Intellectual Property India Publishes Patent Application for 'Ai-Driven Automated Traffic Violation Detection System For Real-Time Identification Of Helmetless Riding, Triple Riding, And Wrong-Way Driving With Automated Evidence Capture And Alert Generation' Filed by Cmr College Of Engineering & Technology

MUMBAI, India, April 17 -- Intellectual Property India has published a patent application (202641042573 A) filed by Cmr College Of Engineering & Technology, Hyderabad, Telangana, on April 2, for 'ai-driven automated traffic violation detection system for real-time identification of helmetless riding, triple riding, and wrong-way driving with automated evidence capture and alert generation.'

Inventor(s) include P. Mahesh Babu; S. Vaishnavi; B. Bharath; P. Tulasi Reddy; B. Akhila; D. Snehitha; Sk. Sana; B. Pranay; D. Yashwanth; and D. Sindhu.

The application for the patent was published on April 17, under issue no. 16/2026.

According to the abstract released by the Intellectual Property India: "The present invention discloses STRIDE - Smart Traffic Rule Identification Detection Extension - an artificial intelligence-based system for automated real-time detection, recording, and reporting of traffic violations on public roadways. The system comprises three integrated functional modules: a video input capture unit that receives continuous live footage from a standard webcam or CCTV camera; a deep learning-based detection unit powered by the YOLOv8 object detection architecture trained on domain-specific datasets to identify violations including helmetless riding, triple riding on two-wheeled motor vehicles, and wrong-direction vehicular movement; and an output and alert dispatch unit that captures timestamped annotated evidence images, extracts vehicle registration numbers using optical character recognition, stores violation records in a structured repository, and dispatches automated notifications via email and SMS to configured enforcement authority recipients. The operator monitoring dashboard provides realtime visual feedback including annotated video streams and violation logs. The system is designed to operate on commodity computing hardware, including laptop computers and single-board embedded systems, without requiring expensive proprietary infrastructure. STRIDE addresses the critical limitations of manual traffic surveillance by delivering scalable, accurate, and continuous automated enforcement support, making it suitable for deployment in urban traffic management, highway surveillance, and smart city governance applications."

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