• Standalone application capable of running in tablets and common personal computers.• Virtual hands on to students about data visualisation and analysis inside the app.• Detailed help-guide and manuals for using the application. • Training s
A web-based intelligent tutoring system for mathematics for school children with an animated agent to engage students throughout the course delivery;A novel algorithm for personalized learning based on affect and cognition. A final report detailing t
A video generation platform that can produce high-quality videos from a variety of input materials with a click of a button. This platform will be accessible through a user-friendly interface and will be designed to support the generation of videos i
An radiology knowledge graphs (KGs) for different body organs,A dataset for radiology report generation,Multimodal deep learning models to generate radiology reports from radiology images.A robust, high-quality software targeted to enhance radiology
A wearable watch-like band, akin to fitness bands, which monitors the patients vitals to detect tonic-clonic seizures and alerts their family or other caregivers in real-time that they're experiencing a seizure as well as Patients GPS Location. Durin
A wearable all-in-one Health Monitoring system with real time monitoring and user interface to monitor and communicate body’s vital information like ECG, Bodyemperature, SPO2 , Blood Pressure, etc. which is critically needed to analyse the body sit
A cutting-edge IoT patch for diabetes patients to measure blood glucose levels, utilizing non-invasive terahertz spectroscopy technology. The process involves transmitting a THz frequency through non-invasive electrodes into the skin, where glucose m
The objective of this project is to develop strategy-aware learning algorithms for PAC learning and generalization from compromised data along with development of privacy preserving control policies for multiagent systems and obfuscator algorithm for
1. Collecting historical data of weather parameters from the IMD-stations 2. Generation of the database by collecting real-time data of soil, weather, and crop parameters from IoT-based EAgriSTM (installation of EAgriSTM at 2-3 different locations) 3
1. Generation of database (Manpower deployed at ICAR-DOGR, Pune) 2. Image data-based disease prediction model using a deep learning algorithm. 3. Development of a mobile application for ease of farmers. 4. Field deployment of mobile-App for around 15
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