Walk through most office buildings at 4 p.m. on a Friday and you will find the HVAC running at full capacity for floors that emptied at lunchtime. The BMS is doing exactly what its schedule tells it to do — and the schedule was written for an occupancy pattern that stopped existing years ago. That gap between assumed occupancy and actual occupancy is where IoT occupancy sensors earn their budget line, and it is also where most deployments quietly underperform because the wrong sensor type was specified for the wrong job.
This guide is written for teams who already know the elevator pitch. Instead, we will look at what actually separates a deployment that feeds reliable data into automation logic from one that produces dashboards nobody trusts after month three.
The term "occupancy sensor" covers two fundamentally different technologies, and conflating them is the most common specification error we see in tender documents.
If your use case is demand-controlled ventilation, capacity compliance, or space consolidation decisions, you need counting — not presence. A PIR sensor will report a floor as "occupied" whether one security guard or two hundred employees are present, and your air handling unit will respond identically to both situations.
Every vendor quotes an accuracy figure. Very few will put it in a contract. Insist on both a contractual floor and an honest explanation of what moves the number. As a benchmark: Vemco commits to a minimum of 96% counting accuracy contractually, with 98–99% typically achieved when conditions allow — good lighting, sensible sensor placement, and predictable visitor flow. Any vendor promising a flat 99% regardless of environment is telling you something about their sales process, not their sensors.
Two accuracy killers deserve specific attention during procurement:
A sensor that only feeds a dashboard pays back slowly. A sensor that feeds automation pays back on the next utility bill. The economics of IoT occupancy sensors change entirely once the data reaches your building systems in real time. This is why the middleware question matters more than the sensor brand: how does occupancy data reach your HVAC controls, your BMS, your security platform?
Platforms like Vemco's VemFusion exist precisely for this handoff — connecting live occupancy data to HVAC, BMS and security systems so that ventilation follows actual headcount rather than a timetable. In offices, universities and public buildings, this is where the waste from always-on systems gets cut: a lecture hall that ventilates for 200 people only when 200 people are actually in it, an office floor where the BMS steps down setpoints the moment the last person badges out through a counted exit.
During evaluation, ask vendors three specific integration questions:
Here is something rarely mentioned in vendor material: bidirectional counting sensors accumulate drift. If a sensor at a floor entrance is 98% accurate, the small residual error in "in" versus "out" counts compounds over a day, and by evening the system may believe three people remain on an empty floor. Mature deployments handle this with scheduled midnight resets, cross-validation between sensors, or reconciliation against access control events. Ask your vendor how they handle drift correction. If the answer is a blank look, keep shopping — this single detail separates integrators who have run occupancy systems in production from those who have only demoed them.
Automation is the fast payback; portfolio decisions are the big one. Twelve months of zone-level occupancy data, analysed through a space utilisation tool such as VemSpace, tells you which floors you can consolidate, which meeting room formats your organisation actually uses, and whether that lease renewal needs all six floors or four. These are seven-figure decisions, and they should not rest on badge swipes — which count arrivals, not presence — or on a facilities manager's walk-through impressions.
The teams getting the most from this data share one habit: they define the decisions they want to make before choosing sensor placement. Counting at building entrances answers headcount questions. Counting at floor and zone thresholds answers consolidation questions. Room-level sensing answers meeting-space questions. Each layer costs more, so map the sensor plan to the decisions, not the other way round.
Teams that skip the pilot phase almost always end up re-commissioning sensors later, at higher cost and with credibility already spent internally.
If you are specifying an occupancy sensing project — whether it is demand-controlled ventilation for a campus, capacity alerting for a public building, or utilisation data ahead of a lease decision — talk to a team that has commissioned these systems in production environments. Contact Vemco Group at vemcogroup.com/contact-us to discuss sensor selection, accuracy validation and BMS integration for your specific building.