Waste Sorting System Using AI: Development of An Embedded Solution for Efficient Waste Management
Waste is causing a serious environmental problem. Waste management and circular economy offers a best alternative for preserving the environment and protecting nature resources. This paper presents an AI-based system for waste identification and sorting, particularly focusing on plastic, which is the less decomposed waste, using computer vision techniques. The data, used for system validation, comprises publicly available datasets and a locally collected dataset, devoted to plastic classification and detection. Performance metrics demonstrate that YOLOv8 outperforms other deep learning solutions, in real-time waste detection and is well suited for implementation on a Raspberry Pi 4 Model B. The system outperforms also existing methods in terms of efficiency, accuracy, and speed, and is a promising solution for addressing the global waste management challenge.
Authors
- Dorra Sellami (ORCID: https://orcid.org/0000-0002-7235-6984)
- Ahmed Fakhfakh (ORCID: https://orcid.org/0009-0005-3219-2371)
- Jihen Frikha Elleuch (ORCID: https://orcid.org/0000-0002-0201-4831)
- Amal Remili
- Mouna Zouari Mahdi
Institutions
- Digital Research Centre of Sfax (TN)
Publication Details
- Published
- 2025-01-09
- DOI
- https://doi.org/10.1109/ipas63548.2025.10924491
- Primary Topic
- Advanced Manufacturing and Logistics Optimization
- Type
- article
- Field-Weighted Citation Impact
- 0.00