Building value proposition for interactive lighting systems in the workplace: Combining energy and occupant perspectives

Kim, Amy A.; Wang, Shuoqi; McCunn, Lindsay J.

doi:10.1016/j.jobe.2019.100752

Cited by 19 publications

(11 citation statements)

References 33 publications

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“…The gains are determined according to the online values of occupancy and priority delivered by the initiator. The target values of photodetectors (t 1:q ) depends on the power consumption of LEDs in (3). Moreover, the variables used in the cost function should be independent of each other [20], thus, a method should be applied to rewrite (3).…”

Section: Preprocessormentioning

confidence: 99%

“…Smart lighting system is an integral part of any modern building that has a direct impact on energy cost, user's comfort, health, and safety. This great importance such systems on the improvement of human life has resulted in rapid adoption of smart indoor lighting in recent years [1][2][3][4][5]. The main components of a smart lighting system include dimmable light-emitting diodes (LEDs), photodetectors, occupancy sensors, and controller units; which have been the leading research topics over the recent years [6][7][8][9][10].…”

Section: Introductionmentioning

confidence: 99%

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Daylight adaptive smart indoor lighting control method using artificial neural networks

Seyedolhosseini

Masoumi

Modarressi

et al. 2020

Journal of Building Engineering

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Accurate and efficient adjustment of maintained illuminance and illuminance uniformity in indoor environments with daylight variations is a tremendous challenge, mainly due to the nonlinear and time-variant nature of lighting control systems. In this paper, we propose a smart lighting control method for indoor environments with both dimmable (controllable) and uncontrollable external light sources. Targeting an indoor environment with multiple zones, each requiring a different lighting condition and equipped with an unequal number of photodetectors and dimmable light sources, this paper presents a novel control mechanism that determines the output flux of each luminary in such a way that each zone (1) receives the required maintained illuminance, (2) illuminance uniformity conditions are met inside each zone, and (3) the power consumption is optimized. This method uses a neural network to learn the impact of each luminary on the maintained illuminance of each zone and adjust the dimming level of the luminaries to establish the required illuminance in the zones. We also rely on photodetectors to measure the daylight illuminance continuously and use it as the bias value for the neural network. The new priority value allows losing some illuminance accuracy (by allowing lager difference between the actual and required maintained illuminance values) for low-priority zones to reduce power consumption. The method has been evaluated in different test cases by chaining the widely-used DIALux tool and some MATLAB toolboxes. The evaluation results show that the method can achieve considerable accuracy by yielding an average Mean Square Error of 1.2 between the demanded and sensed illuminance values. Furthermore, when all sensors except one reference sensor are removed from each zone (to increase user comfort or reduce cost), the mean square error is less than 25.4 across all considered test cases.

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Section: Preprocessormentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Daylight adaptive smart indoor lighting control method using artificial neural networks

Seyedolhosseini

Masoumi

Modarressi

et al. 2020

Journal of Building Engineering

View full text Add to dashboard Cite

show abstract

“…In [17,18], an intelligent lighting system was developed for a typical office environment to evaluate the perception of work-related productivity, efficiency and fatigue of the occupants working on site. In [19] a lighting control system capable of adjusting illuminance, uniformity and correlated color temperature according to students needs was evaluated.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Lighting System to Increase the Attention of Design Students in the Classroom

et al. 2021

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Dynamic lighting is playing a key role in education, by considering the main photometric variables such as the correlated color temperature and the illuminance to increase student’s attention levels inside the classroom. In the case of design students, the project component is fundamental for teaching, where students mainly need to develop activities such as presentation to listen to the teacher instructions, ideation and sketching to propose a solution according to the problem being addressed, and exhibition to present the work that has been done. These activities require specific and adequate lighting conditions to generate a positive impact on the performance of students. This article presents the design of a dynamic lighting system capable of adjusting the correlated color temperature in a range from 2500 K to 6500 K and the illuminance levels in a range from 0 lx to 800 lx to enhance the sustained and fixed attention of design students inside the classroom according to the type of activity that is being developed. The performance of the system was evaluated experimentally by measuring student’s attention inside the ergonomics and usability laboratory by using the Gesell chamber, the Emotiv Epoc EEG Headset with 14 electrodes to measure the brain activity and obtain engagement and focus levels, the eye tracking Tobii glasses, and a protocol to evaluate performance including several surveys and camera observation. In conclusion, the dynamic lighting system can improve the attention of design students by configuring the photometric variables according to the type of activity that is being done.

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“…It has also considered different types of systems designed to achieve energy savings in regard to lighting. Some examples of energy savings utilized lighting systems reviewed in this paper are daylight [17]- [25], occupancy [26], [27], retrofitting [28], and time scheduling-based energy-efficient lighting systems [29]- [31].…”

Section: Introductionmentioning

confidence: 99%

A Review: Buildings Energy Savings - Lighting Systems Performance

et al. 2020

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Lighting systems are one of the highest energy consumptions specifically in buildings. Thus, by designing energy efficient systems, it would contribute much to buildings energy savings. Therefore, this paper motivation is to review a number of lighting systems designs applied to many types of buildings. It is then so important to discover what methods and systems which have been proposed to save energy in buildings in term of lighting. By finding out what proposed systems are for different types of buildings, designers and respective researchers e.g., buildings engineers would find possibility and applicability of such lighting systems for certain types of buildings to achieve higher energy savings than some other systems when applied to the same types of buildings. Such a relation between reviewed lighting systems with types of buildings would be helpful for many researchers from different fields. There exist numerous factors that play an important role in achieving higher energy savings rate on which efficient energy lighting systems rely. This paper aims to review several types of lighting systems designs applied to different types of buildings. Additionally, performance(s) of lighting systems might vary depending on the design of the lighting system to achieve higher buildings' energy savings. In this review paper, several past studies that utilized Information and Communication Technology (ICT) from the perspective of energy Informatics for a smart lighting system that efficiently achieves energy savings have been considered. This paper has considered different types of lighting systems and types of buildings. Cited papers in this review paper are derived from six digital libraries which are: IEEE Xplore Digital Library, ScienceDirect, MDPI, Emerald Insight, ACM DL, and Taylor & Francis Online. INDEX TERMS Lighting systems, buildings energy savings, daylight systems, occupancy-based lighting systems, large scale buildings, sky view factor, rural buildings, ICT for energy informatics.

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Building value proposition for interactive lighting systems in the workplace: Combining energy and occupant perspectives

Cited by 19 publications

References 33 publications

Daylight adaptive smart indoor lighting control method using artificial neural networks

Daylight adaptive smart indoor lighting control method using artificial neural networks

Dynamic Lighting System to Increase the Attention of Design Students in the Classroom

A Review: Buildings Energy Savings - Lighting Systems Performance

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