MUMBAI, India, July 30 -- Intellectual Property India has published a patent application (202641087988 A) filed by Dr. Harisha Naik T; Dr. N Kartik; Mr. Joji John; Dr. Jyoti Kadadevarmath; Dr. Samriti Mahajan; Dr. Neha Saini; Sairam D Hemmige; and Dr. Bhargavi D Hemmige on July 18, 2026, for Deep Learning-Based Health Promotion School Surveillance System.
Inventors include Dr. Harisha Naik T; Dr. N Kartik; Mr. Joji John; Dr. Jyoti Kadadevarmath; Dr. Samriti Mahajan; Dr. Neha Saini; Sairam D Hemmige; and Dr. Bhargavi D Hemmige.
The application for the patent was published on July 24, 2026, under issue no. 30/2026.
Abstract: The present invention discloses a deep learning-based health promotion school surveillance system (100) comprising a sensor interfacing unit (102), a data harmonization processor (104), a feature extraction processor (106), a neural inference processor (108), a surveillance correlation processor (110), and a reporting interface (112). The sensor interfacing unit (102) acquires physiological measurements including heart rate, body temperature, blood oxygen saturation, and physical activity from wearable sensing devices together with environmental measurements including carbon dioxide concentration, particulate matter concentration, ambient temperature, humidity, and acoustic intensity from distributed classroom sensors. The data harmonization processor (104) synchronizes heterogeneous measurements into multi-channel observation matrices, while the feature extraction processor (106) generates spatial-temporal feature tensors incorporating contextual school health information. The neural inference processor (108) executes hardware-accelerated deep neural computation to generate surveillance probability vectors corresponding to multiple health conditions. The surveillance correlation processor (110) calculates temporal deviation coefficients and identify localized health anomalies.
Disclaimer: Curated by HT Syndication.
