IIT Madras researchers develop Data Science & IoT-based pollution monitoring method

Mobile air quality sensors would find extensive use in both personal and public health initiatives.

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.

Elaborating on the findings of this Research, Prof. Raghunathan Rengaswamy, Faculty, Department of Chemical Engineering, IIT Madras, said, “Interestingly, one specific location showed a significant spike of PM2.5 pollution between 2 am and 3 am. This was associated to trucks carrying milk from a major milk distribution hub in this location at this time. PM2.5 spikes were also found in school neighbourhoods during school start and end hours and in commercial zones during peak hours.”

Prof. Raghunathan Rengaswamy added, “Mobile air quality sensors would find extensive use in both personal and public health initiatives. Personal monitoring devices can help people know the extent of pollution in their neighbourhood so that they can take protective measures. Traffic can be rerouted if local pollution levels are known. Government policy changes and smart city planning would benefit enormously from the use of mobile air quality trackers. Our affordable IoT based mobile monitoring network, coupled with data science principles offers unprecedented advantage in gathering hyperlocal insights into air quality. It is the only viable option at present, capable of offering high spatio-temporal awareness that could allow for informed mitigation and policy decisions.”

The devices are capable of measuring 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.

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