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Human thermal comfort, crucial for well-being and productivity, is often improved by personal comfort systems that offer tailored control over environmental conditions while promoting energy efficiency. Previous studies have explored various textile technologies in thermoregulation systems according to user preferences. However, limited research has focused on temperature prediction by artificial intelligence to maximize thermal comfort for varied users. This study proposes a design approach to optimize thermal comfort in electric heating textiles using artificial intelligence, considering user preferences related to age and gender differences. A fuzzy logic model is established as a proof of concept for temperature regulation by varying ambient temperature, followed by developing an artificial neural network model to predict the optimal temperature for maximum comfort. Subsequently, a smart electric heating jacket is fabricated to assess preferred heating temperatures among 50 subjects with varying ages and genders. Results from the artificial neural network model show promising temperature prediction, while subject tests reveal significant differences in skin temperatures based on gender. This emphasizes the need for artificial intelligence-based heating e-textiles to accommodate diverse user needs. The study’s findings are expected to contribute to intelligent temperature regulation in thermal textiles and wearables, benefitting both the industry and consumers through customized heating products.
Lee et al. (Wed,) studied this question.