One of the most essential aspects of Wireless Sensor Networks (WSN) is its energy usage. Many people are interested in it. According to current studies, energy usage in WSN is a difficult issue since energy is a finite resource. Sensor nodes require this energy to function. Energy consumption should be minimised in order to maximise network longevity. In a cluster-based WSN, the cluster head, or cluster leader, is responsible for data gathering, consolidation and exchange with the base station from member nodes. As a result, load balancing in WSNs is a difficult task for maximising network longevity. Because all sensor nodes in a homogeneous network have the same degree of energy, selecting a cluster head will cause it to expire much sooner than a typical node because it must perform more tasks. As a result, we must change the cluster heads on a regular basis to keep the load balanced and the network operating for longer. To address this problem, we employed a novel fitness function and a Gaussian Integrated Bat Algorithm (IBA) to properly balance the load on the network. To determine various performance elements of the proposed load balancing technique, we ran comprehensive simulations. The experiments’ results are promising, indicating that the recommended technique is feasible.