MUMBAI, India, Sept. 22 -- Intellectual Property India has published a patent application (202611088836 A) filed by Uttaranchal University on July 21, 2026, for An Edge-Ai-Based Multi-Modal System For Predicting Emotional Dissonance, Job Satisfaction, And Turnover Intentions In Smart Universities.

Inventors include Ankita Joshi; Jitendra Singh; and Rahul Mahala.

The application for the patent was published on September 18, 2026, under issue no. 38/2026.

Abstract: An edge-AI-based multi-modal system and associated analytical process deploy a distributed, privacy-preserving edge computing architecture to predict emotional dissonance levels, job satisfaction indices, and turnover intention probabilities among faculty and staff within smart university environments. The system consists of multiple autonomous edge computing nodes strategically placed near campus attendance logging terminals, each comprising a single-board computer, such as a Raspberry Pi, interfaced with three multi-modal data collection modules: an RGB camera sensor configured to capture facial expressions and behavioral cues; a touch- screen web interface executing an interactive questionnaire to collect subjective occupational stress and burnout data; and a wearable biometric device equipped with a microcontroller, a heart rate monitor, a galvanic skin response (GSR) sensor, a skin temperature probe, and an ECG circuit to capture physiological stress signals. The wearable device features an automated micro-SD card buffering routine to cache telemetry streams during communication dropouts before transmitting data over a local Bluetooth link. Each edge node runs localized multi-stage pre-processing scripts to normalize data parameters, enhance images, and synchronize timestamps using integrated real-time clock (RTC) and global positioning system (GPS) inputs. A cloud-trained, edge-deployed machine learning model evaluates the compiled multi- modal datasets locally to generate real-time behavioral predictions, which are shown on a local display screen.

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