PIR vs mmWave Occupancy Sensors 2026: How to Choose Camera-Free, Privacy-First Solutions

Which technology fits common use cases?

• Corridor lighting and basic vacancy-based lighting control — Best fit: PIR for low-cost, simple motion-triggered control.
• Open-plan offices, space utilization, desk-level occupancy — Best fit: Thermal or mmWave to detect stationary occupants; thermal is strong for anonymous heat-based counting, mmWave for richer motion details.
• Conference rooms and booking validation — Best fit: Thermal or mmWave to reliably detect stationary people and avoid false unoccupied states.
• Restrooms and sensitive areas where privacy is paramount — Best fit: PIR or thermal; PIR is simple, thermal provides better presence detection while maintaining anonymity.
• Retail footfall, queue measurement, flow analytics — Best fit: mmWave or thermal depending on granularity; mmWave for direction and range analytics, thermal for anonymous density and heatmaps.

Privacy-first considerations (must-haves)

• No optical imaging: Confirm sensors do not capture or reconstruct visual images or video.
• Data minimization: Sensors should output only the data needed, such as counts, presence, or anonymized heatmaps, not raw streams that can be repurposed.
• On-device/edge processing: Raw sensing data should be processed locally to produce anonymized outputs; raw data retention should be minimized or avoided.
• Aggregation & retention policies: Dashboards should show aggregated metrics and retention windows should be limited by policy.
• No PII linkage: System design should avoid linking occupancy events to IDs, badges, or video without explicit consent and safeguards.
• Security & compliance: Encryption in transit and at rest, secure firmware updates, and adherence to relevant privacy regulations or standards.
• Vendor transparency: Documented privacy architecture and clear data handling statements.
• Example: Thermal, camera-free sensing platforms provide anonymous heat patterns and are often preferred for privacy-first deployments.

Practical deployment tips

• Pilot first: Start with a representative pilot of 5–20 sensors to validate detection accuracy, false positives/negatives, and system integration.
• Map sensor coverage: Create coverage maps and place sensors to avoid occlusion, direct sunlight on PIR lenses, and HVAC vents that cause false triggers.
• Calibrate for environment: Test sensors at different ambient temperatures and during peak HVAC cycles to tune sensitivity and thresholds.
• Combine technologies where suitable: Use PIR for low-cost motion-trigger control and mmWave or thermal for rooms requiring stationary detection and analytics.
• Monitor and iterate: Deploy logging and monitoring to capture performance metrics; iterate placement and software settings.

Questions to ask vendors

• What exact outputs does the sensor provide (binary, count, heatmap, direction, range)?
• Does the system process raw sensor data on-device or in the cloud? What data is stored?
• How does the vendor ensure privacy and prevent image reconstruction?
• What are typical false positive and false negative rates for my environment?
• How does the solution integrate with BMS, HVAC, lighting, and analytics platforms?
• What are installation requirements and maintenance needs (power, calibration, firmware updates)?
• What security controls are in place (encryption, authentication, patching)?
• Can the system scale across multiple floors and sites centrally?

Evaluation checklist (pick-and-measure)

• Detection accuracy: Percentage correct occupancy detection vs. ground truth.
• Stationary detection capability: Can it detect still occupants reliably?
• Counting precision: Accuracy of people counts if required.
• Latency & update rate: How quickly the system reports changes.
• False alarm profile: Sources and frequency of false positives and negatives.
• Power & network footprint: Device power draw and bandwidth needs.
• Privacy safeguards: On-device processing, data minimization, and retention policies.
• Integration & API support: Ease of connecting to BMS, analytics, and workplace apps.
• Total cost of ownership: Device price, installation, maintenance, and cloud costs.
• Vendor support & road map: Ongoing updates, security patches, and product evolution.

Future trends to watch in 2026

• Hybrid sensor fusion: Combining PIR, thermal, mmWave, and CO2 for context-aware occupancy models.
• Edge AI advances: More processing at the sensor for privacy and lower bandwidth.
• Standards & certifications: Emerging privacy and interoperability standards for people-sensing devices.
• Regulatory scrutiny: Increasing expectations for demonstrable privacy protections and transparent data practices.
• Cost decline: mmWave and higher-fidelity thermal sensors will continue to become more affordable and common.

Recommendation summary

• Choose PIR when you need low-cost, low-power motion detection for straightforward control tasks like corridor and restroom lighting.
• Choose mmWave when you require higher-fidelity presence detection, counting, directionality, or performance in low-light and cluttered environments.
• Consider thermal camera-free solutions when stationary occupant detection and strong privacy guarantees are essential, especially for conference rooms, desks, and sensitive spaces.
• Always prioritize privacy-by-design: favor on-device processing, minimal data outputs, aggregation, and clear retention policies.
• Pilot before scaling and evaluate sensors against real-world metrics rather than vendor claims.

Privacy-first, camera-free sensing is now a practical, mature option for buildings seeking efficiency while protecting occupants. Selecting the right technology requires matching sensor capabilities to specific use cases, operational constraints, and privacy requirements, backed by pilot testing and vendor diligence.