Temperature sensor data visualisation with Node-RED

Overview

This lesson assumes that a temperature sensor is sending data to The Things Network. In this lesson we will use the MQTT protocol to subscribe to data transmission events. We will create a program in Node-RED to subscribe to the data transmissions and to graph the data coming from the sensor using the in-built Dashboard function in Node-RED.

Learning Objectives

• Learn how to subscribe to a MQTT using the Node-RED MQTT-in node
• Learn how to extract specific sensor data using the Node-RED function node.
• Learn how to create a Dashboard in Node-RED to monitor live data.

Subscribe to MQTT

Open Node-RED

• Click on the Raspberry Pi main drop down menu.
• Select Programming > Node-RED

• Node-RED will automatically open the Terminal on the Raspberry Pi.
• It takes approximately ten seconds for Node-RED to initialise itself.

• To actually use Node-RED you need to open the web browser on the Raspberry Pi.
• Click on the default web browser.
• In the search bar enter localhost:1880
• Localhost is the address of the local or host machine.
• In this example the host address is 192.168.1.168, but your computer will have a different address.
• The number at the end of the URL (1880) is the port number for the Node-RED application.
• Different ports are assigned to different applications using HTTP protocols.
• Note - if you are using UFW (uncomplicated firewall) you may need to open this port otherwise Node-RED will not work.

Subscribing to MQTT

• To subscribe to MQTT we need the 'mqtt in node.
• Find the mqtt in node and drag it onto the Flow 1
• You will notice that the node has both a blue circle and a red triangle.
• The red triangle indicates that the node requires further configuration before it will work

Configuring the mqtt in node

• Double click on the mqtt in node.
• In Properties > Server > select Add new mqtt-broker
• Click on the Edit button to the right - which looks like a pencil

• Enter the following details:
  • Properties > Name > pycom-temperature-1
  • Connection > Server > au1.cloud.thethings.network
  • Connection > Port > 1883
  • Leave all other details as shown in the example below.

• Click on the Security tab
• The Username is whi-seedling-1-pycom@ttn
• The Password is NNSXS.Z625CQKKEWAPSQK467JRSAFFYINH7LTHSUC5CYY.MHEVWHKKLPWXQWESSCALZFVHA6EKUNISQH4IVHKAOXYZRMOH6D7A
• If copying these fields from mediawiki or another computer use right mouse button click copy
• Click on the red Add button to commit the changes.

• You will be asked to complete some final configuration settings.

• Update the following fields:
  • Topic # - The hash symbol means subscribe to all topics
  • QoS 0 - quality of service. A value of zero equates to a low quality. Data losses are acceptable.
  • Output a Parsed JSON Object - JSON format output for all data
  • Name pycom-temperature-1
• Then click on Done to commit all the edits.

• The finished mqtt in node should now appear in the main flow window.
• It will still have a blue circle because the flow has not been Deployed.

Add a Debug Node

• Before we Deploy this first flow we will need to add a Debug node.
• Drag a Debug node from the pallet and connect it to the output of the mqtt in node (pycom-temperature-1).

Set the Debug Window

• The Debug node will show us all the JSON data output coming from mqtt in node.
• To see the Debug output click on the Debug messages tab.

• Click on the Deploy button to make the flow active.
• Message should appear indicating that the flow has been successfully Deployed.
• The mqtt in node will also show a green connected status message underneath the node.

Receiving mqtt data

• When data arrives from the temperature sensor (approximately every 30 minutes) it will appear in the Debug window on the right of the screen.
• The data is presented in a compacted form.

• By clicking on the drop down arrows in the message the different sections of the message can be expanded.
• Expand the uplink_message and the decoded_payload to see the sensor data.