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International Journal of Automation and Smart Technology
Article . 2011 . Peer-reviewed
License: CC BY NC ND
Data sources: Crossref
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Multifunctional Inshore Survey Platform with Unmanned Surface Vehicles

Authors: Wen-Rong Yang; Cing-Ying Chen; Chao-Min Hsu; Chiung-Jung Tseng; Wen-Chang Yang;

Multifunctional Inshore Survey Platform with Unmanned Surface Vehicles

Abstract

Because of extreme weather and frequent natural disasters, improvement of disaster prevention capabilities and early warning technologies is an urgent matter. Inshore areas are where ocean and land intersect; the sea conditions and environment are complex and changeable, and human activities are frequent in these areas. Natural disasters, such as a substantial rise in sea levels, coastal erosion and transitions, and rapid flooding from tsunamis, and human development projects, pollution, and ecological damage must be thoroughly investigated, monitored, recorded, and prevented. The west coast of Taiwan, particularly the southeast coastal plain, is a highly populated narrow area; thus, field survey tools with a high degree of freedom and flexible applications are required for data collection to reach its full potential. The Taiwan Ocean Research Institute developed an unmanned surface vehicle (USV) for the “Long Term Observation for Research Performed in TORI” 2010 project. This USV is a platform that integrates scientific equipment, including Wi-Fi communication and a satellite-based global positioning system (GPS) with navigation images and signals, to form an internal network with onshore control bases to allow the instant acquisition of measured data and enable researchers to conduct surveys in safe conditions. USVs are appropriate for various types of inshore research and surveys, such as marine topography, sediment disposition analysis, inshore engineering measurements, and the monitoring of hydrology, water quality, and the environment. One aim of the Taiwan Ocean Research Institute (TORI) is to establish a method to use the USV for collecting inshore marine topography, hydrology, water quality, and meteorological data. Integrating field investigations of Taiwan’s coastal waters will provide data for verifying numerical simulations and lead scientists to explore novel and unknown areas.

Related Organizations
Keywords

GPS, Information technology, T58.5-58.64, T59.5, Automation, unmanned surface vehicle, inshore research, disaster prevention

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    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    27
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
27
Top 10%
Top 10%
Average
gold