This repository contains the Python implementation for 'Explainable Air Quality Management.' It features federated learning with adaptive model aggregation, quantum-optimized hyperparameter tuning, SHAP-based explainability, and anomaly detection using PrefixSpan. The system enhances AQI prediction and interpretability across IoT sensor nodes. The dataset used in this study, "Explainable Air Quality Management: Adaptive Federated XGBoost Enhanced by Quantum Optimization and SHAP Analysis", is publicly available on Kaggle at https://www.kaggle.com/datasets/saghar001/air-quality-prediction-case-study.