Identification of plastic waste with unmanned aerial vehicle (UAV) using deep learning and internet of things (IoT)

IF 5.4 Q2 ENGINEERING, ENVIRONMENTAL

Journal of hazardous materials advances Pub Date : 2025-02-02 DOI:10.1016/j.hazadv.2025.100622

Asep Denih , Toru Matsumoto , Indriyani Rachman , Gustian Rama Putra , Irma Anggraeni , Ema Kurnia , Endang Suhendar , Anggiat Mora Simamora

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Abstract

Humans produce waste in their daily lives and activities. Waste comes from domestic and industrial activities, including organic and inorganic types. This study aimed to develop a model for a waste identification system to evaluate the plastic waste management that currently being uncommercial. Waste identification can be done quickly, precisely, and accurately using advanced technology, such as edge computing embedded on drones that can capture waste in rivers with various environmental conditions. Different types of waste can be identified according to predetermined specifications as guide data that is further processed using image processing software object detection methods based on mobile SVD. Based on our research in The Cinagara Caringin area, Bogor, this research managed to achieve an accuracy rate of 92 %. Therefore, this study successfully proposed a new method to automatically identify the type of waste using edge computing technology and make a significant contribution to efforts to mitigate the waste problem.

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利用深度学习和物联网技术的无人机识别塑料垃圾

人类在日常生活和活动中产生废物。废物来自家庭和工业活动，包括有机和无机类型。本研究旨在建立一个废物识别系统模型，以评估目前尚未商业化的塑料废物管理。利用先进的技术，可以快速、精确、准确地进行废物识别，例如嵌入在无人机上的边缘计算，可以在各种环境条件下捕获河流中的废物。根据预定的规格识别不同类型的废弃物，作为指导数据，使用基于移动SVD的图像处理软件对象检测方法进行进一步处理。基于我们在茂物的Cinagara Caringin地区的研究，这项研究成功地实现了92%的准确率。因此，本研究成功地提出了一种利用边缘计算技术自动识别废物类型的新方法，为缓解废物问题做出了重大贡献。

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