The "Alert" feature allows users to schedule automatic, regular, and retrospective data analyses on specific data segments. This functionality enables the establishment of alarm trigger criteria based on the results of these analyses.
Creating an alert relies on three main components:
- The frequency of the analysis,
- The data segment to be analyzed,
- The conditions for triggering an alarm.
For missing data alerts, the verification period is specified in the verification field on the left:
A daily alert performs the analysis every day, while a monthly alert executes an analysis monthly.
During a control phase, the alert processes the time series data (the data segment) from the associated sensors to determine whether an alarm should be triggered. The time series analyzed depends on several criteria :
Delay : You can choose to start the alert analysis from its creation or with a delay. The start and end of the analyses depend on the duration and delay. The rule to determine the end date of the analysis is: Execution Date - delay. From there, you can deduce the start date of the analysis using the duration (e.g., Start Date of Analysis = End Date - 24 hours for a daily alert).
Time Step : This determines the data completeness. For a sensor with a 10-minute time step, we expect 6 data points per hour, or 144 data points in 24 hours. If we receive 108 data points in a day, the completeness rate is 75%.
Threshold : This allows you to set the completeness rate that triggers an alarm. In the example above, a medium-criticality alarm is triggered for a completeness rate between 30% and 50%, and a high-criticality alarm is triggered for a rate below 30%.