Intellectual Property India Publishes Patent Application for Machine Learning-Based Real-Time Worker Safety Risk Prediction And Automated Hazard Detection And Alert System

MUMBAI, India, Oct. 5 -- Intellectual Property India has published a patent application (202641109843 A) filed by Dr. V. Santhosh; Prof. Dr. Diwakar Chaudhary; Sudha Singaraju; Jyoti Nagpal; Sudha Rani; Veeresh Biradar; Rinki Bhati; Mr. K. Dinakaran; Dr. G. Charles Babu; Dr. Kushal Pal Singh; Dr. N. Chidambararaj; and A. Kiruthika on September 13, 2026, for Machine Learning-Based Real-Time Worker Safety Risk Prediction And Automated Hazard Detection And Alert System.

Inventors include Dr. V. Santhosh; Prof. Dr. Diwakar Chaudhary; Sudha Singaraju; Jyoti Nagpal; Sudha Rani; Veeresh Biradar; Rinki Bhati; Mr. K. Dinakaran; Dr. G. Charles Babu; Dr. Kushal Pal Singh; Dr. N. Chidambararaj; and A. Kiruthika.

The application for the patent was published on October 02, 2026, under issue no. 40/2026.

Abstract: Machine Learning-Based Real-Time Worker Safety Risk Prediction and Automated Hazard Detection and Alert System is the proposed invention. The proposed invention system acquires real-time data from surveillance cameras, IoT sensors, wearable devices, environmental sensors, and machine-monitoring units. A Multiscale Vision Transformer (MViT) processes video streams to detect workers, personal protective equipment (PPE), machinery, hazardous objects, unsafe postures, falls, restricted-zone entry, and worker–machine proximity. A multimodal fusion module integrates visual features with environmental and operational sensor data, while a temporal risk-prediction module analyzes worker trajectories, activity sequences, exposure duration, machinery conditions, and environmental parameters. A dynamic risk engine generates a safety-risk score and classifies detected conditions according to severity. When a risk exceeds an adaptive threshold, an automated alert module transmits context-aware warnings through wearable devices, mobile applications, alarms, or centralized safety dashboards. The system thereby enables continuous hazard detection, predictive risk assessment, early intervention, and intelligent workplace safety management while reducing dependence on manual monitoring.

Disclaimer: Curated by HT Syndication.