Smart Cameras for ITS in Urban Environment

Magrini, Massimo; Moroni, Davide; Pieri, Gabriele; Salvetti, Ovidio; Perallos, Asier; Hernández-Jayo, Unai; Onieva, Enrique; García‐Zuazola, Ignacio Julio

doi:10.1002/9781118894774.ch9

Cited by 4 publications

(2 citation statements)

References 19 publications

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“…In this section, a smart camera prototype for vision based smart parking is presented. The prototype is based on previous work [3,18]; choices that lead to the selection of specific hardware are motivated and discussed and technical facts are reported. Main emphasis is given to the vision board, which is a custom Printed Circuit Board (PCB) manufactured specifically for the sensor.…”

Section: Vision Based Smart Parkingmentioning

confidence: 99%

Real-Time Smart Parking Systems Integration in Distributed ITS for Smart Cities

Alam

Moroni

Pieri

et al. 2018

Journal of Advanced Transportation

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Intelligent Transportation Systems (ITS) have evolved as a key research topic in recent years, revolutionizing the overall traffic and travel experience by providing a set of advanced services and applications. These data-driven services contribute to mitigate major problems arising from the ever growing need of transport in our daily lives. Despite the progress, there is still need for an enhanced and distributed solution that can exploit the data from the available systems and provide an appropriate and real-time reaction on transportation systems. Therefore, in this paper, we present a new architecture where the intelligence is distributed and the decisions are decentralized. The proposed architecture is scalable since the incremental addition of new peripheral subsystems is supported by the introduction of gateways which requires no reengineering of the communication infrastructure. The proposed architecture is deployed to tackle the problem of traffic management inefficiency in urban areas, where traffic load is substantially increased, by vehicles moving around unnecessarily, to find a free parking space. This can be significantly reduced through the availability and diffusion of local information regarding vacant parking slots to drivers in a given area. Two types of parking systems, magnetic and vision sensor based, have been introduced, deployed, and tested in different scenarios. The effectiveness of the proposed architecture, together with the proposed algorithms, is assessed in field trials.

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Section: Vision Based Smart Parkingmentioning

confidence: 99%

Real-Time Smart Parking Systems Integration in Distributed ITS for Smart Cities

Alam

Moroni

Pieri

et al. 2018

Journal of Advanced Transportation

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“…Although many nodes that might support the creation of a visual sensor network are currently available (see, e.g., [ 44 , 45 ] for a review of some of them), nevertheless none seems to be satisfying for targeting outdoor ITS applications and to have capabilities for M2M communication. Actually, M2M communication is seen to be a key aspect to drive the shift from classical cameras and centralized video processing architecture to smart cameras and distributed video analytics over heterogeneous sensor networks.…”

Section: System Architecture and Componentsmentioning

confidence: 99%

An Intelligent Cooperative Visual Sensor Network for Urban Mobility

Leone

Moroni

Pieri

et al. 2017

Sensors

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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.

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