Simulation evaluations demonstrate age-adaptive energy management for lighting, suggesting innovative solutions for sustainable cities.
Taking advantage of cutting‐edge technologies to efficiently control energy consumption while prioritizing public well‐being is a wise choice for the sustainable development of cities and societies. From this perspective, the proposed approach in this study, which employs real‐time electricity pricing, user age, and user preferences as input parameters for a fuzzy inference system (FIS), aims to balance energy consumption along with people’s lighting requirements. FISs based on linguistic patterns are ideal for establishing communication between individuals and artificial intelligence, especially in smart cities. FIS allows complicated parameters to be defined in a flexible framework that is easily understandable to humans. While this study specifically evaluated the performance of the proposed system for lighting demands, it may also be applied to other purposes and requirements. Results from the system simulations for a commercial setting validate the suggested system’s accuracy. According to the findings, developing appropriate control strategies derived from the established method enables meeting users’ lighting requirements for individuals of different ages. At the same time, this method regulates energy consumption and associated costs. The introduced method is advocated as an innovative solution for developing smarter and more sustainable cities and societies.
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Kalani et al. (2026) studied this question.
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