Suppr超能文献

人工智能在电子废物收集方面的应用:印度家庭电子废物收集和分类的潜在解决方案。

Application of artificial intelligence to enhance collection of E-waste: A potential solution for household WEEE collection and segregation in India.

机构信息

School of Computer Science and Engineering, Vellore Institute of Technology, Chennai, India.

出版信息

Waste Manag Res. 2022 Jul;40(7):1047-1053. doi: 10.1177/0734242X211052846. Epub 2021 Nov 2.

Abstract

Our society has undergone a massive technological revolution over the past decade and electronic appliances have now become ubiquitous. The increase in production of electronic products and the growing inherent need to own the latest technology available has led to a significant increase in the amount of E-waste produced each year. India generated 3.2 million tonnes of E-waste in 2020, with metropolitan cities like Mumbai, Delhi and Bangalore leading the list. Proper management and recycling of E-wastes are critical for the sustainability of any modern city today. While industrial and commercial collection of E-wastes has been in the spotlight, solutions for collection of E-wastes from individual households are limited. This article proposes the implementation of a mobile robot that identifies common electronic wastes based on transfer learning and serves as an attachment to existing municipality garbage trucks. The robot moves around, identifies electronic wastes and performs segregation of the identified material via its arm-based lift and storage mechanism. A convolutional neural network-based identification system has been employed for categorising the E-wastes and yields 96% accuracy. This is a first of its kind attempt, especially in India, to collect and segregate E-wastes from homes and individuals. The system will relieve unskilled labour from the hazardous process while providing a 20% decrease in costs over a 5-year period. The application of this article aims to provide a viable mobile solution for E-waste collection from households with minimal human intervention.

摘要

在过去的十年中,我们的社会经历了一场大规模的技术革命,电子产品现在已经无处不在。电子产品产量的增加和人们对拥有最新技术的固有需求的增长,导致每年产生的电子垃圾数量显著增加。2020 年,印度产生了 320 万吨电子垃圾,孟买、德里和班加罗尔等大都市位居前列。对电子垃圾进行妥善管理和回收利用,对当今任何一个现代化城市的可持续发展都至关重要。虽然工业和商业领域的电子垃圾收集已经成为焦点,但从家庭收集电子垃圾的解决方案有限。本文提出了一种基于迁移学习的识别常见电子废物的移动机器人,并将其作为现有市政垃圾车的附件。该机器人可以四处移动,识别电子废物,并通过其臂式提升和存储机构对识别出的材料进行分类。该机器人采用基于卷积神经网络的识别系统对电子废物进行分类,准确率达到 96%。这是印度首次尝试从家庭和个人收集和分类电子废物。该系统将使非熟练劳动力摆脱危险的处理过程,同时在 5 年内降低 20%的成本。本文的应用旨在提供一种可行的、可移动的家庭电子废物收集解决方案,只需最低限度的人工干预。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/714b/9109239/22a1e455b7b9/10.1177_0734242X211052846-fig1.jpg

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验