<p>Wireless sensor networks are rapidly expanding due to their diverse applications in various fields, including the Internet of Things. One of the main challenges in this domain is the energy limitation of sensors. While energy harvesting can extend the network’s lifetime, the amount of harvestable energy is time-varying. Thus, a technique for managing harvested energy is needed. In this paper, a simpler and more efficient method for the coverage of targets by sensors is proposed. Coverage of targets plays an essential role in the application of wireless sensor networks. Complex algorithms such as machine learning and exploration can increase sensor energy consumption. Hence, an approximate algorithm is suggested to ascertain the minimum number of sensors necessary for the coverage of targets frame by frame. Since sensors and targets are not directly correlated, this algorithm employs a bipartite graph to construct a virtual network. It uses a bipartite graph in which sensors and targets are divided into two sets, and this model is used to select the sensors that cover the most targets, helping reduce the number of sensors required. Subsequently, coloring algorithms are used to determine the minimum number of sensors capable of covering the targets. It is anticipated that this approximate approach will lead to improved energy consumption of sensors and an increased lifespan of wireless sensor networks. Using the proposed algorithm, the network’s lifespan has improved by 11.3% compared to the HSAML algorithm and by 8% compared to the RSS algorithm.</p>