Drones have lots of uses in different areas, but merging them into city airspace brings unique challenges for navigation and traffic control. To tackle these issues, this chapter looks at mixing blockchain and machine learning with drone routing and navigation systems. It dives into two main topics: systems for decentralized drone traffic control and protocols for decentralized coordination, highlighting how blockchain can help drones in communication/routing. Next, it lays out a plan for using blockchain, machine learning, and adaptive routing and navigation together showing how these technologies might team up to make drone operations better. Also, it aims to shed light on the hurdles of blending blockchain with drone navigation networks and the snags that arise when creating and rolling out machine-learning-based drone navigation systems. Some key issues covered include handling data in real-time growth of the system, keeping things private and secure, making different systems work together, following rules, saving energy, and limits on processing real drone data, plus factors like the environment, dynamic cityscapes, and bringing data together. By taking a deep look at these challenges, this chapter gives valuable insights and useful tips for people working on or studying drone navigation to attain sustainable growth in the smart city environment.