MUMBAI, India, Nov. 2 -- Intellectual Property India has published a patent application (202641119431 A) filed by Dr Neelam Sanjeev Kumar; Ankit Sharma; and Yogesh Choudhary on October 06, 2026, for Road Hazard Detection And Risk Analysis Using Deep Learning And Gis-Based Map Visualization.
Inventors include Dr Neelam Sanjeev Kumar; Ankit Sharma; and Yogesh Choudhary.
The application for the patent was published on October 30, 2026, under issue no. 44/2026.
Abstract: Road accidents are a major concern worldwide, often caused by hazardous road conditions, poor infrastructure, and environmental factors. This project, "Road Hazard Detection and Risk Analysis Using Deep Learning and GIS-Based Map Visualization," aims to develop an intelligent system that detects road hazards, analyzes accident risks, and visualizes dangerous locations using deep learning and Geographic Information System (GIS) technology. The proposed system uses computer vision and deep learning models to identify road hazards such as potholes, cracks, damaged road surfaces, and other potential risks from road images or video feeds. The detected hazards are then analyzed based on their type, severity, and geographical location to estimate potential risk levels. GIS-based mapping is integrated to display identified hazards on an interactive map, enabling users to visualize high-risk zones and understand spatial patterns of road safety issues. The system can help authorities prioritize road maintenance, support safer route planning, and improve road safety monitoring. By combining automated hazard detection, risk assessment, and geospatial visualization, this project provides a data-driven approach to identifying road hazards and supporting proactive accident prevention.
Disclaimer: Curated by HT Syndication.
