Living preference modeling of smart homes for different target groups

The smart home concept has been around for more than 30 years. It is nevertheless fair to say that it has not taken off commercially on a wider basis so far, in spite of many optimistic forecasts over the years. One of the main reasons for this, aiming to be addressed in this paper, is that the smart home developments still have not properly matched with the needs and preferences of people in real life. In this paper, we investigate how smart homes will be used in daily life of different target groups. Accordingly, a virtual experiment is applied in which nearly 254 respondents are involved. Through multiple tasks, respondents explore a 3D interactive simulated smart home and report their one day living in it for a weekday and a weekend. A Bayesian Belief Network (BBN) is used to estimate and formulate the relationships of the variables that directly and indirectly influence users' living preferences. Modeled estimations are given for the living preferences of 5 target groups ranging from an individual, who has a free lifestyle and low workload to a dual income family, who has a busy lifestyle and high workload at home. Finally, conclusions are accomplished by analyzing variations of the estimated living preferences among these 5 target groups.