Creating Real-Time Dashboards for Your IoT Data with InfluxDB and Grafana

I've seen it happen in countless projects: a team spends months engineering a brilliant data collection system, only to have the valuable data sit unused in a database, invisible to the people who need it most. Let's be clear: if you can't see your data, you can't act on it. This is where data visualization becomes the most critical part of your IoT solution.

The good news is, you don't need an expensive, complex cloud platform to create professional-grade dashboards. By running the open-source visualization tool Grafana directly on your Industrial IoT Edge Gateway , you can create a powerful, real-time monitoring solution right at the edge. In this guide, we'll show you exactly how to build your first Grafana IoT Dashboard, turning a stream of raw sensor numbers into a clear, actionable view of your operations.

To build our dashboard, we need two key pieces of the "MING" software stack.

●  InfluxDB : The Time-Series Database: Think of InfluxDB as the perfect memory for your sensor data. Unlike a general-purpose database, it's purpose-built to handle massive volumes of timestamped data points, making it incredibly efficient for storing and querying things like temperature, pressure, or vibration over time.

● Grafana: The Visualization Engine: Grafana is the window into your data. It's a powerful open-source platform that connects to data sources like InfluxDB and allows you to build beautiful, interactive dashboards with graphs, gauges, tables, and alerts. You can learn more at the official Grafana: The open and composable observability platform | Grafana Labs .

This guide assumes you have already set up your gateway and are collecting Modbus sensor data using Node-RED and storing it in InfluxDB, as shown in our guide to Processing Modbus Sensor Data at the Edge .

On a Robustel gateway like the EG5120 , accessing Grafana is simple:

1. Log in to the EG5120's web interface.
2. Navigate to Development -> Data Visualization.
3. Ensure Grafana is enabled and click Open Dashboard Designer. This will launch the Grafana interface in a new browser tab.

The fastest way to get started is by importing a pre-made dashboard template. The Robustel IIoT Starter Kit comes with a dashboard file specifically for the S6000U sensor.

1. In the Grafana interface, navigate to the Dashboards section.
2. Click New and then select Import.
3. Click Upload dashboard JSON file and select the S6000-dashboard.json file that comes with the starter kit.
4. After uploading the file, Grafana will ask you to select a data source. From the dropdown menu, choose the built-in InfluxDB data source.
5. Click Import.

That's it! Your dashboard will instantly come to life, populated with real-time data from your sensor.

One of Grafana's most powerful features is its extensive library of plugins, which allow you to add new types of visualizations. The real 'aha!' moment for many users is realizing they can find a panel for almost any data type imaginable.

For example, the pre-built S6000U dashboard uses a special plugin to visualize the tilt sensor. To install it:

1. In Grafana, navigate to Administration -> Plugins and data -> Plugins.
2. Search for the plugin you need (e.g., ACE.SVG).
3. Click Install.

Once installed, the new panel type will be available when you create or edit your Grafana IoT Dashboard.

A well-designed Grafana IoT Dashboard transforms streams of numbers into immediate insights. The pre-built dashboard for the S6000U visualizes all seven of its sensor readings:

• A temperature gauge.
• A humidity line graph.
• A noise volume bar chart.
• Vibration, distance, and tilt readings.

You now have a clear, at-a-glance understanding of your operational environment, powered entirely by your edge gateway.

Powerful data visualization is no longer limited to expensive, cloud-only platforms. By running tools like Grafana and InfluxDB directly on a capable industrial IoT edge gateway like the Robustel EG5120, you can create professional, real-time dashboards right at the edge. This approach provides immediate insights, reduces cloud dependency, and empowers you to make faster, more informed decisions based on your IoT data. The next step is yours: start experimenting, create new panels, and build the custom dashboard that perfectly fits your application's needs.