MUMBAI, India, April 17 -- Intellectual Property India has published a patent application (202641043148 A) filed by Dr. M. Suleman Basha; Dr. B. Bhaskara Rao; Ms. C. Supraja; K. B. Surendra; S. V. Sai Kayan; A. Umesh; and Rajeev Gandhi Memorial College Of Engineering And Technology, Nandyal, Andhra Pradesh, on April 4, for 'transformer-based multi-class road anomaly detection for potholes, speed breakers, and cracks.'

Inventor(s) include Dr. M. Suleman Basha; Dr. B. Bhaskara Rao; Ms. C. Supraja; K. B. Surendra; S. V. Sai Kayan; and A. Umesh.

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 relates to an intelligent road monitoring system for real-time detection and classification of road surface anomalies using artificial intelligence and computer vision techniques. The system utilizes visual data acquired from live camera feeds or recorded video inputs, which are processed into sequential frames for analysis. A deep learning-based object detection model, specifically YOLOv8, is employed to identify and classify road defects such as potholes, cracks, and speed breakers within the captured frames. The system further includes modules for preprocessing input data, extracting regions of interest corresponding to detected anomalies, and associating each detection with geolocation and timestamp information. Detected anomalies are stored along with visual evidence in a structured database, and automated digital reports are generated to facilitate efficient road maintenance and monitoring. A web-based dashboard is provided to enable real-time visualization, data management, and analytical insights, allowing authorities to identify high-risk areas and prioritize repair activities. The invention operates in real time with optimized computational efficiency, making it suitable for deployment in smart city infrastructure, highway monitoring systems, and vehicle-mounted platforms. The proposed system provides a comprehensive, automated, and scalable solution for road condition monitoring, thereby improving road safety, reducing maintenance delays, and enabling data-driven infrastructure management."

Disclaimer: Curated by HT Syndication.