Factors affecting landslides and IoT-based slope monitoring system in Southeast Asia: a review

Abstract Landslides are natural disasters that cause devastating damage to surrounding communities and infrastructure. Southeast Asia (SEA) is a hotspot for landslide occurrence, highlighting the need to understand the underlying mechanisms and contributing factors. The main landslide triggering factor across SEA is rainfall, as increased moisture leads to a decline in soil shear strength and matric suction. Slope monitoring systems are essential for providing early warnings by continuously tracking slope conditions. In recent times, Internet of Things (IoT)-based slope monitoring systems have undergone extensive development and are generally structured into four layers: (i) a sensing layer containing in situ sensors, (ii) a network layer facilitating data transfer, (iii) a platform layer where data computing occurs, and (iv) an application layer allowing user access. Previous systems have primarily monitored soil displacement and soil moisture, while the vegetation cover is often overlooked, despite its critical role in stabilizing slopes and influencing hydrological responses. Key challenges for IoT slope monitoring systems include high energy consumption due to remote sensor locations, data processing limitations resulting from large input, setup cost constraints, and the limited diversity of monitored parameters. Future studies should aim to overcome these challenges and enhance landslide prediction models for more reliable early warning systems.