MUMBAI, India, Sept. 14 -- Intellectual Property India has published a patent application (202641108229 A) filed by Pragati Engineering College on September 09, 2026, for Ai-Based Emotional Digital Twin For Students Using Multimodal Behavioral Analytics, Predictive Emotional Intelligence, Explainable Ai, And Personalized Wellness Recommendation System.
Inventors include Mr. M. V. Rajesh; Mr. Tarra Sekhar; Mrs. N. V. S. Sowjanya; and Mr. M. Brahmaraju.
The application for the patent was published on September 11, 2026, under issue no. 37/2026.
Abstract: The present invention concerns the Artificial Intelligence (AI)-Based Emotional Digital Twin for Students, which is aimed at monitoring, modeling, predicting and enhancing the emotional wellbeing of the students by means of the incorporation of the multimodal data including physiological, behavioral, academic, emotional and environmental data. The inventive system includes the multimodal data acquisition module, preprocessing module, AI processing module, Emotional Digital Twin engine, predictive analytics engine, Explainable Artificial Intelligence (XAI) module, personalized recommendation engine, and privacy-preserving data management platform. The present invention gathers data from wearable sensors, smartphones, cameras, microphones, Learning Management Systems (LMS), attendance systems, academic performance systems, and environmental sensors. The gathered data are processed by means of the machine learning and deep learning algorithms to create the virtual emotional replica of each student. The Emotional Digital Twin acquires emotional traits, stress tolerance, behavioral patterns, recovery behavior and predicts future emotional states such as stress, anxiety, emotional fatigue, and academic burnout before they occur. The present invention creates personalized wellness recommendations based on the predictions made. The invention also entails edge computing, federated learning, encryption, and role-based access control for the purpose of guaranteeing privacy and security in the processing of student information. Through emotional monitoring, prediction of students’ emotions, early detection of risks, and customized interventions, this invention will improve mental wellness among students and decision-making by educators and counselors.
Disclaimer: Curated by HT Syndication.
