COMPREHENSIVE VEHICLE SERVICES & E-COMMERCE PLATFORM WITH PRICE PREDICTION USING ML

Abstract

This literature review presents an integrated web application concept designed to streamline vehiclerelated services, including real-time mechanic alerts, on-demand car washes, car rentals, spare parts sales, and used car price predictions. The platform leverages geolocation data and machine learning algorithms to facilitate seamless service delivery and accurate price estimates. By consolidating these services into a single interface, the web application aims to enhance the convenience and reliability of vehicle ownership. Key features such as real-time mechanic alerts provide users with timely assistance, while the car rental system and spare parts marketplace are envisioned to offer a user-friendly e-commerce experience. The used car price prediction module, already utilizing the XGBoost machine learning model, provides reliable estimates of vehicle resale value. This model was selected for its robustness and efficiency in handling structured data, producing accurate predictions based on various vehicle attributes. Testing results demonstrate the platform’s potential effectiveness in improving response times for mechanic alerts and delivering accurate price predictions. The proposed system offers a promising solution for managing vehicle services, with future improvements focusing on optimizing predictive models and expanding service coverage.