Wireless sensor networks generally have unique lifetime necessities. In any case, the density of the sensors may not be sufficiently substantial to fulfil the coverage requirement while meeting the lifetime constraint in the mean time. Once in a while coverage has to be traded for network lifetime. The proposed efficient pipeline based spatial temporal optimization scheduling for coverage optimization satisfies the coverage problem while meeting the lifetime constraint at the same time. In the proposed optimal scheduling, initially number of nodes in the network is clustered by using energy based one hop clustering algorithm. After the formation of clusters pipeline based spatial temporal optimization algorithm is used for the optimal scheduling. Here the optimization is improved by using trust of each sensor nodes and the area of clusters. Finally, data is aggregated through the optimally scheduled cluster nodes. The experimental results show that our proposed optimization scheduling substantially outperforms other schemes in terms of network lifetime, coverage redundancy and convergence time. © 2019, Springer Science+Business Media, LLC, part of Springer Nature.