Structured surveys or interviews - on-line or off-line, in person or remote - are conventionally used to collect human comfort feedback for buildings. Though these approaches work in principle, they have a number of shortcomings:
- Subjectivity: There is sufficient evidence to suggest variance in subjective well-being responses based on individual differences in respondent’s personality, geographical background and culture.
- Response bias & heuristics: A number of factors such as lack of knowledge (respondents do not know the answer to a question, but answer it anyway), lack of motivation (respondents may not process questions fully) and failures in communication (survey questions may be unclear or misunderstood) are often associated with increased risk of biases and respondent heuristics in survey responses.
- Contextual cues: Subtle cues in the survey context influence how respondent answer questions - most studies are conducted outside of the respondent’s natural working environment which may have unintended consequences on the responses.
- Scalability: Its difficult to collect large sample data sets due to the administrative, financial and other operational overheads of these conventional approaches. This paper presents a unique framework for collection of human comfort feedback in smart built environments called the Learning Trail. The human-building interaction framework enables building visitors and occupants to provide environmental comfort feedback while learning more about a building.
Abstract submitted to CISBAT2019