- Title
- A cooperative crowdsensing system based on flying and ground vehicles to control respiratory viral disease outbreaks
- Creator
- Sahraoui, Yesin; Kerrache, Chaker; Amadeo, Marica; Vegni, Anna; Korichi, Ahmed; Nebhen, Jamel; Imran, Muhammad
- Date
- 2022
- Type
- Text; Journal article
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/184740
- Identifier
- vital:16580
- Identifier
-
https://doi.org/10.1016/j.adhoc.2021.102699
- Identifier
- ISBN:1570-8705 (ISSN)
- 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. © 2021
- Publisher
- Elsevier B.V.
- Relation
- Ad Hoc Networks Vol. 124, no. (2022), p.
- Rights
- All metadata describing materials held in, or linked to, the repository is freely available under a CC0 licence
- Rights
- Copyright © 2021 Elsevier B.V.
- Subject
- 4006 Communications engineering; Covid-19; Crowdsensing; Internet of Things; Internet of vehicles; Sensors; UAVs
- Reviewed
- Funder
- This work was supported by the Deanship of Scientific Research at Prince Sattam bin Abdulaziz University, Saudi Arabia .
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