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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MDPI AG
2021
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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) |
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smart cities smart communities smart mobility congestion support cyber–physical systems Chemical technology TP1-1185 |
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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 |
_version_ |
1718410502891110400 |