Amid rising urbanization and environmental challenges, sustainable solutions are increasingly vital. This paper examines the role of green roofs and vertical gardens in enhancing urban resilience by reducing air pollution. By integrating these green infrastructures with the Autoencoder-Decoder-based Long Short-Term Memory (AeD-LSTM) model, cities can significantly lower pollution levels and improve air quality, promoting healthier living environments. The research quantifies the pollution reduction potential of these green strategies, showing significant decreases in pollution levels post-implementation. It also highlights the synergistic advantages of combining green roofs and vertical gardens, contributing to more resilient urban ecosystems. The findings offer important insights for urban planners and policymakers advocating for green infrastructure to improve urban resilience and sustainability. The proposed model achieves 30 and 40% better accuracy in terms of \(R^{2}\) -score and custom accuracy metrics, respectively. Also, this paper demonstrates a 30% energy savings using the energy consumption metric from the multi-LSTM autoencoder model.