Abstract
A typhoon can produce extremely powerful winds and torrential rain. On August 8th, 2009, Typhoon Morakot hit southern Taiwan. The storm brought a record-setting rainfall, nearly 3000mm (almost 10 feet) rainfall accumulated in 72 hours. Heavy rain changes the stability of a slope from a stable to an unstable condition. Mudslides happened, and made a devastating damage to several villages and buried hundreds of lives. In most of mudslide-damaged residences, the electricity equipments, especially electricity poles, are usually tilted or moved. Since the location and status of each electricity pole are usually recorded in AMI (Advanced Metering Infrastructure) MDMS (Meter Data Management System), AMI communication network is a substantial candidate for constructing the mudslide detection network. To identify the possible mudslide areas from the numerous gathered data, this paper proposes a data analysis method that indicates the severity and a mechanism for detecting the movement.
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Tang, CJ., Dai, M.R. (2010). Using Data from an AMI-Associated Sensor Network for Mudslide Areas Identification. In: Nguyen, N.T., Le, M.T., Świątek, J. (eds) Intelligent Information and Database Systems. ACIIDS 2010. Lecture Notes in Computer Science(), vol 5990. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12145-6_39
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DOI: https://doi.org/10.1007/978-3-642-12145-6_39
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-12144-9
Online ISBN: 978-3-642-12145-6
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