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Smart city article details

Title	Intelligent Waste Bot Using Internet Of Things And Deep Learning For A Smart City
ID_Doc	32689
Authors	Shirwaikar R.; Lamgaonkar Y.; D’souza L.; Khorjuvenkar D.P.
Year	2023
Published	Lecture Notes in Electrical Engineering, 1080 LNEE
DOI	http://dx.doi.org/10.1007/978-981-99-5994-5_25
Abstract	The buildup of solid garbage in metropolitan areas is causing environmental contamination and may be harmful to human health if not adequately controlled. A sophisticated/intelligent waste management system is required to handle various wastes. Separating garbage into its component parts is a crucial stage in waste management and is generally done manually by hand- picking. We propose a bot-based waste management system with nodes consisting of mechanical robotic arms to pick up waste material. Deep learning is a kind of machine learning that harvests information by layering data representation and feature extraction. The robotic arm has been designed to move in the same way as a human arm does. This is accomplished by using an Arduino Nano microcontroller with servo motor control which is programmed in the Java language. Convolution neural network, a deep, feed- forward artificial neural network, was used to accurately assess the image. This technique is offered as a part of a solid waste sorter. The combination of robotic waste management with a deep learning system allows trash to be classified and disposed off automatically. As a result, trash segregation with deep learning includes image acquisition from a camera, object recognition, prediction, and categorization into biodegradable and non-biodegradable categories. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2023.
Author Keywords	Convolution Neural Network; Deep Learning; IoT; Smart City; Waste Segregation

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