In view of the cumbersome and often untimely process of manual collection and observation of frozen soil data parameters, and the damage caused to dams by frost heaving of frozen soil, a remote monitoring and an early wing model for frozen soil in dam areas was presented. The Pt100 temperature sensors and JM seam gauges were used as measurement tools in the system. The sensor layout was designed, based on the actual situation in the monitoring area. A 4G network was used for wireless transmission to monitor frozen soil data in real time. BP neural network was used to predict the parameters of frozen soil. After analysis, four factors including the average temperature of frozen soil, the type of frozen soil, the artificial upper limit of frozen soil and the building construction time were selected to establish an early wing model using fuzzy reasoning. The experimental results showed that the early wing model could reflect the influence on dam buildings of frost heaving and sinking of frozen soil, and provided technical support for predicting the hazard level.