Long Term Energy Savings Through User Behavior Modeling in Smart Homes

The Internet of Things (IoT) has enabled real-time monitoring of energy consumption in smart homes through sensors embedded in the surrounding environment. In the post-pandemic world, domestic energy management has gained importance due to increased work-from-home consumption, making data collection in a smart home a relevant IoT application with many potential energy savings. However, this information is difficult for most users to understand, and existing monitoring systems' savings results degrade over time. To address these challenges, this study presents a novel approach for domestic energy consumption, production, and comfort perception using color-based dashboards enhanced for user feedback interaction. The approach includes the management of in-home appliances and comfort levels according to user preferences to attain long-term energy savings. The approach includes multiple appealing strategies such as 3D representation, mobile connectivity, utility integration, and dynamic information, to increase long-term engagement and provides quantitative data on energy savings achieved for one year, where the average energy consumption was reduced by 19%. It was found that the approach sustained user engagement over time, with users actively participating in energy conservation efforts. A community survey with 208 participants was also developed and studied where 69% of the enquired considered our approach more attractive than existing market solutions, and 79% considered it more useful than existing solutions. Regarding the real-time information presented on our approach, 81% of the participants strongly or totally agree that it can change users' behaviors.

Automated summary

The Internet of Things (IoT) allows real-time monitoring of energy consumption in smart homes using embedded sensors. This study proposes an innovative approach using color-based dashboards to enhance user interaction and achieve long-term energy savings. The approach includes management of appliances and comfort levels based on user preferences. Multiple strategies such as 3D representation and mobile connectivity are implemented to increase user engagement. The approach achieved an average energy consumption reduction of 19% and sustained user engagement over time, with participants considering it more attractive and useful than existing solutions based on a community survey.