Know when Virtual Sensors are valid – and fail safely when they aren’t

Integrity Monitoring ensures that Virtual Sensor outputs remain valid, safe, and trustworthy throughout real‑world operation. It continuously assesses model behavior, input conditions, and output confidence — at the edge or in the cloud.

What it does

01

Model Drift Detection

Detects when model behavior deviates from validated conditions over time.

02

Plausibility Checks

Ensures outputs remain physically and system‑wise plausible.

03

Confidence Scoring

Quantifies how reliable each Virtual Sensor output is at runtime.

04

Anomaly Detection

Identifies abnormal patterns in inputs or outputs early.

05

Safe Fallback Behavior

Enables controlled degradation or fallback when validity limits are exceeded.

06

Diagnostic & DTC Integration

Exposes integrity issues via diagnostic events or trouble codes, enabling clear signaling to existing validation, service, and operations workflows.

DESIGNED FOR SAFETY, VALIDATION
& OPERATION TEAMS

Safety & Reliability Engineers

Ensure Virtual Sensor outputs remain valid under all operating conditions and support safety-relevant system behavior.

Validation & Verification Teams

Monitor model validity across scenarios, updates, and long-term operation — beyond offline testing.

Operations & Platform Teams

Operate Virtual Sensors at scale with transparency, governance, diagnostics, and controlled behavior in the field.

Want to trust Virtual Sensor Outputs
in real-world operation?

Get in Touch