Air Quality Monitoring (AQM) and Prediction: Transitioning from Conventional to AI Techniques

Deterioration of air is one of the important factors which is due to natural and anthropogenic reasons, hence its accurate monitoring and prediction are important as it has a lot of negative impact on society. In this chapter, the traditional method of air quality measurement will be discussed by considering its fundamentals and common principles behind it. Advancement is required in the conventional methods for more accuracy and large set data, hence different artificial intelligence (AI) techniques come into existence, therefore there will be a discussion about the transition from conventional techniques to AI. The current state-of-the-art in air quality measurement utilizing Machine Learning (ML) and Deep Learning (DL) techniques will be interpreted from 2022. Comparative analysis of conventional techniques concerning AI techniques will be discussed by considering major challenges and the future direction of air quality monitoring. In the Conclusion, we can say that balanced solutions between the strengths and weaknesses of both methodologies are needed in the present scenario for better air quality measurement and prediction.