Smart City Gnosys

Smart city article details

Title	Smart Bin: A Waste Classification System For Eco- Friendly Urban Environments
ID_Doc	49190
Authors	Vijay Sathappan M.; Satyanarayan G.D.; Kishore V.; Rathish A.; Sandeep S.; Konguvel E.
Year	2024
Published	2024 3rd International Conference on Artificial Intelligence for Internet of Things, AIIoT 2024
DOI	http://dx.doi.org/10.1109/AIIoT58432.2024.10574802
Abstract	This article introduces an innovative smart bin system designed for efficient waste classification, utilizing the ESP32-CAM module for image capture and OpenCV for object detection. By conducting real-time analysis of captured images, the system accurately identifies and categorizes various types of waste in both indoor and outdoor environments. Through seamless integration of ESP32-CAM's image acquisition and OpenCV's reliable detection algorithms, the system further enhances waste management precision by transmitting detected object data to Zoho Creator via API for real-time analytics. With the capability to detect six major types of waste - paper, plastic, glass, metal, food and e-waste this comprehensive approach not only drives advancements in smart city initiatives but also promotes sustainable practices, contributing to the creation of smarter and more eco-friendly urban environments. Additionally, this article highlights the system's potential to streamline human tasks, providing users with enhanced awareness of specific waste types deposited in the bin. By improving waste collection effectiveness, reducing congregation around waste stations and enabling touch-free waste disposal, this innovative waste classification system effectively mitigates the risk of cross-contamination associated with physical contact. © 2024 IEEE.
Author Keywords	ESP32-CAM; OpenCV; Smart Bin System; Sustainable Urban Environments; Waste Classification

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