MUMBAI, India, May 29 -- Intellectual Property India has published a patent application (202641044392 A) filed by Dr. R. Dayana; Chandrika Banerjee; and Pranesh S, Chennai, Tamil Nadu, on April 7, for 'fuel tracking and driving behaviour analysis system using machine learning and gps based real time monitoring.'
Inventor(s) include Dr. R. Dayana; Chandrika Banerjee; and Pranesh S.
The application for the patent was published on May 29, under issue no. 22/2026.
According to the abstract released by the Intellectual Property India: "This invention is an electronic device that monitors how well a car uses fuel, using satellite positioning (GPS) and analysing how someone drives the vehicle. The device collects live driving data through a mobile app (GPS), which includes where you were driving and captures several driving patterns like speed, acceleration, idling, and how far you went. It also looks at specific vehicle parameters, e.g., engine size and type of fuel used, to calculate the amount of fuel a specific driver and vehicle will use per mile. The system uses machine learning (Gradient Boosting Regressor) to predict the amount of fuel that a driver will use over the course of their trip. The machine learning model has been trained on a data set of over 1600 samples representing cars, motorbikes, and scooters with R2 = 0.94 and MAE = 0.32 L. They have identified several ways to drive that will negatively affect your fuel consumption, such as harsh acceleration, speeding excessively, and uneven speeds. The system includes a scoring algorithm that will track each trip and provide users with recommendations on how to improve their fuel efficiency based on past performance. The system also includes a benchmark database of 87 different makes of cars available in India, allowing drivers to see how their fuel efficiency compares to the fuel efficiency that the manufacturer determined for their vehicle. The structure of the system includes a PostgreSQL backend using FastAPI and a mobile app built with Flutter for use on multiple platforms that has real-time GPS tracking capabilities. Future upgrades to the system will add Internet of Things (loT) functionality and onboard vehicle diagnostics (OBD), which will help with predictive analytics and better fuel management through optimization."
Disclaimer: Curated by HT Syndication.
