—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.
—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: email@example.com).
Kristina Georgieva and Markus König are with the Department of Civil
and Environmental Engineering, Ruhr University Bochum, Germany (e-mail:
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.