The Role of Behavioural Engineering in the Design of Smart Home Systems
Year by year, the impact of climate change on everyday life is becoming more palpable. Immediate action is required now to slow down and, if possible, reverse the process. Whether consciously or unconsciously, activities at the individual level also contribute to climate change. In particular, a large proportion of CO₂ emissions in Germany derivesfrom the heating of households. To some extent, this problem is being addressed by enforced standards for the construction of new energy-efficient residential buildings, both at EU and individual country level. At the moment, however, the share of such buildings in Germany is less than 50 %, and it is old residential buildings that account for the majority of CO₂ emissions, in particular in a city such as Hamburg. The energy efficiency of residential buildings is significantly affected not only by technological but also by behavioral factors. Specifically, the habit of northern European and Scandinavian households of frequent and prolonged ventilation during the cold season significantly increases energy consumption in households. This, in turn, occurs not only in old buildings but equally in new residential buildings equipped with integrated smart ventilation and heating systems, which often do not require manual ventilation. This raises a number of questions about the role of behavioral system design in the context of smart home systems. One concept that deals with the behavioral influence of interactions with digital systems is "digital nudging" or "behavioral engineering". Through deliberate digital interface design choices, digital nudging seeksto change people’s behavior in a directed way, without punishing
deviations from the desired (e.g., “green”) behavior [6]. In our research project, we develop an easy-to-implement digital nudging solution to the context of energy-efficient ventilation for old residential buildings. Further, we aim at comparing its efficiency with fully automated smart home systems as an alternative technological solution for ventilation. In order to compare both approaches, we plan to develop two versions of the solution, a fully automated smart window module solution and a “push” recommendation system for digital nudging that requires people to manually operate windows. The specific research question we want to explore is as follows: "How does digital nudging for optimized ventilation affect energy efficiency in comparison with fully-automated smart home ventilation?". To test this, we 2 plan to conduct a scientific experiment during the wintertime that compares the two approaches of smart home automation and digital nudging and sets it in relation to an untreated baseline group.
Forschungsgruppe
Phillip Rath
Alexander Malyshev
Mentor
Prof. Dr. Jan Recker