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Introduction

This tutorial demonstrates how to connect a simulated device to the Watson IoT platform, vizualise its live data, store its data into a database and leverage Node-RED tool for wiring together hardware devices, APIs and online services.

Sample Architecture

Objectives

  • You will collect sensor data from a Watson IOT service.
  • You will simulate a temperature sensor.
  • You will discover how to leverage Node-RED to connect IoT.
  • You will store the collected data into a NoSQL database.
  • You will use Watson to translate messages.

Pre-Requisites

Steps

  1. Start the Simulated device
  2. View the live sensor data
  3. Connect your device to the Watson IOT Platform
  4. Use Node-RED to read the sensor data
  5. Store the device data into a No SQL database
  6. Translate messages with Watson

Step 1 - Start the Simulated device

We will use a simulator of a temperature sensor. This sensor also simulates Humidity and Object Temperature.
This way, we don't require an actual hardware device to test our application.

  1. In a new browser window or on a smartphone, browse to IOT Sensor.
    Alternatively, enter this short URL: http://ibm.biz/iotsensor

    Sensor simulator

  2. Note the Device Id (displayed in the top right corner).

Step 2 - View the live sensor data

  1. In a new browser window, browse to Watson IOT Platform quickstart.
    Alternatively, enter this short URL: http://ibm.biz/iotquickstart

    IOT Quickstart

  2. Enter the device id.

  3. Vizualise the live sensor data.

Step 3 - Connect your device to the Watson IOT Platform

You've seen my data, what next? Now you will use your device in an application created with IBM Cloud.

  1. Create an app using Internet of Things Platform Starter from the category Starter Kits in the Catalog.

  2. Provide the application name, modify the host name, if required, and click Create.
    Note: Wait for a few minutes for your app to start running.

  3. When your app is running, select the app URL or type it into the browser to open the Node-RED flow editor

    https://<appname>.mybluemix.net

  4. You see a ready-made flow that can process temperature readings from a simulated device.

Step 4 - Use Node-RED to read the sensor data

  1. In the Node-RED workspace, double-click the IBM IoT App In node to open the configuration dialog.

    IOT App IN node

  2. In the Authentication type field, select Quickstart from the pull-down list. Enter the Device ID field and click OK.
    Make sure that the device id is entered in lowercase, and that there are no leading or trailing space characters.

  3. Look for the Deploy button in the upper right hand corner of your Node-RED workspace. The deploy button is now red; click it to deploy your flow.

    Node-RED Deploy

  4. Open the debug pane on the right. You will see that the flow is generating Temperature Status messages.

  5. Increase the temperature value on the simulator to see the messages change in the debug pane.
    Note that a different message appears if the temperature exceeds 40 degrees.

Step 5 - Store the device data into a No SQL database

  1. In Node-RED flow editor, add a Cloudant out node

    Cloudant out node

  2. In the Service type field, select the name of Cloudant service bound to Node.js runtime from the pull-down list.
    Enter a dabatase name in lowercase. Keep the default operation insert and finally give a name to the node.

Cloudant configuration

  1. Deploy the flow. Return to the IBM Cloud Console, go to the Cloudant console and navigate into the records.

Cloudant console

Step 6 - Translate messages with Watson.

The warning messages generated in Node-RED uses English by default. You may want to translate those messages into your oww language.

  1. In IBM Cloud Console, create a new service Language Translator to your app.

  2. From the Dashboard, open your app using Internet of Things Platform Starter and connect this new service Language Translator to your app.

  3. In Node-RED flow editor, insert a new Language Translator node into the existing flow.

  4. Modify the flow accordingly to translate those messages.

    Watson Language Translator

  5. Deploy the updated flow.

  6. Observe the translated output based on the selected language.

Resources

For additional resources pay close attention to the following: