AI-powered waste management: a case study on the application of YOLOv5 and K-means clustering in urban communities

Tianzhuzi Tan; Xueying Dong; Qishun Xu; Nuo Zou

doi:10.1117/12.3012490

21 December 2023 AI-powered waste management: a case study on the application of YOLOv5 and K-means clustering in urban communities

Tianzhuzi Tan, Xueying Dong, Qishun Xu, Nuo Zou

Author Affiliations +

Proceedings Volume 12970, Fourth International Conference on Signal Processing and Computer Science (SPCS 2023); 1297044 (2023) https://doi.org/10.1117/12.3012490
Event: Fourth International Conference on Signal Processing and Computer Science (SPCS 2023), 2023, Guilin, China

Abstract

Urban waste management is a pressing global issue that demands innovative and universally applicable solutions. This paper introduces a revolutionary approach to waste management that harnesses the power of artificial intelligence(AI)and community engagement. By integrating the YOLOv5 image detection algorithm, K-Means clustering, and integer programming within a community-based framework, we present a method that transcends geographical and cultural boundaries, offering a universally applicable solution to waste management. The potential implications of this approach are profound. Not only does it offer a practical solution to waste management in urban communities, but it also fosters community engagement and environmental awareness. This study, therefore, serves as a beacon for future research and practice in sustainable urban living, demonstrating the transformative potential of AI when applied to real-world challenges.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Tianzhuzi Tan, Xueying Dong, Qishun Xu, and Nuo Zou "AI-powered waste management: a case study on the application of YOLOv5 and K-means clustering in urban communities", Proc. SPIE 12970, Fourth International Conference on Signal Processing and Computer Science (SPCS 2023), 1297044 (21 December 2023); https://doi.org/10.1117/12.3012490

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