DEPARTMENT OF Artificial Intelligence & Data Science

Our department is committed to advancing innovation through groundbreaking research projects that address real-world challenges. With funding from esteemed institutions and industry leaders, our research spans multiple domains, including artificial intelligence, computer vision, and automation. Our goal is to develop impactful solutions that contribute to technological progress and societal well-being.

• • One of our ongoing projects, the MULTI AGENTIC SYSTEM POWERED BY LLM FOR ENHANCED PROJECT MANAGEMENT AND KNOWLEDGE PRESERVATION, is funded by APJ Abdul Kalam Technological University with a grant of ₹21,750 for the year 2024-2025. This project aims to develop a multi agentic framework for enhanced project management and knowledge preservation of software projects.

• • Another project IMPLEMENTATION OF AN AI-POWERED NON-VERBAL COMMUNICATION COACH is funded by APJ Abdul Kalam Technological University with a grant of ₹30,000 for the year 2024-2025.  This project aims to develop a feedback system to analyze non-verbal cues in job interviews. It detects facial expressions, eye contact, posture, and gestures to provide personalized improvement suggestions. By tracking progress over time, the system helps users refine their non-verbal communication for better interview success.

• • Another major initiative is the Capstone Project: SMART CARRIER ROBOT, supported by The Muthoot Group, with a substantial funding of ₹3,50,000. This project focuses on developing an autonomous system to navigate the college campus, ensuring efficient and secure parcel delivery, particularly from the college gate to college reception.

• • Another ongoing project is SIGN LANGUAGE TO SPEECH CONVERSION, aiming to develop a software application capable of recognizing sign language gestures of a deaf individual and converting them into spoken language in real-time.

PRODUCTS DEVELOPED

• • MITS Admission Management Software – Version 1
    The MITS Admission Management Software – Version 1 is an innovative web application developed by Abijith Biju, Amal, Abhiram, Nandakrishnan, Hanna Sabu and Hamda, the 2019-23 graduated batch students under the expert guidance of Dr. Cerene Mariam Abraham. Designed to streamline the admission process for B.Tech courses at MITS, this software addresses the challenges faced in previous years with third-party products, offering a seamless, user-friendly experience for both students and administrators.

• • MITS Rank List Management System
    The MITS Rank List Management System is a purpose-built web application developed by the 2019-23 graduated batch under the guidance of Dr. Cerene Mariam Abraham. Designed to streamline the rank list and counselling process for MITS management merit quota admissions, this software provides a seamless and transparent experience for students and administrators alike.

• • MAAC – MITS Admission Assistant Chatbot
    The MITS Admission Assistant Chatbot (MAAC) is an intelligent, AI-driven web application developed by Eldho (M.Tech 2020-22 batch), Joel (B.Tech 2019-23 batch), and Jazzir (B.Tech 2020-24 batch) under the guidance of Dr. Cerene Mariam Abraham. Designed to streamline the admission inquiry process, MAAC enhances user experience by providing instant responses to queries regarding admissions at MITS.

CAPSTONE PROJECT

• • Smart Carrier Robot
    Faculty Investigators: Ms. Anoopa S, Dr. Cerene Mariam Abraham, Dr. Sumam Mary Idicula
    Student Investigators: Asher V cherish, BalaKrishnan kK S, Avathar R Nair, Mohammed Nazel (2021-25), Hazal, Bobby, Abhay, Timon, Uma (2022-26), Amal, Sourav, Binaya, Milan, Akshat, Veni (2023-27)
    Funding Amount: Rs. 350000
    Project description: The Smart Carrier Robot is an autonomous system designed to navigate the college campus, ensuring efficient and secure parcel delivery, particularly from the college gate to college reception. This robot’s adaptability also makes it suitable for broader societal applications, such as assisting hospitals in delivering medical supplies, operating in metro stations for handling logistics, and participating in disaster relief efforts by transporting essential items to hard-to-reach areas. The robot’s design includes features like obstacle detection and alert systems, ensuring reliable service under various conditions. The project aims to develop an advanced navigation system for an autonomous delivery robot, designed to operate seamlessly in various outdoor settings. By integrating lidar and camera sensors, the system performs real-time terrain mapping and obstacle detection, ensuring accurate navigation across different terrains. The inclusion of a YOLO-based pedestrian motion prediction algorithm allows the robot to anticipate and respond to pedestrian movements, enhancing safety and efficiency. Additionally, the system continuously adapts to dynamic changes in the environment, providing a robust and flexible navigation solution.

• • Sign Language to Speech Conversion
    Faculty Investigators: Ms. Anoopa S, Dr. Cerene Mariam Abraham, Dr. Sumam Mary Idicula
    Student Investigators: Alby P Varghese, Muhammed Irfan, Adwaith, Bala Murali, Adithya S Kumar, Azeem V S, Anaina Samsan (2022-26), Aadinath Pulikkathara Deepak, Aparnamol K S (2023-27)
    Funding Amount: Rs. Nil
    Project description: The project aims to develop a software application capable of recognizing sign language gestures of a deaf individual and converting them into spoken language in real-time. This technology seeks to enhance communication accessibility for the deaf community by bridging the gap between sign language and spoken language users. By leveraging computer vision and machine learning techniques, the software interprets sign language gestures captured through a camera feed and generates corresponding spoken language output. The project targets robustness, accuracy, and usability to facilitate seamless and effective communication between deaf individuals and non-signing individuals.
    Objectives :

    • • Recognize and interpret a wide range of sign language gestures with high accuracy and in real-time.
    • • Convert recognized gestures into spoken language output using synthesized speech.
    • • Ensure usability by providing an intuitive interface and reliable performance across various environmental conditions.
    • • Facilitate better communication between deaf individuals and non-signing individuals, thereby promoting inclusivity and accessibility.
    • • Explore and integrate advancements in computer vision and machine learning to continually improve the system’s recognition capabilities.

Research Publications

Patents & Copyrights

Funded Projects

Books/Book Chapters with reputed publishers