MUMBAI, India, July 7 -- Intellectual Property India has published a patent application (202641081092 A) filed by Mlr Institute Of Technology on July 01, 2026, for Yolov5 Based Real-Time Detection Of Traffic Violations For Smart City Surveillance.
Inventors include Dr. Ajmeera Kiran; Ms. Madupu Srinithya; Mr. Shaik Saniya; and Mr. Mittapelli Abhinav.
The application for the patent was published on July 03, 2026, under issue no. 27/2026.
Abstract: In this invention, “YOLOv5 Based Real-Time Detection of Traffic Violations for Smart City Surveillance” is disclosed as an intelligent traffic monitoring and enforcement system that utilizes deep learning and computer vision technologies to automatically detect traffic violations from live video streams. The invention acquires video data from CCTV cameras, traffic surveillance systems, and smart city monitoring networks and processes the captured frames using a YOLOv5-based object detection model. The system accurately identifies vehicles, motorcycles, riders, helmets, pedestrians, and other traffic-related entities in real time. A violation detection module analyzes detected objects and determines the occurrence of traffic offenses such as helmet non-compliance, triple riding, seatbelt violations, red-light jumping, illegal parking, wrong-way driving, lane violations, and other predefined traffic infractions. Upon detection of a violation, a number plate recognition module employing Optical Character Recognition (OCR) and Automatic Number Plate Recognition (ANPR) techniques extracts the vehicle registration number for identification purposes. The extracted information, along with captured evidence, timestamps, and location details, is stored in a centralized database for further processing. The invention further incorporates an automated e-challan generation module that calculates penalties, verifies previous violation records, and generates digital challans for enforcement actions. A web-based administrative dashboard enables authorized personnel to monitor violations, review evidence, manage penalty records, and generate analytical reports. The system supports continuous real-time operation, scalable deployment, and integration with intelligent transportation systems and smart city infrastructures. By combining YOLOv5 object detection, traffic violation analysis, vehicle identification, automated penalty generation, and centralized monitoring within a unified framework, the invention enhances road safety, improves traffic law enforcement efficiency, reduces manual monitoring efforts, minimizes human error, and contributes to the development of safer, smarter, and more efficient urban transportation environments.
Disclaimer: Curated by HT Syndication.
