volume 10 issue 2 pages 169-192

An intelligent system for energy management in smart cities based on big data and ontology

Publication typeJournal Article
Publication date2020-04-28
scimago Q1
wos Q1
SJR0.991
CiteScore12.7
Impact factor4.6
ISSN20466099, 20466102
Renewable Energy, Sustainability and the Environment
Building and Construction
Civil and Structural Engineering
Management, Monitoring, Policy and Law
Urban Studies
Human Factors and Ergonomics
Abstract
Purpose

This research paper aims at proposing a framework based on semantic integration in Big Data for saving energy in smart cities. The presented approach highlights the potential opportunities offered by Big Data and ontologies to reduce energy consumption in smart cities.

Design/methodology/approach

This study provides an overview of semantics in Big Data and reviews various works that investigate energy saving in smart homes and cities. To reach this end, we propose an efficient architecture based on the cooperation between ontology, Big Data, and Multi-Agent Systems. Furthermore, the proposed approach shows the strength of these technologies to reduce energy consumption in smart cities.

Findings

Through this research, we seek to clarify and explain both the role of Multi-Agent System and ontology paradigms to improve systems interoperability. Indeed, it is useful to develop the proposed architecture based on Big Data. This study highlights the opportunities offered when they are combined together to provide a reliable system for saving energy in smart cities.

Practical implications

The significant advancement of contemporary applications (smart cities, social networks, health care, IoT, etc.) requires a vast emergence of Big Data and semantics technologies in these fields. The obtained results provide an improved vision of energy-saving and environmental protection while keeping the inhabitants’ comfort.

Originality/value

This work is an efficient contribution that provides more comprehensive solutions to ontology integration in the Big Data environment. We have used all available data to reduce energy consumption, promote the change of inhabitant’s behavior, offer the required comfort, and implement an effective long-term energy policy in a smart and sustainable environment.

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GOST |
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GOST Copy
Sayah Z. et al. An intelligent system for energy management in smart cities based on big data and ontology // Smart and Sustainable Built Environment. 2020. Vol. 10. No. 2. pp. 169-192.
GOST all authors (up to 50) Copy
Sayah Z., Kazar O., Lejdel B., Laouid A., Ghenabzia A. An intelligent system for energy management in smart cities based on big data and ontology // Smart and Sustainable Built Environment. 2020. Vol. 10. No. 2. pp. 169-192.
RIS |
Cite this
RIS Copy
TY - JOUR
DO - 10.1108/SASBE-07-2019-0087
UR - https://www.emerald.com/insight/content/doi/10.1108/SASBE-07-2019-0087/full/html
TI - An intelligent system for energy management in smart cities based on big data and ontology
T2 - Smart and Sustainable Built Environment
AU - Sayah, Zaoui
AU - Kazar, Okba
AU - Lejdel, Brahim
AU - Laouid, Abdelkader
AU - Ghenabzia, Ahmed
PY - 2020
DA - 2020/04/28
PB - Emerald
SP - 169-192
IS - 2
VL - 10
SN - 2046-6099
SN - 2046-6102
ER -
BibTex |
Cite this
BibTex (up to 50 authors) Copy
@article{2020_Sayah,
author = {Zaoui Sayah and Okba Kazar and Brahim Lejdel and Abdelkader Laouid and Ahmed Ghenabzia},
title = {An intelligent system for energy management in smart cities based on big data and ontology},
journal = {Smart and Sustainable Built Environment},
year = {2020},
volume = {10},
publisher = {Emerald},
month = {apr},
url = {https://www.emerald.com/insight/content/doi/10.1108/SASBE-07-2019-0087/full/html},
number = {2},
pages = {169--192},
doi = {10.1108/SASBE-07-2019-0087}
}
MLA
Cite this
MLA Copy
Sayah, Zaoui, et al. “An intelligent system for energy management in smart cities based on big data and ontology.” Smart and Sustainable Built Environment, vol. 10, no. 2, Apr. 2020, pp. 169-192. https://www.emerald.com/insight/content/doi/10.1108/SASBE-07-2019-0087/full/html.