A Reinforcement Learning–Based Approach for Smart Lighting and Shading in Buildings
Fadwa Lachhab
LabSIV, Department of Computer Science, Faculty of Sciences
Ibn Zohr University, Agadir, Morocco
and
InterDisciplinary Applied Research Laboratory-LIDRA
International University of Agadir-Universiapolis, Agadir, Morocco
Mohamed Bakhouya
LERMALab, College of Engineering and Architecture
International University of Rabat
Sala El Jadida, Morocco
Abstract
Lighting systems in commercial and residential buildings constitute a major source of the world energy consumption. Optimizing energy efficiency through lighting management requires an optimal control strategy in order to balance daylighting requirements while maintaining visual comfort in illuminated spaces. This paper introduces a reinforcement learning (RL)–based approach using the Q-learning algorithm to optimize lighting and shading control, maintaining constant illuminance with maximum visual comfort. A prototype was developed in a laboratory to test the scenario, using internet of things (IoT) and artificial intelligence (AI) technologies, for lighting and shading control. AI techniques are integrated to enable a smart conversation between lighting and shading systems in order to maintain the required light level. A real-time chatbot based on natural language processing (NLP) is integrated with IoT techniques in order to provide a user-friendly building automation system. Experiments have been conducted for validation purposes and obtained results show the effectiveness of the proposed solution by maintaining the ideal level of lighting with efficient consumption. In fact, the proposed control is capable of optimizing energy consumption by more than 45% against a normal lighting operation while maintaining occupants’ visual comfort within a suitable illuminance.
Keywords: lighting control; shading control; energy efficiency; Internet of Things; artificial intelligence; visual comfort
Cite this publication as:
F. Lachhab and M. Bakhouya, “A Reinforcement Learning–Based Approach for Smart Lighting and Shading in Buildings,” Complex Systems, 34(4), 2026 pp. 455–478.
https://doi.org/10.25088/ComplexSystems.34.4.455
