EFFICIENT IOT-ENABLED HIGH SPEED AND ENERGY EFFICIENT EARLY LANDSLIDE DETECTION AND MONITORING SYSTEM BASED ON GEOTECHNICAL PARAMETERS

Abstract

Landslides are a growing threat in steep regions of the world, taking lives and damaging property. The recent damages caused by landslides demand that authorities pay attention to catastrophe risk mitigation strategies. One crucial risk reduction strategy is the creation of an efficient landslide early warning system (LEWS), which will allow authorities and the public at large to be informed in advance of any landslide incidents. In order to construct a system of early warning for landslides, a wireless sensing network may collect data on the geological features and a few physical surroundings characteristics. The recommended system's primary objective is to predict when a landslide could happen and alert authorities to prevent or at least minimize casualties. In this study, we show how Internet of Things-based sensors (temperature, soil moisture ,humidity) may be used to observe and alert authorities to impending landslide danger. An advanced landslide tracking system built on Internet of Things infrastructure is shown here. The system is comprised of a group of self-sufficient wearable sensors, each of which wears a sensor costume designed for tracking landslides, and a microprocessor that aggregates data from a wide variety of sensors.

Keywords

• landslide
• detection
• monitoring
• internet of things
• wireless sensors energy efficient