AI-Based Forecasting of Air Quality and Pollution Levels in Pakistan
Keywords:
AI-based forecasting, air quality prediction, pollution levels, machine learning, deep learninAbstract
Air pollution in Pakistan, particularly in urban centers like Lahore and Karachi, has reached alarming levels, adversely affecting public health and the environment. Traditional air quality monitoring methods often fall short in providing timely and accurate forecasts. This paper explores the application of Artificial Intelligence (AI) techniques, including machine learning and deep learning models, to predict air quality indices and pollution levels. By integrating meteorological data, satellite imagery, and ground-based sensor data, AI models can offer real-time forecasting capabilities. The study evaluates various AI models' performance in predicting pollutants such as PM2.5 and PM10, aiming to enhance early warning systems and inform policy decisions for better air quality management in Pakistan
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