One of the most widely advertised capabilities of 5G targets the massive Machine-Type Communication (mMTC) giving the development of Internet of Things (IoT) solutions center stage in the new generation of mobile networks. In this paper, we address the possibility of detecting people on city streets thanks to deployment of commercial sensors, connected to the 5G network, that capture WiFi probes transmitted by people's smart devices. We first outline the motivation of such a scenario. Then, we illustrate our implemented architecture and present the results detected in an area near the Politecnico di Torino within the 5G EVE H2020 project. We show that our architecture can monitor real-time data coming from the installed sensors and thus estimate the number of people present in an area by simply collecting anonymized MAC addresses and timestamps from smart devices of passers-by.

IoT for Real Time Presence Sensing on the 5G EVE Infrastructure / Rusca, Riccardo; Casetti, CLAUDIO ETTORE; Giaccone, Paolo. - ELETTRONICO. - (2021). ((Intervento presentato al convegno Mediterranean Communication and Computer Networking Conference (MedComNet 2021) tenutosi a Online nel 15-17 June 2021 [10.1109/MedComNet52149.2021.9501245].

IoT for Real Time Presence Sensing on the 5G EVE Infrastructure

Riccardo Rusca;Claudio Casetti;Paolo Giaccone
2021

Abstract

One of the most widely advertised capabilities of 5G targets the massive Machine-Type Communication (mMTC) giving the development of Internet of Things (IoT) solutions center stage in the new generation of mobile networks. In this paper, we address the possibility of detecting people on city streets thanks to deployment of commercial sensors, connected to the 5G network, that capture WiFi probes transmitted by people's smart devices. We first outline the motivation of such a scenario. Then, we illustrate our implemented architecture and present the results detected in an area near the Politecnico di Torino within the 5G EVE H2020 project. We show that our architecture can monitor real-time data coming from the installed sensors and thus estimate the number of people present in an area by simply collecting anonymized MAC addresses and timestamps from smart devices of passers-by.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2897852