PROBABILISTIC REAL-TIME DATA FUSION IN WIRELESS SENSOR NETWORKS WITH ZIGBEE

In dense wireless sensor networks, data fusion techniques can be used to increase decision dependability. Typically, applications consume data in a periodic fashion imposing firm deadlines in messages sent and in data fusion task. This paper considers a dense network, connected by Zigbee technology. A probabilistic real-time parallel data fusion approach was developed. It is proposed an algorithm that enables the master node to adapt itself to the network density. The approach increases significantly power consumption efficiency and allows a tradeoff between quality of data fusion and power consumption efficiency.