Introduction: Smart Green House With Intel Edison and Microsoft Azure
I have attended the Intel IoT Roadshow here in Silicon Valley during last weekend, and made this cool project – Smart Green House. Intel provided a bunch of sensors, and I thought of doing something with green house.I have placed various sensors inside the green house, and the system will monitor current condition (soil temperature, moisture, light, ph level, ultra violet, water et ), and report to the back end cloud. Backend knows the current profile of the green house(I have used radish plant for demo), and if there is anything abnormal, green house system will adjust the settings. For example, if the temperature is high then the system will turn on the fan. If the water level is low, then the system will automatically turn on water pump. I have placed the LCD display unit outside to see the current health level, and if anything unusual with green house then the display will be red, and notification will be send as SMS.
Step 1: Implementation Details
Core of this project is the Intel IoT developer kit which they have provided to the first 150 attendees, and I was lucky enough to get one. In addition to the default kit, I have managed to get the mini water pump, water flow control, fan, light etc. I have used Intel XDK IoT edition for the development and used the Node.JS / Java script to read/write to hardware/sensors. Intel SDK team did pretty decent job in documenting everything, and enoughsample codes, and I could set up the first sensor up and running in couple of hours including the XDK and drivers installation. Here comes the code sample to read the temperature value from the sensor connected to the analog pin.
// Load Grove module
var groveSensor = require('jsupm_grove');
// Create the temperature sensor object using AIO pin 0
var temp = new groveSensor.GroveTemp(0);
console.log(temp.name()); //Print the sensor name
var celsius = temp.value();
console.log(celsius + " degree"); //Print the temperature
Similarly, I have read values from all the sensors, and sent the same to Azure Event hub. I couldn’t find any AMQP 1.0 node package to connect to the Azure event hub, hence I used the REST api to post the reading in every second. During the start of the app, green house system will connect the Azure backend to retrieve the profile for the current plant, and in this case it got the profile for radish plant. Since the green house system already got the plant profile at the start, any reactive action (eg:- turn on water pump, turn on fan etc) don’t require network/backend connectivity. Hence we don’t put the plants on risk incase if there is any network outage.
Step 2: Dashboard
Once I get the sensor values at Azure event hub, data gets forwarded to Stream Analytics service, and then the output of the stream is directed to the Power BI for dashboard. Here is a dashboard from my demo. More details available at http://sreesharp.com
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