Abstract
Connected thermostats control the HVAC in buildings by adjusting the setpoint temperatures without losing the comfort temperature. These devices consider end user profiles, preferences, and schedules to reduce electrical energy consumption. However, users are reluctant to use connected thermostats due to behavior and usability problems with the interfaces or the product. Typically, users do not use connected thermostats correctly, which can lead to increased rather than decreased electrical consumption. Thus, the S4 product concept is emerging as a strategy and framework to design functional prototypes to provide user-friendly sensing, smart, sustainable, and social features. An S4 product enables communication between products and between products and end users. Such communication can provide better understanding of the type of consumer who uses the product. Gamification and serious games are emerging as a strategy to shape human behavior to achieve goals; however, such strategies are not applied to product design. Fuzzy logic can be applied to human reasoning and has been used in intelligent systems based on if-then rules. Nevertheless, to the best of our knowledge, applying a gamification strategy based on fuzzy logic to develop an S4 connected thermostat has not been studied previously. Therefore, a framework that integrates gamification and serious games elements using fuzzy logic is proposed to develop a tailored gamification human machine interface. Thus, the proposed framework could tackle the behavior and usability problems of connected thermostats to teach, engage, and motivate end users to become energy aware, thereby reducing electrical consumption.
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Research Project supported by Tecnologico de Monterrey and UC Berkeley under the collaboration ITESM-CITRIS Smart thermostat, deep learning and gamification (https://citris-uc.org/2019-itesm-seed-funding/).
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Méndez, J.I., Ponce, P., Meier, A., Peffer, T., Mata, O., Molina, A. (2020). S4 Product Design Framework: A Gamification Strategy Based on Type 1 and 2 Fuzzy Logic. In: McDaniel, T., Berretti, S., Curcio, I., Basu, A. (eds) Smart Multimedia. ICSM 2019. Lecture Notes in Computer Science(), vol 12015. Springer, Cham. https://doi.org/10.1007/978-3-030-54407-2_43
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