Sponsor: The Design School
Team: Nina Sharp (PI), Giorgia Chiazzo (Co-PI), Zeel Raju Prajapati (RA)
This study aims to examine the use of IPA to control lighting and thermal conditions at home by collecting and analyzing online customer reviews of the top five best-selling Alexa devices posted online. The reviews were analyzed considering their star rating and the corpus of the text. To understand users’ sensations and experiences in interactions with IPAs for environmental controls, we employed text-mining tools such as sentiment analysis and topic modeling. We only included reviews that contained keywords related to the two target categories: (1) smart lights and (2) smart thermostats.
The findings of this study provide insights that help with analyzing users’ perceptions, experiences, sentiments, and needs in controlling their lighting and the thermal environment through IPAs; this could be used in the future adaptation of IPAs and smart home devices by designers and manufacturers.
Shishegar, N., Chinazzo, G., and Prajapati, Z. (under review). The use of intelligent personal assistants for controlling indoor environment at homes: A text-mining analysis. Journal of Building Engineering.
Chinazzo, G., Shishegar, N., Wu, D., and Webbeking, B. (under review). Employing user-generated content (UGC) to advance smart buildings, BuildSys.