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- Title
Internet-of-Video Things Based Real-Time Traffic Flow Characterization.
- Authors
Khan, Ali; Khattak, Khurram S.; Khan, Zawar H.; Gulliver, T. A.; Imran, Waheed; Minallah, Nasru
- Abstract
Real-world traffic flow parameters are fundamental for devising smart mobility solutions. Though numerous solutions (intrusive and non-intrusive sensors) have been proposed, however, these have serious limitations under heterogeneous and congested traffic conditions. To overcome these limitations, a low-cost real-time Internet-of-Video-Things solution has been proposed. The sensor node (fabricated using Raspberry Pi 3B, Pi cameral and power bank) has the capability to stream 2 Mbps MJPEG video of 640x480 resolution and 20 frames per second (fps). The Camlytics traffic analysis software installed on a Dell desktop is employed for traffic flow characterization. The proposed solution was field-tested with vehicle detection rate of 85.3%. The novelty of the proposed system is that in addition to vehicle count, it has the capability to measure speed, density, time headway, time-space diagram and trajectories. Obtained results can be employed for road network planning, designing and management.
- Subjects
INHOMOGENEOUS materials; STREAMING video &; television; INTELLIGENT transportation systems; RASPBERRY Pi; MANAGEMENT
- Publication
EAI Endorsed Transactions on Scalable Information Systems, 2021, Vol 8, Issue 33, p1
- ISSN
2032-9407
- Publication type
Article
- DOI
10.4108/eai.21-10-2021.171596