Fog-based Marine Environmental Information Monitoring Towards Ocean of Things
The deepening of ocean measurement work requires higher transmission bandwidth and information calculation efficiency, which provides an opportunity for fog computing. Compared to cloud computing, fog computing shows distribution because it concentrates data, processing, and application on devices at the edge of the network. In this paper, the Ocean of Things (OoT) framework is designed for marine environment monitoring based on IoT technology. The OoT is divided into three layers, including data acquisition layer, fog layer, and cloud layer. In the fog layer, in order to complete the quality control of the sensor measurement data, we use the numerical gradient based method to process the original acquisition data. And improved D-S algorithm is designed for multi-sensor information fusion, reducing data capacity and improving data quality. In the cloud layer, we build ocean information change models based on fog layer data to predict the dynamic ocean environment. The designed fog layer is evaluated based on marine multi-sensor information. The results have shown that fog-based multi-sensor data processing shows low time consumption and high reliability. Moreover, this paper uses the real temperature datasets to evaluate the prediction accuracy of the cloud model. Finally, we tested the performance of the designed OoT framework with multiple datasets. The simulation results show that the framework can improve the efficiency of data utilization at sea and improve the efficiency of information utilization.