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Non-intrusive sensing refers to technologies that detect presence, movement, or environmental conditions without capturing or exposing personally identifiable information (PII).
What is non-intrusive sensing?
- Thermal sensing: Detects heat signatures rather than visual images, producing anonymized occupancy signals.
- Camera-free: Uses sensors that do not create photographic or video imagery.
- Spatial intelligence: Insight about how spaces are used — occupancy counts, dwell times, and movement flows — aggregated and analyzed for decision-making.
- Edge processing: Local data processing at or near the sensor to reduce raw data transfer and protect privacy.
Benefits include privacy preservation, lower regulatory risk, reduced employee concern, and reliable occupancy data for operations.
Many workplaces want to be smarter—saving energy, optimizing space, and improving safety—while maintaining ethical standards.
Why ethical workplaces need non-intrusive sensing
- Protecting privacy: Avoiding cameras and personally identifiable data reduces surveillance concerns.
- Building trust: Transparent, privacy-forward systems reinforce employee confidence.
- Meeting compliance: Minimizing PII simplifies adherence to privacy laws and internal policies.
- Enabling better decisions: Accurate, anonymized metrics let facilities teams optimize space and costs without compromising people.
Non-intrusive sensing supports the balance between operational goals and people-centered ethics.
Butlr offers a thermal, camera-free sensing platform designed for privacy and spatial insights.
How Butlr’s platform delivers privacy-first people sensing
- Camera-free thermal sensors detect heat patterns, not faces or images.
- Anonymized outputs provide counts and movement data, not identities.
- Edge and cloud processing options minimize data exposure and permit local aggregation.
- Integrations with building management systems, analytics dashboards, and workplace apps enable operational workflows.
These features collectively make it possible to gain useful metrics while ensuring that individuals remain anonymous.