The proliferation of IoT devices and the growing deployment of 5G networks combine to provide the perfect ecosystem for advanced smart city use cases. In this paper, we address the possibility of detecting and quantifying flows of people on city streets thanks to deployment of commercial sensors, connected to the 5G network, that capture WiFi probes transmitted by people's smartphones. We first outline the motivation and challenges of such a scenario. Then, we illustrate our approach and present results derived from live measurements in a testbed deployed in the city of Turin within the 5G-EVE project. We show that we can quite accurately estimate transit flows by simply collecting anonymized MAC addresses and timestamps from smartphones of passers-by.

IoT-based Mobility Tracking for Smart City Applications / Gebru, Kalkidan; Casetti, CLAUDIO ETTORE; Chiasserini, Carla Fabiana; Giaccone, Paolo. - STAMPA. - (2020), pp. 326-330. (Intervento presentato al convegno EuCNC 2020 tenutosi a Dubrovnik (Croatia) nel June 2020) [10.1109/EuCNC48522.2020.9200941].

IoT-based Mobility Tracking for Smart City Applications

Kalkidan Gebru;Claudio Casetti;Carla Fabiana Chiasserini;Paolo Giaccone
2020

Abstract

The proliferation of IoT devices and the growing deployment of 5G networks combine to provide the perfect ecosystem for advanced smart city use cases. In this paper, we address the possibility of detecting and quantifying flows of people on city streets thanks to deployment of commercial sensors, connected to the 5G network, that capture WiFi probes transmitted by people's smartphones. We first outline the motivation and challenges of such a scenario. Then, we illustrate our approach and present results derived from live measurements in a testbed deployed in the city of Turin within the 5G-EVE project. We show that we can quite accurately estimate transit flows by simply collecting anonymized MAC addresses and timestamps from smartphones of passers-by.
File in questo prodotto:
File Dimensione Formato  
1570629639.pdf

accesso aperto

Descrizione: Articolo principale
Tipologia: 2. Post-print / Author's Accepted Manuscript
Licenza: PUBBLICO - Tutti i diritti riservati
Dimensione 1.53 MB
Formato Adobe PDF
1.53 MB Adobe PDF Visualizza/Apri
EuCNC_2020.pdf

non disponibili

Descrizione: Articolo principale
Tipologia: 2a Post-print versione editoriale / Version of Record
Licenza: Non Pubblico - Accesso privato/ristretto
Dimensione 221.19 kB
Formato Adobe PDF
221.19 kB Adobe PDF   Visualizza/Apri   Richiedi una copia
Pubblicazioni consigliate

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2815294