An Intelligent Cooperative Visual Sensor Network for Urban Mobility
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 traffi...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2017-11-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/17/11/2588 |
| _version_ | 1798003961952731136 |
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| author | Giuseppe Riccardo Leone Davide Moroni Gabriele Pieri Matteo Petracca Ovidio Salvetti Andrea Azzarà Francesco Marino |
| author_facet | Giuseppe Riccardo Leone Davide Moroni Gabriele Pieri Matteo Petracca Ovidio Salvetti Andrea Azzarà Francesco Marino |
| author_sort | Giuseppe Riccardo Leone |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-04-11T12:15:56Z |
| format | Article |
| id | doaj.art-3c1b93dbc4774816b9946ce0bc9db884 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-11T12:15:56Z |
| publishDate | 2017-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-3c1b93dbc4774816b9946ce0bc9db8842022-12-22T04:24:19ZengMDPI AGSensors1424-82202017-11-011711258810.3390/s17112588s17112588An Intelligent Cooperative Visual Sensor Network for Urban MobilityGiuseppe Riccardo Leone0Davide Moroni1Gabriele Pieri2Matteo Petracca3Ovidio Salvetti4Andrea Azzarà5Francesco Marino6Institute of Information Science and Technologies, National Research Council of Italy, 56124, Pisa, ItalyInstitute of Information Science and Technologies, National Research Council of Italy, 56124, Pisa, ItalyInstitute of Information Science and Technologies, National Research Council of Italy, 56124, Pisa, ItalyInstitute of Information Science and Technologies, National Research Council of Italy, 56124, Pisa, ItalyInstitute of Information Science and Technologies, National Research Council of Italy, 56124, Pisa, ItalyScuola Superiore Sant’Anna of Pisa, 56124, Pisa, ItalyScuola Superiore Sant’Anna of Pisa, 56124, Pisa, ItalySmart 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.https://www.mdpi.com/1424-8220/17/11/2588visual sensor networksreal time image processingembedded visionIoT middlewareinternet of thingsintelligent transportation systemssmart cities |
| spellingShingle | Giuseppe Riccardo Leone Davide Moroni Gabriele Pieri Matteo Petracca Ovidio Salvetti Andrea Azzarà Francesco Marino An Intelligent Cooperative Visual Sensor Network for Urban Mobility Sensors visual sensor networks real time image processing embedded vision IoT middleware internet of things intelligent transportation systems smart cities |
| title | An Intelligent Cooperative Visual Sensor Network for Urban Mobility |
| title_full | An Intelligent Cooperative Visual Sensor Network for Urban Mobility |
| title_fullStr | An Intelligent Cooperative Visual Sensor Network for Urban Mobility |
| title_full_unstemmed | An Intelligent Cooperative Visual Sensor Network for Urban Mobility |
| title_short | An Intelligent Cooperative Visual Sensor Network for Urban Mobility |
| title_sort | intelligent cooperative visual sensor network for urban mobility |
| topic | visual sensor networks real time image processing embedded vision IoT middleware internet of things intelligent transportation systems smart cities |
| url | https://www.mdpi.com/1424-8220/17/11/2588 |
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