Build your IOT Application in a Day

IoT Application - Furnace Monitoring system
By Ranjith kumar DSM August 29, 2019

Just think a while if you can build your IOT application in a day. Yes! You read it right. We recently did a major update of the MQTTRoute where our customers will be able to embed their ML & AI algorithms and create their own application. MQTTRoute helps you host and manage your application easily. This just leaves your development challenge for your IOT Server application. MQTTRoute comes with a default user interface, however visualization needs to be built for specific vertical. We recently run an internal hackathon at Bevywise to build applications over our framework. Interestingly, we were able to build an IOT application in a day. The application built was a Industrial Furnace monitoring. This blog portrays the hacks used to build the application.

Industrial Furnace Temperature Monitoring – Sample Application

Monitoring and control of temperature of the furnaces is crucial with respect to its usage in the industries as it directly affects the quality of the product that is being created. We created a simulated device similar to a monitoring edge device which pushes data to the MQTT Broker. The goals set for the application were:

  • live graph of the incoming temperature
  • Historical hourly average of the temperature
  • Alarm when the temperature exceeds a range
  • Alarm when current temperature exceeds the previous hour average

Create a live graph

MQTT Broker is programmed in a way that it pushes the incoming device data to the user interface using the web socket. You will be able to add your own code to create live graphs. In this hackathon, plotly is used by the developer. The data on temperature of the furnace collected is presented as a line graph in the dashboard. This is done by configuring custom_ui_server.py file.

 

reference code for line graph


xaxis: {
type: ‘date’,
range: [olderTime, futureTime]
}
};
Plotly.relayout (graph_id, minuteView);
Plotly.extendTraces (graph_id, update, d)

Create a historical graph

The historical graph on hourly average data can be created by the Data Crunching process. The schedule module is used to automate the creation of hourly average data. Custom implementation for the average of data developed in a separate method and configured in the schedule to be called every 60 minutes in  custom_scheduler.py file.

 


def schedule_conf( ):
schedules={}
schedules={
‘STATUS’ : ‘DISABLE’,
‘SCHEDULES’ : [
{‘OnceIn’ : 1,‘methodtocall’ : oneminschedule },
{‘OnceIn’ : 5,‘methodtocall’ : fiveminschedule } ] }
return schedules

After processing the data, the data is pushed to the user interface through the web socket. The bar graph is created using plotly to display the crunched data.

 

reference code for bar graph


x: [ data1 [i] [‘time1’] ]
y: [ data1 [i] [‘value’] ]
Plotly.newPlot ( ‘history’, data123,layout, {displayModeBar:false, responsive:true}, {scrollZoom: true} );

We believe you will be able to add your own algorithm similar to the above.

Create a live Alarm

The variation in the temperature can be noted and displayed in a widgets. For a certain range of temperature values the data will be shown in varied colours to alarm for a temperature variations. Here, the data will be shown as red coloured text if the temperature is above 500 degree Celsius (default value) and blue coloured text if the temperature is below 500 degree Celsius. The default temperature range set can be changed according to your need. You can add your own widgets and notifications to the user interface by customizing custom_ui_server.py file. To schedule your alarms use  custom_scheduler.py file.

 

reference code for text_widget


if ( key == “message-integer” || key == “message-float” || key == “message-string” ) {
var message = data1 [key] [‘message’][0] ;
document.getElementById(id).innerHTML = message + String.fromCharCode(176)+unit+ ;
}

Create Alerts

The comparison of incoming data with the previous hourly average data can be done. Alerts can be created with the compared data. If the temperature exceeds the hourly average temperature then the data blinks by creating an alert. This can be done by adding event based triggers using the scheduling module. Add your own algorithm to create alerts in custom_scheduler.py file.

 

reference code for alarm_widget


if ( p_avg < data3 [‘msg’] [‘message’] [0] ){
document.getElementById (“alert”).innerHTML=data3 [‘msg’] [‘message’] [0] + “ALERT!” + “Temperature High”;
}

Dashboard for IOT Application in a day

All the widgets created by the developer was put on a separate page, as it can be used as a dashboard to be projected/displayed onto to a bigger screen. This has been done as a custom URL inside the custom_ui_server.py similar to the following code snippet.

 

Add your URL here



def custom_urls():
urllist={
“AUTHENTICATION”:’DISABLE’,
“urls”:[{“/extend/Dashboard”:dashboard}]
}
return urllist

The hackathon IoT Application built in a day is available on GitHub for trying it out. Download the MQTT Broker now to start building your application today.

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