Development of Smart Waste Bin Segregation using Image Processing

2021 IEEE 13th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM) Pub Date : 2021-11-28 DOI:10.1109/HNICEM54116.2021.9732038

Froilan N. Jimeno, Briely Jay A. Briz, Marvin Roy P. Artiaga, Randy E. Angelia, Noel B. Limsangan

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引用次数: 5

Abstract

In the Philippines, solid waste management is still a significant problem. Improper waste disposal causes serious health problems and environmental risks such as contamination of the water systems, floods, ground and air pollution, and diseases. Unfortunately, most people mistakenly believe that not segregating waste is acceptable. This study aims to develop and design a Smart Waste Bin Segregation using Image Processing and assist waste segregation through waste identification and segregation built on machine learning capable of navigating the one-time path set by the user. In particular, create an intelligent waste bin segregation prototype using image processing with three classifications. These classifications are the biodegradable, non-bio-degradable, and unknown intended to segregate solid waste into its respective bins and conduct accuracy tests using appropriate statistical tools. This device is designed for school use and may also be used in other establishments if more waste is trained, alleviate the waste segregation problem and help build an eco-friendlier society without compromising health and hygiene. The proponents successfully materialized the device, and function tests yielded an overall result of 97.33% accuracy.

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基于图像处理的智能垃圾箱分类系统的开发

在菲律宾，固体废物管理仍然是一个重大问题。不当的废物处理会造成严重的健康问题和环境风险，如水系统污染、洪水、地面和空气污染以及疾病。不幸的是，大多数人错误地认为不分类垃圾是可以接受的。本研究旨在开发和设计一个使用图像处理的智能垃圾箱隔离系统，并通过基于机器学习的废物识别和隔离来辅助废物隔离，该机器学习能够导航用户设置的一次性路径。特别地，使用具有三种分类的图像处理创建了一个智能垃圾箱分类原型。这些分类是可生物降解的、不可生物降解的和未知的，目的是将固体废物分类到各自的垃圾箱中，并使用适当的统计工具进行准确性测试。这一装置是为学校设计的，如果对更多的废物进行培训，减轻废物分类问题，并在不损害健康和卫生的情况下帮助建立一个生态友好型社会，也可用于其他机构。支持者成功实现了该装置，功能测试的总体结果准确率为97.33%。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

2021 IEEE 13th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM)

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