IIT Madras Developes Low-cost Methods For Mobile Pollution Monitoring

Indian Institute of Technology Madras (IIT Madras) Researchers have developed a low-cost mobile air pollution monitoring framework in which, pollution sensors mounted on public vehicles can dynamically monitor the air quality of an extended area at high spatial and temporal resolution.   

Traditionally, ambient air quality is measured in monitoring stations and reported as ‘Air Quality Index’ (AQI). Since these stations are at fixed locations, they only measure the air quality of a small geographic area.  

Air pollution however is dynamic with locations just a few hundred meters away from each other exhibiting different levels of pollution. Levels can also vary at different times of the day. However, setting up more stations is not practical because of the high costs. 

Towards tackling this issue, IIT Madras Researchers, have developed a new IoT-based mobile air pollution monitoring technology wherein low-cost air quality sensors are mounted on vehicles to gather spatio-temporal air quality data. For the cost of a single reference monitoring station, it would be possible to map an entire city at high resolution using these low-cost mobile monitoring devices.   

Led by Prof. Raghunathan Rengaswamy, Dean (Global Engagement) and Faculty, Department of Chemical Engineering, IIT Madras, Project Kaatru (air in Tamil) leverages IoT, big data and data science to achieve the following goals: 

• Obtain pan-India hyperlocal air quality map 

• Exposure assessment for each Indian citizen 

• Data driven solutions for policy, intervention and mitigation strategies 

The devices can measure multiple parameters, ranging from PM1, PM2.5, PM10 and gasses such as NOx and SOx. In addition to pollutants, the devices can assess road roughness, potholes and UV index among others. The modular design of the device allows for sensors to be replaced on demand. Figure 1 shows the parameters that can be sensed by the IoT mobile monitoring devices.  

The patented IoT side view mirror design enables the devices to be retrofitted on any kind of vehicle, ranging from buses to cars and even two wheelers.  

The IoT devices are also equipped with GPS and GPRS systems to collect and transmit location information. Data Science principles are used to analyse the large volume of data generated from these IoT devices.