Document Type

Article

Publication Date

2021

DOI

10.3390/s21227652

Publication Title

Sensors

Volume

21

Issue

22

Pages

7652 (1-24)

Abstract

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.

Comments

© 2021 by the authors.

This is an open access article distributed under the Creative Commons Attribution 4.0 International (CC BY 4.0) License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Original Publication Citation

Olariu, S., & Popescu, D. C. (2021). SEE-TREND: SEcurE Traffic-Related EveNt Detection in smart communities. Sensors, 21(22), 1-24, Article 7652. https://doi.org/10.3390/s21227652

ORCID

0000-0002-3776-216X (Olariu)

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