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Article

SEE-TREND: SEcurE Traffic-Related EveNt Detection in Smart Communities

1
Department of Computer Science, Old Dominion University, 3300 Engineering & Computational Sciences Bldg., Norfolk, VA 23529, USA
2
Department of Electrical and Computer Engineering, Old Dominion University, 231 Kaufman Hall, Norfolk, VA 23529, USA
*
Author to whom correspondence should be addressed.
Academic Editor: Enrico Meli
Sensors 2021, 21(22), 7652; https://doi.org/10.3390/s21227652
Received: 18 October 2021 / Revised: 8 November 2021 / Accepted: 12 November 2021 / Published: 18 November 2021
(This article belongs to the Special Issue Artificial Intelligence and Internet of Things in Autonomous Vehicles)
It has been widely recognized that one of the critical services provided by Smart Cities and Smart Communities is Smart Mobility. This paper lays the theoretical foundations of SEE-TREND, a system for Secure Early Traffic-Related EveNt Detection in Smart Cities and Smart Communities. SEE-TREND promotes Smart Mobility by implementing an anonymous, probabilistic collection of traffic-related data from passing vehicles. The collected data are then aggregated and used by its inference engine to build beliefs about the state of the traffic, to detect traffic trends, and to disseminate relevant traffic-related information along the roadway to help the driving public make informed decisions about their travel plans, thereby preventing congestion altogether or mitigating its nefarious effects. View Full-Text
Keywords: smart cities; smart communities; smart mobility; congestion support; cyber–physical systems smart cities; smart communities; smart mobility; congestion support; cyber–physical systems
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MDPI and ACS Style

Olariu, S.; Popescu, D.C. SEE-TREND: SEcurE Traffic-Related EveNt Detection in Smart Communities. Sensors 2021, 21, 7652. https://doi.org/10.3390/s21227652

AMA Style

Olariu S, Popescu DC. SEE-TREND: SEcurE Traffic-Related EveNt Detection in Smart Communities. Sensors. 2021; 21(22):7652. https://doi.org/10.3390/s21227652

Chicago/Turabian Style

Olariu, Stephan, and Dimitrie C. Popescu. 2021. "SEE-TREND: SEcurE Traffic-Related EveNt Detection in Smart Communities" Sensors 21, no. 22: 7652. https://doi.org/10.3390/s21227652

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