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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM65214
Volume:
10 |
6 |
Jun 2026
Pages:
1-4
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Department of Computer Engineering
Sinhgad Academy Of Engineering, Pune
Department of Computer Engineering
Sinhgad Academy Of Engineering, Pune
Department of Computer Engineering
Sinhgad Academy Of Engineering, Pune
Department of Computer Engineering
Sinhgad Academy Of Engineering, Pune
Department of Computer Engineering
Sinhgad Academy Of Engineering, Pune
In everyday life, many individuals end up keeping items that are no longer useful to them but could still be valuable to someone else. Instead of being reused, these items are often discarded, which contributes to waste generation and environmental issues. To address this problem, EcoSwap has been developed as a digital platform that enables users to exchange items directly without involving any monetary transactions. The application allows users to upload details of items they wish to give away, explore listings available in their nearby area, and interact with other users through real-time communication. It also supports secure exchange mechanisms to ensure a reliable swapping process. In addition, the system incorporates intelligent features such as personalized item suggestions, an AI-powered assistant to guide users, and integration with charity organizations for donation purposes. The platform is implemented using technologies like Next.js and Supabase, along with basic machine learning techniques to enhance usability and recommendation accuracy. Overall, EcoSwap demonstrates how a well-designed technology solution can encourage responsible consumption, reduce unnecessary waste, and foster a collaborative community environment.
KEYWORDS
EcoSwap provides a practical approach to promoting sustainable habits by encouraging users to reuse items rather than discard them. The platform brings together simple concepts and modern technologies to create a system that is both effective and easy to use. Through its implementation, it showcases how features such as real-time interaction, intelligent recommendations, and AI-based assistance can be applied in real-world scenarios. The project also emphasizes the importance of developing solutions that support community engagement while addressing environmental concerns. Looking ahead, the platform can be further enhanced by introducing a mobile application, improving the recommendation logic, and scaling the system to accommodate a larger user base.
1. Botsman, R., & Rogers, R. (2010). Collaborative Consumption. 2. Brown, T. et al. (2020). Language Models Research. 3. Covington, P. et al. (2016). Recommendation Systems. 4. Hamari, J. et al. (2016). Sharing Economy Study. 5. Koren, Y. et al. (2009). Recommender Systems. 6. Makridakis, S. et al. (2018). Forecasting Methods. 7. Scikit-learn Documentation. 8. Supabase Documentation. 9. Next.js Documentation.
Publication Date
6/20/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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