MUMBAI, India, Feb. 6 -- Intellectual Property India has published a patent application (202541122351 A) filed by Nandha Engineering College, Erode, Tamil Nadu, on Dec. 5, 2025, for 'uav-assisted intelligent routing system for emergency vehicles based on traffic density and crowd monitoring.'
Inventor(s) include C Pratheeba; B Dhanush Kumar; M S Gokul; A Jagapriyan; S V Soundharyaa; and S Swetha.
The application for the patent was published on Feb. 6, under issue no. 06/2026.
According to the abstract released by the Intellectual Property India: "The present invention relates to an AI-enabled multi-drone traffic detection and hospital route optimization system designed for real-time emergency response and ambulance routing. The system integrates artificial intelligence (AI), computer vision, graph-based pathfmding algorithms, and loT communication through Telegram, to identify the most efficient hospital route by analyzing live traffic conditions captured via drone surveillance. The proposed system utilizes drone video feeds positioned at multiple hospital zones to detect and count vehicles using the YOLO (You Only Look Once) deep learning algorithm. Real-time traffic density from each drone location is processed alongside geographical road network data obtained from OpenStreetMap (OSMnx). The system applies Dijkstra's shortest path algorithm, where the edge cost is computed as a function of distance and traffic density, to determine the optimal hospital with the lowest weighted route cost. Once the best route is identified, a Folium-generated map is produced to visualize the path from the accident location to the selected hospital. The map is saved as an HTML file, automatically uploaded to GitHub via API, and converted into a publicly accessible link. A screenshot of the route map is captured using Selenium and the Python Imaging Library (PJL) to create a static image. The Telegram bot interface then delivers a detailed message to users containing the best hospital name, distance and vehicle count, live route map link, and map screenshot, ensuring rapid, data-driven emergency decision-making. This invention provides a smart, automated, and efficient emergency routing framework that minimizes delay, enhances real-time awareness, and supports intelligent ambulance dispatching: By combining AI-based traffic detection, Dijkstra's algorithm, and loT communication, the system achieves high accuracy, scalability, and reliability, advancing the field of AI-driven intelligent transportation and emergency management systems."
Disclaimer: Curated by HT Syndication.
