Federated Learning for Low-Latency IoT Communications

Many sectors have been transformed by the growth of the Internet of Things devices, but it also presents difficulties, particularly in the latency of data exchange. In this research, I suggest a unique distributed federated learning architecture for low-latency Internet of Things communications. I empower IoT devices to jointly train machine learning models without compromising data privacy by utilizing federated learning techniques. To accomplish low-latency IoT communications, the architecture prioritizes communication efficiency optimization. Use Python to create this design and provide experimental data to show how successful.