Thermal occupancy sensors detect the presence, motion, and activity of people by sensing heat signatures rather than capturing visual images. When combined with real-time analytics and alerting, these sensors can identify behaviors that often precede falls — such as nighttime wandering, unassisted transfers, and prolonged dwelling in high-risk zones — and notify caregivers to intervene.
Key benefits
- Non-visual, privacy-preserving sensing
- Continuous, real-time monitoring
- Actionable alerts and aggregated analytics
- Low-burden deployment in occupied spaces
Thermal sensors use infrared detection to sense differences in heat. They typically operate at a resolution sufficient to track human-sized heat signatures and movement vectors but without forming identifiable visual images.
Core components
- Heat-based sensors: Detect temperature contrasts and motion caused by people moving through a space.
- On-device or edge processing: Filters raw signals to identify presence, position, direction, and activity while minimizing data transmitted centrally.
- Real-time analytics and rules engine: Converts sensor outputs into alerts (for example, “patient left bed unassisted”) or aggregated metrics (for example, daily bathroom visits).
- Integration layer: Connects sensor outputs to nurse call systems, mobile notifications, or building management systems for automated responses.
Because the sensors do not capture video, they maintain a high level of privacy while still providing meaningful behavioral insights.