Environmental Monitoring with TPS, Azure, and PowerBI

Step 0: Configure and Assemble the TPS

• Open LTPS Web Interface by simply entering its IP address in your browser, select the "Tibbits Layout" tab, and push the "Launch TPS Configurator..." button.

• Setup Tibbits Layout as shown on the screenshot below and click File/Save

Note: TPS needs to be rebooted to take new Tibbits Layout into effect.

• Assemble TPS according to the Tibbits Layout

Attention: it's strongly recommended to shut down TPS before placing/removing Tibbits.

Step 1: First application

Node.js, Git and Python 2.7 are installed on each LTPS by default, but NPM is not.

• For installing, connect it to your device with SSH and do the following:

# Setup package repositories
smart channel --add 150a type=rpm-md name="LTPS all" baseurl=http://tibbo.com/downloads/LTPS/packets/all/ -y
smart channel --add 150c type=rpm-md name="LTPS cortexa" baseurl=http://tibbo.com/downloads/LTPS/packets/cortexa8hf_neon/ -y
smart update
# Install NPM
smart install nodejs-npm -y

then

# Create folder for application
cd /opt/node-apps/
mkdir environment
cd environment
# Install required modules
npm install @tibbo-tps/tibbit-28
npm install @tibbo-tps/tibbit-30
npm install @tibbo-tps/tibbit-35

/opt/node-apps/ folder is proposed to be used for your Node.JS apps.

• In any IDE or even a text editor create azure-app-0.js file with your application:

var tibbit28 = require("@tibbo-tps/tibbit-28").init("S11");
var tibbit35 = require("@tibbo-tps/tibbit-35").init("S13");
var tibbit30 = require("@tibbo-tps/tibbit-30").init("S15");
setInterval(function(){
var illuminationData = tibbit28.getData();
var humidityData = tibbit30.getData();
var pressureData = tibbit35.getData();
var dateTime = new Date();
console.log("Date/Time: "+dateTime);
console.log("Illumination: "+illuminationData.illumination);
console.log("Humidity: "+humidityData.humidity);
console.log("Temperature: "+humidityData.temperature);
console.log("Pressure: "+pressureData.pressure);
},1000);

• Upload it to /environment folder and run:

$ node azure-app-0.js
Date/Time: Tue Jul 19 2016 13:50:54 GMT+0000 (UTC)
Illumination: 115
Humidity: 43.755340576171875
Temperature: 28.05670928955078
Pressure: 738.7398681640625

Step 2: Setting Up Microsoft Azure IoT Hub

Microsoft Azure IoT Hub is a service that allows bi-directional communications between your devices and a solution back end. To complete this part of the tutorial you'll need:

• TPS device(s) prepared as shown on the Step 0

• An active Azure account

• A PC with installed Node.js

Create an IoT Hub

• Sign in to the Azure Portal

• Choose New > Internet of Things > Azure IoT Hub

• Configure your IoT Hub, then click "Create"

• Wait a few minutes until your IoT Hub has been created then select All Resources > [name of your IoT hub] and click "Keys" icon.

• In the Shared access policies blade select the "iothubowner" item and then copy the value of "Connection string" field.

Step 3: Registering Device Identities

There are three ways to register device identities: with a script using Azure API, with GUI App (for Windows only) and with multiplatform CLI tool. The third way seems to be the most convenient one.

Note: To use iothub-explorer you need Node.js version 4.x or later installed

• On your PC run:

npm install -g iothub-explorer@latest

• then:

$ iothub-explorer login <connection-string>
Session started, expires Thu Jul 21 2016 13:22:10 GMT+0400

where <connection-string> is an iothubowner connection string from Step 2.

• To register a new device and get its connection string:

$ iothub-explorer create <device-name> --connection-string
Created device tps-centreville
...
connectionString: HostName=iot-tps.azure-devices.net;DeviceId=tps-centreville;SharedAccessKey=fSCVQIY..TOprSsDE=

Where <device-name> is e.g. "tps-centreville".

• Make note of the connections string.

Step 4: Making devices IoT-enabled

• Connect with SSH to the TPS, change folder to /environment and do:

npm install azure-iot-device
npm install azure-iot-device-amqp

• Create azure-app-1.js file with the following app:

var clientFromConnectionString = require('azure-iot-device-amqp').clientFromConnectionString;
var Message = require('azure-iot-device').Message;
var connectionString = '<THE DEVICE CONNECTION STRING FROM STEP 3>';
var client = clientFromConnectionString(connectionString);
var tibbit28 = require("@tibbo-tps/tibbit-28").init("S11");
var tibbit35 = require("@tibbo-tps/tibbit-35").init("S13");
var tibbit30 = require("@tibbo-tps/tibbit-30").init("S15");
client.open(function(err){
if(err){
 console.log('Could not connect: ' + err);
}else{
 console.log('Client connected');
 setInterval(function(){
     var illuminationData = tibbit28.getData();
     var humidityData = tibbit30.getData();
     var pressureData = tibbit35.getData();
     var time = new Date().toISOString();
     var data = JSON.stringify({
         deviceId: 'tps-centreville',
         humidity: humidityData.humidity,
         temperature: humidityData.temperature,
         pressure: pressureData.pressure,
         illumination: illuminationData.illumination,
         time: time
     });
     var message = new Message(data);
     client.sendEvent(message, function (err) {
         if(err){
             console.log(err.toString());
         }else{
             console.log("Message sent: " + message.getData());
         }
     });
 },60000)
}
});

• Upload it to /opt/node-apps/environment folder on the TPS and run:

$ node azure-app-1.js
Client connected
Message sent: {"deviceId":"tps-centreville","humidity":37.1016960144043,"temperature":31.370407104492188,"pressure":742.8632202148438,"illumination":136,"time":"2016-07-21T10:19:07.490Z"}
Message sent: {"deviceId":"tps-centreville","humidity":37.1016960144043,"temperature":31.370407104492188,"pressure":743.2034301757812,"illumination":137,"time":"2016-07-21T10:20:10.582Z"}
Message sent: {"deviceId":"tps-centreville","humidity":37.1016960144043,"temperature":31.380477905273438,"pressure":743.2034301757812,"illumination":138,"time":"2016-07-21T10:21:12.003Z"}

Event monitoring is the most remarkable and very useful feature for the purpose of debugging iothub-explorer. With iot-explorer, you can easily observe events sent by your devices to cloud and vice versa.

Note: this command requires providing iothubowner connection string even if you're already logged in.

• On your PC do:

$ iothub-explorer <connection-string> monitor-events tps-centreville
Monitoring events from device tps-centreville
Event received:
{ deviceId: 'tps-centreville',
humidity: 37.1016960144043,
temperature: 31.380477905273438,
pressure: 743.2034301757812,
illumination: 138,
time: '2016-07-21T10:21:12.003Z' }

You can see every event as soon as it's sent to IoT hub.

Step 5: Configure Stream Analytics

Note: To compelete this part of the tutorial you'll need an active Microsoft Power BI subscription.

Before the information can be delivered to Power BI, it must be processed by a Azure Stream Analytics job.

• Choose New > Internet of Things > Stream Analytics Job

• Configure the Job, then click "Create"

• Wait a couple of minutes until the Job has been created, then select All resources > name of your Stream Analytics Job

• Click Inputs > Add

Set up input in the following way:

• Input alias : data-from-tps

• Source Type : Data stream

• Source : IoT Hub

• Subsriptiopn : Use IoT hub from current subscription

• Endpoint : Messaging

• Shared access policy name : iothubowner

• Consumer group : powerbi

• Click "Create"

Set up output:

• Output alias : data-to-powerbi

• Click Otputs > Add

• Choose Power Bi as sink

• Click Authorize and enter your Power BI credentials in the appearing window

• Enter Dataset Name and Table Name, e.g. "telemetry" and "environment", respectively

• Click "Create"

Now it's time to enter the query:

• Click Query

• Enter the following:

SELECT
AVG(humidity) AS humidity,
AVG(temperature) AS temperature,
AVG(pressure) AS pressure,
AVG(illumination) AS illumination,
System.Timestamp AS time,
IoTHub.ConnectionDeviceId AS deviceId
INTO
[data-to-powerbi]
FROM
[data-from-tps] TIMESTAMP by time
GROUP BY
TumblingWindow(Second, 60), IoTHub.ConnectionDeviceId

• Click Save

Stream Analytics Query Language is a subset of SQL. Complete language documentation can be found here. There is also a very useful set of examples.

The query above, in short words, splits the timeline into 60-second periods and returns average values of humidity, temperature, pressure, and illumination for each period and each device.

• Start your job

Step 6: Visualizing your data

Open your Power BI workspace. Soon after you started the Stream Analytics job, a new dataset appears in the Navigation Bar. Report creation should not be a great challenge. Use "time" as Axis, "deviceId" as Legend and temperature/humidity/illumination/pressure as Value.

Step 7: Adding devices

• Register second device as described in Step 3.

• Upload and run code from Step 4 with modified connectionString value.

In short time the second curve appears in the report.