Overview

This repository contains a solution to take readings from a touch sensor and send them to cloud (Microsoft Azure) for real-time analytics, using Node.JS on a Raspberry Pi running Raspbian OS.

Prerequisites

1. Raspberry Pi
2. Touch sensor and buzzer
3. Azure subscription
4. Power BI online account (you can create a free trial at https://www.powerbi.com)

Steps

To get this to work, follow the steps below:

1. Without giving power to the Raspberry Pi yet, make sure you have connected the touch sensor to the Raspberry Pi as per below. Pin mapping of Raspberry Pi is available here.

   • GND of touch sensor to GND (Pin 6) of Raspberry Pi
   • VCC of touch sensor to 5V PWR (Pin 2) of Raspberry Pi
   • SIG of touch sensor to GPIO 2 (Pin 3) of Raspberry Pi

Note: GND, VCC and SIG are specified near the touch sensor pins.

Follow this setup for connections with the Buzzer:

-   RED of Buzzer to GPIO 4 (Pin 7) of Raspberry Pi
-   BLACK of Buzzer to GND (Pin 9) of Raspberry Pi

2. Connect the HDMI cable from the Raspberry Pi to the Monitor. Also, connect the wired keyboard and wired mouse to the USB slots in the Raspberry Pi.

3. Power up the Pi, by connecting it to a power socket. Wait for a minute once this is done. If you are using a Raspberry Pi 2, connect the WiFi module to the USB port of the Pi. You will see the Internet icon in the taskbar (usually at the top right of the screen) - select the appropriate SSID and connect to it. (Alternative way : Click on the link and follow the instructions here to configure WiFi for the Pi). If you are using a Raspberry Pi 3, there is no need to connect a separate WiFi module.

4. Put the Raspberry Pi and your development machine on the same network. Get the IP address of the Pi (by viewing the IP on a display connected to the Pi - go to Terminal and type ifconfig).

5. From your laptop, ensure you are able to ping the Pi using the IP - open cmd and ping the IP. You should be getting a successful ping.

6. Go back to your laptop and open a SSH client (use Putty if you are on a Windows machine), and SSH into the Pi using its IP. Default username: pi , default password: raspberry .

7. Open a FTP client, like Filezilla, and access the Pi using the IP. (Username and password as same, Default port as 22)

8. Go to Putty, and follow these steps:

   git clone https://github.com/rexington/quick2wire-gpio-admin.git
   
   cd quick2wire-gpio-admin
   
   make
   
   sudo make install
   
   sudo adduser $USER gpio
   

   gpio-admin export 2 (Ignore the error message if any.)

   gpio-admin export 4 (Ignore the error message if any.)

   cd ..

   mkdir iotplay

9. Go back to your laptop and clone this repository.

   git clone https://github.com/saurabhkirtani/touch-sensor-azureIoT.git

   cd touch-sensor-azureIoT

10. Open your Azure account by going to https://portal.azure.com. If you've been ditributed a Azure pass, you can redeem it by following the instructions here: https://www.microsoftazurepass.com/howto. (If you don't have an Azure account, you can get a free trial here: https://azure.microsoft.com/en-in/free/)

11. Setup IoT Hub in your Azure account. Instructions here. - Choose Southeast Asia as the region.

12. Install the Device Explorer utility (if on a Windows dev machine) if you don't have it already. Then, create a new device and note down the device connection string. Instructions here. If you are on a non-Windows dev machine, use the iothub-explorer CLI tool - instructions are here.

13. Paste the device connection string obained from the above step in connectionString variable in the file pi-gpio-to-cloud.js (which you would have obtained in your laptop after cloning the repository)

14. Go to Filezilla and upload the 2 files - package.json and pi-gpio-to-cloud.js to the Raspberry Pi's iotnext directory.

15. Now go back to Putty, ensure you are in the iotplay directory. Run npm install to install all the required dependencies automatically. This process can take about a minute or so to complete.

16. Run the pi-gpio-to-cloud.js file with sudo - sudo node pi-gpio-to-cloud.js. If successful, you will start seeing '-------' every one second, and as soon as you touch the touch sensor, the buzzer should ring and the value should be sent to Azure.

17. The data is now being sent to Azure. You can verify that the data is being sent to Azure by using the same Device Explorer tool above. Go to the Data tab, choose the device, and click on Monitor. Now touch the touch sensor again - the data format being sent is of the form {"VoteCount":1,"TimeFlag":"2016-11-09T20:22:53.845Z"}

18. We'll now analyze this data real-time in the cloud, by using a Stream Analytics job and Power BI dashboards. Follow along.

Create Stream Analytics jobs

1. Go to portal.azure.com

2. Click + sign, search for Stream Analytics job, click on Create. Give it a name "iotplay-sa", select the same region and the same resource group as that of your IOT Hub.

3. Click on iotplay-sa, click on "Inputs" and add a new input. Give an input alias name like "input1", select option "Data Stream" , Source as "IoT Hub", use IoT Hub from the current subscription, and choose the same IoT Hub you had created earlier. Endpoint: Messaging. Shared access policy name: iothubowner. Event serialization format: JSON.

4. Click on "Outputs" and add a new output. Give an output alias name "outputpbi", Sink: Power BI , Authorize Power BI if you have an account, else signup and authorize yourself. Table name - iotplay-table Dataset name - iotplay-dataset

5. Click on "Query". Copy Paste this query in the box given

   `
   SELECT VoteCount INTO outputpbi FROM input1 
   `
   

6. Go back to your Stream Analytics job and click on "Start"; it may take sometime.

Creating PowerBI report

1. Go to [PowerBI.com] (http://www.powerbi.com)
2. A dataset by the name iotplay-dataset should appear on the left bottom, under the 'Datasets'- click on it.
3. From right side toolbox, select votecount and select the Gauge chart in Visualizations.
4. Click on Pin visual, give a name to your Report.
5. Then select the name of Dashboard you want it to be pinned to, or Create a new Dashboard, and it'll get pinned to the same.
6. Go to the Dashboards tab in the Left menu and open the Dashboard you have just created.
7. Now touch the sensor - and the value should update in the Power BI within a few seconds. You'll be able to see real-time data from the sensor getting analyzed on the cloud!

Congratulations! You have completed this workshop.

Credits

The code uses this NPM module for GPIO read and write.