Wireless sensor networks (WSNs) are popular in real world applications. Because of the characteristics of the resource-constrained and battery-aware sensors; in WSNs energy used has establish to be a major interesting subject of research. WSNs compose battery-powered nodes which are connected with the base station to for definite action or task. As sensor nodes are battery-powered i.e. it has become dead subsequent to the consumption of the battery which is also called lifetime of WSNs. So utilizing the energy in well-organized way has results in prolonging the lifetime of the WSNs. The general aim has to get the drawbacks of the BEENISH i.e. well known multi-level heterogeneous energy aware protocol. In BEENISH ultra-super nodes are mostly elected as CH as compare to super, advance and normal nodes, and so, on. In this way energy inspired by all nodes is equally distributed. But BEENISH has neglected the utilization of intercluster data aggregation which has reason flooding. So to overcome this issue a new inter cluster data aggregation and neural network based BEENISH protocol has been proposed. Neural network has improved the cluster head selection of the BEENISH utilizing the various factors such as range of neighborhood of individual nodes, nodes waiting time etc. MATLAB tool will be used to design and implementing the performance of the given protocols.