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Utilize este identificador para referenciar este registo: http://hdl.handle.net/10314/8047

Título: AvoidCrowd - Walking Crowd Detection System
Autores: Pereira, Delfim
Pedro, André
Gonçalves, Celestino
Silveira, Clara
Data: 26-Mar-2023
Resumo: The Covid-19 pandemic has drastically changed the daily lives of peo ple around the world in the last two years. This work describes the implementa tion of an application, for Android mobile devices, aimed at the user who usually goes on walks and wants to avoid the constant use of a face mask and avoid crowds. With this application the user defines from how many detected Bluetooth devices he wants to be warned to put on the mask. He may be with a group or even in an area where people are in constant movement. There is an assumption that there is a high probability that each pedestrian is carrying a smartphone and that the probability of having Bluetooth turned on and detectable is a little lower. Attempts were made to find another applications with this approach, but without success. They will certainly arise because the answer given by the AvoidCrowd application, and the current need of such tools so demands it.
URI: http://hdl.handle.net/10314/8047
ISBN: 978-989-654-836-0
Aparece nas Colecções:Artigos em Revista Internacional (ESTG)

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