MUMBAI, India, Sept. 28 -- Intellectual Property India has published a patent application (202621097021 A) filed by Pro. Linesh Tulshiram Khadke; G. Karunya Sai; Kalidas P; Dr. Phatangare Ambadas Somnath; Dr. Amitkumar Ranjitbhai Patel; Dr. Pendurthy Anthony Sunny Dayal; Dr. Shilpi Agarwal; Ms. Nivedita Pawar; Rakesh Chintalapudi; S. Saheetha Banu; Mr. Billa Vamsi Krishna; and Sudha K on August 11, 2026, for Machine Learning-Based System For Analyzing And Enhancing Physical Activity And Health- Related Fitness Of Students In Higher Education Institutions.
Inventors include Pro. Linesh Tulshiram Khadke; G. Karunya Sai; Kalidas P; Dr. Phatangare Ambadas Somnath; Dr. Amitkumar Ranjitbhai Patel; Dr. Pendurthy Anthony Sunny Dayal; Dr. Shilpi Agarwal; Ms. Nivedita Pawar; Rakesh Chintalapudi; S. Saheetha Banu; Mr. Billa Vamsi Krishna; and Sudha K.
The application for the patent was published on September 25, 2026, under issue no. 39/2026.
Abstract: The present invention discloses the development of an AI-based system for assessing and improving the level of physical activity and overall health and fitness of the students at higher education institutions. This AI system combines wearable devices, smartphones, fitness records of the institution, and self-recorded activity information for continuously collecting parameters such as the level of physical activity, heart rate, sleeping time, level of exercises, body mass index, and sedentary behavior. An AI analytics engine analyzes collected information to detect individual fitness profiles, categorize physical activity, predict health and fitness risks, and provide personalized exercise advice. The adaptive recommendation engine helps the students to have tailored workout routine, activity goals, recovery tips, and nutrition tips. The institutional dashboard allows institutional representatives to analyze the overall trend of fitness, assess participation, and develop wellness programs. FIG.1
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