Kaatru in Tamil stands for wind. According to the WHO, 9 out of 10 people worldwide breathe polluted air. Team Kaatru from IIT Madras aims to provide a solution for air pollution. We give our users real time data of the purity of air that they breathe. Similar to how a Google map provides a real time location of traffic in various roads, the Kaatru App will provide a real time spatial and temporal map of air pollution. 

Our project has four main components. 

  • The first part is the setting up of the air pollution monitoring hardware device. This device is assembled by our team and is deployed at specific stationary points and on moving vehicles. This device comprises of various sensors such as the Particulate Matter content in ambient air, Temperature, Humidity, Air Speed, Multiple Gas Sensors etc. 
  • These sensors are assembled along with GPS and GPRS systems which send the data about various parameters and ambient air to the central cloud server. There is also a memory card module to store the data locally. 
  • Once this data from across various locations and time reaches the server, they need to be processed for us to make sense of it. The air quality parameters are then visualized by plotting it in a 3D map. 
  • Data Analytics is used to derive insights from this huge chunk of data which are of huge business potential. Prediction algorithms and Time Series Analysis is used in order to fill any kind of missing data at any location at any point of time. 

Our team’s USP and strength lies in data analytics and modelling. It is a crucial aspect in this system, as the capital cost of these sensors are very high and the accuracy is only moderate. With this constraint, we need to map the air quality of the entire city. Mounting the devices that measure air quality onto moving vehicles is one of the best solutions to overcome this constraint. With today’s advancement in AI and ML, we are able to use the expertise in software and analytics to overcome the limitations of hardware.



Posted on

April 23, 2019

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