Sensor based Landslide Early Warning System - SLEWS

  Copyright: © LIH  

Scope

The joint project SLEWS aims at a systemic development of a prototyping alarm- and early warning system to address different kinds of natural hazards citing landslides as an example.

Due to the progressive development of urban areas and infrastructure, more and more people settle in environments that are or become endangered by mass movements. This situation is being complicated by the fact that the dependency of our today’s society on a functioning infrastructure and number of human or objects in endangered areas increases at the same time. The SLEWS is based on a ad-hoc wireless sensor network (WSN) for landslide monitoring and on the application of innovative service based web technologies integrating OGC standards for data processing and retrieval. Currently existing monitoring systems for early warning are available in terms of monolithic systems. This is a very cost-intensive way considering installation as well as operational and personal expenses.

The application of a WSN and of highly flexible sensors, also from the automotive area provides the ability to set up very flexible, easy to set up, secure and cost-efficient monitoring systems. The intelligent integration of different sensors on the motes may be used to improve data quality and function control by sensor fusion. On a larger scale intelligent sensor set ups and positioning can be used to cross validate information by network fusion. Even from foreign providers data can be integrated due to an open platform strategy using web processing services (WPS).

The planned service based spatial data infrastructure (SDI) will involve sensors, geodata, recent information and communication, as well as methods and models to estimate parameters with relevance to stability of landslides. The new approach provides the possibility for any involved institution to get user adapted information in a very early state independent from a hierarchical information structure. Improvement of user interfaces and possibility of model and prognosis integration are of major interest and will lead to the development of new standards.