Document Type
Article
Publication Date
2-3-2025
Department
College of Computing; Department of Applied Computing
Abstract
Current waste sorting mechanisms, particularly those relying on manual processes, semi-automated systems, or technologies without Artificial Intelligence (AI) integration, are hindered by inefficiencies, inaccuracies, and limited scalability, reducing their effectiveness in meeting growing waste management demands. This study introduces a prototype waste sorting machine that integrates an AI-driven vision system with a Programmable Logic Controller (PLC) for high-accuracy automated waste sorting. The system, powered by the YOLOv8 deep learning model, achieved sorting accuracies of 88% for metal cans, 75% for paper, and 91% for plastic bottles, with an overall precision of 90%, a recall of 80%, and a mean average precision (mAP50) of 86%. The vision system provides real-time classification, while the PLC manages conveyor and actuator operations to ensure seamless sorting. Experimental results in a controlled environment validate the system’s high accuracy, minimal processing delays, and scalability for industrial recycling applications. This innovative integration of AI vision with PLC automation enhances sorting efficiency, reduces ecological impacts, and minimizes labor dependency. Furthermore, the system aligns with sustainable waste management practices, promoting circular economy principles and advancing the Sustainable Development Goals (SDGs).
Publication Title
Applied Sciences
Recommended Citation
Almtireen, N.,
Rawashdeh, N.,
Reddy, V.,
Sutton, M.,
Nedvidek, A.,
Karn, C.,
&
et. al.
(2025).
PLC-Controlled Intelligent Conveyor System with AI-Enhanced Vision of Efficient Waste Sorting.
Applied Sciences,
15(3).
http://doi.org/10.3390/app15031550
Retrieved from: https://digitalcommons.mtu.edu/michigantech-p2/1423
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
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Publisher's Statement
© 2025 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).