Landsliding Early Warning Prototype Using MongoDB and Web of Things Technologies

Abstract

Nowadays Wireless Sensors Networks (WSN) are intensively used for environment monitoring. As a bridge to the physical world, WSN can gather handy data even in hazard sites. Access to hazard data is particularly crucial when anticipating risks of disasters. When integrated into the Web of Things and a Big Data database, the WSN offers a promising way to sketch an online picture of the monitored site. The paper describes a prototype of a landsliding risk early warning system hosted by a Web of Things technology and MongoDB as a Big Data database. The developed prototype collects and displays runtime telemetry observations on precipitation, soil movement and soil moisture forwarded by sensors. Sensors nodes are implemented in a Tunisian landsliding high risk zone. Embedded daemon scripts trigger specific warning alerts when some bounded values are reached.