Energy-efficient street lighting through embedded adaptive intelligence
Energy-efficient street lighting through embedded adaptive intelligence
Streetlights place a heavy demand on electricity usage, providing significant financial and environmental burdens. Consequently, initiatives to reduce energy consumption have been proposed, usually by turning off or dimming the streetlight. In this paper, we propose an adaptive lighting scheme based on traffic sensing, which adaptively adjusts streetlight brightness based on current traffic conditions. The algorithm has been validated through simulation using the SUMO and OMNeT++ tools and, for two different geographical locations, the energy consumption evaluated with respect to traffic speed and volume. The simulation results presented indicate that the proposed lighting scheme can consume up to 30% less energy when compared to the state-of-the-art.
978-1-4799-0314-6
Lau, Sei Ping
7f257719-b0b1-4666-8fc8-6c442f4dfc40
Merrett, Geoff V.
89b3a696-41de-44c3-89aa-b0aa29f54020
White, Neil M.
c7be4c26-e419-4e5c-9420-09fc02e2ac9c
29 May 2013
Lau, Sei Ping
7f257719-b0b1-4666-8fc8-6c442f4dfc40
Merrett, Geoff V.
89b3a696-41de-44c3-89aa-b0aa29f54020
White, Neil M.
c7be4c26-e419-4e5c-9420-09fc02e2ac9c
Lau, Sei Ping, Merrett, Geoff V. and White, Neil M.
(2013)
Energy-efficient street lighting through embedded adaptive intelligence.
Symposium on Intelligent Transportation Systems (ICALT-ITS’2013), Sousse, Tunisia.
29 - 31 May 2013.
(doi:10.1109/ICAdLT.2013.6568434).
Record type:
Conference or Workshop Item
(Paper)
Abstract
Streetlights place a heavy demand on electricity usage, providing significant financial and environmental burdens. Consequently, initiatives to reduce energy consumption have been proposed, usually by turning off or dimming the streetlight. In this paper, we propose an adaptive lighting scheme based on traffic sensing, which adaptively adjusts streetlight brightness based on current traffic conditions. The algorithm has been validated through simulation using the SUMO and OMNeT++ tools and, for two different geographical locations, the energy consumption evaluated with respect to traffic speed and volume. The simulation results presented indicate that the proposed lighting scheme can consume up to 30% less energy when compared to the state-of-the-art.
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Published date: 29 May 2013
Venue - Dates:
Symposium on Intelligent Transportation Systems (ICALT-ITS’2013), Sousse, Tunisia, 2013-05-29 - 2013-05-31
Organisations:
Electronic & Software Systems, EEE
Identifiers
Local EPrints ID: 350780
URI: http://eprints.soton.ac.uk/id/eprint/350780
ISBN: 978-1-4799-0314-6
PURE UUID: e8c57853-3f22-4a5d-a781-f4caa2831071
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Date deposited: 08 Apr 2013 13:15
Last modified: 15 Mar 2024 03:23
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Contributors
Author:
Sei Ping Lau
Author:
Geoff V. Merrett
Author:
Neil M. White
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