Landslide Early Warning System Based on Multi Sensors and Artificial Internet of Things (AIoT) : A Review - Mudarris (Micronic: Journal of Multidisciplinary Electrical and Electronics Engineering, 2024)
Landslides occur due to shifting soil, flooding, and rainfall with high intensity of rain resulting in excessive water content in the ground. It takes a system that can acquire data in the field to predict the occurrence of landslides. Slope condition analysis is an analysis that must be carried out to find out how fast and appropriate action must be taken if the slope collapses or landslides. This study focuses on developing an effective Landslides Early Warning System (LEWS) that provides real-time information. In the literature study to understand some of the methods used based on previous research. This survey follows the steps by conducting a research question (RQ), then searching and observing previous research from the journal database. Based on ten articles, this study concludes that currently, there are various types of people who use Machine Learning taken from GIS Maps, use geosensors to detect ground shifts, detect rain to anticipate landslides on mountain slopes, and use Lo-Ra radio to transmit information on ground displacement. Based on the literature review that has been carried out, a LEWS system design using multiple sensors and the Artificial Internet of Things (IoT) can be developed.