Optimizing Daylight Glare and Circadian Entrainment in a Daylight-Artificial Light Integrated Scheme
Human circadian rhythm varies with different combinations of light sources. Natural light and dark patterns regulate the sleeping and waking cycles of the human body. This study aimed to develop a simplified model for daylight glare and circadian entrainment in an existing controlled daylight-artifi...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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IEEE
2022-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9749205/ |
| _version_ | 1811332007008927744 |
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| author | Veena Mathew Ciji Pearl Kurian Nevin Augustine |
| author_facet | Veena Mathew Ciji Pearl Kurian Nevin Augustine |
| author_sort | Veena Mathew |
| collection | DOAJ |
| description | Human circadian rhythm varies with different combinations of light sources. Natural light and dark patterns regulate the sleeping and waking cycles of the human body. This study aimed to develop a simplified model for daylight glare and circadian entrainment in an existing controlled daylight-artificial light integrated system. In addition, the effects of window orientation, occupant position, artificial light, daylight, and a combination of both on Circadian Stimulus (CS) were investigated. In a daylit interior space, window orientation, shading control and occupant seating position play a significant role in the CS. Simplified models to predict Daylight Glare Probability (DGP) and CS were estimated from the dataset. The developed nonlinear CS estimation models have R-squared values of 0.983 and 0.974. The precision of the models was evaluated in terms of standard error of regression (S) and AIC score. Multi-Objective Genetic Algorithm based optimization technique was developed using the above models to minimize glare and maximize CS in the working space. This optimisation methodology aids in implementing a complete automation algorithm for the test workbench to achieve visual comfort and circadian entrainment. |
| first_indexed | 2024-04-13T16:29:28Z |
| format | Article |
| id | doaj.art-23d1de06b82a4a11b7696d164be3eeda |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-04-13T16:29:28Z |
| publishDate | 2022-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-23d1de06b82a4a11b7696d164be3eeda2022-12-22T02:39:37ZengIEEEIEEE Access2169-35362022-01-0110381743818810.1109/ACCESS.2022.31650239749205Optimizing Daylight Glare and Circadian Entrainment in a Daylight-Artificial Light Integrated SchemeVeena Mathew0Ciji Pearl Kurian1https://orcid.org/0000-0002-5222-3041Nevin Augustine2Department of Electrical and Electronics Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, IndiaDepartment of Electrical and Electronics Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, IndiaDepartment of Instrumentation and Control Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, IndiaHuman circadian rhythm varies with different combinations of light sources. Natural light and dark patterns regulate the sleeping and waking cycles of the human body. This study aimed to develop a simplified model for daylight glare and circadian entrainment in an existing controlled daylight-artificial light integrated system. In addition, the effects of window orientation, occupant position, artificial light, daylight, and a combination of both on Circadian Stimulus (CS) were investigated. In a daylit interior space, window orientation, shading control and occupant seating position play a significant role in the CS. Simplified models to predict Daylight Glare Probability (DGP) and CS were estimated from the dataset. The developed nonlinear CS estimation models have R-squared values of 0.983 and 0.974. The precision of the models was evaluated in terms of standard error of regression (S) and AIC score. Multi-Objective Genetic Algorithm based optimization technique was developed using the above models to minimize glare and maximize CS in the working space. This optimisation methodology aids in implementing a complete automation algorithm for the test workbench to achieve visual comfort and circadian entrainment.https://ieeexplore.ieee.org/document/9749205/Circadian stimulusvertical eye illuminancedaylight glare probabilitynon-linear regression modelsmulti-objective genetic algorithm optimization |
| spellingShingle | Veena Mathew Ciji Pearl Kurian Nevin Augustine Optimizing Daylight Glare and Circadian Entrainment in a Daylight-Artificial Light Integrated Scheme IEEE Access Circadian stimulus vertical eye illuminance daylight glare probability non-linear regression models multi-objective genetic algorithm optimization |
| title | Optimizing Daylight Glare and Circadian Entrainment in a Daylight-Artificial Light Integrated Scheme |
| title_full | Optimizing Daylight Glare and Circadian Entrainment in a Daylight-Artificial Light Integrated Scheme |
| title_fullStr | Optimizing Daylight Glare and Circadian Entrainment in a Daylight-Artificial Light Integrated Scheme |
| title_full_unstemmed | Optimizing Daylight Glare and Circadian Entrainment in a Daylight-Artificial Light Integrated Scheme |
| title_short | Optimizing Daylight Glare and Circadian Entrainment in a Daylight-Artificial Light Integrated Scheme |
| title_sort | optimizing daylight glare and circadian entrainment in a daylight artificial light integrated scheme |
| topic | Circadian stimulus vertical eye illuminance daylight glare probability non-linear regression models multi-objective genetic algorithm optimization |
| url | https://ieeexplore.ieee.org/document/9749205/ |
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