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Poster: Solar-Powered Adaptive Street Lighting Evaluated with Real Traffic and Sunlight Data

Published: 01 November 2015 Publication History

Abstract

Street lighting is an important resource; it has been shown to reduce crime, improve road safety, and increase economic activity. These benefits, however, come with a cost: an annual emission of 64 million tonnes of CO2. Solar-powered street lighting is attractive for its use of renewable energy and its ease of installation (particularly in off-grid applications), but sizing and control is a non-trivial task. This paper describes TALiSMaN-Green, a traffic-aware street lighting scheme which takes account of road users as well as the available energy to dynamically adjust lighting levels. Simulations using real traffic and sunlight data illustrate that solar-powered streetlights can be managed to deliver consistent usefulness throughout the night.

References

[1]
A. Andreas and S. Wilcox. Solar radiation monitoring station (sorms) humboldt state university, 2007. {Online} http://dx.doi.org/10.5439/1052559.
[2]
S. P. Lau, A. S. Weddell, G. V. Merrett, and N. White. Energy-neutral solar-powered street lighting with predictive and adaptive behaviour. In ENSsys '14 Proceedings of the 2nd International Workshop on Energy Neutral Sensing Systems, pages 13--18. ACM, November 2014.
[3]
A. Sobral. Vehicle detection, tracking and counting, 2012. {Online} https://www.behance.net/andrewssobral.

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  1. Poster: Solar-Powered Adaptive Street Lighting Evaluated with Real Traffic and Sunlight Data

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    cover image ACM Conferences
    SenSys '15: Proceedings of the 13th ACM Conference on Embedded Networked Sensor Systems
    November 2015
    526 pages
    ISBN:9781450336314
    DOI:10.1145/2809695
    Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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    Publication History

    Published: 01 November 2015

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    Author Tags

    1. energy prediction
    2. street lighting

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    SenSys '15 Paper Acceptance Rate 27 of 132 submissions, 20%;
    Overall Acceptance Rate 174 of 867 submissions, 20%

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