Why choose non-camera sensors in 2026?
Non-camera sensors deliver space utilization, HVAC optimization, and safety insights while reducing visual privacy concerns. Advances in sensor AI and clearer regulatory expectations in 2026 make these solutions practical for modern workplaces.
Benefits
- Preserve employee privacy by avoiding recognizable images.
- Provide reliable occupancy and flow data for energy savings and space planning.
- Reduce regulatory friction compared with camera-based surveillance (when deployed correctly).
- Support health, safety, and operational efficiency goals.
Regulatory landscape and obligations
Germany’s data protection and labor rules remain strict. Key legal frameworks and authorities should guide sensor deployments and privacy controls.
Key legal frameworks
- GDPR (General Data Protection Regulation): requires lawful basis, purpose limitation, data minimization, transparency, and data subject rights.
- BDSG (Federal Data Protection Act): national supplement to GDPR with specific German provisions.
- Works Constitution Act (Betriebsverfassungsgesetz): grants works councils co-determination rights concerning monitoring and technical systems affecting employees.
- Arbeitsrecht and Arbeitsschutzgesetz (Occupational Health & Safety): require safe workplaces and may justify certain monitoring for safety or regulatory compliance.
- EU AI Act (applicable rules by 2026): introduces requirements for AI systems depending on risk classification.
- Local supervisory authorities: each German state has a Data Protection Authority and the Federal Commissioner (BfDI) for federal bodies.
Practical implications
- Employee consent is often not a valid legal basis due to power imbalance; prefer legitimate interest or legal obligation and document assessments carefully.
- Works councils must be involved early for any monitoring that affects employees.
- Perform a Data Protection Impact Assessment (DPIA) when processing is likely to pose high risks.
Key terms (brief definitions)
DPIA
Data Protection Impact Assessment — a structured process to identify and mitigate privacy risks.
Pseudonymization
Processing data so it can no longer be attributed to a specific person without additional information.
Anonymization
Irreversible transformation so that individuals cannot be identified.
On-device processing
Analysis performed locally on the sensor device rather than sending raw data to a server.
Spatial intelligence
Insights about movement and occupancy patterns derived from sensors without identifying individuals.