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Pocket-sized sensors bring earthquake science to schools

Sensor for Quake Catcher Network
These pocket-sized seismic sensors have to be mounted to the floor and connected to desktop computers or laptops to collect seismic data. For the QCN school project in Taiwan, they are used to offer local students hands-on learning in geosciences and cloud computing. Image courtesy Wen-Tzong Liang.

Last year, the magnitude 9.0 Tohoku earthquake in Japan illustrated once again the devastating impact of natural disasters on human lives. But the seismic sensor stations necessary for detecting earthquakes and improving hazard mitigation come with a hefty price tag, often costing much more than developing countries can afford.

During the International Symposium on Grids and Clouds 2012 in Taipei last month, researchers from Taiwan presented a school project aimed at making science education more accessible to students. Using grid-enabled software and a cloud-based learning platform, local high school students are being taught how to use low-cost seismic sensors at school and home to track earthquakes. The project also collects additional seismic data that can be used for further seismological research.

"Our goal is to devise a model curriculum that can be used to integrate geoscience education and cloud computing technology in senior high school classrooms," said Kate Huihsuan Chen, project leader and seismologist at National Taiwan Normal University (NTNU) in Taipei. Funded by the National Science Council in Taiwan, the project is also led by science educator Chun-Yen Chang from NTNU, seismologist Wen-Tzong Liang from Academia Sinica's Institute of Earth Sciences (IES), and Eric Yen from the Academia Sinica Grid Computing Center (ASGC).

Grid-enabled earthquake science

The project is based on the Quake-Catcher Network (QCN), a distributed computing network initiated by Stanford University and University of California, Riverside that links individual computers into a real-time motion sensing network. While a number of newer laptops come equipped with internal accelerators that can be used to detect earthquakes, desktop computers and older laptops need to be connected via USB cable to external microelectromechanical sensors (MEMS) that are mounted to the floor.

BOINC, an open source software kit for volunteer grid computing, is then used to transmit the recorded data to local and global QCN servers via the Internet, where it can be further processed and analyzed by seismologists.

"Since last year, the IES and ASGC, which operates the local QCN server and lends its technical expertise to the project, have been promoting QCN-based projects in Asia. This project brings us a step further in promoting citizen earthquake science and increasing awareness of seismic hazards," Liang said.

Bringing education and Earth science together

Located on the Pacific Ring of Fire, a horseshoe-shaped area characterized by its large number of earthquakes and volcanic eruptions, Taiwan currently operates a dense network of more than 200 real-time seismic sensor stations. However, these stations offer limited mobility and are very costly. In comparison, the pocket-sized MEMS sensors used by QCN can be easily deployed and are available for a fraction of the price.

A student in Taiwan learns how to use a sensor in the Quake Catcher Network.
The project team instructed the high school students in how to install the QCN sensors at home and use BOINC, an open source software kit for volunteer grid computing that is used to record and transmit seismic data. Image credit Vivian Tiän-Tiän Chang.

Since last year, the scientists have been working together with teachers and students from Lanyang Girls' High School, in Yilan County, to establish a QCN-based network of these low-cost sensors. The county, located in northeastern Taiwan, was chosen because of its high level of seismic activity, solid information and communication infrastructure, and the even distribution of schools, Liang said at ISGC. That even distribution of schools translates to a more even distribution of seismic sensors, as other schools have been contacted to help deploy additional MEMS sensors on their grounds.

The students were taught how to install the sensors at home and use BOINC. This will help increase the density of the existing sensor station network, while giving the students practical experience with basic scientific concepts and how they relate to earthquakes. Web-based software, such as an interactive cloud-based learning platform, has been designed to provide useful results for students and help visualize the scientific aspects of earthquakes to facilitate understanding.

Through a series of workshops and briefings, the seismologists and educators provide teachers with the required expertise and offer solutions to practical problems. They have also created a Facebook page where students and teachers can ask questions, post comments, or share their data.

Overcoming obstacles

Although there have been similar ventures in other regions and countries, the teaching materials used are of limited use for this project, since they need to be adapted to meet the specific requirements set out in the local curriculum and translated from English or other languages to Chinese. For this reason, the scientists are now developing new visualization methods that can be used in innovative classroom experiments to help the students gain a better understanding, from their collected data, of seismic waves and their impact.

Interacting directly with the global real-time data stored on QCN servers is also still somewhat difficult using the existing software, Chen said. This makes it harder for students to see immediate results and how their data fits into the bigger picture. The researchers are concerned that this may eventually lead to a loss of motivation over time. To overcome these obstacles, they are looking into ways to develop new applications with more educational features that can be used in class or at home. Software that is currently in development includes tools to view and exchange waveform data both online and offline.

Extending QCN-based school projects to other regions

What also has the researchers excited is the prospect of extending similar projects to other regions. The model can be applied to other earthquake-prone regions with a larger number of developing countries, such as Southeast Asia. It can help raise public awareness of earthquake hazards, particularly among the younger generation, and reduce costs for countries that cannot afford the installation and management of high-priced seismic sensor stations. A similar seismic network in the metropolitan area of Manila in the Philippines, based on the current QCN school project in Taiwan, is now in its early planning stages.

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