machine. Therefore, In this project we build a system using media pipe and OpenCV that tracks our Push-ups, ensuring that we use the proper form for each and every rep. In this project we have designed and built a desktop app that can analyze and count the number of pushups. With this intelligence feature and an attractive user interface, our application is expected to make fitness more enjoyable.
Team Members:
Mohamed Haji S - III CSBS
Praveen P - III CSBS
Mohamed Ibrahim M - III CSBS
So many thefts in ATM by the Employees has been reported in past days. In this Project we propose a three step authentication step to prevent ATM theft by the employee. If the Employee wants to access the ATM Machine he or she has to undergo three step authentications:
Team Members:
Barvin D S - III CSBS
Mohamed Sirajul Muneer Z - III CSBS
Dhanushkiren R - III CSBS
Abishek - II CSBS
Description: The AI-based tree enumeration system utilizes computer vision and machine learning to automatically identify and enumerate trees in a given area, aiding in efficient urban forestry management. Disaster management integration involves real-time monitoring of the enumerated trees, allowing for proactive risk assessment and response planning during natural disasters or emergencies using drones. The system features a Question-Answer bot that provides instant responses to user queries, offering valuable information on tree data, disaster preparedness, and emergency procedures. The comprehensive solution combines AI-driven tree data management, disaster monitoring, and an interactive QA bot to enhance urban resilience and facilitate effective disaster response strategies
Team Members:
Barvin D S - III CSBS
Mohamed Sirajul Muneer Z - III CSBS
Dhanushkiren R - III CSBS
Description: The AI-based smart voting system employs OTP authentication, enhancing the security and integrity of the voting process. Face recognition technology ensures biometric verification, preventing unauthorized access and ensuring the identity of the voter. Strong authentication measures, such as multi-factor authentication, add an additional layer of security to safeguard the integrity of the voting system. This innovative solution enhances the efficiency and trustworthiness of the voting process, promoting a secure and transparent democratic experience.
Team Members:
Barvin D S - III CSBS
Mohamed Sirajul Muneer Z - III CSBS
Dhanushkiren R - III CSBS
Description: This AI-based system employs advanced object detection algorithms to assist visually impaired individuals by identifying and describing their surroundings in real-time. Additionally, integrated voice translation technology enables the system to convert this information into spoken words, providing users with a comprehensive understanding of their environment. Through the seamless combination of object detection and voice translation, the solution aims to enhance accessibility for the visually impaired, enabling them to navigate and comprehend their surroundings more independently and effectively
Team Members:
Barvin D S - III CSBS
Mohamed Sirajul Muneer Z - III CSBS
Mohamed Haji S - III CSBS
Mohamed Ibrahim M - III CSBS
Description: The automatic time table generator utilizes key comments as input triggers to dynamically create relevant and coherent content. Employing natural language processing and machine learning techniques, the system interprets and expands upon the provided comments, generating comprehensive and contextually appropriate content. This innovative approach streamlines content creation by leveraging user-provided cues, offering a time-efficient solution for producing high-quality text across various applications, from writing to social media management.
