Estimating Energy Savings in Smart Street Lighting by Using an Adaptive Control System
The driving force behind the smart city initiative is to offer better, more specialized services which can improve the quality of life of the citizens while promoting sustainability. To achieve both of these apparently competing goals, services must be increasingly autonomous and continuously adapti...
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2014-05-01
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Series: | International Journal of Distributed Sensor Networks |
Online Access: | https://doi.org/10.1155/2014/971587 |
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doaj-ead40ea0b1a0483e87411b33926fde622020-11-25T03:09:24ZengSAGE PublishingInternational Journal of Distributed Sensor Networks1550-14772014-05-011010.1155/2014/971587971587Estimating Energy Savings in Smart Street Lighting by Using an Adaptive Control SystemSoledad Escolar0Jesús Carretero1Maria-Cristina Marinescu2Stefano Chessa3 Computer Science Department, University Carlos III of Madrid, Leganés, 28911 Madrid, Spain Computer Science Department, University Carlos III of Madrid, Leganés, 28911 Madrid, Spain Computer Science Department, University of Pisa and ISTI-CNR, 56127 Pisa, Italy CASE Department, Barcelona Supercomputing Center, 08034 Barcelona, SpainThe driving force behind the smart city initiative is to offer better, more specialized services which can improve the quality of life of the citizens while promoting sustainability. To achieve both of these apparently competing goals, services must be increasingly autonomous and continuously adaptive to changes in their environment and the information coming from other services. In this paper we focus on smart lighting, a relevant application domain for which we propose an intelligent street light control system based on adaptive behavior rules. We evaluate our approach by using a simulator which combines wireless sensor networks and belief-desire-intention (BDI) agents to enable a precise simulation of both the city infrastructure and the adaptive behavior that it implements. The results reveal energy savings of close to 35% when the lighting system implements an adaptive behavior as opposed to a rigid, predefined behavior.https://doi.org/10.1155/2014/971587 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Soledad Escolar Jesús Carretero Maria-Cristina Marinescu Stefano Chessa |
spellingShingle |
Soledad Escolar Jesús Carretero Maria-Cristina Marinescu Stefano Chessa Estimating Energy Savings in Smart Street Lighting by Using an Adaptive Control System International Journal of Distributed Sensor Networks |
author_facet |
Soledad Escolar Jesús Carretero Maria-Cristina Marinescu Stefano Chessa |
author_sort |
Soledad Escolar |
title |
Estimating Energy Savings in Smart Street Lighting by Using an Adaptive Control System |
title_short |
Estimating Energy Savings in Smart Street Lighting by Using an Adaptive Control System |
title_full |
Estimating Energy Savings in Smart Street Lighting by Using an Adaptive Control System |
title_fullStr |
Estimating Energy Savings in Smart Street Lighting by Using an Adaptive Control System |
title_full_unstemmed |
Estimating Energy Savings in Smart Street Lighting by Using an Adaptive Control System |
title_sort |
estimating energy savings in smart street lighting by using an adaptive control system |
publisher |
SAGE Publishing |
series |
International Journal of Distributed Sensor Networks |
issn |
1550-1477 |
publishDate |
2014-05-01 |
description |
The driving force behind the smart city initiative is to offer better, more specialized services which can improve the quality of life of the citizens while promoting sustainability. To achieve both of these apparently competing goals, services must be increasingly autonomous and continuously adaptive to changes in their environment and the information coming from other services. In this paper we focus on smart lighting, a relevant application domain for which we propose an intelligent street light control system based on adaptive behavior rules. We evaluate our approach by using a simulator which combines wireless sensor networks and belief-desire-intention (BDI) agents to enable a precise simulation of both the city infrastructure and the adaptive behavior that it implements. The results reveal energy savings of close to 35% when the lighting system implements an adaptive behavior as opposed to a rigid, predefined behavior. |
url |
https://doi.org/10.1155/2014/971587 |
work_keys_str_mv |
AT soledadescolar estimatingenergysavingsinsmartstreetlightingbyusinganadaptivecontrolsystem AT jesuscarretero estimatingenergysavingsinsmartstreetlightingbyusinganadaptivecontrolsystem AT mariacristinamarinescu estimatingenergysavingsinsmartstreetlightingbyusinganadaptivecontrolsystem AT stefanochessa estimatingenergysavingsinsmartstreetlightingbyusinganadaptivecontrolsystem |
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1724662721525317632 |