Geo AI Tech To Monitor, Predict Air Quality Across India: ISRO Chair Professor
The Geo Artificial Intelligence and Random Forests-based tools and technologies will predict and monitor air quality for Delhi, Mumbai, Bengaluru, Chennai, Kolkata, and other cities of India to help achieve Sustainable Development Goals (SDGs), informed Prof. P G Diwakar, ISRO Chair Professor, National Institute of Advanced Studies while addressing the gathering at India Clean Air Summit (ICAS) 2023, a premier event on air pollution, organised by the Centre for Air Pollution Studies (CAPS) at the Center for Study of Science, Technology, and Policy (CSTEP).
Prof. Diwakar said that these computer-based tools are being harnessed in India to pool data from different sources. “We must link up SDGs and air pollution indicators, as highlighted by the United Nations 2030 Agenda. Particularly in the context of SDGs 3.9 which reflects on health-related issues, and SDG 11.6, which reflect on cities and liveability indices in them. Using geospatial technology, we need to create well-distributed ground observation points to measure in-situ pollution parameters, which can further be integrated with space data for modeling. These multi-parametric sensors should be strategically placed to collect data from all representative points in a city or township.”
He added that when we do mathematical modeling for seamlessly estimating pollution, on how air pollution can be addressed, it is necessary to have a geospatial outlook and modeling based on space and ground observations for Particulate Matter (PM), Nitrogen Oxides (NOx), (SOx), etc., and it could be linked to Aerosol Optical Depth (AOD), derived from Satellites sources, like, INSAT-3D/ 3DR, MODIs etc. “We need to bring in the weather data into the modelling framework, such as, wind speed, wind direction, surface air pressure, temperature, humidity, etc, that play a major role as part of the model. The estimation of road fractions based on road type and carrying capacity in an urban setup is critical as they are the cause of a lot of pollution in the urban setup, and all these could be well-integrated into numerical models to build forecasting and assessment. These have been tested for Bengaluru and very good results have been seen. We are also building geo-AI models that use classic Machine Learning and random forest theory, among others to provide not only current estimates seamlessly, but also forecasts effectively. These models that use data from ground and space can be very well integrated for a better life tomorrow,” Prof. Diwakar informed.
AI is the ability of a computer to do tasks that are usually done by humans, and for this, they require human intelligence and discernment. whereas Random Forest is a machine learning algorithm, which combines the output of multiple decision trees to reach a single result. In both these cases, historical data becomes very essential. We have already compiled about 50 years of historical data, basically from various satellite sources, and we are also stacking all the possible ground-based observations.
Detailing the project, Prof. Diwakar said: “We have initiated a pilot project in Bangalore and are actively assessing its effectiveness. Our aim is to extend this technology to predict and monitor air quality in heavily polluted cities such as Delhi, Mumbai, Chennai, Kolkata, and others. With unwavering confidence in our model’s capabilities, we will leverage historical data to predict and validate present air quality — an unprecedented feat in our country’s history. Our approach utilises conventional Artificial Neural network techniques, integrating diverse inputs from both space and ground sources to construct a robust predictive model. Spearheaded by the National Institute of Advanced Studies (NIAS), this project is set to be a collaborative effort among various groups.
Emphasising the crucial role of geospatial data, the model will operate within a comprehensive geospatial framework. All data will seamlessly integrate into the meticulously curated geospatial database. “As progress is made, the focus will extend beyond air pollution to encompass broader SDGs, addressing issues such as water pollution, electromagnetic radiation, and more. This holistic initiative reflects the commitment to pioneering transformative solutions that transcend conventional boundaries,” said Prof. Diwakar.
With the assistance of advanced technological interventions, India has seriously initiated the process to implementing the SDGs, and the results are getting noticed and acknowledged globally. For example, Prof V. Faye McNeill, Professor, Departments of Chemical Engineering and Earth and Environmental Sciences at Columbia University, has made certain observations with regard to India making major strides towards clean air and the groundwork being laid to achieve the goal.
Speaking on the occasion, Selvi PK, Scientist, Central Pollution Control Board, said, “Within the expansive realm of SDGs, a staggering 248 indicators illuminate our path. When we assess and rank our nation, these indicators become our guiding stars. This comprehensive approach encompasses diverse dimensions, spanning from air and water quality to various forms of pollution. As custodians of pollution control, our mission aligns with the National Clean Air Program (NCAP) to curtail PM2.5 and PM10 by 30-40 per cent by 2026.”
“Through innovative schemes like Extended Producer Responsibility (EPR), we’re tactfully reducing emissions across waste streams, whether it's plastics or e-waste. Monitoring NCAP’s progress, Prana stands as a testament, ushering transparency through centralised data. This very mechanism, we believe, holds the potential to seamlessly oversee the entirety of our initiatives, including the broader canvas of SDGs,” Selvi added.
