Using Sensors with Internet of Things for Landslide Detection System: A Systematic Literature Review

Abstract

Landslides are among the most common natural disasters in regions with high rainfall and unstable geological conditions. To improve the effectiveness of mitigating this disaster, various Internet of Things (IoT)-based early detection systems have been developed. This research uses Systematic Literature Review (SLR) approach to analyze various sensor technologies and IoT in landslide monitoring system. Based on the analysis, it was found that soil moisture sensor, accelerometer, and piezometer are the most commonly used technologies in the monitoring system. Soil moisture sensors measure the moisture content in the soil, accelerometers detect unstable soil movement, while piezometers measure soil pore pressure. In addition, communication technologies such as LoRa-WAN and Narrowband-IoT (NB-IoT) enable real-time data transmission with low power consumption and wide coverage. The results show that the use of IoT technology can improve the accuracy of landslide early detection. However, there are still some major challenges in implementing this system, mainly related to the limited network infrastructure in remote areas and the relatively high cost. Therefore, this research recommends the development of a more efficient early detection system, adaptive to extreme environmental conditions, and considering integration with artificial intelligence technology to improve prediction and response to potential landslides. Thus, IoT-based detection systems can contribute significantly to landslide mitigation and risk reduction efforts