Abstract
Building space accounts for one of the largest operational costs for companies. While space management has traditionally been done based on human observations, technology solutions are increasingly been considered. In this paper, we consider advanced sensing systems that provide location data at a certain spatio-Temporal granularity. Location data analytics is then considered to realize two space management applications: (i) space utilization, and (ii) workspace recommendation. Towards this end, location data is processed to determine potential workspaces. The processed historic location data is used to compute defined metrics that characterize space utilization. Filtering of real-Time location data is presented to recommend workspaces that may be potentially unoccupied and present to a user. Using datasets from an experimental office testbed, we evaluate the proposed sensing and analytics solution.
Original language | English |
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Title of host publication | 2017 IEEE 13th World Congress on Services : SERVICES 2017 : 25-30 June 2017, Honolulu, Hawaii : Proceedings |
Editors | Rami Bahsoon, Zhixiong Chen |
Place of Publication | Piscataway |
Publisher | Institute of Electrical and Electronics Engineers |
Pages | 1-8 |
Number of pages | 8 |
ISBN (Electronic) | 9781538620021 |
DOIs | |
Publication status | Published - 13 Sept 2017 |
Externally published | Yes |
Event | 13th IEEE World Congress on Services (SERVICES 2017) - Honolulu, United States Duration: 25 Jun 2017 → 30 Jun 2017 Conference number: 13 http://www.wikicfp.com/cfp/servlet/event.showcfp?eventid=62419©ownerid=97262 |
Conference
Conference | 13th IEEE World Congress on Services (SERVICES 2017) |
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Abbreviated title | SERVICES 2017 |
Country/Territory | United States |
City | Honolulu |
Period | 25/06/17 → 30/06/17 |
Internet address |