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.
Highlights
It has been widely recognized that one of the critical services provided by Smart Cities and
Among the services offered by Smart Cities and Smart Communities, Smart mobility is, and in all likelihood will remain, one of the most challenging to provide in a coherent and sustainable fashion
In order to promote Smart Mobility in the Smart Communities of the near future, there is a critical need to detect trends in traffic flow, including premonitory signs of imminent slowdown and congestion. Such a system would allow drivers to make more informed decisions about their travel, preventing congestion altogether or mitigating its nefarious effects. To address this critical need, the main objective of this paper is to lay the theoretical foundations of SEE-TREND: a system for Secure Early Traffic-Related EveNt Detection in Smart Cities and Smart Communities
Summary
This introductory section is intended to offer a succinct review of Smart Cities and Smart Communities.
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