Processing Complex Events in Fog-Based Internet of Things Systems for Smart Agriculture

The recent growth of the Internet of Things' services and applications has increased data processing and storage requirements. The Edge computing concept aims to leverage the processing capabilities of the IoT and other devices placed at the edge of the network. One embodiment of this paradigm is Fog computing, which provides an intermediate and often hierarchical processing tier between the data sources and the remote Cloud. Among the major benefits of this concept, the end-to-end latency can be decreased, thus favoring time-sensitive applications. Moreover, the data traffic at the network core and the Cloud computing workload can be reduced. Combining the Fog computing paradigm with Complex Event Processing (CEP) and data fusion techniques has excellent potential for generating valuable knowledge and aiding decision-making processes in the Internet of Things' systems. In this context, we propose a multi-tier complex event processing approach (sensor node, Fog, and Cloud) that promotes fast decision making and is based on information with 98% accuracy. The experiments show a reduction of 77% in the average time of sending messages in the network. In addition, we achieved a reduction of 82% in data traffic.

Automated summary

The growth of Internet of Things services and applications has led to increased data processing and storage requirements. The concept of Edge computing leverages the processing capabilities of devices at the network edge, with Fog computing providing an intermediate processing tier that can reduce end-to-end latency, data traffic, and Cloud computing workload. Combining Fog computing with Complex Event Processing and data fusion techniques has the potential to generate valuable knowledge and aid decision-making processes in IoT systems.