Precision agriculture compressed sensing and data fusion algorithm for wireless sensor networks

In order to improve the energy efficiency of WSN nodes and prolong the life of the network, reduce data redundancy. In this paper, proposed the spatial correlation node data compression and fusion algorithm based on the theory of compressed sensing. Firstly, make signal node random projection based on time correlation, then, for random routing instability and network transmission of data fusion technology reconstruction energy effects, proposed the energy consumption of compressed sensing and clustering data fusion technology. The experiment showed that after data fusion, not only effectively removes the redundant information of neighbouring nodes, and the reconstruction error is small, and can accurately realize data decompression, thereby reducing the node communication in wireless sensor network capacity, reduce power consumption of node, provides important support for the field environment in large scale wireless sensor network deployment.