Smart city solutions: Comparative analysis of waste management models in IoT-enabled environments using multiagent simulation

<p>Effective waste management arises as a crucial challenge for smart city development in the current era of rapid urbanization, shifting towards sustainability and public health. Harnessing modern technologies, especially the integration of the Internet of Things (IoT) with intelligent waste...

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Main Author: Dr. Iftikhar Hussain (17986624) (author)
Other Authors: Dr. Adel Elomri (17986627) (author), Dr. Laoucine Kerbache (17986630) (author), Dr. Abdelfatteh El Omri (17986633) (author)
Published: 2024
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author Dr. Iftikhar Hussain (17986624)
author2 Dr. Adel Elomri (17986627)
Dr. Laoucine Kerbache (17986630)
Dr. Abdelfatteh El Omri (17986633)
author2_role author
author
author
author_facet Dr. Iftikhar Hussain (17986624)
Dr. Adel Elomri (17986627)
Dr. Laoucine Kerbache (17986630)
Dr. Abdelfatteh El Omri (17986633)
author_role author
dc.creator.none.fl_str_mv Dr. Iftikhar Hussain (17986624)
Dr. Adel Elomri (17986627)
Dr. Laoucine Kerbache (17986630)
Dr. Abdelfatteh El Omri (17986633)
dc.date.none.fl_str_mv 2024-04-01T00:00:00Z
dc.identifier.none.fl_str_mv 10.1016/j.scs.2024.105247
dc.relation.none.fl_str_mv https://figshare.com/articles/journal_contribution/Smart_city_solutions_Comparative_analysis_of_waste_management_models_in_IoT-enabled_environments_using_multiagent_simulation/25243015
dc.rights.none.fl_str_mv CC BY 4.0
info:eu-repo/semantics/openAccess
dc.subject.none.fl_str_mv Engineering
Control engineering, mechatronics and robotics
Environmental engineering
Information and computing sciences
Distributed computing and systems software
Sustainable cities
Waste management
Wireless sensor networks
IoT-enabled bins
Vehicle routing
Agent-based simulation modeling
dc.title.none.fl_str_mv Smart city solutions: Comparative analysis of waste management models in IoT-enabled environments using multiagent simulation
dc.type.none.fl_str_mv Text
Journal contribution
info:eu-repo/semantics/publishedVersion
text
contribution to journal
description <p>Effective waste management arises as a crucial challenge for smart city development in the current era of rapid urbanization, shifting towards sustainability and public health. Harnessing modern technologies, especially the integration of the Internet of Things (IoT) with intelligent waste bins, can revolutionize urban waste collection, optimizing efficiency and reducing costs. This paper delves into a multiagent simulation-based framework for understanding and assessing the dynamics of an IoT-enabled smart waste management system. Initiating with the intricate process of garbage generation, we shift our focus to the real-time monitoring capabilities of IoT-connected waste bins. The study further explores protocols to regulate bin status, along with timing mechanisms to trigger garbage collection rounds. Subsequently, a predictive routing system is introduced to determine the most efficient garbage collection routes. For the bins’ filled level tracking, the ultrasonic sensors are commonly used that send out sound waves and track their echo return time, whereas weight sensors measure the garbage load in the bin, providing insights into waste production trends. For data transmission from bins to the central system, various communication technologies such as Wi-Fi, cellular networks, and long-distance networks are considered. Through a simulation, we contrast the innovative IoT-enabled sensor-based collection mechanism against the conventional periodic review strategy. Field experiments at the Al Rayyan locale, proximate to Doha, Qatar, facilitate the model demonstration. By leveraging region-specific data, we simulated various aspects including economic factors, environmental impact, public satisfaction, and operational efficiencies. The findings indicate that with an average daily garbage generation of 1.3 kg per individual, the sensor-driven mechanism remarkably outperforms the periodic review approach by covering fewer distances with fewer trucks, while concurrently achieving the key objectives of cost-efficiency, environmental preservation, public satisfaction, and reduced employee workload. This research contributes to the developing field of smart city technology by providing critical insights for urban planners, policymakers, and technologists attempting to build more sustainable, efficient, and livable cities.</p><h2>Other Information</h2> <p> Published in: Sustainable Cities and Society<br> License: <a href="http://creativecommons.org/licenses/by/4.0/" target="_blank">http://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1016/j.scs.2024.105247" target="_blank">https://dx.doi.org/10.1016/j.scs.2024.105247</a></p>
eu_rights_str_mv openAccess
id Manara2_e6ad8822380f9624a7ee74a67231f4e9
identifier_str_mv 10.1016/j.scs.2024.105247
network_acronym_str Manara2
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oai_identifier_str oai:figshare.com:article/25243015
publishDate 2024
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rights_invalid_str_mv CC BY 4.0
spelling Smart city solutions: Comparative analysis of waste management models in IoT-enabled environments using multiagent simulationDr. Iftikhar Hussain (17986624)Dr. Adel Elomri (17986627)Dr. Laoucine Kerbache (17986630)Dr. Abdelfatteh El Omri (17986633)EngineeringControl engineering, mechatronics and roboticsEnvironmental engineeringInformation and computing sciencesDistributed computing and systems softwareSustainable citiesWaste managementWireless sensor networksIoT-enabled binsVehicle routingAgent-based simulation modeling<p>Effective waste management arises as a crucial challenge for smart city development in the current era of rapid urbanization, shifting towards sustainability and public health. Harnessing modern technologies, especially the integration of the Internet of Things (IoT) with intelligent waste bins, can revolutionize urban waste collection, optimizing efficiency and reducing costs. This paper delves into a multiagent simulation-based framework for understanding and assessing the dynamics of an IoT-enabled smart waste management system. Initiating with the intricate process of garbage generation, we shift our focus to the real-time monitoring capabilities of IoT-connected waste bins. The study further explores protocols to regulate bin status, along with timing mechanisms to trigger garbage collection rounds. Subsequently, a predictive routing system is introduced to determine the most efficient garbage collection routes. For the bins’ filled level tracking, the ultrasonic sensors are commonly used that send out sound waves and track their echo return time, whereas weight sensors measure the garbage load in the bin, providing insights into waste production trends. For data transmission from bins to the central system, various communication technologies such as Wi-Fi, cellular networks, and long-distance networks are considered. Through a simulation, we contrast the innovative IoT-enabled sensor-based collection mechanism against the conventional periodic review strategy. Field experiments at the Al Rayyan locale, proximate to Doha, Qatar, facilitate the model demonstration. By leveraging region-specific data, we simulated various aspects including economic factors, environmental impact, public satisfaction, and operational efficiencies. The findings indicate that with an average daily garbage generation of 1.3 kg per individual, the sensor-driven mechanism remarkably outperforms the periodic review approach by covering fewer distances with fewer trucks, while concurrently achieving the key objectives of cost-efficiency, environmental preservation, public satisfaction, and reduced employee workload. This research contributes to the developing field of smart city technology by providing critical insights for urban planners, policymakers, and technologists attempting to build more sustainable, efficient, and livable cities.</p><h2>Other Information</h2> <p> Published in: Sustainable Cities and Society<br> License: <a href="http://creativecommons.org/licenses/by/4.0/" target="_blank">http://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1016/j.scs.2024.105247" target="_blank">https://dx.doi.org/10.1016/j.scs.2024.105247</a></p>2024-04-01T00:00:00ZTextJournal contributioninfo:eu-repo/semantics/publishedVersiontextcontribution to journal10.1016/j.scs.2024.105247https://figshare.com/articles/journal_contribution/Smart_city_solutions_Comparative_analysis_of_waste_management_models_in_IoT-enabled_environments_using_multiagent_simulation/25243015CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/252430152024-04-01T00:00:00Z
spellingShingle Smart city solutions: Comparative analysis of waste management models in IoT-enabled environments using multiagent simulation
Dr. Iftikhar Hussain (17986624)
Engineering
Control engineering, mechatronics and robotics
Environmental engineering
Information and computing sciences
Distributed computing and systems software
Sustainable cities
Waste management
Wireless sensor networks
IoT-enabled bins
Vehicle routing
Agent-based simulation modeling
status_str publishedVersion
title Smart city solutions: Comparative analysis of waste management models in IoT-enabled environments using multiagent simulation
title_full Smart city solutions: Comparative analysis of waste management models in IoT-enabled environments using multiagent simulation
title_fullStr Smart city solutions: Comparative analysis of waste management models in IoT-enabled environments using multiagent simulation
title_full_unstemmed Smart city solutions: Comparative analysis of waste management models in IoT-enabled environments using multiagent simulation
title_short Smart city solutions: Comparative analysis of waste management models in IoT-enabled environments using multiagent simulation
title_sort Smart city solutions: Comparative analysis of waste management models in IoT-enabled environments using multiagent simulation
topic Engineering
Control engineering, mechatronics and robotics
Environmental engineering
Information and computing sciences
Distributed computing and systems software
Sustainable cities
Waste management
Wireless sensor networks
IoT-enabled bins
Vehicle routing
Agent-based simulation modeling