Desk Utilisation Sensors: How to Choose and Deploy in 2026
Desk utilisation sensors measure how often individual desks in your office are actually used, not booked, not assigned, but physically occupied. For most organisations, the data is immediately confronting: average desk utilisation in hybrid offices runs at 40-60% on peak days and considerably lower across the working week. That gap between real estate cost and actual use is the business case for desk sensing, and for the desk ratio changes and space reductions that follow from it.
Quick verdict
For accuracy at desk level, under-desk PIR sensors (Disruptive Technologies, Spacewell) or desk-level capacitive/pressure sensors (Serraview, Robin) are more reliable than building-level WiFi or badge data. For privacy-safe counting with high accuracy, Density’s ToF sensors at desk cluster level are appropriate where individual desk granularity is not needed. Always collect at least 6 weeks of data before drawing conclusions, weekly variation is high and seasonal patterns affect results significantly.
Why desk utilisation data matters
Most organisations have paid for more desk space than they need post-hybrid-work transition. The challenge is that intuition, facilities manager estimates, and even badge data significantly overstate actual desk use. Under-desk sensor data tells you:
- The actual utilisation rate of each desk, zone, and floor
- Peak hours and peak days, which days actually require maximum capacity
- Which desk types (window desks, enclosed zones, collaborative areas) are most sought-after
- Whether your desk booking system data matches reality (it usually does not)
Armed with six months of desk sensor data, most facilities managers can justify reducing desk count by 15-30% through more accurate desk ratio setting, targeted hot-desking expansion, or lease renegotiation. The annual rental saving per desk reclaimed in a Tier 1 city typically pays for the entire sensor deployment many times over.
Sensing technologies for desk-level measurement
| Technology | Accuracy | Privacy | Install complexity | Battery life |
|---|---|---|---|---|
| Under-desk PIR | High | High (no image) | Low (peel-and-stick) | 1-3 years |
| Desk pad pressure sensor | Very high | Very high | Low (placed under keyboard) | 1-2 years |
| Time-of-Flight (ToF) overhead | High (zone level) | Very high | Medium (ceiling mount) | N/A (wired) |
| Camera + AI (overhead) | Very high | Medium | Medium | N/A (wired) |
| WiFi location proxy | Low | Low (tracks devices) | Low (software) | N/A |
| Badge tap-in | Low | Low (tracks individuals) | Low (existing infra) | N/A |
Disruptive Technologies under-desk sensors
Disruptive Technologies (DT) makes extremely compact wireless sensors, about the size of a large coin, with a proprietary low-power protocol and claimed 15-year battery life. Their Proximity sensor detects presence via capacitive sensing when placed under a desk surface; their Motion sensor uses passive infrared for the same purpose. Both connect to a Cloud Connector hub (one hub per ~200 sensors) via DT’s proprietary network. No WiFi or Zigbee infrastructure needed.
The 15-year battery claim is distinctive, at scale, sensor battery maintenance is a material operational cost. A deployment of 500 desk sensors with standard WiFi sensors would require 500+ battery replacements every 1-2 years. Check disruptive.io for current pricing.
Spacewell (formerly Vecos)
Spacewell is a workplace management platform that includes desk and room sensors as part of an integrated space management suite. Their sensors are PIR-based, under-desk mounted, and feed into the Spacewell analytics and desk booking platform. The value proposition is integration: sensor data, desk booking, space analytics, and facilities management reporting in a single platform. Check spacewell.io for current pricing.
Robin Powered desk sensors
Robin’s desk sensors integrate directly with the Robin booking platform to enable hot desk check-in confirmation and auto-release of unchecked-in bookings. If you are deploying Robin as your desk booking system, adding Robin sensors is the natural extension, the integration is pre-built and the data flows directly into Robin’s utilisation analytics. Check robinpowered.com for current sensor and platform pricing.
Using WiFi and badge data as a proxy (and its limitations)
Some organisations attempt to measure desk utilisation using WiFi client counts or badge-in data. Both are imprecise for desk-level analysis:
- WiFi data counts devices on the network, not people at desks, personal phones, tablets, IoT devices all inflate counts
- Badge data records building entry, not which floor or desk a person used
- Neither captures actual time at desk vs. time in meeting rooms or away from the office
WiFi and badge data are useful for building-level headcount estimates and peak day identification, they are not substitutes for desk-level sensor data when you need to make real estate decisions based on granular utilisation evidence.
Deployment and data collection approach
- Install sensors across all zones simultaneously, comparing zones only works if all are measured in the same period
- Run for a minimum of 6 weeks before analysis, exclude the first 2 weeks as staff awareness of monitoring affects behaviour temporarily
- Segment by zone, not just total, floor, neighbourhood, desk type, and day-of-week breakdowns reveal the usage patterns that drive real decisions
- Cross-reference with booking data, the gap between booking data and sensor data reveals ghost booking and utilisation friction
- Present data before making changes, sharing utilisation data with department heads before any space change builds trust and reduces resistance
Related: desk booking software guide and occupancy sensor comparison.