Fog-Based Marine Environmental Information Monitoring Toward Ocean of Things

Abstract

The deepening of ocean measurement work requires higher transmission bandwidth and information calculation efficiency, which provides an opportunity for fog computing. Compared with cloud computing, fog computing shows distribution because it concentrates data processing and application on devices at the edge of the network. In this article, the Ocean of Things (OoT) framework is designed for marine environment monitoring based on the Internet of Things technology. The OoT is divided into three layers: 1) data acquisition layer; 2) fog layer; and 3) 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. An improved D-S algorithm is designed for multisensor information fusion, reducing the data capacity and improving data quality. In the cloud layer, we build ocean information change models based on the fog layer data to predict the dynamic ocean environment. The designed fog layer is evaluated based on marine multisensor information. The results have shown that fog-based multisensor data processing shows low time consumption and high reliability. Moreover, this article uses real temperature data sets to evaluate the prediction accuracy of the cloud model. Finally, we tested the performance of the designed OoT framework with multiple data sets. The simulation results show that the framework can improve the efficiency of data utilization at sea and improve the efficiency of information utilization.