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Analyzing Air Quality using the Internet of Things. Dustin FranZ. Research Project. Purdue University Calumet Professor Ricardo Calix. Internet of Things ( IoT ). What is it? Uniquely identifiable objects or things in an Internet-like structure What can it do? Internet of Cows
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Analyzing Air Quality using the Internet of Things Dustin FranZ
Research Project Purdue University Calumet Professor Ricardo Calix
Internet of Things (IoT) • What is it? • Uniquely identifiable objects or things in an Internet-like structure • What can it do? • Internet of Cows • Reduce Poverty gap in India • Environmental Monitoring
What things? • Arduino Microcontrollers connected to environmental sensors • Why Environmental Monitoring? • Important in NWI • Why Arduino? • Arduino is cheap • It’s fun!
What exactly are you monitoring? • MQ7 • Carbon Monoxide (CO) • MQ131 • Ozone (O3) • Matches type of data collected by the Indiana Department of Environmental Management (IDEM)
Arduino IDE Program structure #Include Libraries //Define Global Variables Setup() { //initialize connections} Loop(){ //Read and send data }
HTTP • REST(Representational State Transfer) • Easy to use APIs • HTTP method • PUT • Why not GET? • Status Codes • Data Formats • CSV • JSON
Cosm • A twitter for data • Sharable • Searchable • Similar problems
Using the IoT for the IoT • What can we do with just two features? • Also have time and location! • More features! • Weather API • Temperature, Humidity, …
Python Script • To gather all of this information into a single location • Grabs data from cosm • every 5 mins • Weather API has restrictions • Updated every 30 mins • JSON • Outputs to CSV file defgetTemp grab weather data return weather data defwriteToCSV grab cosm data call getTemp every 30 mins write data to csv defdoWork call writeToCSV for each feed ##main## call doWork every 5 mins
Problem statement We’ve collected data from different locations in northwest Indiana and also collected polluted data from car emissions Use Weka to use this data to try to predict polluted data vs non-polluted data
Dataset MQ131 MQ7 Polluted latitude Longitude temperature in Fahrenheit dew point in Fahrenheit Precipitation in the last hour in Inches pressure in in Hg Relative humidity Date and Time
WEKA Ranker Naïve Bayes
Problems Sensors often have a warm up period Sensors are sensitive and can easily produce bad data Getting polluted data
Moving Forward • Need more data of different types (Polluted data) • Need more features to better analyze data • Hope to submit to a journal • Related research • Automatic Semantic Content Enrichment of Sensor Network Based Information