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Sensor-driven, human-in-the-loop lighting control
Open accessAbstract
Smart indoor lighting systems use occupancy and light sensor data to adapt artificial lighting in accordance with changing occupancy and daylight conditions. Such systems can be designed to reduce lighting energy consumption significantly. However, these systems cannot account for individual user preferences at the workplace in real time. We propose a sensor-driven, human-in-the-loop lighting system that incorporates user feedback in addition to occupancy and light sensor inputs. In this system, luminaires transmit unique visible light communication identifier signals. By processing the image captured by a smartphone camera, a user obtains two pieces of information: visible light communication identifiers of luminaires in the vicinity and average image pixel value. A control algorithm is designed that incorporates these user inputs along with occupancy and light sensor inputs to determine the dimming levels of the luminaires to achieve illumination levels acceptable to users. We compare the performance of the proposed lighting control system with a sensor-driven lighting control system in an office test bed.
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A sophisticated lighting control system involves an occupancy sensor and a light sensor to control the light based on natural light and achieve efficiency.
“Tan et al. [98] say that a sophisticated lighting control system involves an occupancy sensor and a light sensor to control the light based on natural light and achieve efficiency.”
From Machine Learning Methods in Smart Lighting Toward Achieving User Comfort: A Survey (2022) · cites this paper as Tan et al. [98]
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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
“Tan et al. [98] say that a sophisticated lighting control system involves an occupancy sensor and a light sensor to control the light based on natural light and achieve efficiency.”
Background
Metadata
- Authors
- Tan, F., Caicedo, D., Pandharipande, A., & Zuniga, M.
- Affiliations
- Signify (Netherlands) (NL)
- Delft University of Technology, Delft, The Netherlands
- Corresponding author
- Pandharipande, A
- Venue
- Lighting Research & Technology
- Publisher
- SAGE Publications
- Published
- 2017-02-21
- Volume
- 50
- Issue
- 5
- Pages
- 660-680
- ISSN
- 0024-3426 (ISSN-L)
- 1477-1535
- 1477-0938
- OpenAlex
- W2590955327
- Cited by
- 33
- References
- 0
- Citations by year
- 2026: 4 · 2025: 2 · 2024: 3 · 2022: 6 · 2021: 7 · 2020: 4 · 2019: 4 · 2018: 3
- FWCI
- 2.81
- Type
- journal article
- Language
- en
- Open access
- green
- research.tue.nl
- Locations
- Lighting Research & Technology (publishedVersion)
- TU/e Research Portal (publishedVersion, other-oa)
- TU/e Research Portal (submittedVersion)
- TU/e Research Portal (submittedVersion, other-oa)
- Topics
- Physical Sciences › Engineering › Building and Construction › Building Energy and Comfort Optimization
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Optical Wireless Communication Technologies
- Physical Sciences › Engineering › Architecture › Facilities and Workplace Management
- Keywords
- intelligent lighting control, human-in-the-loop control, user feedback, visible light communication, occupant preferences, lighting energy consumption, occupancy detection, optical sensing, smartphone camera, lighting fixtures, dimming control, office lighting
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