When developing IoT systems you’re often dealing with a huge amount of time series data. Basically key-value pairs bound to a timestamp. Or maybe you are debugging some sensor output or feedback controller only using text output on your terminal. Getting a sense of what kind of data your sensors are outputting is not easy when you’re dealing with tens, hundreds or even thousands of sensors and measurements.
Various tools already exist to visualize time series data. They are very good at visualizing large amounts of data in multiple different ways. But setting these tools up often takes time and the learning curve to effectively configure the visualizations to view your data is often an unwelcome bump in the road when all you care about is getting a sense of the data you’re dealing with without bothering with the details.
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| Real-time data visualized using simple graphs with minimum lag. |
When developing, testing and prototyping, it is essential that you get good understanding, how your system performs in real-time and also within a longer time-frame. You don’t want to spend time configuring and setting up visualizations tools. This is why we put together Quick Visual Dashboard. A local or cloud deployed visualization tool where you can input data using standard TCP or MQTT protocols. With simple script templates done in Python, uploading data to the tool can be done in no time.
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| Built-in geospatial data support to see how and where your data is on the map in real-time. |
The data is preprocessed and backed by InfluxDB. This means that after you’re done with your initial prototyping and you stop caring about real time data - you can go back and use industry proven tools like Grafana to further investigate all the details of your time series data at any point in time.
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| Using Grafana it is possible to dive deeper into historical time-series data. |
Christian Talmo, Full-stack Developer, Ixonos
Stanislav Radomskiy, Senior SW Designer, Ixonos
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