MUMBAI, India, Feb. 6 -- Intellectual Property India has published a patent application (202541084363 A) filed by Ravindra College Of Engineering For Women, Kurnool, Andhra Pradesh, on Sept. 4, 2025, for 'a dynamic model integrating machine learning and real-time apis for best path prediction.'
Inventor(s) include C. Ahalya; M. Jyothirmai; B. Geetharani; P. Kishor Kumar; K. Venkata Siva Reddy; A. Rajendra Babu; Syed Ishrath Moin; Dr. M. Jayalakshmi; and Dr. Mohebbanaaz.
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: "Unlike traditional static navigation systems, our approach continuously adapts to real-time inputs without relying on physical IoT hardware. The system fetches live traffic data from TomTom API and weather updates from Open-Meteo API to analyze critical parameters such as congestion levels, road closures, rain, fog, and temperature variations. This real-time data is processed using a Random Forest Classifier algorithm, which operates in two phases: Training Phase: 90% of historical data is used to train the model, allowing it to learn input- output relationships and improve accuracy. Testing Phase: 10% of the data is used to evaluate the model's performance, ensuring reliable and accurate predictions. By leveraging these real-time APIs and advanced machine learning techniques, our system provides dynamic, data-driven route optimization that minimizes travel time and enhances safety. The optimized route is displayed using an interactive mapping tool (Folium in Python), allowing users to visualize the best travel path based on live conditions. This approach offers an efficient, adaptable, and intelligent solution for urban travel, helping commuters navigate with greater confidence while reducing road congestion and travel uncertainties."
Disclaimer: Curated by HT Syndication.
