The DOI matches its Crossref record.
Smart office for managing energy of lighting control system
Abstract
The energy consumed by office building is increasing year by year especially during peak hours. In this paper, in order to reduce the energy consumption, a new light control system is designed and simulated. By using artificial intelligence, it could be possible to control and monitor the energy consumption of the building efficiently. The developed design reduces significantly the energy consumption by applying fuzzy logic control to control the lighting system, without affecting the comfort of the occupant. Our design simulated and validated by using LabVIEW for one floor of the office building as a first step. The results depict that our developed system reduce the energy by 30 % without affecting the comfort of the occupant.
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In the citing paper
“Sakaci et al. [77] said that the consumption of electrical energy from office lighting has a correlation with the workload in the office and will increase during peak hours.”
From Machine Learning Methods in Smart Lighting Toward Achieving User Comfort: A Survey (2022) · cites this paper as Sakaci et al. [77]
Citations
Cites
No references could be resolved yet.
Research works printed but not linked: 15
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- melhem, 2017, Optimization and Energy Management in Smart Home Considering Photovoltaic, Wind, and Battery Storage System With Integration of Electric Vehicles, Can J Electr Comput Eng, 40, 128, 10.1109/CJECE.2017.2716780 · DOI
- 0, Energy Efficiency
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- 10.1109/ACCESS.2016.2621752 · DOI
Cited by
Sorted by citations
Machine Learning Methods in Smart Lighting Toward Achieving User Comfort: A Survey
Putrada, A. G., Abdurohman, M., Perdana, D., & Nuha, H. H. (2022) · IEEE Access · doi:10.1109/access.2022.3169765 · Cited by 101
“Sakaci et al. [77] said that the consumption of electrical energy from office lighting has a correlation with the workload in the office and will increase during peak hours.”
Background
Metadata
- Authors
- Sakaci, F. H., Cetiner, E., Chaouch, H., & Yener, S. C.
- Affiliations
- Sakarya University (TR)
- ORCID
- Chaouch, Haithem
- Venue
- 2018 6th International Istanbul Smart Grids and Cities Congress and Fair (ICSG)
- Publisher
- IEEE
- Published
- 2018-04
- Pages
- 101-104
- OpenAlex
- W2835537771
- Cited by
- 12
- References
- 0
- Citations by year
- 2024: 1 · 2023: 3 · 2022: 2 · 2021: 1 · 2020: 3 · 2019: 2
- FWCI
- 2.97
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- International Istanbul Smart Grids and Cities Congress and Fair (ICSG) (publishedVersion)
- Topics
- Physical Sciences › Engineering › Building and Construction › Building Energy and Comfort Optimization
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Smart Grid Energy Management
- Physical Sciences › Engineering › Building and Construction › Building energy efficiency and sustainability
- Keywords
- office building energy consumption, lighting control systems, fuzzy logic control, artificial intelligence, occupant comfort, energy consumption monitoring, peak shaving, LabVIEW simulation
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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