Authors : Kirupa P.; Akash A.; Disha S.; Gokul M.; Hirthick S.; Shruthi M.; Sundhareshwaran R.

Volume/Issue : Volume 9 - 2024, Issue 12 - December

Google Scholar : https://tinyurl.com/ydfx495e

Scribd : https://tinyurl.com/y7d79sdr

DOI : https://doi.org/10.5281/zenodo.14539761

Abstract : The rise in consumer awareness around environmental sustainability has highlighted the importance of sustainable practices, including the use of refurbished products as a cost-effective and eco-friendly alternative to new goods. However, the refurbished product market remains fragmented, with trust and transparency challenges. This project proposes an AI- powered e-commerce platform that enhances the buying and selling experience for refurbished products by leveraging advanced machine learning algorithms. Key features include AI-driven product authentication, dynamic price optimization, personalized recommendations, a robust rating and review system, and partnerships with certified refurbishing facilities to promote sustainable sourcing. By addressing market limitations, this platform aims to foster a reliable and transparent ecosystem for refurbished goods, empowering consumers with affordable, high-quality options while supporting a circular economy and reducing environmental impact.

Keywords : Refurbished Products, Artificial Intelligence, E- Commerce, Sustainability, Product Authentication, Price Optimization.

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