MUMBAI, India, July 7 -- Intellectual Property India has published a patent application (202641075338 A) filed by Hindusthan Institute Of Technology on June 18, 2026, for Artificial Intelligence Based Road Maintenance And Aler System.
Inventors include Dr. C. Natarajan; Dr. C. Kalamani; Dr. B. Paulchamy; Dr. K. Mahendrakan; K. Mahaveer; A. Nagulan Christobar; S. Rakesh; and K. Vignesh.
The application for the patent was published on July 03, 2026, under issue no. 27/2026.
Abstract: Efficient road maintenance and safety management are critical for ensurmg reliable transportation infrastructure and reducing accidents. Traditional maintenance practices often rely on manual inspections and reactive measures, leading to increased costs, delays, and safety risks. The proposed AI-based Road Maintenance and Safety System that leverages computer vision, Internet of Things (loT) sensors, and machine learning algorithms to monitor road conditions in real time and enhance safety. The system employs image processing and deep learning techniques to detect potholes, cracks, debris, and other surface anomalies from camera and drone footage. Additionally, sensor data such as traffic flow, weather, and vibration patterns are analyzed to predict potential road failures and optimize maintenance schedules. For safety enhancement, the AI model integrates real-time traffic and environmental data to identify hazardous zones and alert drivers through connected vehicle networks. The proposed system aims to reduce maintenance costs, improve response time, and enhance overall road safety through predictive analytics and automated decision- making. Experimental results and simulations demonstrate that AI-driven approaches can significantly improve the accuracy, efficiency, and sustainability of road infrastructure management. The system aims to provide a low-cost, efficient, and reliable solution for measuring distances and detecting obstacles in real time in various fields such as smart parking, robotic navigation, and road safety.
Disclaimer: Curated by HT Syndication.
