We proposed a smart autonomous weed detection and removal system using AI and IoT technologies. The weeder help farmer to reduce man power , time and increase efficiency of work done in farming .
● Objectives of the Project: 1. To develop a digital twin of motor-gearbox systems to simulate faulty data 2. To develop machine learning algorithms for predictive maintenance. 3. Use case for testing and validation at the lab.
The Legal Intelligence and Decision Support System (LIDSS) project, led by Prof. Indrajit Dube with a multidisciplinary team, integrates AI and NLP to revolutionize legal research and adjudication. LIDSS deciphers complex legal documents, provides co
Our project presents a ground breaking initiative that marries extended reality (XR) technology with the capabilities of artificial intelligence (AI) and machine learning (ML) to revolutionize medical education. By creating an interactive and dynamic
We aim to develop a personalized pollution monitoring system with the following features: 1. The device apart from sensing air & noise parameters should be able to generate alerts (caution with the suggestive measures) to the user based on his/her he
Recognizing the importance of managing traffic to reduce the congestion costs and the strength of Artificial Intelligence in providing evolving solutions, the present study aims to develop an Artificial Intelligence based system for effectively manag
Development of the RMAFF machine for nano-finishing of the CAM profiled shafts with in-process surface roughness measurement and assistance in the process of feedback-based system control using Fiber Bragg Grating system.
Numerical simulation and appliaction of AI is carried out under different conditions to find out the relaibility of energy pile for space heating and cooling. Initially the plan was conduct experimental work to real scale demonstration, however, due
The proposed AI based eco-system for agriculture is an integrated crop management system which used the sensor inputs, farmer’s expertise and required data from cloud to provide amounts and type of inputs based on actual needs of cultivation. The p
The project aims to develop a real time performance monitoring system for smart concrete roads under actual traffic loading. AI based pavement performance models and traffic prediction models will be developed by utilizing real time pavement response
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