The increase in heavy rainfall events has contributed to the increase in floods and slope failures. These natural disasters can lead to severe loss of human lives. Monitoring and early warning may be the most promising ways to reduce the damage caused by natural disasters. Low-power wide-area networks (LPWANs) are new and efficient techniques for establishing monitoring methods. In this study, a new type of monitoring system, employing three types of LPWANs, was introduced. Radio wave propagation tests, monitoring data, and the effect of temperature on the inclination data were explained. The radio wave propagation tests were used to determine the proper locations for the gateway (GW) and sensors that comprise the monitoring system. The system was able to successfully collect the measurement data at each observation site. However, errors were still found in the measurement data for several reasons, such as electrical circuit problems, battery problems, and environmental effects. Moreover, an unstable correlation between temperature and the inclination data was observed. Thus, the moving average filter was applied in order to smooth out the fluctuations in the inclination data. Nonetheless, random noise was still present in the inclination data. It was determined, therefore, that only long-term inclination data trends should be used to predict displacement data.