abstract
- © Springer Nature Switzerland AG 2019.The correct and continuous use of s3 products at home can be beneficial for the environment and at the same time could generate cost savings on bills. An automated home where the user has no interaction may be the most efficient and eco-friendly option, but it is not always the most comfortable option for the user. On the other hand, if the user interacts with the system as he pleases, the system may be wasting energy, so a middle point must be found. If the system learns about the user¿s behavior and tries to shape it in order to make it eco-friendlier with the correct motivation, an engagement to this kind of behavior can be achieve. A first approach of the framework is presented, where a classification of the type of consumer is proposed depending on its personality to find his engagement on ecological behavior (EB). First, an artificial neural network is used to get the personality of the consumer. Then a Mamdani inference system is used with the result of the ANN to get an initial level of ecological behavior engagement.