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On the Coverage of Bus-Based Mobile Sensing
A cost-effective approach to gather information in a smart city is to embed sensors in vehicles such as buses. To understand the limitations and opportunities of this model, it is fundamental to investigate the spatial coverage of such a network, especially in the case where only a subset of the bus...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6022044/ https://www.ncbi.nlm.nih.gov/pubmed/29925791 http://dx.doi.org/10.3390/s18061976 |
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author | Cruz Caminha, Pedro Henrique de Souza Couto, Rodrigo Maciel Kosmalski Costa, Luís Henrique Fladenmuller, Anne Dias de Amorim, Marcelo |
author_facet | Cruz Caminha, Pedro Henrique de Souza Couto, Rodrigo Maciel Kosmalski Costa, Luís Henrique Fladenmuller, Anne Dias de Amorim, Marcelo |
author_sort | Cruz Caminha, Pedro Henrique |
collection | PubMed |
description | A cost-effective approach to gather information in a smart city is to embed sensors in vehicles such as buses. To understand the limitations and opportunities of this model, it is fundamental to investigate the spatial coverage of such a network, especially in the case where only a subset of the buses have a sensing device embedded. In this paper, we propose a model to select the right subset of buses that maximizes the coverage of the city. We evaluate the model in a real scenario based on a large-scale dataset of more than 5700 buses in the city of Rio de Janeiro, Brazil. Among other findings, we observe that the fleet of buses covers approximately 5655 km of streets (approximately 47% of the streets) and show that it is possible to cover 94% of the same streets if only 18% of buses have sensing capabilities embedded. |
format | Online Article Text |
id | pubmed-6022044 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-60220442018-07-02 On the Coverage of Bus-Based Mobile Sensing Cruz Caminha, Pedro Henrique de Souza Couto, Rodrigo Maciel Kosmalski Costa, Luís Henrique Fladenmuller, Anne Dias de Amorim, Marcelo Sensors (Basel) Article A cost-effective approach to gather information in a smart city is to embed sensors in vehicles such as buses. To understand the limitations and opportunities of this model, it is fundamental to investigate the spatial coverage of such a network, especially in the case where only a subset of the buses have a sensing device embedded. In this paper, we propose a model to select the right subset of buses that maximizes the coverage of the city. We evaluate the model in a real scenario based on a large-scale dataset of more than 5700 buses in the city of Rio de Janeiro, Brazil. Among other findings, we observe that the fleet of buses covers approximately 5655 km of streets (approximately 47% of the streets) and show that it is possible to cover 94% of the same streets if only 18% of buses have sensing capabilities embedded. MDPI 2018-06-20 /pmc/articles/PMC6022044/ /pubmed/29925791 http://dx.doi.org/10.3390/s18061976 Text en © 2018 by the authors. 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 (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Cruz Caminha, Pedro Henrique de Souza Couto, Rodrigo Maciel Kosmalski Costa, Luís Henrique Fladenmuller, Anne Dias de Amorim, Marcelo On the Coverage of Bus-Based Mobile Sensing |
title | On the Coverage of Bus-Based Mobile Sensing |
title_full | On the Coverage of Bus-Based Mobile Sensing |
title_fullStr | On the Coverage of Bus-Based Mobile Sensing |
title_full_unstemmed | On the Coverage of Bus-Based Mobile Sensing |
title_short | On the Coverage of Bus-Based Mobile Sensing |
title_sort | on the coverage of bus-based mobile sensing |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6022044/ https://www.ncbi.nlm.nih.gov/pubmed/29925791 http://dx.doi.org/10.3390/s18061976 |
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