CI-TEAM Implementation Project: The Quake-Catcher Network, a low-cost, high-density strong motion network

加州大学河滨分校和斯坦福大学正在合作推进地震捕捉网络（QCN）的发展，这是一个新的分布式地震监测网络，利用3轴加速度计，这已经成为许多笔记本电脑的标准设备，以及一个由“公民科学家”组成的志愿者社区。这些加速度计的低成本和小尺寸使得创建一个廉价、密集的网络成为大洛杉矶盆地现有地震网络的补充。该网络还为在K-12教室中推广地球科学教育提供了一种廉价的工具，为学生提供了进行实际操作、探究式调查的机会。网络是通过使用伯克利网络计算开放基础设施（BOINC）分布式软件处理软件包实现的，当与传感器采集软件结合使用时，该软件包可以超高效地处理、传输和分析地震数据。当检测到强烈的新动作时，监测加速度计的志愿者会向中央服务器发送小数据包；波形数据只有在确认发生地震时才会上传。此规划拨款用于完成QCN计算软件的平台独立版本的开发；通过外展增加网络中的志愿者人数；完成在K-12教室内使用的互动软件的开发；向K-12学校派发200个USB加速计和教材；并评估通过网络提供的数据。

The University of California-Riverside and Stanford University are collaborating to advance development of the Quake-Catcher Nework (QCN), a new distributed network for earthquake monitoring that utilizes 3-axis accelerometers, which have become standard equipment in many laptop computers, and a volunteer community of 'citizen scientists'. The low cost and small size of these accelerometers enables creation of an inexpensive, dense network that supplements existing seismic networks in the Greater Los Angeles Basin. The network also provides an inexpensive vehicle for promoting geoscience education within K-12 classrooms that provides students with the opportunity to conduct hands-on, inquiry-based investigations. Networking is achieved through the use of the Berkeley Open Infrastructure for Network Computing (BOINC) distributed software processing package, which allows, when combined with the sensor acquisition software, ultra-efficient processing, transfer, and analysis of the seismic data. Volunteers monitoring the accelerometers send small data packets to the central server when strong new motions are detected; waveform data only uploads when an earthquake is confirmed. This planning grant is being used to finish development of the platform independent version of the QCN computing software; increase the number of volunteers in the network through outreach; complete development of interactive software for use within K-12 classrooms; distribute 200 USB accelerometers and educational materials to K-12 schools; and evaluate data contributed through the network.