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General Information
    • ISSN: 1793-8236 (Online)
    • Abbreviated Title Int. J. Eng. Technol.
    • Frequency:  Quarterly 
    • DOI: 10.7763/IJET
    • Executive Editor: Ms.Yoyo Y. Zhou
    • Abstracting/ Indexing: Chemical Abstracts Services (CAS) EBSCO, Google Scholar, Ulrich Periodicals Directory, Crossref, ProQuest, Index CopernicusEI (INSPEC, IET).
    • E-mail: ijet@vip.163.com
Prof. T. Hikmet Karakoc
Anadolu University, Faculty of Aeronautics and Astronautics, Turkey

IJET 2014 Vol.6(6): 520-529 ISSN: 1793-8236
DOI: 10.7763/IJET.2014.V6.752

An Internet-Enabled Wireless Multi-Sensor System for Continuous Monitoring of Landslide Processes

Kay Smarsly, Kristina Georgieva, and Markus König
Abstract—Monitoring and early warning systems, although being capable of continuously collecting field data related to landslide processes, are usually unable to autonomously detect and analyze signs of landslides in real time. This paper presents the design and experimental implementation of an autonomous landslide monitoring system. Besides reliably issuing early warnings in case of detected slope anomalies, the monitoring system is primarily designed to support human individuals in assessing the risk of landslide and to improve the understanding of the slope behavior, which may help to reduce economic losses and fatalities caused by landslides. Specifically, intelligent wireless sensor nodes are distributed in the observed slope to autonomously collect, analyze and communicate relevant environmental parameters in real time. Supporting remote analyses of the collected field data, a web application, which is installed on a computer connected to the on-site sensor nodes, enables an automated dissemination of slope parameters through the Internet. Last but not least, geospatial information stemming from external sources is integrated into the monitoring system to provide a comprehensive overview of landslide-related slope conditions.

Index Terms—Monitoring of slope movements, wireless sensor networks, early warning systems, artificial intelligence, smart sensors, Internet computing.

Kay Smarsly is with the Department of Civil Engineering, Bauhaus University Weimar, Germany (e-mail: kay.smarsly@uni-weimar.de).
Kristina Georgieva and Markus König are with the Department of Civil and Environmental Engineering, Ruhr University Bochum, Germany (e-mail: kristina.georgieva@rub.de, markus.koenig@inf.bi.rub.de).


Cite: Kay Smarsly, Kristina Georgieva, and Markus König, "An Internet-Enabled Wireless Multi-Sensor System for Continuous Monitoring of Landslide Processes," International Journal of Engineering and Technology vol. 6, no. 6, pp. 520-529, 2014.

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