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Detecting faulty street lamps with illumination maps

Published: 16 April 2012 Publication History

Abstract

Badly lit roads usually lead to vehicle accidents and encourage crime in the area. Therefore, it is important to detect faulty street lamps rapidly and report them to related authorities to keep roads safe. Currently, communities still mostly depend on electrical inspectors to check street lamps regularly, which may result in long time delays for repair. Recent studies focus on add networking capability into street lamp poles to enable real-time reports on the healthy status of lamps. However, such a smart system increases costs to add sensors and network modules in every street lamp; therefore, it is nearly impossible to realize this kind of system in a short term. We propose a new method to detect faulty lamps. We designed equipment that could be installed on fixed bus routes and collect the lighting intensity along the routes. We created illumination maps in meter-level resolution. The differences between illumination maps created at different times can help identify the changes of lighting intensity in specific locations. We executed a proof-of-concept experiment that shows our method is feasible. This method can be extended to a city-wide scale at low cost. As a result, this would detect faulty street lamps along main roads and prevent accidents and crime by shortening the duration of badly lit streets.

References

[1]
F. R. Beyer; K. Ker, "Street lighting for prevention of road traffic injuries", Injury Prevention, vol. 15, issue 4, pp. 282--282, August 2009.
[2]
Y. Chen; Z. Liu, "Distributed Intelligent City Street Lamp Monitoring and Control System Based on Wireless Communication chip nRF401," Networks Security, Wireless Communications and Trusted Computing, 2009. NSWCTC '09. International Conference on, vol. 2, no., pp. 278--281, 25-26 April 2009.

Cited By

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  • (2019)Imaging Measurements for Public Lighting Predictive Maintenance2019 11th International Symposium on Advanced Topics in Electrical Engineering (ATEE)10.1109/ATEE.2019.8724910(1-5)Online publication date: Mar-2019
  • (2013)Poster abstractProceedings of the 12th international conference on Information processing in sensor networks10.1145/2461381.2461430(325-326)Online publication date: 8-Apr-2013

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      cover image ACM Conferences
      IPSN '12: Proceedings of the 11th international conference on Information Processing in Sensor Networks
      April 2012
      354 pages
      ISBN:9781450312271
      DOI:10.1145/2185677

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      Published: 16 April 2012

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      Author Tags

      1. failure detection
      2. fault
      3. street lamp

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      • (2019)Imaging Measurements for Public Lighting Predictive Maintenance2019 11th International Symposium on Advanced Topics in Electrical Engineering (ATEE)10.1109/ATEE.2019.8724910(1-5)Online publication date: Mar-2019
      • (2013)Poster abstractProceedings of the 12th international conference on Information processing in sensor networks10.1145/2461381.2461430(325-326)Online publication date: 8-Apr-2013

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