Design with Perfect Sense: the Adoption of Smart Sensor Technologies (SST) in Architectural Practice
Location
Grand Wailea, Hawaii
Event Website
https://hicss.hawaii.edu/
Start Date
8-1-2019 12:00 AM
End Date
11-1-2019 12:00 AM
Description
Recent development in the Internet of Things (IoT) has enabled real-time data-driven decision making in diverse industries. For example, over the last few years, the introduction of smart sensor technologies such as Watson IoT has led to various data-driven solutions in space planning, real-estate management, and energy conservation. Despite the recent development, these technologies are not widely used in architectural practice. In the wake of this trend, this research aims at understanding how architects and design professionals can be supported to further utilize smart sensor technologies in their practice. Based on the Technology-Organization-Environment framework and a series of interviews, the major influencing factors on user adoption were identified. This study contributes to both theory and practice by identifying six contributing factors, namely perceived risk and value, commitment to learn and collaborate, as well as knowledge and trust.
Design with Perfect Sense: the Adoption of Smart Sensor Technologies (SST) in Architectural Practice
Grand Wailea, Hawaii
Recent development in the Internet of Things (IoT) has enabled real-time data-driven decision making in diverse industries. For example, over the last few years, the introduction of smart sensor technologies such as Watson IoT has led to various data-driven solutions in space planning, real-estate management, and energy conservation. Despite the recent development, these technologies are not widely used in architectural practice. In the wake of this trend, this research aims at understanding how architects and design professionals can be supported to further utilize smart sensor technologies in their practice. Based on the Technology-Organization-Environment framework and a series of interviews, the major influencing factors on user adoption were identified. This study contributes to both theory and practice by identifying six contributing factors, namely perceived risk and value, commitment to learn and collaborate, as well as knowledge and trust.
https://aisel.aisnet.org/hicss-52/os/business_value_of_smart_devices/5