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LONG RANGE LANDSLIDE EARLY WARNING DEVICE.

Authors: Ramon P. Flores, Cheerobie B. Aranas and Maricel M. Matuto.;

LONG RANGE LANDSLIDE EARLY WARNING DEVICE.

Abstract

The project Long Range Early Warning Device for Landslide was designed to measures the current movement and moisture content of the soil, that includes the device?s position and orientation that sends the data to base station every 2 minutes. The device is connected to a pole while its base is buried securely to the ground. The device used wireless telemetry system using high powered RF Transceivers connected with Yagi antenna. It supports directional long-range communication; base station and remote station is positioned with the distance of 2.74 km line of sight. The data will be sent to the cloud and can be accessed in public viewing through www.thingspeak.com (free version; it is an IOT analytics platform service) The device has LED indicator light that is serves as devices transmit - receive status. Red light indicates standby mode while green indicator light activates when data was received. There are three categories that the landslide micro monitor displays; normal environmental, alert level 1 as low hazard, and its status show high hazard landslide occurrence when it reaches alert level 2. At the base station; Alarms will be based on the type of hazards the data gives. The methodology used in the study was scaling method to provide the efficient and effective output. The installation of the device within the areas susceptible to landslide provide satisfactory as a result of the analysis in the following: a) Soil moisture and movement detection testing regarding the percentage of the moisture content and the tilting of the device. b) The warning station provides level of alarms when a transmitter was triggered on its hazard level.

Keywords

base station IOT Landslide remote station Warning Device.

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This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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