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WEVA Features

The WAGO Energy Visualization App (WEVA) is an professional-grade ecosystem engineered for high-precision energy management. By combining deterministic data polling with modern visualization, it empowers plant engineers to optimize consumption and ensure network stability.

🏗️ Local Network Server Architecture​

Unlike cloud-dependent solutions, WEVA operates strictly within your local industrial network.

  • Zero Latency: Direct interaction with on-site controllers.
  • Data Sovereignty: Your energy data never leaves your facility.
  • High Availability: Independent of external internet outages.

MODBUS Connected Devices

📊 Real-Time Power Analysis​

Visualize critical electrical parameters with laboratory-grade precision.

  • Easy Graph Creation: Easily plot real-time graphs from the data gotten.
  • Dynamic Charting: Interactive trend analysis for voltage, current, and frequency.
  • Instantaneous Values: Live updates from every connected Modbus device.

Live Graphs Display

🛠️ Configuration & Control​

WEVA provides bidirectional communication for active device management.

  • Modbus Write Support: Modify register setpoints directly from the web interface.
  • Device Management: Add and configure new WAGO controllers without downtime.
  • User Permissions: Granular access control for Admins and Viewers.

Configuration and Control Placeholder

🚨 Intelligent Alarm Management​

WEVA provides user defined thresholds for various measurements. When a measurement exceeds the defined threshold, the user will be notified.

  • Critical Errors: High-priority alerts when thresholds are exceeded. Once acknowledged, the alert will be cleared.
  • Threshold Warnings: Thresholds can be set to trigger an alert when a measurement exceeds or drops below a certain value. No acknowledgment is required for these warnings.
  • System Information: Alarms simply for notifications. No acknowledgment is required for these warnings. These alerts are purely informational and do not require any user interaction.

Alarm Tray Open

💾 Long-Term Data Retention​

Data points streamed and recorded by users are persisted to a database.

  • SQL Persistence: Reliable storage of historical trends.
  • CSV Export: Standardized data extraction in CSV format only.
  • Data Integrity: Continuous logging even when the user interface is closed.

NOTE: This works as long as the Docker container is not interrupted

Streaming Data from Device

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