Landslide early warning systems: a perspective from the internet of things

Vladimir Henao-Céspedes, Yeison Alberto Garcés-Gómez, María Nancy Marín Olaya


Populations located in the vicinity of slopes and soils derived from volcanic ash are constantly at risk due to the possibility of landslides. Such is the case of the city of Manizales, Colombia, which, due to its geomorphological characteristics, has experienced a significant number of landslides that have caused human and economic losses. The Internet of things (IoT) has allowed important technological advances for monitoring, thanks to the low cost and wide coverage of IoT-based systems. Slope monitoring and the development of landslide early warning systems (EWS) have been positively impacted by IoT developments, which shows a relationship. The objective of this article is to review, from the scientific production, the relationship between IoT and EWS. For this purpose, a fragmenting-deriving-combining methodology is applied to focus on a research trends analysis of the subject, from macro-areas such as IoT and EWS to micro areas such as EWS by IoT-based landslides. Finally, the analysis concluded that the conceptual models of IoT and EWS for landslides have some correspondence in some of their layers.


early warning system; internet of things; landslide; risk; scientific production;

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International Journal of Electrical and Computer Engineering (IJECE)
p-ISSN 2088-8708, e-ISSN 2722-2578

This journal is published by the Institute of Advanced Engineering and Science (IAES) in collaboration with Intelektual Pustaka Media Utama (IPMU).