Federated learning revolutionizes machine learning by enabling collaborative training across decentralized nodes, without centralized data aggregation. Beyond privacy, it enhances system adaptability, robustness, security, and collaboration. This research leverages federated learning to optimize global systems, addressing challenges and fostering innovation in real-world distributed scenarios. With a focus on adaptability, robustness, and collaboration, the project redefines machine learning deployment in various sensitive contexts, including global energy distribution, personalized mobility, drone transportation within the Honda Research Institute EU (HRI-EU).