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Using passive Wi-Fi for community crowd sensing during the COVID-19 pandemic
Sensing passersby and detecting crowded locations is a growing area of research and development in the last decades. The COVID-19 pandemic compelled authorities and public and private institutions to monitor access and occupancy of crowded spaces. This work addresses the detection of crowds in point...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9844951/ https://www.ncbi.nlm.nih.gov/pubmed/36686620 http://dx.doi.org/10.1186/s40537-022-00675-3 |
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author | Ribeiro, Miguel Teixeira, Diogo Barbosa, Pedro Nunes, Nuno Jardim |
author_facet | Ribeiro, Miguel Teixeira, Diogo Barbosa, Pedro Nunes, Nuno Jardim |
author_sort | Ribeiro, Miguel |
collection | PubMed |
description | Sensing passersby and detecting crowded locations is a growing area of research and development in the last decades. The COVID-19 pandemic compelled authorities and public and private institutions to monitor access and occupancy of crowded spaces. This work addresses the detection of crowds in points of interest (POI) by using a territory grid analysis categorizing POIs by the services available in each location and comparing data gathered from a community passive Wi-Fi infrastructure against mobile cellular tower association data from telecom companies. In Madeira islands (Portugal), we used data from the telecom provider NOS for the timespan of 4 months as ground truth and found a strong correlation with sparse passive Wi-Fi. An official regional mobile application shows the occupancy data to end-users based on the territory categorization and the passive Wi-Fi infrastructure in POIs. Occupancy data shows historical hourly trends of each location, and the real-time occupation, helping visitors and locals plan their commutes better to avoid crowded spaces. |
format | Online Article Text |
id | pubmed-9844951 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-98449512023-01-18 Using passive Wi-Fi for community crowd sensing during the COVID-19 pandemic Ribeiro, Miguel Teixeira, Diogo Barbosa, Pedro Nunes, Nuno Jardim J Big Data Research Sensing passersby and detecting crowded locations is a growing area of research and development in the last decades. The COVID-19 pandemic compelled authorities and public and private institutions to monitor access and occupancy of crowded spaces. This work addresses the detection of crowds in points of interest (POI) by using a territory grid analysis categorizing POIs by the services available in each location and comparing data gathered from a community passive Wi-Fi infrastructure against mobile cellular tower association data from telecom companies. In Madeira islands (Portugal), we used data from the telecom provider NOS for the timespan of 4 months as ground truth and found a strong correlation with sparse passive Wi-Fi. An official regional mobile application shows the occupancy data to end-users based on the territory categorization and the passive Wi-Fi infrastructure in POIs. Occupancy data shows historical hourly trends of each location, and the real-time occupation, helping visitors and locals plan their commutes better to avoid crowded spaces. Springer International Publishing 2023-01-17 2023 /pmc/articles/PMC9844951/ /pubmed/36686620 http://dx.doi.org/10.1186/s40537-022-00675-3 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Research Ribeiro, Miguel Teixeira, Diogo Barbosa, Pedro Nunes, Nuno Jardim Using passive Wi-Fi for community crowd sensing during the COVID-19 pandemic |
title | Using passive Wi-Fi for community crowd sensing during the COVID-19 pandemic |
title_full | Using passive Wi-Fi for community crowd sensing during the COVID-19 pandemic |
title_fullStr | Using passive Wi-Fi for community crowd sensing during the COVID-19 pandemic |
title_full_unstemmed | Using passive Wi-Fi for community crowd sensing during the COVID-19 pandemic |
title_short | Using passive Wi-Fi for community crowd sensing during the COVID-19 pandemic |
title_sort | using passive wi-fi for community crowd sensing during the covid-19 pandemic |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9844951/ https://www.ncbi.nlm.nih.gov/pubmed/36686620 http://dx.doi.org/10.1186/s40537-022-00675-3 |
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