Abstract
Smart cities are demanding solutions for improved traffic efficiency, in order to guarantee optimal access to mobility resources available in urban areas. Intelligent video analytics deployed directly on board embedded sensors offers great opportunities to gather highly informative data about traffic and transport, allowing reconstruction of a real-time neat picture of urban mobility patterns. In this paper, we present a visual sensor network in which each node embeds computer vision logics for analyzing in real time urban traffic. The nodes in the network share their perceptions and build a global and comprehensive interpretation of the analyzed scenes in a cooperative and adaptive fashion. This is possible thanks to an especially designed Internet of Things (IoT) compliant middleware which encompasses in-network event composition as well as full support of Machine-2-Machine (M2M) communication mechanism. The potential of the proposed cooperative visual sensor network is shown with two sample applications in urban mobility connected to the estimation of vehicular flows and parking management. Besides providing detailed results of each key component of the proposed solution, the validity of the approach is demonstrated by extensive field tests that proved the suitability of the system in providing a scalable, adaptable and extensible data collection layer for managing and understanding mobility in smart cities.
Highlights
By 2050 over 70% of the world’s population will live in cities, metropolitan areas and surrounding zones
Intelligent Transportation Systems (ITS) solutions in combination with the pervasive sensing capabilities provided by Wireless Sensor Networks (WSN) can help in tackling the cruising-for-parking problem: by the use of WSN it is possible to build a neat spatio-temporal description of urban mobility that can be used for guiding drivers to free spaces and for proposing adaptive policies for parking access and pricing [3]
In an ITS system, in which the roadside network is composed of an Internet of Things (IoT)-compliant visual sensor network devices, the remote management of the nodes as well as their cooperation and data collection functionalities can be all managed by an IoT middleware
Summary
By 2050 over 70% of the world’s population will live in cities, metropolitan areas and surrounding zones. ITS solutions in combination with the pervasive sensing capabilities provided by Wireless Sensor Networks (WSN) can help in tackling the cruising-for-parking problem: by the use of WSN it is possible to build a neat spatio-temporal description of urban mobility that can be used for guiding drivers to free spaces and for proposing adaptive policies for parking access and pricing [3]. Instead in [7] cooperation among nodes is obtained by offloading computational tasks connected to image feature computation from one node to another With respect to these previous works, one of the main contributions of this paper is the definition and validation of a self-powered cooperative visual sensor network designed for acting as a pervasive roadside wireless monitoring network to be installed in the urban scenario to support the creation of effective Smart.
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