Author:
Samuel Toepke
Affiliation:
Private Engineering Firm, United States
Keyword(s):
Population Estimation, Structure Occupancy Curve, Gis, Social Media, Geofencing, Enterprise Architecture, Volunteered Geographic Data.
Related
Ontology
Subjects/Areas/Topics:
Applications
;
Pattern Recognition
;
Web Applications
Abstract:
Human-use statistics of an occupied building are critical for resource consumption planning,
emergency/crisis response, and long-term community design. Without an active access-control policy, it is
difficult to get an accurate measure of the spatiotemporal occupancy of a building during use hours. This
research presents a novel method of estimating building use patterns, based on freely available and
volunteered data from social media. Modern social media services such as Twitter and Instagram give users
the ability to create geospatially enabled posts, submitted using pervasive computing devices. By applying
geofencing to the pertinent social media data, an aggregate estimate of 24-hour use can be generated for a
structure. Using geospatial data from the aforementioned social media services, steps for gaining the
aggregate building occupation estimations are delineated, several high-traffic buildings are selected as use
cases, and results/follow-on work are discussed.