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Estimating the Environmental Impact of Green IoT Deployments

The Internet of Things (IoT) is demonstrating its huge innovation potential, but at the same time, its spread can induce one of highest environmental impacts caused by the IoT industry. This concern has motivated the rise of a new research area aimed at devising green IoT deployments. Our work falls...

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Detalles Bibliográficos
Autores principales: Baldini, Edoardo, Chessa, Stefano, Brogi, Antonio
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9920983/
https://www.ncbi.nlm.nih.gov/pubmed/36772576
http://dx.doi.org/10.3390/s23031537
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author Baldini, Edoardo
Chessa, Stefano
Brogi, Antonio
author_facet Baldini, Edoardo
Chessa, Stefano
Brogi, Antonio
author_sort Baldini, Edoardo
collection PubMed
description The Internet of Things (IoT) is demonstrating its huge innovation potential, but at the same time, its spread can induce one of highest environmental impacts caused by the IoT industry. This concern has motivated the rise of a new research area aimed at devising green IoT deployments. Our work falls in this research area by contributing to addressing the problem of assessing the environmental impact of IoT deployments. Specifically, we propose a methodology based on an analytical model to assess the environmental impact of an outdoor IoT deployment powered by solar energy harvesting. The model inputs the specification of the IoT devices that constitute the deployment in terms of the battery, solar panel and electronic components, and it outputs the energy required for the entire life-cycle of the deployment and the waste generated by its disposal. Given an existing IoT deployment, the models also determine a functionally equivalent baseline green solution, which is an ideal configuration with a lower environmental impact than the original solution. We validated the proposed methodology by means of the analysis of a case study conducted over an existing IoT deployment developed within the European project RESCATAME. In particular, by means of the model, we evaluate the impact of the RESCATAME system and assess its impact with respect to its baseline. In a scenario with a 30-year lifespan, the model estimates for the system more than 3 times the energy required by its baseline green solution and a waste for a volume 15 times greater. We also show how the impact of the baseline increases when assuming deployments in locations at increasing latitudes. Finally, the article presents an implementation of the proposed methodology as a web service that is publicly available.
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spelling pubmed-99209832023-02-12 Estimating the Environmental Impact of Green IoT Deployments Baldini, Edoardo Chessa, Stefano Brogi, Antonio Sensors (Basel) Article The Internet of Things (IoT) is demonstrating its huge innovation potential, but at the same time, its spread can induce one of highest environmental impacts caused by the IoT industry. This concern has motivated the rise of a new research area aimed at devising green IoT deployments. Our work falls in this research area by contributing to addressing the problem of assessing the environmental impact of IoT deployments. Specifically, we propose a methodology based on an analytical model to assess the environmental impact of an outdoor IoT deployment powered by solar energy harvesting. The model inputs the specification of the IoT devices that constitute the deployment in terms of the battery, solar panel and electronic components, and it outputs the energy required for the entire life-cycle of the deployment and the waste generated by its disposal. Given an existing IoT deployment, the models also determine a functionally equivalent baseline green solution, which is an ideal configuration with a lower environmental impact than the original solution. We validated the proposed methodology by means of the analysis of a case study conducted over an existing IoT deployment developed within the European project RESCATAME. In particular, by means of the model, we evaluate the impact of the RESCATAME system and assess its impact with respect to its baseline. In a scenario with a 30-year lifespan, the model estimates for the system more than 3 times the energy required by its baseline green solution and a waste for a volume 15 times greater. We also show how the impact of the baseline increases when assuming deployments in locations at increasing latitudes. Finally, the article presents an implementation of the proposed methodology as a web service that is publicly available. MDPI 2023-01-30 /pmc/articles/PMC9920983/ /pubmed/36772576 http://dx.doi.org/10.3390/s23031537 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Baldini, Edoardo
Chessa, Stefano
Brogi, Antonio
Estimating the Environmental Impact of Green IoT Deployments
title Estimating the Environmental Impact of Green IoT Deployments
title_full Estimating the Environmental Impact of Green IoT Deployments
title_fullStr Estimating the Environmental Impact of Green IoT Deployments
title_full_unstemmed Estimating the Environmental Impact of Green IoT Deployments
title_short Estimating the Environmental Impact of Green IoT Deployments
title_sort estimating the environmental impact of green iot deployments
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9920983/
https://www.ncbi.nlm.nih.gov/pubmed/36772576
http://dx.doi.org/10.3390/s23031537
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