Data Fusion in Wireless Sensor Network using Simpson's 3/8 rule

Wireless Sensor Network (WSN) is an anthology of distributed sensor nodes that constantly monitors physical and ecological conditions. Depending on the application, node count in WSN ranges from few hundreds to thousands. A node in Sensor Network constantly monitors and communally passes their data through the network to a Sink Node. Based on literatures, a trivial issue in densely deployed sensor network, the data collected from adjacent nodes has higher level of similarity and data redundancy. To overcome the redundancy issue, the proposed method called “Numerical Integration Technique” includes - Simpson's 3/8 rule to reduce data redundancy. On performance analysis, the proposed method achieves higher rate of data aggregation compared to Kalman Filter and minimizes energy utilization caused by not transmitting the redundant data.