# Intelligent Office Lighting Control Using Natural Light and a GA-BP Neural Network-Based System
## 1 Introduction  
The office environment plays a crucial role in both daily life and work, with lighting conditions significantly influencing not only visual health but also physiological and psychological well-being [1]. While designing office buildings, appropriate lighting solutions can not only reduce energy consumption, but also help maintain stable indoor heating and cooling loads, all while promoting people's health and productivity [2, 3]. The effective use of natural daylight, particularly through the regulation of blinds, is an effective approach to mitigating glare and enhancing energy efficiency [4, 5, 6]. In 1998, [PERSON] et al. at the University of California established two parallel laboratory environments to evaluate the interaction between automated blinds and dimmable lighting systems. After a year of monitoring, they concluded that dimmable lighting systems significantly outperformed static blinds in terms of energy savings. At the time, computer simulation software was still in its developmental stages, and the adjustable blinds system could only operate at three distinct angles. Despite these limitations, the study highlighted the substantial energy-saving potential of integrating adjustable blinds with lighting control systems [7]. In 2002, [PERSON] and [PERSON] et al. proposed a controller based on a genetic algorithm to optimize the angle of blinds, incorporating user-preferred illumination levels to mitigate natural glare [8]. Later, [PERSON] applied a BP neural network to predict indoor natural illuminance distribution using outdoor illuminance and other environmental factors as inputs, demonstrating significant practical value [9]. [PERSON] employed a fuzzy control algorithm to adaptively regulate indoor illuminance by analyzing the relationship between illuminance and energy efficiency, achieving real-time dynamic responses to environmental changes [10]. In 2017, [PERSON], [PERSON], and [PERSON] analyzed the relationship between natural light quality and user perception by measuring brightness and illumination in three differently oriented office spaces in Naples, Italy. Their study found that, while brightness patterns were consistent across offices under similar weather conditions, the user perceptions of visual comfort varied based on the time of day and weather conditions. These perceptions did not always align with the established daylight performance metrics, such as daylight usability and glare probability. The findings suggest that, although natural light can enhance indoor comfort and energy efficiency, it can also cause visual discomfort. Therefore, daylight design must balance the goal of maximizing daylight capture with the need to offset the associated risks of discomfort. The authors recommend incorporating external shading systems, especially in the morning when direct sunlight is strongest, to enhance visual comfort [11]. In 2018, [PERSON], [PERSON], and [PERSON] conducted orthogonal experiments at Shanghai Jiao Tong University in China to investigate the effects of various lighting conditions on office job performance. The study analyzed the influence of illuminance (ILL), illuminance uniformity (U-ILL), and correlated color temperature (CCT) on worker productivity. The results indicated that participants experienced the highest levels of satisfaction, attention, and productivity in environments with a high illuminance, high illumination uniformity, and high or medium color temperature. These lighting conditions also corresponded with the lowest levels of stress, perceived work difficulty, and fatigue. Additionally, the study showed that lighting conditions significantly influenced neurobehavioral function, with different conditions enhancing perception, learning, and memory. A lower illumination, reduced uniformity, and medium color temperature were found to improve executive and thinking functions [12].