In many environmental monitoring applications, since the data periodically sensed by wireless sensor nodes usually
are of high temporal redundancy, prediction based data aggregation is an important approach for reducing data
communication and saving sensor nodes’ energy. We proposed a temporal correlation based data aggregation scheme in
this paper which utilizes time series model to predict the data of next several periods at both ordinary sensors and
aggregators based on the same amount of recent sensed values. We show through experiments that our proposed scheme
can provide considerable aggregation ratio while maintaining a low prediction error rate.