Implication of AI for integrated decision making in housing energy efficiency from outside: A conceptual platform.

Over the past several years, efforts have been made to use artificial intelligence (AI) in explaining what people are thinking, thus facilitating their decision-making. In a housing context, AI is employed to identify the housing heat loss from the external environment. Recent studies stress the lack of attention on exploring the interplay between the different aspects of housing energy efficiency. Occupants’ perceptions and attitudes are also identified as another gap in achieving the housing energy efficiency target baseline. Although there are many online databases which provide proper information in relation to housing energy efficiency, they are not able to explain the interplay between different aspects of this concept, and to link the information to different people’s perceptions and attitudes. In the context of the current study, we argue that AI is able to tell which building is suitable for responding to an occupant’s perceptions of housing energy efficiency from the outside. This paper develops a conceptual platform for this study, drawing on an extensive review of the literature. The literature was reviewed in two different stages. Firstly, an overall review collated evidence and rationale for supporting the main argument of the study. Then a number of previous studies which adopted different research methodologies were discussed to develop the methodological platform of the study. The conducted reviews show that AI is able to predict the interplay between the different aspects of housing energy efficiency and to explain occupants’ perceptions of housing energy efficiency from the outside, via developing a smart online photo-based database through a combination of secondary data related to different aspects of housing energy efficiency and primary data related to occupants’ perceptions of housing energy efficiency. This database is applicable in evaluating the energy efficiency of a house in relation to occupants’ needs, expectations, and preferences, and in providing a balanced interplay between the different aspects of housing energy efficiency.