Presentation by Garrett Millar, North Carolina State University

View slides from the presentation, and listen to an audio recording.

Talk Abstract: Mobile sensing technologies like smart watches are going mainstream. With improvements in quality, affordability, and ability, they provide a unique opportunity for spatial sciences. They particularly provide the opportunity to understand not only how people behave, but more importantly, how they experience their environment. By providing a human-centered approach for extracting contextual physiological information from mobile sensor data, geospatial analytics provides the capability to derive where, when, and in particular, how people’s behavior, experience, and health relate to their surrounding environment. Results are directly applicable in domains such as urban planning, environmental health, and epidemiology, wherein researchers can efficiently explore how human behavior varies as a function of location, space, and time. This talk will be delivered with an overall focus on People & the Environment. During which, various geo-analytical guidelines, techniques, and software tools, will be presented for empirically measuring people's environmental interaction and experience.

Speaker Bio: Garrett Millar is a User Experience Researcher and Geospatial Scientist. In 2016, he earned his Bachelor's Degree in Psychology at North Carolina State University. Carrying extensive domain knowledge in the Cognitive Sciences, particularly the experience and knowhow for collecting biometric data, Garrett transitioned to the field of Geospatial Science in 2017. Where now, as a third year PhD student at North Carolina State's Center for Geospatial Analytics, he develops and evaluates geospatial applications and visualizations. A particular focus of his research is placed on using mobile sensing technologies like smart watches to improve our understanding of how people experience their environment. Lastly, he and his 6-month old German Shepherd puppy, Cassius, really enjoy the outdoors.