Choosing the best performing nodes in a wireless sensor network to monitor a target may reduce the total number of working nodes while meeting the need for global tracking reliability. However, the vast majority of recent studies choose sensor nodes that are geographically near to the target rather than those that are correlated with the precise spot of the objective. Consequently, these solutions cannot satisfy all network objectives. The wireless sensor network (WSN) is an integral part of the Internet of Things. The expansion and use of the Internet of Things have increased the need for heterogeneity in WSNs. The rapid depletion of batteries has been a significant barrier to future research into the potential of wireless sensor networks (WSN). The optimisation of battery life in WSNs has garnered considerable focus. Nonetheless, a long-lasting WSN depends on an effective cluster chief election method. In this context, it is suggested that the informational value of sensing nodes be measured using a joint distance-weighted metric. In experiments, EANS has been shown to be better than state-of-the-art methods because it uses less energy and is easier to compute while keeping tracking precision.