people sensing for Smarter Buildings: Privacy-First Occupancy Analytics

People sensing drives measurable improvements across facilities. Representative use cases and observed impacts include:

• Energy optimization (HVAC & lighting): Use real-time room occupancy to zone HVAC and lighting, reducing runtime; deployments show energy reductions in conditioned spaces ranging from 10–30% when paired with controls and scheduling.
• Room and desk utilization: Identify underused meeting rooms and hot desks; realigning space can increase utilization by 15–40% and avoid expensive real estate leases.
• Workplace safety and emergency response: Real-time counts and location heatmaps improve evacuation accounting and incident response times.
• Operational planning: Data-driven janitorial, security, and maintenance scheduling reduces wasted labor and improves service quality.
• Retail and campus flow analytics: Measure peak footfall and dwell times to optimize layouts, signage, and staffing.

Example: A mid-size corporate campus using thermal people sensing reduced meeting room underutilization by 28% within three months by consolidating spaces and updating booking policies—while respecting employee privacy.

Use the following criteria and questions to evaluate vendors and projects; apply pilots and metrics to validate vendor claims before enterprise rollout.

Accuracy & granularity

• What is the detection accuracy under real-world conditions (furniture, partitions, multi-occupancy)?
• Can the solution count people, detect dwell time, and map flows at the room or sub-room level?

Privacy and compliance

• Does sensing require camera images or personally identifiable data?
• What data retention and anonymization policies are enforced?

Integration and openness

• Are there APIs, standard connectors (BACnet, MQTT), and dashboarding capabilities?
• Can insights be exported to CAFM, scheduling, or analytics platforms?

Deployment & operations

• How intrusive is installation, and what is the expected time-to-value?
• Does the system provide edge processing to reduce bandwidth and latency?

ROI and cost model

• What are the expected savings (energy, space, personnel) and payback period?
• Are sensors leased or bought, and what are recurring cloud analytics costs?

Scalability & maintenance

• How easily can additional zones be added?
• What is the expected maintenance cadence and lifetime?

A pragmatic deployment approach to validate people sensing and deliver ROI.

• Define objectives (3–5 measurable KPIs): energy reduction %, peak capacity, or utilization improvements.
• Select pilot zones (3–6 spaces): mix high-traffic, low-traffic, and sensitive spaces.
• Baseline measurement: collect pre-deployment usage and energy data for 2–4 weeks.
• Deploy sensors & configure analytics: prioritize privacy, low latency alerts, and integration points.
• Measure outcomes over 8–12 weeks: track KPI shifts and qualitative user feedback.
• Iterate and scale: refine rules, integrate with BMS, and roll out across the portfolio.

This staged approach minimizes disruption and ensures people sensing drives tangible operational changes.

Different sensing approaches offer distinct trade-offs; choose based on privacy, accuracy needs, and deployment context.

• Thermal, camera-free sensing (privacy-first): High privacy, reliable in varied lighting, good for counts and flow without identity.
• Camera-based computer vision: High spatial detail and behavior recognition, but raises major privacy and compliance challenges.
• Badge/fob systems: Useful for access logs but miss unauthenticated visitors and informal collaboration usage.
• CO₂/air-quality proxies: Low-cost and useful for trend detection but poor at precise, room-level counts and short-duration events.

Trade-offs: Camera systems often offer richer analytics but at the cost of trust and compliance complexity. Thermal people sensing balances accuracy, privacy, and deployability for most building applications.

Example calculation for a 50,000 ft² office with HVAC costs of $100,000/year and an 18% HVAC runtime reduction from targeted zoning and vacancy-driven controls.

• Annual HVAC saving: $100,000 × 0.18 = $18,000.
• Add lighting and operational savings (cleaning, staffing): $8,000/year.
• Total annual savings: $26,000.
• Sensor and deployment cost (one-time): $60,000.
• Payback: $60,000 / $26,000 ≈ 2.3 years.

When scaled across portfolios or combined with lease optimization, payback periods shorten significantly. Use accurate baselines and conservative estimates to avoid overpromising.

• Start with clear KPIs tied to business outcomes (energy, space, safety).
• Prioritize privacy in communications to employees and occupants—transparency builds trust.
• Integrate people sensing with BMS and scheduling systems to automate actions.
• Use pilots to tune analytics thresholds and validate accuracy in the specific environment.
• Monitor drift: recalibrate models when layouts or occupancy patterns change (renovations, new tenants).
• Combine data sources for richer insight—merge anonymous people sensing with scheduling and sensor telemetry (CO₂, power) for context.

Well-implemented people sensing delivers clear operational value: lower energy use, better space decisions, safer environments, and stronger occupant trust when privacy is prioritized. Use a structured evaluation framework, pilot rigorously, and favor solutions—like thermal, camera-free platforms—that balance accuracy with privacy. With the right data and integrations, people sensing becomes the backbone of smarter, more efficient buildings.