Analysis of Vehicle Detection with WSN-Based Ultrasonic Sensors

Existing traffic information acquisition systems suffer from high cost and low scalability. To address these problems, the application of wireless sensor networks (WSNs) has been studied, as WSN-based systems are highly scalable and have a low cost of installing and replacing the systems. Magnetic, acoustic and accelerometer sensors have been considered for WSN-based traffic surveillance, but the use of ultrasonic sensors has not been studied. The limitations of WSN-based systems make it necessary to employ power saving methods and vehicle detection algorithms with low computational complexity. In this paper, the authors model and analyze optimal power saving methodologies for an ultrasonic sensor and present a computationally-efficient vehicle detection algorithm using ultrasonic data. The proposed methodologies are implemented and evaluated with a tiny microprocessor on real roads. The evaluation results show that the low computational complexity of the authors algorithm does not compromise the accuracy of vehicle detection.

• Record URL:
  • http://www.mdpi.com/1424-8220/14/8/14050
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/14248220
• Supplemental Notes:
  • © 2014 Youngtae Jo and Inbum Jung.
• Authors:
  • Jo, Youngtae
  • Jung, Inbum
• Publication Date: 2014

Language

• English

Media Info

• Media Type: Digital/other
• Features: Figures; Photos; References; Tables;
• Pagination: pp 14050-14069
• Serial:
  • Sensors
  • Volume: 14
  • Issue Number: 8
  • Publisher: MDPI AG
  • ISSN: 1424-8220
  • Serial URL: http://www.mdpi.com/journal/sensors
• Publication flags:

  Open Access (libre)

Subject/Index Terms

• TRT Terms: Driver information systems; Sensors; Traffic surveillance; Ultrasonic detectors; Vehicle detectors; Wireless LANs
• Subject Areas: Data and Information Technology; Highways; Operations and Traffic Management; I73: Traffic Control;

Filing Info

• Accession Number: 01539772
• Record Type: Publication
• Files: TRIS
• Created Date: Oct 1 2014 2:20PM