The goal of this study is to reduce the energy consumption of the sensing network and enhance the overall life cycle of the network. This study proposes a data fusion algorithm for wireless sensor networks based on improved ant colony optimization (IACO) to reduce the amount of data transmitted by wireless sensor networks (WSN). This study updates pheromones for multiple optimal routes to improve the global optimal route in search function. The algorithm proposed in this study can reduce node energy consumption, improve network load balancing and prolong network life cycle. Through data fusion, regression analysis model and information processing of each node, this study uses an improved ant colony algorithm to identify the transferals avoid superfluous energy waste caused by long-span network transferal, set the shortest route and transmit data to the central node. The algorithm proposed in this study is conducive to improving the life cycle and stable network, that is, the most suitable and effective way to improve the energy consumption rate of the sensing nodes.