Design and implementation of an intelligent waste classification device

Yung-Hsiang  Chen; Chan-Hong  Chao

doi:10.59400/cai2331

Design and implementation of an intelligent waste classification device

Yung-Hsiang Chen Department of Mechanical Engineering, National Pingtung University of Science and Technology, Pingtung 912301, Taiwan
Chan-Hong Chao Department of Electrical Engineering, Kun-Shan University, Tainan 710303, Taiwan

Article ID: 2331

Keywords: intelligent waste classification; Raspberry Pi; teachable machine; image recognition; recycling; waste classification

Abstract

This study presents a guideline for an intelligent waste classification device developed using a Raspberry Pi, a camera, and Google’s Teachable Machine (TM) for image recognition. The device is designed to identify waste and classify it into recyclable and non-recyclable categories to improve recycling efficiency. The system is primarily controlled by the Raspberry Pi, with the camera capturing images, which are then processed by TM for image model training to facilitate waste classification. This paper describes the hardware and software components as well as their applications and verifies the effectiveness of the device in practical use. The device is cost-effective, offers good scalability, and is practical for waste classification in households, offices, and public spaces. This study provides valuable insights for the design and future applications of intelligent waste classification systems.

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Published

2025-03-10

How to Cite

Chen, Y.-H., & Chao, C.-H. (2025). Design and implementation of an intelligent waste classification device. Computing and Artificial Intelligence, 3(1), 2331. https://doi.org/10.59400/cai2331

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Design and implementation of an intelligent waste classification device

Abstract

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