Connected thermostats (CTs) often save less energy than predicted because consumers may not know how to use them and may not be engaged in saving energy. Additionally, several models perform contrary to consumers' expectations and are thus not used the way they are intended to. As a result, CTs save less energy and are underused in households. This paper reviews aspects of gamification and serious games focused on engaging consumers. A gamification and serious games framework is proposed for saving energy that is tailored by a fuzzy logic system to motivate connected thermostat consumers. This intelligent gamification framework can be used to customize the gamification and serious game strategy to each consumer so that fuzzy logic systems can be adapted according to the requirements of each consumer. The framework is designed to teach, engage, and motivate consumers while helping them save electrical energy when using their thermostats. It is described the proposed framework as well as a mockup that can be run on a cellphone. Although this framework is designed to be implemented in CTs, it can be translated to their energy devices in smart homes.
The users' behavior in a house impacts the amount of electrical energy consumption in the electrical products of the household; therefore, energy consumption can be optimized by using sense, smart and sustainable products (S 3 ) as Social Products (SPs) for saving energy in the housing. The SPs communicate between devices and consumers through game design elements known as gamification that can yield behavioral changes in users. Furthermore, behavioral models can shape human behavior to motivate the individual to achieve a specific target, like saving energy. For the energy consumption reduction in households, it is proposed a structure with SPs that uses a gamification Human Machine Interface in each device to communicate between products and consumer in a Smart Home (SH). In this descriptive paper, it is proposed a three-steps structure that applies to every social product. First, it requires the classification of the type of end-user, the behavior, and usability problems when the product is deployed. Then, through the analysis of fuzzy logic, either type 1 or type 2, it is proposed which housing gamification elements best tailors the interface for each appliance. Finally, the application sends stimulus to individuals to test their performance and motivation to use each social product. After every social product has its proper gamification, it is possible to have interconnected SPs to get a Gamified SH. Besides, this Gamified SH could communicate with other Gamified Smart Homes to obtain a Gamified community.
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