Internet-of-Video Things Based Real-Time Traffic Flow Characterization

Authors

DOI:

https://doi.org/10.4108/eai.21-10-2021.171596

Keywords:

Internet of Video Things (IoVT), Raspberry Pi (RPi), Video Streaming, Intelligent Transportation Systems (ITS), Camlytics

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.

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Published

21-10-2021

How to Cite

1.
Khan A, Khattak KS, Khan ZH, Gulliver TA, Imran W, Minallah N. Internet-of-Video Things Based Real-Time Traffic Flow Characterization. EAI Endorsed Scal Inf Syst [Internet]. 2021 Oct. 21 [cited 2024 Nov. 21];8(33):e9. Available from: https://publications.eai.eu/index.php/sis/article/view/2049