Federated learning is an innovative approach to machine learning that allows smart devices to learn from data while keeping it on the device, rather than sending it to a central server for processing. This decentralized approach not only enhances privacy and security but also enables more efficient use of resources, making it an ideal solution for smart cities and the Internet of Things (IoT) devices that power them.
Smart cities are urban areas that use technology and data to improve the quality of life for their citizens, optimize resource consumption, and enhance overall efficiency. IoT devices play a crucial role in smart cities, collecting and processing data from various sources such as traffic sensors, air quality monitors, and energy meters. This data is then used to make informed decisions and implement effective policies.