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

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 promo...

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Autores principales: Stephan Olariu, Dimitrie C. Popescu
Formato: article
Lenguaje:EN
Publicado: MDPI AG 2021
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Acceso en línea:https://doaj.org/article/fd03f1f4ebd84669b1ccb9acc24e648d
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spelling oai:doaj.org-article:fd03f1f4ebd84669b1ccb9acc24e648d2021-11-25T18:58:13ZSEE-TREND: SEcurE Traffic-Related EveNt Detection in Smart Communities10.3390/s212276521424-8220https://doaj.org/article/fd03f1f4ebd84669b1ccb9acc24e648d2021-11-01T00:00:00Zhttps://www.mdpi.com/1424-8220/21/22/7652https://doaj.org/toc/1424-8220It 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.Stephan OlariuDimitrie C. PopescuMDPI AGarticlesmart citiessmart communitiessmart mobilitycongestion supportcyber–physical systemsChemical technologyTP1-1185ENSensors, Vol 21, Iss 7652, p 7652 (2021)
institution DOAJ
collection DOAJ
language EN
topic smart cities
smart communities
smart mobility
congestion support
cyber–physical systems
Chemical technology
TP1-1185
spellingShingle smart cities
smart communities
smart mobility
congestion support
cyber–physical systems
Chemical technology
TP1-1185
Stephan Olariu
Dimitrie C. Popescu
SEE-TREND: SEcurE Traffic-Related EveNt Detection in Smart Communities
description 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.
format article
author Stephan Olariu
Dimitrie C. Popescu
author_facet Stephan Olariu
Dimitrie C. Popescu
author_sort Stephan Olariu
title SEE-TREND: SEcurE Traffic-Related EveNt Detection in Smart Communities
title_short SEE-TREND: SEcurE Traffic-Related EveNt Detection in Smart Communities
title_full SEE-TREND: SEcurE Traffic-Related EveNt Detection in Smart Communities
title_fullStr SEE-TREND: SEcurE Traffic-Related EveNt Detection in Smart Communities
title_full_unstemmed SEE-TREND: SEcurE Traffic-Related EveNt Detection in Smart Communities
title_sort see-trend: secure traffic-related event detection in smart communities
publisher MDPI AG
publishDate 2021
url https://doaj.org/article/fd03f1f4ebd84669b1ccb9acc24e648d
work_keys_str_mv AT stephanolariu seetrendsecuretrafficrelatedeventdetectioninsmartcommunities
AT dimitriecpopescu seetrendsecuretrafficrelatedeventdetectioninsmartcommunities
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