The massive increase in population density in cities has led to several urban problems, such as an increment of air pollution, traffic congestion, and a faster spread of infectious diseases. With the rapid innovation in the intelligent sensors technology, and its integration into smart vehicles and Unmanned Aerial Vehicles (UAVs), a novel sensing paradigm has been promoted, namely vehicular crowdsensing, which leverages on-board sensors to capture information from the surrounding environment. Collected data are then analyzed to take proper countermeasures. In this paper, we present a smart coordination mechanism between UAVs and ground vehicles (GVs), which sense information like body temperature and breathing rate of people, in order to support a variety of monitoring applications, including discovering the presence of infectious diseases. In our framework, namely GUAVA, aerial and ground vehicles are equipped with GPS devices and thermal cameras to monitor specific geographic areas, detect humans’ vital parameters and, at the same time, discover duplicate data by identifying matching faces in thermal video sequences with the GaussianFace algorithm. The sensing tasks in hard-to-reach places are assigned to UAVs, with the ability to power up wirelessly from the nearest GV and offload the collected monitoring images to it. Simulation results have assessed our proposed framework, showing good performance in terms of distinct Quality of Service (QoS) metrics

A cooperative crowdsensing system based on flying and ground vehicles to control respiratory viral disease outbreaks / Sahraoui, Yesin; Kerrache, Chaker Abdelaziz; Amadeo, Marica; Vegni, Anna Maria; Korichi, Ahmed; Nebhen, Jamel; Imran, Muhammad. - In: AD HOC NETWORKS. - ISSN 1570-8705. - 124:102699(2022), pp. 1-13. [10.1016/j.adhoc.2021.102699]

A cooperative crowdsensing system based on flying and ground vehicles to control respiratory viral disease outbreaks

Amadeo, Marica;
2022-01-01

Abstract

The massive increase in population density in cities has led to several urban problems, such as an increment of air pollution, traffic congestion, and a faster spread of infectious diseases. With the rapid innovation in the intelligent sensors technology, and its integration into smart vehicles and Unmanned Aerial Vehicles (UAVs), a novel sensing paradigm has been promoted, namely vehicular crowdsensing, which leverages on-board sensors to capture information from the surrounding environment. Collected data are then analyzed to take proper countermeasures. In this paper, we present a smart coordination mechanism between UAVs and ground vehicles (GVs), which sense information like body temperature and breathing rate of people, in order to support a variety of monitoring applications, including discovering the presence of infectious diseases. In our framework, namely GUAVA, aerial and ground vehicles are equipped with GPS devices and thermal cameras to monitor specific geographic areas, detect humans’ vital parameters and, at the same time, discover duplicate data by identifying matching faces in thermal video sequences with the GaussianFace algorithm. The sensing tasks in hard-to-reach places are assigned to UAVs, with the ability to power up wirelessly from the nearest GV and offload the collected monitoring images to it. Simulation results have assessed our proposed framework, showing good performance in terms of distinct Quality of Service (QoS) metrics
2022
UAVs, Covid-19, Crowdsensing, Sensors, Internet of Things, Internet of vehicles
File in questo prodotto:
File Dimensione Formato  
Sahraoui_2022_j.adhoc_cooperative_editor.pdf

non disponibili

Descrizione: Versione editoriale
Tipologia: Versione Editoriale (PDF)
Licenza: Tutti i diritti riservati (All rights reserved)
Dimensione 1.64 MB
Formato Adobe PDF
1.64 MB Adobe PDF   Visualizza/Apri   Richiedi una copia
Sahraoui_2022_j.adhoc_cooperative_post.pdf

Open Access dal 07/10/2023

Descrizione: post-print
Tipologia: Documento in Post-print
Licenza: Creative commons
Dimensione 1.36 MB
Formato Adobe PDF
1.36 MB Adobe PDF Visualizza/Apri

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/20.500.12318/118785
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 16
  • ???jsp.display-item.citation.isi??? 13
social impact