Why is it important?

Air pollution is one of the world’s largest environmental causes of diseases and premature deaths. Out of different air pollutants, particulate matter (PM) has been identified as one of the most dangerous pollutants. Every year millions of people die and many more become seriously ill with cardiovascular and respiratory diseases because of long-term exposure to PM. With increasing urbanization, the situation is only going to get worse.

AQI Remarks Colour Effect on health
0-50 Good Minimal Effect
51-100 Satisfactory Minor breathing discomfort to sensitive people
101-200 Moderate Breathing discomfort to the people with lungs, asthma and heart diseases
201-300 Poor Breathing discomfort to most people on prolonged exposure
301-400 Very Poor Respiratory illness on prolonged exposure
over 400 Severe Affects healthy people and seriously impacts those with existing diseases

What are we trying to do?

A low cost sensor node was developed in IIIT to measure the level of Particulate Matter and other air impurities.The denser deployment of such low-cost sensors can provide real-time access of pollution data with high spatio-temporal resolution. Hence these low-cost portable ambient sensor nodes provide a huge opportunity in increasing the spatio-temporal resolution of the air pollution information and are even able to verify, fine-tune or improve the existing ambient air quality models. Government and citizens can use this information to identify pollution hot-spots, to make timely and localized decisions regarding reduction and prevention of air pollution.


  • Monitor the quality of air in and around the campus by measuring the following parameters
    • PM2.5, PM10 in μg/m³
    • Temperature in °C and RH in %
    • CO, NO2, NH3, CO2 concentrations in ppm
    • AQI(Air Quality indicator)
  • Issue alerts in case the quality deteriorates below acceptable levels.
  • Data logging available for every 15 minutes
  • Denser deployment identifying pollution at minute level.


  • Denser deployment identifying pollution at minute level.
  • Data analytical models for extrapolating the measurements at micro level and macro level.

Data Model & Datasets