In a war field sensor network, the data collection process is based on the energy that exists in the sink node as well as in intermediate nodes. Since sensor nodes are typically much dense, data collected by sensor nodes have considerable redundancy. An effective data collection approach is developed to eliminate redundancy, reduce the number of broadcasts, and to save energy. We have deployed the new source-aware method to collect the data in a fast and efficient manner. The source- aware is needed at every node for sink conformation, which is used to find the correct next sink neighbor in the network. We propose a time situate recurrence estimation procedure (TSRE) with the support of uncertain rule sets to collect the data efficiently. This strategy follows the set of guidelines in which every node assigns different esteem for the configuration of the data collection and this range of esteems specify the feasible advantages of the data. Also, the strategy performs a time situate recurrence estimation procedure to complete the interruption identification framework with the assistance of a received sink pattern. This method recognizes the interruption effectively and produces favorable outcomes and also find a separate path in the network. In these ways all source nodes will assign each neighbor for data collection. In this network, every source will use node sink for data transmission in the system. Based on the received sink pattern, this approach improves the data collection efficiency of the task or the application being executed and reduces the energy consumption in the network. The novelty of this approach is verified by comparison with the existing method which shows enhancement in the throughput efficiency, data collection efficiency and delay minimization of the overall network.