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Tomas M. Fernandez-Steeger, RWTH Aachen University (Germany)
Christian Arnhardt, RWTH Aachen University (Germany)
Abdullah Kallash, RWTH Aachen University (Germany)
Rafig Azzam, RWTH Aachen University (Germany)
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Due to increasing vulnerability of society to natural hazards the requirements for early warning and monitoring systems continuously grow at the same time. Especially reliable real-time data for the detection of hazards and subsequently fast warning and response are of high relevance to protect humans and infrastructure. The project "Sensor based Landslide Early Warning System" (SLEWS) concerns with the development of such a system for landslide hazard using modern technologies and recent methods.
The complex mechanisms of mass movements are measured and detected by low cost, but precise measuring sensors, which are integrated in a wireless sensor network (WSN). Today's generation of modern wireless, so called Ad-hoc sensor networks, offer the possibility to monitor even large areas. Within the Sensor Network data are passed on by small self organizing and self configuring units, called nodes or motes, to a data collection point (gateway). Each note consists of a processing unit, a memory, WLAN chip and one or more sensors. The gateway provides the interface to central processing and data retrieval units (laptop, server or internet) outside the network. The Multi-hop structure of the network allows a rapid, fail-safe and especially self organizing communication between different nodes of the WSN. Depending on connection and signal strength, each sensor node is able to search individually the best link to other points of the network. This helps to avoid the failure of the system even if some of the nodes break down. The use of an Ad-hoc network permits a non hierarchic data exchange and thus allows a very simple and fast adaption of the network to changed conditions.
For the detection and monitoring of different kinds of landslide processes (slide, drift, topple and fall), small, but very precise Micro-Electronic-Mechanical Systems (MEMS) are integrated into the WSN. In addition to tilt and acceleration sensors, displacement transducers are used for elongation measurements. Furthermore, newtechnologies like acoustic emission sensors to detect elastic wave signals from deformation and elevation sensors (Altimeter) will be tested. The fusion of different, but even same measuring sensor (sensor redundancy) of the same and other sensor nodes contributes substantially to the decision making. It allows a better interpretation of data and helps to reduce malfunctions and false alarm rates.The network data are processed outside the network in a service orientated special data infrastructure (SDI) by standardized OGC (open Geospatial Consortium) conform services and visualized according to the requirements of the end-user. The usage of standardized interfacestructures opens the possibility to integrate the WSN easily to other monitoring and alarm systems and improves flexibility. In comparison to existing monitoring and early warning systems, the described system is characterized by a flexible structure, cost efficiency and high fail-safe level.
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