Slope failure and debris flow cause lots of casualties and property loss. Many causalities and economic losses are caused by natural disasters, such as landslides and slope failures, every year. This critical problem motivated that there is a need for an early warning system to mitigate accidents/Failures and economic losses. Most of the studies on real-time early warning systems have been carried out by predicting landslide-prone areas, but studies related to the prediction of landslide occurrence time points by the real-time monitoring of slope displacement are still insufficient and requires further research. In this Project, a three dimensional displacement sensor, rain sensor and water level sensor along with Internet of Things (IoT) monitoring system were combined together, to monitor slope failure through cutting experiments of a real-scale model slope. Real-time monitoring of the slope movement was performed simultaneously via a low-cost, efficient, and easy-to-use IoT system. Based on the obtained displacement data, an advanced data analysis methods was performed. Finally, a slope instrumentation standard was proposed based on the slope of the inverse displacement for early evacuation before slope failure.