Understanding how a workplace is truly used is the first step to planning for a modern, functional space that effectively meets mission needs. Occupancy Data has proven to be a vital tool for agencies to accurately evaluate space utilization and manage property accordingly. GSA is testing and piloting technologies for tracking daily occupancy data to identify the most effective, scalable methods of collecting and analyzing anonymized data for informing trends in how occupants are returning to the office, so that agencies can be empowered with reliable data for planning and developing spaces that are the ideal size and configuration for its mission and workforce.
Occupancy data collection technology
A description of the types of occupancy data collection technology that GSA is currently piloting are below, listed in order of relative degree of accuracy in measuring current occupancy rates.
Occupancy sensors are electronic devices that are able to detect motion and recognize when a person has entered a room. There are various occupancy sensing technologies, but the most common are passive infrared, microwave, ultrasonic, and video image processing.
Typically ceiling mounted, sensors provide real-time occupancy rates that can be connected to a building's Internet of Things (IoT) network. The data can be fed back to building management systems and booking systems that can automate lighting, HVAC, and ventilation control whilst also providing historic daily counts for occupancy analytics systems to understand desk usage, meeting room efficiency and space utilization.
Badge swipe data
This collection type relies on anonymized Personal Identity Verification card swipe data at building access points to count the number of unique credentials - isolating only the first credential use of the day for each cardholder to eliminate any impact from multiple entries to multiple spaces over the course of the day.
Badge swipe data can provide a historic daily count of the number of unique credential individuals in a space or building, daily building density based on square foot per person, and annual rent per person occupying the space.This collection type leverages existing infrastructure required for meeting OMB Memo M-19-17 [PDF] regarding building access.
Mobile location data
This collection type is a contractor-developed platform that uses anonymized cell phone data commercially licensed from data suppliers, combined with inputs from multiple sources (e.g., selected geofence, visit data, dwell time data, and census data) to generate occupancy estimates by day, week and month; peak occupancy estimates by hour of day; and estimated occupancy rates by day of week.
The goal of this collection type is to identify a commercially available mechanism to model estimated historic building utilization and occupancy rates that are cost efficient and scalable across a broader portfolio to identify relative building usage trends without installing devices, the manual collection of entry and exit, or collection of Personally Identifiable Information.