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Title	Ai And Iot-Enabled Smart Urban Waste Management System For Efficient Collection, Segregation, And Disposal
ID_Doc	6909
Authors	Devi A.; Singh N.; Thandra N.; Gupta N.; Salman Z.N.; Natarajan K.
Year	2025
Published	E3S Web of Conferences, 619
DOI	http://dx.doi.org/10.1051/e3sconf/202561903002
Abstract	This 'Smart Urban Waste Management System' outlines an innovative architecture for the current challenges in urban waste management through the application of IoT, AI and Blockchain technologies to increase the efficiency, transparency, and sustainability. IoT enabled smart bins with sensors are used in the system for monitoring waste levels for tracking waste levels and generating real time data for waste management platforms. Using computer vision, AI powered algorithms are leveraged to predict waste generation patterns for waste generation planning, to optimize waste collection routes for collection optimisation and automation of waste segregation. Additionally, blockchain technology enables secure and transparent tracking of waste collection, segregation and disposal in urban waste management systems, with accountability. IoT communication protocols such as LoRaWAN and NB-IoT are implemented to guarantee low cost and high scalability, using minimal power, fitting very well in any large city. In this dissertation, we investigate how these technologies can be joined seamlessly to form a circular, data-driven urban waste management ecosystem that helps to achieve the principles of the circular economy by encouraging resource repurposing and energy recovery. © The Authors, published by EDP Sciences.
Author Keywords	AI in Urban Waste Management; Blockchain for Waste Tracking; IoT-Enabled Waste Systems; Predictive Waste Analytics; Smart City Infrastructure; Smart Waste Management

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