MUMBAI, India, June 26 -- Intellectual Property India has published a patent application (202441098745 A) filed by Gowrishangar I R; and Yuwlnganesh K S on December 13, 2024, for Human Interface Monitoring And Digital Twins To Collect Workstation Data In The Cloud.
Inventors include Gowrishangar I R; Yuwlnganesh K S; and Vignesh S.
The application for the patent was published on June 19, 2026, under issue no. 25/2026.
Abstract: ANNEXURE III The claiming of novelty of Personal Protection Equipment Detection Application as illustrated in the following steps. ABSTRACT In industrial settings, ensuring safety and operational efficiency has become increasingly critical, as workplace accidents pose risks to both personnel and productivity. Traditional safety systems often lack the real-time responsiveness needed to detect safety gear compliance effectively. This study addresses these limitations by integrating Human Interface Monitoring with Di1,ital Twiri technology to enable accurate, real-time workstation monitoring and safety compliance.The primary aim of this project is to develop an automated safety monitoring system that· detects compliance with personal protective equipment and proactively intervenes to prevent unsafe operations. The proposed system uses object detection models, specifically YOL0v8 for detecting safety gear and MTCNN for facial detection. Data collected from real- time video feeds is processed on a Raspberry Pi, which communicates wi.th a Programmable Lo1,ic Controller (PLC) to control workstation equipment. This setup includes key components such as environmental sensors, a digital twin visualization platform, and an alert system that captures and logs non-compliance incidents.Experimental results .show an average Fl score of 0.81 across detected safety classes, with detection precision reaching 0.88 for critical items like masks and helmets. The system accurately identifies missing safely gear in real time, enabling immediate machine shutdowns when necessary. This implementation reduces the risk of accidents due to human error while maintaining uninterrupted operations. The findings demonstrate that this cost-effective system can enhance safety compliance in industrial environments through efficient and reliable safety monitoring. Keywords: Industrial safety, human interface monitoring, digital twin, real~time object detection, YOL0v8, programmable logic controller
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