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Automated Outlier Detection & Management

This functionality empowers Proqio users to identify, manage, and respond to abnormal or critical deviations in their monitoring data. It ensures cleaner datasets, reduces noise in monitoring outputs, and enhances the reliability of early warning systems.

Why is this functionality useful?

In large monitoring projects, sensor data can occasionally include sudden spikes, drops, or other anomalies caused by temporary interference, environmental conditions, or sensor drift. These outliers can obscure meaningful patterns and trigger unnecessary alerts.
With Automated Outlier Detection, Proqio helps you maintain high data integrity by automatically filtering and managing these anomalies in real time—so your graphs, dashboards, and alerts always reflect accurate conditions on the ground.

Feature Highlights

1. Automated Real-Time Outlier Detection

  • Intelligent Filtering: Proqio continuously scans incoming data inputs (e.g., displacement, temperature, pressure, chemical concentrations) and flags outliers in real time.

  • Customizable Setup: Users can define and adjust acceptable data ranges and outlier rules for each instrument type directly within its configuration settings.

  • Automatic Deletion (Clean Graphs): Any readings detected outside configured thresholds are automatically deleted, ensuring that your visualizations immediately reflect clean, reliable data. 

2. Comprehensive Logging and Visibility

  • Centralized Outlier Logs: Access a complete record of all automated outlier actions under Monitoring > Alerts, maintaining full transparency.

  • Map Alert Integration: Outlier events are visually represented in the Alert Panel on the map, offering instant, location-based context for abnormal readings.

3. Data Recovery and Audit Trail

  • Recovery Option: All deleted readings are securely stored and can be viewed or restored from the Logs section, ensuring that no data is permanently lost.

  • Audit Trail: Allows users to maintainin a verifiable record of every automatic deletion, enabling accountability and traceability for all outlier actions.

How does it work?

Step 1: Configure Outlier Detection

  1. Open any Instrument Setup in your project.

  2. Navigate to the Alert section.

  3. Open the new Outliers page.

  4. Set your upper and lower boundaries for acceptable readings.

Step 2: Monitor and Manage Outlier Events

  1. Go to the Monitoring section.

  2. Open the Alert tab.

  3. Review and manage quarantine triggers, where outlier readings are flagged or removed automatically.

     4.   To review past outlier events, restore deleted data or delete quarantined readings, access the Logs section.