Data Integrity in Structural Monitoring

What this topic covers

Protect completeness, traceability and meaning from sensor to engineering decision.

Core monitoring ideas

Data integrity includes correct identity, units, timestamps and configuration.

Manual edits and recalibration should be traceable.

Cybersecurity and quality controls should prevent silent changes from becoming structural conclusions.

Interpretation limits

Sampling and storage should match the phenomenon: slow settlement and rapid vibration need different strategies.

Evidence and data quality

Analytics should surface uncertainty, missing data and sensor faults rather than hide them inside a score.

Lifecycle use

AI, machine learning and digital twins support review; they do not replace structural engineering accountability.