Intellectual Property India Publishes Patent Application for Ai-Driven Real-Time Facial Recognition-Based Inmate Identification And Monitoring For Intelligent Prison Surveillance

MUMBAI, India, Nov. 2 -- Intellectual Property India has published a patent application (202641124480 A) filed by St. Joseph'S Institute Of Technology; Devadashini S; Divyashree M; and Janagiraman S on October 17, 2026, for Ai-Driven Real-Time Facial Recognition-Based Inmate Identification And Monitoring For Intelligent Prison Surveillance.

Inventors include St. Joseph'S Institute Of Technology; Devadashini S; Divyashree M; and Janagiraman S.

The application for the patent was published on October 30, 2026, under issue no. 44/2026.

Abstract: Rising security demands and the necessity of an automated and accurate surveillance system in correctional facilities has driven towards implementation of an intelligent surveillance system. In this paper we propose a novel AI based real-time face recognition-based inmates identification and monitoring system for enhanced prison security and operational efficiency. This system employs computer vision and machine learning to accurately recognize inmate faces on live video streams and authenticate them against an already established inmate database. The system works continuously to feed live video stream from the cameras and identify the persons in real-time. In case of any unauthorized or unidentified person the system instantly provides the real-time alert, capture necessary evidence and generates alert for further analysis. It also keeps the history record of inmate’s movement in a structured format, providing the authorities to keep an eye on the operations and monitor that everything is functioning in a systematic manner. A comprehensive graphical user interface is designed for the surveillance, alert system and inmate profile management to provide a simple yet efficient and comprehensive visualization. The proposed system is very lightweight, affordable and can be implemented on ordinary computers without the requirement of expensive GPUs. The experimental results show that the system is efficient in terms of surveillance and reduction in manpower.

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