# Optimizing Ambiance: Intelligent RGB Lighting Control in Structures Using Fuzzy Logic
###### Abstract
By considering in the influence of other environmental variables, the system ensures energy efficiency and aids in preventing overstimulation. The research has led to several contributions:  
1. Development of an AloT Lighting System: An innovative RGB lighting control system based on AloT technology is introduced. Acting as an invisible master of ceremonies, this system dynamically adjusts lights to create favorable environments and enhance spatial perception. 2. Integration of weather sensors: The proposed system integrates with weather sensors to adapt lighting to changing environmental conditions. This approach reflects a profound understanding of the correlation between climate and lighting preferences, thus enabling personalized environments. 3. Neuro-fuzzy control for customization: A novel approach is introduced using neuro-fuzzy control to correlate environmental variables with artificial lighting conditions. This allows for precise and adaptive adjustments in response to changes in human emotions, fostering friendly and swiftly adaptable environments. 4. Application in social and enclosed structures and environments: The system is tailored for structures of diverse nature, serving as a visual stimulus to contribute to intended emotional states in the target audience. This practical application suggests  
Figure 2: Workflow of the system and methodology in the research. the versatility and adaptability of the system in structures such as offices, homes, or public spaces. 5. Energy efficiency and sustainability: Highlights the system's capacity to reduce energy consumption through efficient lighting implementation. This contribution not only prioritizes emotional well-being but also emphasizes environmental sustainability and resource optimization. This holds significance as it has been proved that 90% of the time when natural light is available individuals in Western societies tend to stay indoors, be it in academic, work, or recreational environments. The system hypotheses are implemented via fuzzy rules and the system is validated through a pilot test. A concept test is conducted, demonstrating the system's real capacity, with significant outcomes. Among these, an average frequency of 9.8 Hz during the test indicates a calm state, supporting the hypothesis that adaptive lighting positively influences emotions. This paper provides a comprehensive description of the construction of the instrumentation system, enabling other researchers to replicate and expand upon this approach. Moreover, this study serves as a conduit for comprehending and implementing the proposed AIoT technology in scenarios where devices can extend beyond merely illuminating a space. With a neuro-fuzzy system that adjusts automatically based on collected information, the system can be placed in different social contexts, irrespective of language or cultural barriers. This is achieved due to the system adaptability using AI to fine-tune controller parameters. The research is anchored in the objective of enhancing the control capabilities of a system for turning artificial lighting on and off within a structure. While the system is based on maintaining levels based on CCT values, this implies a limitation in the approach susceptible to errors, it enables the use of other approaches in future research. This system aims to create structures with a \"sense\", to generate stimuli in accordance with intention, thereby requiring each component of the system to be self-contained and operate independently. However, this architecture implies system compatibility with different elements of the AIoT concept as part of a broader technological ecosystem. The remainder of this paper is structured as follows: First, relevant previous research informing the research approach is presented. Then, the foundational concepts underpinning the proposal are introduced. Second, the system's design and features will be discussed. Third, the development parameters used, the implementation, and the tests conducted will be discussed.