| Summary: | Many efforts have been made to create scenarios whereby interconnecting IoT can be used. The primary objective of these efforts has been to centralize its access as a single list and to monitor its use and trigger its different functionalities from apps. However, few efforts have addressed the problem of electricity consumption from those devices in the context of a residence. Existing datasets for machine predictive systems are focused on data analytics for global consumption but neglect the use of such solutions by the common citizen as a means of re-educating our citizens and optimizing electricity consumption. Without considering the environmental impact and the urgent need to address this growing global emergency, ordinary citizens require systems that help them be aware of what they consume and thus aspire to make a change. In this work, we propose a methodology that builds on the formal mathematical modeling and development of a simulator to substitute the need to collect real data from real world context of use, as well as an interactive system that integrates the whole process. By adding this module to the architecture our prior work, this work is ready for use in real-life scenarios where electrical consumption could be significantly reduced.
|
|---|