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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Main Authors: Soledad Escolar, Jesús Carretero, Maria-Cristina Marinescu, Stefano Chessa
Format: Article
Language:English
Published: SAGE Publishing 2014-05-01
Series:International Journal of Distributed Sensor Networks
Online Access:https://doi.org/10.1155/2014/971587
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spelling 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
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AT mariacristinamarinescu estimatingenergysavingsinsmartstreetlightingbyusinganadaptivecontrolsystem
AT stefanochessa estimatingenergysavingsinsmartstreetlightingbyusinganadaptivecontrolsystem
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