@inproceedings{a8cddd912f3546f08ef9571da0139964,
title = "Application of Early Warning System for Monitoring Landslide Vulnerability of Slope",
abstract = "There are many methods to mitigate rainfall-triggered landslide haz- ards. Among the available methods, the Landslide Early Warning System (LEWS) is one of the soft-type methods. A low-cost LEWS based on the Internet of Things (IoT) was developed and tested on laboratory model tests. To verify its effective- ness the LEWS is deployed in the field. The moisture and acceleration sensors were used to collect the raw data on moisture content and tilt angle. Both types of sensors were embedded in the monitoring holes within the slope at different depths. A rain gauge was also installed to support the rainfall data obtained from the Japan Meteorological Agency (JMA). The result shows that the deployed system is able to effectively measure the moisture contents and soil deflection angles.",
keywords = "Early Warning System, Landslide, Monitoring, Rainfall, Sensor",
author = "Hidayat, {Muhammad N.} and Hemanta Hazarika and Masanori Murai and Haruichi Kanaya",
note = "Publisher Copyright: {\textcopyright} The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.; 7th International Conference on Geotechnics, Civil Engineering and Structures, CIGOS 2024 ; Conference date: 04-04-2024 Through 05-04-2024",
year = "2024",
doi = "10.1007/978-981-97-1972-3_86",
language = "English",
isbn = "9789819719716",
series = "Lecture Notes in Civil Engineering",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "772--780",
editor = "Cuong Ha-Minh and Pham, {Cao Hung} and Vu, {Hanh T. H.} and Huynh, {Dat Vu Khoa}",
booktitle = "Proceedings of the 7th International Conference on Geotechnics, Civil Engineering and Structures, CIGOS 2024 - Advances in Planning, Architecture and Construction for Sustainable Development",
address = "Germany",
}