Structure Occupancy Curve Generation using Geospatially Enabled Social Media Data

Samuel Toepke

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.

References

  1. Aubrecht, Christoph, Joachim Ungar, and Sergio Freire, 2011. "Exploring the potential of volunteered geographic information for modeling spatio-temporal characteristics of urban population: a case study for Lisbon Metro using foursquare check-in data." International Conference Virtual City and Territory (7è: 2011: Lisboa) (pp. 57-60).
  2. Batista e Silva, Poelman, Martens, Lavalle, 2013. Population Estimation for the Urban Atlas Polygons. Rep. no. EUR 26437 EN. Ispra: European Commission, Joint Research Center, Italy. Print. ISBN 978-92-79-35089-4.
  3. Bhaduri, Budhendra, et al, 2007. "LandScan USA: a highresolution geospatial and temporal modeling approach for population distribution and dynamics." GeoJournal 69.1-2 (pp. 103-117).
  4. Convention Center | San Jose - Innovation Starts Here | Team San Jose., 2015. Convention Center | San Jose - Innovation Starts Here | Team San Jose. [ONLINE] Available at: http://www.sanjose.org/plan-a-meetingevent/venues/convention-center. [Accessed 19 September 2015].
  5. Dong, B. and Andrews, B., 2009, July. Sensor-based occupancy behavioral pattern recognition for energy and comfort management in intelligent buildings. In Proceedings of building simulation (pp. 1444-1451).
  6. EPSG:3857 - OpenStreetMap Wiki, 2015. EPSG:3857 - OpenStreetMap Wiki. [ONLINE] Available at: http://wiki.openstreetmap.org/wiki/EPSG:3857. [Accessed 19 September 2015].
  7. Event Center Arena - Wikipedia, the free encyclopedia, 2015. Event Center Arena - Wikipedia, the free encyclopedia. [ONLINE] Available at: https://en.wikipedia.org/wiki/Event_Center_Arena. [Accessed 19 September 2015].
  8. Freire, S., Florczyk, A. and Ferri, S., 2015. Modeling dayand nighttime population exposure at high resolution: Application to volcanic risk assessment in campi flegrei. 12th International Conference on Information Systems for Crisis Response and Management.
  9. Fuchs, G., Andrienko, N., Andrienko, G., Bothe, S. and Stange, H., 2013, November. Tracing the German centennial flood in the stream of tweets: first lessons learned. Proceedings of the second ACM SIGSPATIAL international workshop on crowdsourced and volunteered geographic information (pp. 31-38).
  10. GNIP Representative, 23 Jul. 2015. “Re: Twitter Data Discussion.” Message to the author. E-mail.
  11. GNIP - The World's Largest and Most Trusted Provider of Social Data, 2015. The Source for Social Data. [Accessed 17 October 2015].
  12. Google App Engine: Platform as a Service - App Engine - Google Cloud Platform, 2015. Google App Engine: Platform as a Service - App Engine - Google Cloud Platform. [ONLINE] Available at: https://cloud.google.com/appengine/docs. [Accessed 19 September 2015].
  13. Grimes, John G, 2008. "Global Positioning System Standard Positioning Service Performance Standard." GPS Navster, Department of Defense.
  14. Kuan, Joe, 2015. Learning Highcharts 4. Packt Publishing Ltd. [Accessed 19 September 2015].
  15. Kubanek, J., Nolte, E.M., Taubenböck, H., Wenzel, F. and Kappas, M., 2014. Capacities of remote sensing for population estimation in urban areas. In Earthquake Hazard Impact and Urban Planning (pp. 45-66).
  16. La Victoria Taqueria - 405 Photos - Mexican - Downtown - San Jose, CA - Reviews - Menu - Yelp, 2015. La Victoria Taqueria - 405 Photos - Mexican - Downtown - San Jose, CA - Reviews - Menu - Yelp. [ONLINE] Available at: http://www.yelp.com/biz/la-victoriataqueria-san-jose-2. [Accessed 19 September 2015].
  17. Laituri, Melinda, and Kris Kodrich, 2008. "On line disaster response community: People as sensors of high magnitude disasters using internet GIS." Sensors 8.5 (pp. 3037-3055).
  18. Martin, D., Cockings, S. and Harfoot, A., 2013. “Development of a geographical framework for census workplace data.” Journal of the Royal Statistical Society: Series A (Statistics in Society), 176(2) (pp. 585-602).
  19. Martin, D., Cockings, S. and Leung, S., 2015. Developing a flexible framework for spatiotemporal population modeling. Annals of the Association of American Geographers, 105(4) (pp. 754-772).
  20. Mennis, Jeremy, and Torrin Hultgren, 2006. "Intelligent dasymetric mapping and its application to areal interpolation." Cartography and Geographic Information Science 33.3 (pp. 179-194).
  21. Namiot, Dmitry, and Manfred Sneps-Sneppe, 2013. "Geofence and network proximity." Internet of Things, Smart Spaces, and Next Generation Networking. Springer Berlin Heidelberg (pp. 117-127).
  22. Oracle Technology Network for Java Developers | Oracle Technology Network | Oracle, 2015. Oracle Technology Network for Java Developers | Oracle Technology Network | Oracle . [ONLINE] Available at: http://www.oracle.com/technetwork/java/index.html. [Accessed 19 September 2015].
  23. Popular times - Google My Business Help, 2015. Popular times - Google My Business Help. [ONLINE] Available at: https://support.google.com/business/answer/6263531? hl=en. [Accessed 19 September 2015].
  24. Richardson, Ian, Murray Thomson, and David Infield, 2008. "A high-resolution domestic building occupancy model for energy demand simulations." Energy and buildings 40.8 (pp. 1560-1566).
  25. Rose, Amy N., and Eddie A. Bright, 2014. The LandScan Global Population Distribution Project: Current State of the Art and Prospective Innovation. Oak Ridge National Laboratory (ORNL).
  26. Sims, Weber, Bhaduri, Thakur, and Resseguie, 2015. "Application of Social Media Data to High Resolution Mapping of a Special Event Population." Proc. 13th Int. Conf. GeoComp (pp. 159-164).
  27. Smith, Aaron, 2015. US Smartphone Use in 2015. Pew Research Center.
  28. South Hall | San Jose - Innovation Starts Here | Team San Jose, 2015. South Hall | San Jose - Innovation Starts Here | Team San Jose. [ONLINE] Available at: http://www.sanjose.org/plan-a-meetingevent/venues/south-hall. [Accessed 19 September 2015].
  29. The Tech Museum of Innovation - Wikipedia, the free encyclopedia, 2015. The Tech Museum of Innovation - Wikipedia, the free encyclopedia. [ONLINE] Available at: https://en.wikipedia.org/wiki/The_Tech_Museum_of_ Innovation. [Accessed 19 September 2015].
  30. Toepke, Samuel Lee, and R. Scott Starsman, 2015. "Population Distribution Estimation of an Urban Area Using Crowd Sourced Data for Disaster Response." 12th International Conference on Information Systems for Crisis Response and Management.
Download


Paper Citation


in Harvard Style

Toepke S. (2016). Structure Occupancy Curve Generation using Geospatially Enabled Social Media Data . In Proceedings of the 2nd International Conference on Geographical Information Systems Theory, Applications and Management - Volume 1: GISTAM, ISBN 978-989-758-188-5, pages 32-38. DOI: 10.5220/0005822800320038


in Bibtex Style

@conference{gistam16,
author={Samuel Toepke},
title={Structure Occupancy Curve Generation using Geospatially Enabled Social Media Data},
booktitle={Proceedings of the 2nd International Conference on Geographical Information Systems Theory, Applications and Management - Volume 1: GISTAM,},
year={2016},
pages={32-38},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005822800320038},
isbn={978-989-758-188-5},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 2nd International Conference on Geographical Information Systems Theory, Applications and Management - Volume 1: GISTAM,
TI - Structure Occupancy Curve Generation using Geospatially Enabled Social Media Data
SN - 978-989-758-188-5
AU - Toepke S.
PY - 2016
SP - 32
EP - 38
DO - 10.5220/0005822800320038