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Building occupants are continuously exposed to multiple indoor environmental stimuli, including thermal, visual, acoustic, and air quality related factors. Moreover, personal and contextual aspects can be regarded as additional domains influencing occupants' perception and behaviour. The scientific literature in this area typically deals with these multiple stimuli in isolation. In contrast to single-domain research, multi-domain research analyses at least two different domains, for example, visual and thermal. The relatively few literature reviews that have considered multi-domain approaches to indoor-environmental perception and behaviour covered only a few dozen articles each. The present contribution addresses this paucity by reviewing 219 scientific papers on interactions and cross-domain effects that influence occupants' indoor environmental perception and behaviour. The objective of the present review is to highlight motivational backgrounds, key methodologies, and major findings of multi-domain investigations of human perception and behaviour in indoor environments. The in-depth review of these papers provides not only an overview of the state of the art, but also contributes to the identification of existing knowledge gaps in this area and the corresponding need for future research. In particular, many studies use "convenience" variables and samples, there is often a lack of theoretical foundation to studies, and there is little research linking perception to action.

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Naturally ventilated offices enable users to control their environment through the opening of windows.Whilst this level of control is welcomed by users it creates risk in terms of energy performance, especially during the heating season. In older office buildings, facilities managers usually obtain energy information at the building level. They are often unaware or unable to respond to non-ideal facade interaction by users often as a result of poor environmental control provision. In the summer months, this may mean poor use of free cooling opportunities, whereas in the winter, space heating may be wasteful. This paper describes a low cost, camera based system to automatically diagnose the status of each window (open or closed) in a facade.The system is shown to achieve a window status prediction accuracy level of 90%-97% across both winter and summer test periods in a case study building. A number of limitations are discussed including winter daylight hours, impact of rain and the use of fixed camera locations and how these may be addressed.Options to use this window opening information to engage with office users are explored.

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