Optimizing Air Pollution Forecasting Models Through Knowledge Distillation For Indian Cities

Air pollution is a problem in cities that are growing really fast. In cities in India like Delhi, Mumbai and Chennai the air is often too polluted because of things like cars, factories and a lot of people. It is very important to know what the air will be like ahead of time so the government and people who take care of the environment can do something about it and warn people when the air is bad. This project is about making a system to predict air pollution using special computer techniques. The system uses two things: Graph Convolutional Networks and a special kind of model called Transformer-enhanced Gated Recurrent Unit. These help figure out how pollution works in areas and how it changes over time. The Graph Convolutional Networks part looks at how different air monitoring stationsre related and the Transformer-enhanced Gated Recurrent Unit part looks at how pollution changes from one time to another. To make the system work better it also uses something called knowledge distillation. This is where a big complicated model teaches a model what it knows. This helps the system work faster and use computer power while still being accurate. So the system can be used in time to monitor the environment. The system takes air quality data from monitoring stations gets it ready to use finds features about the area and time and then predicts what the pollution will be like in the future. This system is better than ways of predicting pollution because it uses a combination of special computer techniques. This system can be used in real-world situations like watching the environment in cities warning people about health problems warning about pollution and managing smart cities. By giving predictions the system can help people in charge make good decisions to reduce pollution and keep people healthy. Air pollution forecasting like this can really. The system can support many different applications, like urban environmental monitoring and public health advisory systems because air pollution is a major concern.