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Review | Green Intelligent Systems and Applications | Volume 5 - Issue 2 - 2025 | 123-139 | https://doi.org/10.53623/gisa.v5i2.706
© 2025 by the author(s), and is licensed under the Creative Commons Attribution 4.0 International (CC BY 4.0) License Creative Commons Attribution 4.0 International (CC BY 4.0) License

A Systematic Literature Review of YOLO and IoT Applications in Smart Waste Management

Author(s): Trisna Gelar ORCID https://orcid.org/0000-0002-9915-7205 , Sofy Fitriani , Setiadi Rachmat ORCID https://orcid.org/0000-0002-0312-9892
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Computer Engineering and Informatics Department, Politeknik Negeri Bandung, West Java, Indonesia

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Green Intelligent Systems and Applications

Green Intelligent Systems and Applications

Volume 5 - Issue 2 - 2025

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The increase in urbanization and global population expansion resulted in increased garbage production, causing considerable environmental and public health issues that exceeded traditional waste management approaches. To tackle these challenges, automated waste detection and analysis integrated computer vision, especially deep learning, with the Internet of Things (IoT) in intelligent waste management applications. This comprehensive literature review investigated a wide range of You Only Look Once (YOLO) applications in IoT-based waste detection and management, demonstrating its efficacy in addressing global waste issues. Employing specific keywords and Boolean operators, the review followed a rigorous methodology to explore reputable electronic databases for peer-reviewed articles published from 2019 to 2025. The primary findings indicated that different iterations of YOLO (v3 to v12) were integrated with diverse IoT devices and computing setups, including edge and centralized systems. These integrations facilitated four crucial applications: hazardous waste management, monitoring of smart bins, classification of waste types, and detection of litter in public spaces. This integration enhanced sustainability through improved waste management practices, increased efficiency in waste processes, and reduced manual labor requirements. Challenges included precise waste identification in complex scenarios, adaptation to fluctuating environmental conditions, and ensuring dependable, low-power operation of IoT devices. To sum up, the integration of YOLO and IoT established a robust basis for intelligent waste management, transforming reactive approaches into proactive strategies. Moving forward, research should prioritize enhancing the integration and power management of IoT sensors, optimizing edge deployment, and developing more resilient YOLO models.

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SUBMITTED: 29 May 2025
ACCEPTED: 25 July 2025
PUBLISHED: 4 August 2025
SUBMITTED to ACCEPTED: 57 days
DOI: https://doi.org/10.53623/gisa.v5i2.706

Cite this article
Gelar, T., Fitriani, S., & Rachmat, S. (2025). A Systematic Literature Review of YOLO and IoT Applications in Smart Waste Management. Green Intelligent Systems and Applications, 5(2), 123–139. https://doi.org/10.53623/gisa.v5i2.706
Keywords
IoT Object Detection SLR Waste Management YOLO
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