Authors: Tanu Yadav, Neelam Sahu, Deepak Sahu
Abstract: The rapid expansion of the pre-owned automobile industry has increased the demand for reliable and intelligent digital platforms for vehicle trading. Traditional used-car marketplaces often face challenges such as lack of transparency, inefficient search mechanisms, inconsistent pricing, and fraudulent listings, which reduce user trust and overall customer satisfaction. This research proposes an AI- powered car marketplace designed to improve the process of buying, selling, and exchanging second- hand vehicles through intelligent automation and secure digital infrastructure. The proposed system integrates advanced technologies including intelligent search optimization, personalized recommendation systems, automated listing moderation, and secure authentication mechanisms to enhance platform reliability and usability. The platform provides users with detailed vehicle listings, filtering and comparison features, responsive communication channels, and mobile-friendly accessibility to simplify customer interaction and decision-making. The backend architecture is developed to support scalable data management and efficient transaction handling using modern web technologies. Artificial Intelligence modules are incorporated to improve recommendation accuracy, optimize search relevance, and identify suspicious or duplicate listings. Experimental evaluation indicates that the proposed system improves search efficiency, recommendation precision, and operational transparency compared to conventional online used-car trading systems. The research demonstrates how AI-driven digital marketplaces can enhance trust, user engagement, and efficiency within the pre-owned vehicle industry while providing a scalable solution suitable for modern automotive e-commerce applications.
