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

Published in SAGE Publications
PMID: 34726090

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.

About the journal
JournalData powered by TypesetWaste Management and Research: The Journal for Sustainable Economy
PublisherData powered by TypesetSAGE Publications
Open AccessYes