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Efficient waste management is crucial in reducing environmental pollution and promoting sustainability. This paper presents an automated waste classification and sorting system that integrates deep learning with Arduino-based hardware for real-time waste disposal. The system employs the YOLOv8 object detection model to classify waste into three categories: biodegradable, non-biodegradable, and hazardous. A laptop's integrated camera captures waste images, which are processed by a deep learning model to determine the appropriate bin for disposal. The hardware system consists of an Arduino board controlling servo motors that open designated pressable bins based on the classification. Experimental results demonstrate high classification accuracy and efficient real-time sorting, reducing human effort and enhancing waste management efficiency.
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Copyright © 2025, This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC-BY-NY-SA). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Corresponding Author: Deepak, amdeepakthegreat@gmail.com
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.
Conflict of interest: The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Publisher’s note: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
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