With the rapid development and application of Artificial Intelligence and the Internet of Things (AIoT), new challenges are posed to the network’s useful life, reliability, and coverage. The current wireless sensor network (WSN) consists of a large number of self-organizing sensor nodes deployed in monitoring areas, exhibiting advantages such as low cost, energy efficiency, self-organization, and large-scale deployment. However, how to further extend the network life and enhance the coverage reliability of wireless sensor networks remains a primary challenge in current research. To address these challenges, a coverage reliability assessment model is proposed by integrating the backbone network with coverage models, collaborative sensing of sensor nodes, and spatial correlation. Subsequently, a coverage reliability optimization algorithm based on the confident information coverage model is proposed. On one hand, the algorithm utilizes the confident information coverage model to ensure collaborative sensing of data, enhancing network service quality. On the other hand, it employs backbone network optimization for routing to conserve energy consumption. Furthermore, to validate the superiority of the proposed algorithm, sensor multi-states, and coverage rate are taken as evaluation metrics, with RMSE threshold and energy consumption as performance indicators. The proposed algorithm is compared with ACR and CICR algorithms. Finally, a verification model is built on Matlab simulation software. Simulation results demonstrate that the proposed algorithm significantly improves coverage reliability.