Auto Track: A Web Platform to Manage Servicing, Predict Resell Price and Optimize Vehicle Performance

Auto-Track: Revolutionizes Vehicle Management through Data-Driven Insights is an innovative web application built on the MERN stack, designed to modernize vehicle ownership by offering a streamlined platform for essential tasks such as scheduling appointments with top-rated garages, based on user ratings and reviews. It also features secure document storage for vehicle registration and insurance. Auto Track automatically tracks service history, offering detailed information like service dates, garage locations, parts replaced, costs, and visual documentation, enabling users to make informed decisions. The core feature is a machine learning model that analyses a vehicle’s service history to predict resale value, empowering users to make better pricing decisions or plan future maintenance investments. Additional functionalities, such as timely service reminders and on-demand roadside assistance, improve the user experience by promoting preventive maintenance and ensuring rapid assistance in emergencies. The present work discusses the development and functionality of Auto Track, focusing on its potential to enhance vehicle management and build trust through data-driven insights. Future enhancements may include optimizing the machine learning model, integrating fuel efficiency tracking based on driving behavior, and connecting with other automotive services to offer a new vehicle management ecosystem, positioning Auto Track as a transformative tool in vehicle ownership.