Optimizing Waste Management through IoT and Analytics: A Case Study Using the Waste Management Optimization Test

This research examines how Internet of Things (IoT) technology and advanced analytics may be integrated into trash management. The results show a notable improvement in waste collection efficiency, cost savings, and environmental sustainability. Significant operational cost reductions were achieved...

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Bibliographic Details
Main Authors: Kuzhin Marat F., Joshi Abhishek, Mittal Vaibhav, Khatkar Monika, Guven Ugur
Format: Article
Language:English
Published: EDP Sciences 2024-01-01
Series:BIO Web of Conferences
Subjects:
Online Access:https://www.bio-conferences.org/articles/bioconf/pdf/2024/05/bioconf_rtbs2024_01090.pdf
Description
Summary:This research examines how Internet of Things (IoT) technology and advanced analytics may be integrated into trash management. The results show a notable improvement in waste collection efficiency, cost savings, and environmental sustainability. Significant operational cost reductions were achieved by reducing the number of overfilled trash cans by 20% and the frequency of collections by 15% as a consequence of real-time data capture using IoT sensors. Additionally, a 25% reduction in trip distance was made possible by data-driven route optimization, which also resulted in a 10% drop in fuel use and a decrease in carbon emissions. The data-driven strategy also found areas for recycling, which increased the amount of recyclables collected by 15%. These findings highlight the promise that data-driven trash management has for improving both environmental and economic sustainability while tackling the problems associated with urban garbage.
ISSN:2117-4458