Back Propagation Neural Network-Based Routing Optimization for IoT

The Internet of Things (IoT) has fundamentally changed how we engage with the environment that surrounds us by facilitating the connection of various devices and the flow of data between them. However, as the complexity of IoT networks increases, effective routing becomes more and more important to guarantee that data transfer and network performance are at their best. It is possible that traditional routing algorithms would not be able to manage the size and fluidity of Internet of Things networks. Optimizing the routing of Internet of Things devices has necessitated the use of more cutting-edge methods, such as the Back Propagation Neural Network (BPNN), which has been developed by researchers. In this research paper, we provide a unique strategy to handle the routing optimization issue in IoT by employing BPNNs. Back Propagation Neural Networks is a kind of neural network. By using the tremendous capabilities of artificial neural networks, the BPNN-based routing optimization intends to improve the efficacy of IoT networks as well as their adaptability.