Real-time daylight modeling method for lighting systems based on RBFNN

Wa Si; Xun Pan; Harutoshi Ogai

doi:10.1145/3057039.3057100

Real-time daylight modeling method for lighting systems based on RBFNN

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Daylight harvesting has great potential of energy saving by utilizing daylight in buildings, and the accuracy of daylight data is essential to realize daylight harvesting in lighting control systems. This paper proposes a modified RBFNN structure for daylight modeling and presents a Real-time Daylight Modeling (RTDM) method, which needs only a few illumination sensors for real-time modeling of daylight. The method uses real-time sensor data to regulate a pre-stored RBFNN (which represents the relationship between position and daylight illuminance in one scenario of daylight) to calculate real-time daylight illuminance inside the room. Simulations in a middle-sized office model show that: 1) RTDM can realize real-time daylight modeling with higher accuracy compared with existing modeling methods; 2) lighting control system using RTDM can save considerable energy by daylight harvesting.

Original language	English
Title of host publication	Proceedings of 2017 9th International Conference on Computer and Automation Engineering, ICCAE 2017
Publisher	Association for Computing Machinery
Pages	318-325
Number of pages	8
Volume	Part F127852
ISBN (Electronic)	9781450348096
DOIs	https://doi.org/10.1145/3057039.3057100
Publication status	Published - 2017 Feb 18
Event	9th International Conference on Computer and Automation Engineering, ICCAE 2017 - Sydney, Australia Duration: 2017 Feb 18 → 2017 Feb 21

Other

Other	9th International Conference on Computer and Automation Engineering, ICCAE 2017
Country	Australia
City	Sydney
Period	17/2/18 → 17/2/21

Keywords

Daylight modeling
Lighting control
RBFNN

ASJC Scopus subject areas

Human-Computer Interaction
Computer Networks and Communications
Computer Vision and Pattern Recognition
Software

Access to Document

10.1145/3057039.3057100

Fingerprint Dive into the research topics of 'Real-time daylight modeling method for lighting systems based on RBFNN'. Together they form a unique fingerprint.

Cite this

Real-time daylight modeling method for lighting systems based on RBFNN. / Si, Wa; Pan, Xun; Ogai, Harutoshi.

Proceedings of 2017 9th International Conference on Computer and Automation Engineering, ICCAE 2017. Vol. Part F127852 Association for Computing Machinery, 2017. p. 318-325.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Si, W, Pan, X & Ogai, H 2017, Real-time daylight modeling method for lighting systems based on RBFNN. in Proceedings of 2017 9th International Conference on Computer and Automation Engineering, ICCAE 2017. vol. Part F127852, Association for Computing Machinery, pp. 318-325, 9th International Conference on Computer and Automation Engineering, ICCAE 2017, Sydney, Australia, 17/2/18. https://doi.org/10.1145/3057039.3057100

@inproceedings{2f5b9f9752554ae987cb42a68ecba68a,

title = "Real-time daylight modeling method for lighting systems based on RBFNN",

abstract = "Daylight harvesting has great potential of energy saving by utilizing daylight in buildings, and the accuracy of daylight data is essential to realize daylight harvesting in lighting control systems. This paper proposes a modified RBFNN structure for daylight modeling and presents a Real-time Daylight Modeling (RTDM) method, which needs only a few illumination sensors for real-time modeling of daylight. The method uses real-time sensor data to regulate a pre-stored RBFNN (which represents the relationship between position and daylight illuminance in one scenario of daylight) to calculate real-time daylight illuminance inside the room. Simulations in a middle-sized office model show that: 1) RTDM can realize real-time daylight modeling with higher accuracy compared with existing modeling methods; 2) lighting control system using RTDM can save considerable energy by daylight harvesting.",

keywords = "Daylight modeling, Lighting control, RBFNN",

author = "Wa Si and Xun Pan and Harutoshi Ogai",

year = "2017",

month = feb,

day = "18",

doi = "10.1145/3057039.3057100",

language = "English",

volume = "Part F127852",

pages = "318--325",

booktitle = "Proceedings of 2017 9th International Conference on Computer and Automation Engineering, ICCAE 2017",

publisher = "Association for Computing Machinery",

note = "9th International Conference on Computer and Automation Engineering, ICCAE 2017 ; Conference date: 18-02-2017 Through 21-02-2017",

}

TY - GEN

T1 - Real-time daylight modeling method for lighting systems based on RBFNN

AU - Si, Wa

AU - Pan, Xun

AU - Ogai, Harutoshi

PY - 2017/2/18

Y1 - 2017/2/18

N2 - Daylight harvesting has great potential of energy saving by utilizing daylight in buildings, and the accuracy of daylight data is essential to realize daylight harvesting in lighting control systems. This paper proposes a modified RBFNN structure for daylight modeling and presents a Real-time Daylight Modeling (RTDM) method, which needs only a few illumination sensors for real-time modeling of daylight. The method uses real-time sensor data to regulate a pre-stored RBFNN (which represents the relationship between position and daylight illuminance in one scenario of daylight) to calculate real-time daylight illuminance inside the room. Simulations in a middle-sized office model show that: 1) RTDM can realize real-time daylight modeling with higher accuracy compared with existing modeling methods; 2) lighting control system using RTDM can save considerable energy by daylight harvesting.

AB - Daylight harvesting has great potential of energy saving by utilizing daylight in buildings, and the accuracy of daylight data is essential to realize daylight harvesting in lighting control systems. This paper proposes a modified RBFNN structure for daylight modeling and presents a Real-time Daylight Modeling (RTDM) method, which needs only a few illumination sensors for real-time modeling of daylight. The method uses real-time sensor data to regulate a pre-stored RBFNN (which represents the relationship between position and daylight illuminance in one scenario of daylight) to calculate real-time daylight illuminance inside the room. Simulations in a middle-sized office model show that: 1) RTDM can realize real-time daylight modeling with higher accuracy compared with existing modeling methods; 2) lighting control system using RTDM can save considerable energy by daylight harvesting.

KW - Daylight modeling

KW - Lighting control

KW - RBFNN

UR - http://www.scopus.com/inward/record.url?scp=85020933135&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85020933135&partnerID=8YFLogxK

U2 - 10.1145/3057039.3057100

DO - 10.1145/3057039.3057100

M3 - Conference contribution

AN - SCOPUS:85020933135

VL - Part F127852

SP - 318

EP - 325

BT - Proceedings of 2017 9th International Conference on Computer and Automation Engineering, ICCAE 2017

PB - Association for Computing Machinery

T2 - 9th International Conference on Computer and Automation Engineering, ICCAE 2017

Y2 - 18 February 2017 through 21 February 2017

ER -