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Using passive Wi-Fi for community crowd sensing during the COVID-19 pandemic.
Ribeiro, Miguel; Teixeira, Diogo; Barbosa, Pedro; Nunes, Nuno Jardim.
  • Ribeiro M; ITI/LARSyS, Instituto Superior Técnico, Lisbon, Portugal.
  • Teixeira D; Mathematics, Instituto Superior Técnico, Lisbon, Portugal.
  • Barbosa P; DEI, Instituto Superior Técnico, Lisbon, Portugal.
  • Nunes NJ; ITI/LARSyS, Instituto Superior Técnico, Lisbon, Portugal.
J Big Data ; 10(1): 7, 2023.
Article in English | MEDLINE | ID: covidwho-2196490
ABSTRACT
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.
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Full text: Available Collection: International databases Database: MEDLINE Language: English Journal: J Big Data Year: 2023 Document Type: Article Affiliation country: S40537-022-00675-3

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Full text: Available Collection: International databases Database: MEDLINE Language: English Journal: J Big Data Year: 2023 Document Type: Article Affiliation country: S40537-022-00675-3