Air pollution is considered one of the grievous issues now, which is responsible for almost 11,000 deaths per year at the moment and will be rising as the population continues to increase. As per the reports, more than 160,000 people could die in the next decade from strokes and heart attacks due to air pollution, similar to more than 40 heart and circulatory disease deaths related to air pollution each day.   

Air pollution is defined as the presence of toxic chemicals or compounds in the air at levels that pose a health risk. In a much broader sense, air pollution is the presence of elements in the air that are not present or have a lower ratio in the air. Such pollution causes detrimental changes to our quality of life by damaging the ozone layer or even leading to a global war. According to reports, around 4.2 million premature deaths were caused by poor outdoor air in 2016, among which 90% of them in low and middle-income countries (Nat Geo 2019). Air pollution is counted as the fourth largest threat to human health after BP, dietary risk and smoking, per the World Economic Forum. Climate change and pollution being the hot topic, the significance of Artificial Intelligence in this area also draws attention. Researchers believe AI will be at the forefront of this battle for life.  

AI is predicted to create knowledge, improve air quality management and assist in analysing air pollution. What makes it more interesting is that there is no limit to the understanding that AI might require to make these kinds of forecasts. The opportunities and potential of AI are getting broader with the arrival of breakthroughs in the field.   

AI and air pollution  

We have been witnessing the flourishing of AI and a vigorous rise in integrating AI into various sectors in India. The hyperlinking connection of AI into each detail present is only because of its continuous updation, which boosts human efficiency and discovery. As expert systems are undergoing regular advancements, it is significant to realise their implication in an area beyond businesses and other common industries. The challenge brings a rhetorical shift from human-friendly AI to Earth-friendly AI, which requires completely harnessing knowledge base systems to build a sustainability revolution. After studying 80 AI apps, PwC has documented how AI is assisting us in changing the game on the issue of air pollution.  

• Weather and climate science and forecasting: deep learning networks and energy-intensive computing assist in forecasting the difficulties of ‘real world’ systems into calculations. This has increased forensic discoveries and prognoses.   
• Smart disaster response: Instilling simulations and analysing real-time data of weather events. Benefits are extended to disaster preparation, signalling early warnings and prioritising responses.   
• Autonomous and electric vehicles: They help reduce greenhouse gas emissions and deal with ecological driving, thereby setting a transition for the future.   
• Energy source optimisation: upholding the demand and supply of energy sources, AI has assisted in prolonging weather conditions by integrating the reliability of such power sources for a global incentive.   

Barriers to AI adoption in India’s climatic scenario  

As per the research journal published by the Asian Journal of Management, the following are the potential barriers for India in its track to apply AI:  

• Absence of data ecosystems: The current data situation in India needs to be much more promising for Artificial Intelligence to grow as a portfolio across industries. By ‘enabling data’, they refer to the required volume of data that AI tools will utilise to produce an output efficiently. This output can be quantitative or qualitative according to the task performed.   
• Low intensity of AI research: India is a developing country with massive potential for Artificial Intelligence in every major sector. However, the level of core research being conducted for fundamental research is relatively low. Also, most companies try hard to complete the transformation of core research into applications for the market.   
• Inadequate availability of AI expertise, workforce and skilling opportunities: Artificial Intelligence is a complex concept which requires expertise and workforce to master. However, India has yet to reach the level of skilling opportunities it needs to compete globally.   
• High resource cost and low awareness of AI adoption in business processes: The cost of implementing Artificially Intelligent business processes has been increasing in the last decade in India. This is due to the lowered awareness of these functions arising from a need for more investment.   
• The issue with cultural barriers: Human beings are famous for resisting change. We are creatures of habit, and once we develop a system of conducting a mission that seems to effectively and efficiently get the job done, we prefer it. It often takes some encouragement before we witness the total gains Artificial Intelligence will bring. Also, we will then understand the worth of the disruption and expense that will inevitably be caused by changing procedures or adopting new processes. 

• https://www.researchgate.net/publication/343550628_Application_of_Artificial_Intelligence_in_Curbing_Air_Pollution_The_Case_of_India
• Photo by Chris LeBoutillier on Unsplash