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Crowd management in urban settings has mostly relied on either classical, non-automated mechanisms or spontaneous notifications/alerts through social networks. Such management techniques are heavily marred by lack of comprehensive control, especially in terms of averting risks in a manner that ensures crowd safety and enables prompt emergency response. In this paper, we propose a Markov Decision Process...
Advances in the Internet of Things (IoT) infrastructures are enabling the gathering, processing and inference of a wide array of data, enabling more agile decision management frameworks in several contexts, including vehicle routing and navigation. Coupled with crowd-sensing, these decision management frameworks gain further advantage in terms of data availability. This work concerns itself with safety...
Road fatalities in Saudi Arabia are expected to reach an alarming rate of one death per hour in 2015. In this paper, we describe a framework for vehicular sensing that is directly aimed at instilling safe driving. The presented architecture utilizes access to vehicle's CAN-Bus through an OBD-II connector. The access is processed using both on-vehicle smartphone and in-the-cloud processing. Road conditions...
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