MUMBAI, India, Aug. 17 -- Intellectual Property India has published a patent application (202641095568 A) filed by Sai Vidya Institute Of Technology on August 07, 2026, for "pothole Detection & Smart Road Model".
Inventors include Mr. Eshwaraj; Mr. Gowtham B; Dr. M B Ananthayya; Dr. Shantakumar B Patil; Mr. Chandrashekara Lingaiah Nagaratna; Mr. Goutham M R; Mr. Shashank Naik A T; Mr. Kishan Gowda V; Mr. Chinmay M; Mr. Althaf B Kallimani; and Mr. Dhanush N.
The application for the patent was published on August 14, 2026, under issue no. 33/2026.
Abstract: Road infrastructure is a critical component of transportation systems, and timely detection of potholes is essential for ensuring road safety, reducing vehicle damage, and minimizing maintenance costs. The Pothole Detection & Smart Road Model is an intelligent system designed to automatically identify potholes using sensors and embedded technology while providing real-time information to road users and maintenance authorities. The proposed model integrates ultrasonic sensors, vibration sensors, and a microcontroller to detect irregularities in road surfaces. When a pothole is identified, the system records its location using GPS and transmits the information through an IoT platform to a central monitoring system. The collected data can be visualized on a dashboard, enabling municipal authorities to prioritize maintenance activities efficiently. Additionally, the model can alert approaching drivers through a mobile application or smart display, thereby reducing the risk of accidents. The smart road concept also supports continuous monitoring of road conditions, improving the efficiency of infrastructure management. By automating pothole detection, the system reduces dependence on manual inspections, lowers operational costs, and enables faster maintenance decisions. The prototype is suitable for urban roads, highways, and smart city applications. The proposed system is cost-effective, scalable, and capable of enhancing road safety through real-time monitoring and data-driven maintenance. Future improvements may include the integration of artificial intelligence and computer vision for higher detection accuracy, predictive maintenance, and automated road condition analysis.
Disclaimer: Curated by HT Syndication.
