Implementation of smartphone-based color temperature and wavelength control LED lighting system

Moon, Surk‐Sik; Kwon, Sook-Youn; Lim, Jae-Hyun

doi:10.1007/s10586-016-0548-y

Cited by 16 publications

(8 citation statements)

References 13 publications

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“…Some researchers advocated the integrated lighting control with occupancy sensors, photocells, and central control module for users' convenience and better experience [23]. A few researchers developed mobile applications for better user experience in terms of operability and mobility [18,30,31,36]. Evidence indicated that a well-designed mobile application can not only improve user experience, but also guarantee the compliance of illumination regulations and reduce energy consumption [36].…”

Section: Related Workmentioning

confidence: 99%

“…It is noteworthy that more and more learning-context based lighting control systems have been recently proposed for classrooms [18]. These proposed systems followed existing psychological research findings by applying lower brightness and CCT for subjects like arts and language, and higher brightness and CCT for subjects like science and mathematics [31][32][33]. As summarized in Table 2, these systems provided illumination settings and control methods for a few basic learning scenarios.…”

Section: Related Workmentioning

confidence: 99%

“…Such a method is limited due to small sample sizes, short test duration, and limited variables considered in each study. These restrictions were believed to be the major causes that led to inconsistency among existing results from previous studies [11,16,31]. Although the uses of IoT technology provide the context for new data sources, a real challenge is the integration of multiple systems and datasets [54].…”

Section: Classroom Lighting Environment Data-collection and Self-optimentioning

confidence: 99%

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Development and Implementation of a Self-Optimizable Smart Lighting System Based on Learning Context in Classroom

Sun

Zhang²,

Cao

2020

IJERPH

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Illumination is one of the most important environmental factors in the classroom. Researchers have discovered that lighting settings have significant impact on students’ performance. Although light-emitting diode (LED) lighting systems can precisely control brightness level and correlated color temperature (CCT), existing designs of LED lighting control systems for classrooms are focused on energy-saving but lack context-based illumination control ability. In this study, a smart lighting system with continuous evolution capability was developed. It can adjust brightness, CCT, and illuminance distribution dynamically according to specific learning context. This system allows not only manual control, but also automatic switching of scenes by integrating with school schedules. Based on existing knowledge about lighting preference, 10 lighting modes confined in the comfortable zone of Kruithof curve were proposed for various classroom scenarios. Moreover, a classroom environmental data-processing framework for collecting and analyzing learning context, illumination settings, environmental data, and students’ performance data was introduced. This framework can help researchers explore the correlation between student performance and environmental parameters.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Classroom Lighting Environment Data-collection and Self-optimentioning

confidence: 99%

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Development and Implementation of a Self-Optimizable Smart Lighting System Based on Learning Context in Classroom

Sun

Zhang²,

Cao

2020

IJERPH

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“…This meets their visual needs, but does not necessarily provide the proper light intensity and spectral composition required for the stimulation of the circadian system, thus leading to circadian disruption [14][15][16]. Studies tried to lessen the problem by simulating natural light's wavelengths and color temperatures using light-emitting diode (LED) fixtures [14,[17][18][19][20][21]. The challenge was to fully match the continuous visible spectrum of the natural light by mixing the LEDs [20].…”

Section: Introductionmentioning

confidence: 99%

Role of Architectural Design in Creating Circadian-Effective Interior Settings

Alkhatatbeh

Asadi

2021

Energies

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Daylight variability throughout the day makes it an ideal light source for the stimulation of humans’ circadian systems. However, the key criteria, including proper quantity, quality, and hours of access to daylight, are not always present inside the built environment. Therefore, artificial light is necessary to complement the human’s visual and non-visual needs for light. Architectural design parameters, such as window area, orientation, glazing material, and surface reflectance alter the characteristics of both daylight and artificial light inside buildings. These parameters and their impact on lighting design should be considered from the early design stages to attain a circadian-effective design. In response to this need, a design approach called Human-Centric Lighting (HCL) was introduced. HCL places humans, and their visual and non-visual needs, in the center of the design process. It manipulates the light-related factors, such as spectrum and intensity, within the built environment for circadian benefits. The effect of HCL on lighting energy efficiency is still not clear. This paper reviews essential architectural design parameters and their impacts on circadian lighting design, considers the HCL design process and explores the most widely used circadian lighting metrics and standards.

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“…Park et al put forward a novel model-based PID gain design method to improve the performances of dynamic bending light (DBL) module that change horizontal angle [4]. Some researchers have studied outdoor lighting systems [5,6], while others have studied indoors such as classrooms and homes [7][8][9][10]. Wireless control technology was added to the lighting system, but they still need people to participate in and control and have not achieved an energy-saving effect.…”

Section: Introductionmentioning

confidence: 99%

Station green lighting system based on sensor network

Wang

Qin

2019

J Wireless Com Network

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Aiming at the problems of high energy consumption, chaotic lines, and inconsistent lighting sources in many stations, this paper presents a simple, reliable, and convenient station green lighting system based on sensor network. According to the arrival and departure time of the train, the lighting equipment of the corresponding track is automatically closed, which saves the power resources and human resources, and improves the service life of the lighting equipment. In addition, an intelligent illumination control method based on BP neural network is proposed. The test is carried out in the real environment of the station. The designed system can intelligently adjust the working conditions of the lighting system, save energy to the greatest extent and meet the practical requirements.

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Implementation of smartphone-based color temperature and wavelength control LED lighting system

Cited by 16 publications

References 13 publications

Development and Implementation of a Self-Optimizable Smart Lighting System Based on Learning Context in Classroom

Development and Implementation of a Self-Optimizable Smart Lighting System Based on Learning Context in Classroom

Role of Architectural Design in Creating Circadian-Effective Interior Settings

Station green lighting system based on sensor network

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