In the last few months, I have gradually shifted to use Node-RED as the tool for demonstrating and prototyping Azure IoT solutions. In particular, I configure a dashboard to display the ambient information sent from the device and verify the data received by an Azure IoT Hub and stored in an Azure storage account using Azure Storage Explorer form my desktop. Ideally, I would configure all on an Arduino or a Raspberry Pi. To make it more portable, I also do it with a local Ubuntu VM, so no need to plug in anything and I can demo a simple IoT setup anytime and anywhere on demand with Internet connectivity. Briefly, here’s an outline of what I did.
1. Installing & Starting Node-RED
On my Ubuntu (16.04 LTS) VM, update and upgrade everything, followed by install Node-Red.
If you need to make a require node module globally available in Node_RED, edit the file, ~/.node-red/settings.js accordingly. Here, I made the module, math.js, globally available and used it to round the ambient data to two decimal points.
Now, start Node-RED, as the below.
As activities being carried out in Node-RED, this session displays the log with diagnostics in real-time.
In Ubuntu, when close out the terminal session running Node-RED, somehow it also stops the Node-RED service. This is different than how it behaves in Raspberry Pi where closing a Node-RED terminal session will not stop the service.
2. Accessing Node-RED IDE
The default port for Node-RED IDE is 1880, as shown below accessing the service from localhost. If preferred, authentication can be enabled and port changed by following what is stated in documentation and the above-mentioned settings.js file.
By default, there are a number of nodes installed as show on the left panel. And you may install addition nodes to better fit the needs.
3. Install additional Nodes
There are ample nodes and flows in Node-RED web site which you may install a from and contribute to. In addition to install these node modules with a command line interface, doing it interactively is also an option. In the IDE, click the upper right waffle within the Node-RED session and click ‘Manage palette’. If you do not see the option, update npm to the latest should make this option appear. As shown below, the Nodes tab presents the nodes installable directly or already installed currently. The
and on the install tab, you may keyword-search the Node-RED repository for relevant modules. Below, I search the modules relevant to Azure.
A few modules, I frequently install including:
4. Develop & Deploy a Node-RED Process Flow
To create a flow, start dragging selected nodes from the left panel to the canvas and construct flows by connecting the nodes. There copious amount of contents with how-to instructions on Node-RED in Internet already. Or if you like to do it in an old fashioned way, like me, by reading the document. The following is a simulated device with a few nodes to send and display ambient data to an Azure IoT Hub call thisiothub, as the following.
Here, I added a config node to set the global variable to set the baseline temperature, humidity and pressure for a simulation run. Node-RED will always initialize a config node prior to executing all flows presented on the canvas.
The timestamp node sets the time interval for sending data. When developing and troubleshooting, I set it to a long period between messages to minimize the noises. When demoing, I will then set it based on a customer’s requirements. Each time, the timestamp triggers, the connected nodes are consequently executing the programmed the logic, respectively.
In this setting, each emission by the timestamp node has the following effects.
This IoT Device function prepares the message payload and updates current ambient data which are global variables.
The temperature, humidity and pressure functions pipe the data stored in the global variables to a configured Node-RED dashboard.
This IoT Hub
This node has the host name of a target Azure IoT hub, here thisiothub, and the device connection information is provided in the function, This IoT Device.
This is a debug node. Once dragged to the canvas, it will automatically rename itself to msg.payload. Once connected, this node becomes a standardout of Node-RED. And you can examine the output in the debug tab in the right panel. In the screen capture above, you will find that I rounded the data to two decimal points and send it with mqtt.
Gauges and Charts
A main reason motivating me to use Node-RED is the simplicity to configure and deploy a dashboard directly on an IoT device. Data visualization is essential for an IoT solution which is all about data. The ability to deploy a dashboard right there and when on demand is a significant time saver and a noticeable advantage. It did however took me some practices to correctly place those gauges and charts the way I wanted. Once configured, the dashboard is published automatically at http://node-red-instance/ui and here is what I got.
Verifying the Data Sent to Azure IoT Hub
There are two tools I use for managing and examining the activities between an IoT device and Azure IoT Hub. Namely, iothub-explorer for Linux and Device Explorer for Windows. The latter is a sharp tool for Windows users to examine data, .
And a convenient way to get the connection strings.
I also deployed a sample web app which plots the temperature and the humidity data received form thisiotdevice in real time, as shown.
So either from Azure IoT Hub or directly on the device, we may present the data visually.
Ubuntu frequently stopped Node-RED when a deployment had failed connecting to Azure IoT Hub, and the node will also lost the host name data. And I had to frequently restart the services and re-enter the Azure IoT Hub host name in the node configuration. And it is better to leave the terminal session where you started the Node-RED service visible at all time to restart the service as needed. I once spent hours troubleshooting a flow, researching material and was not able to figured out why, only to later find out the Node-RED service exited its session upon a failed deployment behind the scene.
Node-RED is a great learning and prototyping tool. And once learned, you can create process logic based on data flows relatively easily. It is visual and a picture is always worth a thousand words
p align=”left”>Azure IoT Hub is the Swiss army knife for formulating an IoT solution. It does the heavy lifting for registering, securing and managing devices with interfaces to integrate other Azure or 3rd-party services. The recent announcement of Azure IoT Edge opens up many scenarios and opportunities to increase ROI by processing data right where they are collected. Which is what I plan to include to the next version of my Node-RED flow. Stay tuned.