Towards Cleaner Skies : Transforming Air Quality Prediction in Smart Cities with Artificial Intelligence

Air quality management is a critical concern for urban environments facing rapid population growth and increasing pollution levels. Smart cities leverage advanced technologies like the Internet of Things (IoT) and Artificial Intelligence (AI) to tackle this challenge. This study explores the role of AI in predicting air quality, with a specific focus on its applications in smart cities. Using a systematic literature review (SLR), we analyze data collection methods, predictive modeling techniques, and performance evaluation metrics. The results highlight the potential of machine learning and deep learning models in improving prediction. However, challenges remain, including data quality, contextual variability, and resource-intensive implementation. Our findings underscore the need for further research to optimize AI-driven solutions for urban air quality management, ensuring healthier and more sustainable cities.