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    Clustering Indoor Location Data for Social Distancing and Human Mobility to Combat COVID-19

    Yuan Ai Ho1, Chee Keong Tan1,*, Yin Hoe Ng2

    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 907-924, 2022, DOI:10.32604/cmc.2022.021756

    Abstract The world is experiencing the unprecedented time of a pandemic caused by the coronavirus disease (i.e., COVID-19). As a countermeasure, contact tracing and social distancing are essential to prevent the transmission of the virus, which can be achieved using indoor location analytics. Based on the indoor location analytics, the human mobility on a site can be monitored and planned to minimize human’s contact and enforce social distancing to contain the transmission of COVID-19. Given the indoor location data, the clustering can be applied to cluster spatial data, spatio-temporal data and movement behavior features for proximity detection or contact tracing applications.… More >

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