Daylight adaptive smart indoor lighting control method using artificial neural networks

Abstract

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.

Influence of the Adaptation of Balconies to Loggias on the Lighting Climate inside an Apartment Building under Cloudy Sky

“…It is widely used and considered as one of the simplest methods to describe the amount of daylight received on a specific point in a room. The minimum and average daylight factors for rooms have been defined as 1.5% and 3%, respectively [30,31].…”

“…The horizontal support plate statically acts as a simple plate and is supported by vertical walls, columns, or through frames. It is usually bounded on three sides by walls [31].…”

Design and Application of a Smart Lighting System Based on Distributed Wireless Sensor Networks

“…In order to determine dimming levels of luminaires, two different control methods are utilized: open-loop method and close-loop method. The open-loop method measures the incoming daylight and signals a controller to proportionately dim the luminaire based on the daylight contribution [42]. The closed-loop method adjusts the luminaire dimming level to ensure that the combined contribution from daylight and artificial light maintains the desired illumination level.…”

“…However, the open-loop method is more economical due to considering the limited processing capability of microcontroller in a sensing module and also, more robust to errors in the placement of light sensors. In addition, optimization algorithms and machine learning are applied to control methods to minimize total illuminance [10,14,34] and make the control system smart [42], respectively. Although the optimization algorithms can achieve high energy savings, they consume more computational resources and much time and seldom consider the movement of people.…”

Tackling Heterogeneous Color Registration: Binning Color Sensors

“…Intelligent systems for interior lighting are conceived to automatically find the optimal balance between energy consumption, legal requirements, visual performance, user comfort, and health considerations [ 1 ]. A closed-loop feedback design with input from optical sensors seems to be most expedient and has already been adopted successfully in practical research [ 2 , 3 , 4 , 5 , 6 , 7 , 8 ] in order to ensure that such systems are capable of monitoring and dynamically adapting to continuous changes in the environmental conditions and the lighting parameters, e.g., caused by variations of the natural daylight entry through windows and skylights [ 9 , 10 , 11 ] or by degradation and temperature processes in the luminaires [ 12 , 13 , 14 ].…”