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As an important data scheduling tool, wireless sensor network is an effective way for human to interact with nature. However, the number of sensors in wireless sensor networks is limited and easily affected by irrelevant factors. Therefore, this paper proposes a non-uniform clustering routing algorithm based on the interval type-2 TSK fuzzy system and efficient data fusion. The clustering is to minimize network losses to the greatest extent and extend its life time. The general clustering method may lead to load imbalance. Heterogeneous classification and clustering were performed. At the same time, the efficient data fusion technology is introduced to divide the scheduling process into several cycles, use the time gap for data acquisition, and reduce the dimension operation to further improve the efficiency of data transmission. On the MATLAB platform, this algorithm and the other four algorithms, such as adaptive clustering level, are analyzed and tested, and they are divided into monitoring ranges of 200m×200m and 1000m×1000m. The experimental results show that in monitoring areas of different sizes, the clustering effect, network throughput and node loss rate indexes of the algorithm used in the study are as follows: Are obviously due to other algorithms. In a small range, the average residual capability of the algorithm is improved by 49.7% compared with the adaptive clustering hierarchical algorithm. In a large range, the HND index of the proposed algorithm is improved by 98.7% compared with the adaptive clustering hierarchical algorithm. Therefore, the algorithm adopted in this study has excellent performance.