Workplace Occupancy Sensor Hardware: CRE Buyer's Guide

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Introduction

Occupancy sensors are hardware devices that detect the presence, movement, or count of people in a space. Facilities managers in commercial real estate (CRE) use these sensors to optimize energy use, improve space utilization, and support workplace safety and cleaning strategies. This guide explains hardware choices, evaluation criteria, deployment considerations, and a procurement checklist to help you buy the right sensor solution for your buildings.

Why occupancy sensors matter for CRE

Reduce HVAC and lighting costs by enabling demand-driven control.
Provide real-time and historical space-utilization data for planning.
Improve cleaning and maintenance workflows with targeted effort.
Support compliance and safety functions (e.g., emergency egress counts).

Decisions about sensor hardware affect data quality, integration costs, and privacy risk, so choosing carefully up front reduces rework and increases ROI.

Common sensor types

Passive Infrared (PIR): Detects motion via changes in infrared energy. Best for detecting movement in enclosed spaces; low power and cost. PIR struggles with static occupants.
Ultrasonic: Emits sound waves and detects reflections. Good for detecting small movements and presence in cubicles, but can be sensitive to acoustic noise and airflow.
Microwave Doppler: Emits microwave signals and measures frequency shift from movement. Can penetrate certain materials and cover larger volumes, but may be triggered by non-human motion.
Dual- or multi-mode sensors: Combine technologies (e.g., PIR + ultrasonic) to reduce false positives/negatives by cross-validating detections.
Thermal imaging sensors: Measure heat signatures to detect people and patterns. Higher accuracy for counting and presence while being less sensitive to lighting. Typically more expensive.
Camera-based (vision) sensors: Use image processing to count and classify occupants. Provide rich data but raise privacy concerns and higher bandwidth and processing needs. Edge processing can mitigate raw-image storage.
CO2 sensors: Measure carbon dioxide concentration as an indirect proxy for occupancy in ventilated spaces. Useful for ventilation control but less precise for instant counts.

Key specifications to evaluate

Coverage area and detection pattern: Specify floor area and mounting height the sensor supports and ensure the detection footprint matches the space geometry.
Detection type: Presence (binary), motion, directional movement, or headcount accuracy; match to your use case.
Accuracy and error rates: Seek datasheets or test results stating false positive/negative rates or counting accuracy under typical conditions.
Latency and sampling rate: Faster sampling gives real-time responsiveness for control; slower sampling conserves power.
Power options: PoE, low-voltage DC, mains, or battery; consider maintenance and wiring impacts.
Connectivity and protocols: Support for BACnet, Modbus, MQTT, REST APIs, or proprietary protocols to ensure BMS and analytics compatibility.
Mounting options: Ceiling, wall, recessed, or pendant; ceiling-mounted devices often give best coverage for open spaces.
Environmental rating: Operating temperature range and IP rating for exposed deployments.
Security features: Firmware signing, encryption (TLS), secure boot, and credential management.
Certifications: CE, UL, FCC, and any region-specific safety or wireless certifications.

Integration and data management

Integration targets: BMS for HVAC and lighting control, IWMS/CAFM for space planning, workplace apps for desk booking, and analytics platforms for long-term insight.
Data formats: Confirm available telemetry such as occupancy events, counts, and dwell time and whether sensors push data or require polling.
Edge vs cloud processing: Edge processing reduces bandwidth and privacy exposure by sending aggregated results; cloud processing enables richer analytics but raises transmission and storage concerns.
APIs and developer support: Robust APIs and clear documentation reduce integration time—request API examples, rate limits, and SDKs from vendors.

Deployment considerations per space type

Open-plan offices: Ceiling-mounted thermal or dual-mode sensors provide robust coverage and better counting than PIR.
Private offices and meeting rooms: Door-mounted counters or ceiling sensors with smaller coverage zones work well; room scheduling needs reliable binary occupancy detection.
Conference rooms: Counting accuracy matters for compliance and utilization; consider thermal imaging or camera-based sensors with anonymized counts.
Corridors and stairwells: Motion-triggered lighting often uses PIR or microwave; account for false triggers from cleaning carts.
Restrooms and locker rooms: Use non-imaging detectors (PIR, ultrasonic) rather than cameras for privacy-sensitive areas.
Parking and large volume spaces: Radar, microwave, or thermal arrays can detect vehicles and human presence in varying conditions.

Privacy, compliance, and ethics

Anonymization: Prefer sensors that output counts or anonymized presence signals rather than raw images or identifiable data.
Legal compliance: Check local laws (e.g., GDPR-type regulations) for biometric data and workplace monitoring and obtain legal counsel for camera-based solutions.
Transparency: Inform occupants about sensor types, purpose, and data retention through visible signage and privacy notices.
Data minimization: Collect only data necessary for the use case and retain it only as long as needed.

Procurement checklist for buyers

Define clear use cases and KPIs (energy savings %, utilization rates, etc.).
Document technical requirements: coverage, accuracy, mounting, power, and environmental constraints.
Specify integration needs: supported protocols, APIs, and BMS compatibility.
Set security requirements: encryption, firmware updates, and device lifecycle management.
State privacy constraints: imaging allowed, retention policies, and on-device anonymization.
Require POC options: ability to trial sensors in representative spaces.
Calculate total cost of ownership: hardware, installation, connectivity, licensing, cloud fees, and maintenance.
Define support and warranty terms: SLAs, replacement policies, and firmware update cadence.
Assess scalability and vendor roadmap for additional floors and sites.

Maintenance, testing, and commissioning

Commissioning: Test sensor coverage and false-trigger behavior during different occupancy conditions and times of day.
Firmware and lifecycle updates: Establish a process for secure firmware updates and patch management.
Routine calibration and battery replacement: Schedule checks for battery-powered devices and recalibrate if environmental changes occur.
Monitoring: Use device health telemetry to flag failures, tampering, or degraded performance.

Measuring ROI and KPIs

Energy savings: Track reductions in kWh and HVAC runtime after sensor-driven controls.
Space utilization: Monitor peak vs average occupancy, desk utilization percentage, and meeting room no-show rates.
Maintenance efficiency: Measure reductions in unnecessary cleaning cycles or reactive maintenance tasks.
Employee experience: Track booking satisfaction and perceived workspace availability.
Payback period: Calculate TCO versus annual savings to determine expected payback.

Vendor evaluation tips

Request references and site examples similar to your building types.
Run a pilot: limited deployment in representative spaces to validate performance and integration.
Evaluate long-term relationships: ensure vendors support firmware updates, security patches, and scaling.
Compare licensing models: perpetual hardware costs versus recurring cloud or analytics fees.
Check interoperability: favor vendors that support open standards like BACnet and MQTT for future flexibility.

Resources and next steps

Start by mapping your building types and defining primary use cases (control vs analytics). Run a small proof-of-concept with representative sensors and measure data quality against your KPIs before a full rollout. Consult vendor collateral and industry campaign materials for case studies and comparative data during evaluation.

Conclusion

Choosing occupancy sensor hardware for CRE requires matching technology to the use case, planning integration with existing systems, and addressing privacy and maintenance. Use pilots to validate real-world performance, prioritize secure and standards-based products, and calculate TCO against measurable KPIs. With thoughtful procurement and deployment, occupancy sensors deliver operational savings and actionable insights that improve building performance and occupant experience.

Workplace Occupancy Sensor Hardware: CRE Buyer's Guide for Facilities Managers