MUMBAI, India, July 24 -- Intellectual Property India has published a patent application (202611067808 A) filed by Dr. Anuj Williams; Dr. Namita Goswami; Dr Sheenu Chauhan; Dr. Harikesh Bijoria; Dr. Santvana Bapna; Dr. Rahul Gupta; Prof. Dr. Geeta Gupta; Dr. Krishan Kant Meena; Dr. Firoz Akhtar; Archana Agrawal; Dr. Ayushi Agrawal; Ms. Sulekha Pateriya; and Purnima Dadhich on May 29, 2026, for Ai-Based Multidisciplinary Teacher Satisfaction Prediction System For Institutional Burnout Prevention And Wellness Optimization.
Inventors include Dr. Anuj Williams; Dr. Namita Goswami; Dr Sheenu Chauhan; Dr. Harikesh Bijoria; Dr. Santvana Bapna; Dr. Rahul Gupta; Prof. Dr. Geeta Gupta; Dr. Krishan Kant Meena; Dr. Firoz Akhtar; Archana Agrawal; Dr. Ayushi Agrawal; Ms. Sulekha Pateriya; and Purnima Dadhich.
The application for the patent was published on July 17, 2026, under issue no. 29/2026.
Abstract: The present invention discloses an AI-based multidisciplinary teacher satisfaction prediction system (100) for institutional burnout prevention and wellness optimization. The system (100) comprises an emotional intelligence analytical module (101) processing speech, sentiment, facial and psychological data; a workload optimization engine (102) evaluating teaching, examination, administrative and digital workload; an attendance behavioural monitoring module (103) analysing attendance, leave and participation patterns; and a student feedback analytical framework (104) assessing classroom interaction quality. An AI prediction engine (105) simultaneously fuses the feature vectors from modules (101) to (104) using machine learning and neural network architectures to generate calibrated burnout probability, resignation risk and productivity decline forecasts. A stress score generation module (106) normalizes these outputs, a satisfaction prediction dashboard (107) visualizes wellness intelligence and intervention recommendations, and a cloud-integrated institutional analytical system (108) centrally reports workforce sustainability analytics, together establishing a closed-loop wellness optimization ecosystem that predicts dissatisfaction before institutional disruption.
Disclaimer: Curated by HT Syndication.
