A Model for Low Power, High Speed and Energy Efficient Early Landslide Detection System Using IoT

A landslide, also called as landslip appear to be the most threatening disaster of all time especially in the hillside regions. It involves enormous surface movements including debris flows, slopes failure, rock fall etc. It mainly occurs when the land slopes become unstable. Other measures that als...

Full description

Saved in:
Bibliographic Details
Published inWireless personal communications Vol. 117; no. 4; pp. 2713 - 2728
Main Authors Dhanagopal, R., Muthukumar, B.
Format Journal Article
LanguageEnglish
Published New York Springer US 01.04.2021
Springer Nature B.V
Subjects
Online AccessGet full text

Cover

Loading…
More Information
Summary:A landslide, also called as landslip appear to be the most threatening disaster of all time especially in the hillside regions. It involves enormous surface movements including debris flows, slopes failure, rock fall etc. It mainly occurs when the land slopes become unstable. Other measures that also lead to landslides are Ground water changes, Earthquakes, Floods, Volcano eruptions and Heavy rainfalls. People among these hill areas doesn’t know about the disaster that’s about to happen massively. The perfect way to avoid such hazards is by predicting it at initial phase with maximum accuracy. There are many wired and wireless supervising systems available to detect landslides which require higher cost and maintenance. But we have a suitable solution for this with Internet of Things (IoT) based approach. It improves objects control and detection remotely between various networks thereby creating possibilities for direct communication between physical and computer-based world. By this approach Landslides can be predicted at the initial phase. If there is a higher chance of Landslide then an alert will be sent to disaster management sector immediately to take necessary precautions so that enormous precious lives can be protected. This paper proposes a model for IoT based Landslide detection mechanisms in detail.
ISSN:0929-6212
1572-834X
DOI:10.1007/s11277-019-06933-7