abstract
- © 2021, Springer Nature Switzerland AG.Residential energy efficiency decreases electricity consumption and saves energy worldwide. Moreover, 86% of the residential buildings use thermostats that control the Heating, Ventilation, and Air-Conditioning (HVAC) system. The energy consumption can decrease from 11% to 18% due to user behavior modifications accompanied by strategies such as feedback and gamification. Social products use gamification features to interact with the end-user and other devices. However, tailored gamified Human-Machine Interfaces (HMI) must consider five personality traits. As a result, implementing Artificial Neural Networks (ANN) within the HMIs can classify the type of user and deploy a tailored strategy to save energy and promote behavioral changes. Thus, this paper shows a three-step framework to develop a rapid prototype using Arduino and MATLAB/Simulink to predict which type of gamified interface is needed depending on the personality traits.