GSTDTAP
项目编号1822136
Use of Artificial Intelligence towards Automation of Analog Seismogram Digitization
Miaki Ishii
主持机构Harvard University
项目开始年2018
2018-08-15
项目结束日期2020-07-31
资助机构US-NSF
项目类别Standard Grant
项目经费154017(USD)
国家美国
语种英语
英文摘要Seismometers have been recording ground motion since the late 1800s, and about 100 years of the recordings are in analog form (e.g., paper recordings) that cannot be examined using modern techniques. These data contain information about earthquakes, volcano eruptions, subsurface changes, changes in weather pattern, to name the few, and are vital for understanding various phenomena that affect the Earth and how they evolve over time. This project aims to make a significant step forward in converting these analog data into usable digital format by introducing artificial intelligence to the conversion process. Currently, there is a software that takes a record image and generates digital seismograms, but it requires substantial human interaction making this process slow, impractical, or impossible. Successful implementation of artificial intelligence will allow more data to be processed quickly for use by the scientific community, which is a significant broader impact.

The project will start by examining the digitized analyses to determine and build the training database to be used for the construction of the neural network. The investigators will also identify steps that will benefit most from implementation of artificial intelligence procedures to decrease human interaction and improve accuracy of the digitization of seismograms. Neural networks for image classification and object identification are now available and will be examined to find the algorithm that is most suitable for the seismogram digitization process. The improved digitization software will be openly available to increase users and provide a robust tool to convert analog seismogram images to research-quality digital seismograms. It will enable the seismological community to retrieve data that for application of modern analyses, and open opportunities for new types of research to be done.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
文献类型项目
条目标识符http://119.78.100.173/C666/handle/2XK7JSWQ/73073
专题环境与发展全球科技态势
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Miaki Ishii.Use of Artificial Intelligence towards Automation of Analog Seismogram Digitization.2018.
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