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A Smart Device Using Low-Cost Sensors to Detect Earthquakes

机译:使用低成本传感器检测地震的智能设备

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Due to the significant development of hardware and software technologies in mobile and embedded computing, small hand-held devices such as smartphones have been used to detect earthquakes. In the past few years, there were efforts to detect earthquakes using a low-cost acceleration sensors inside a smartphone. However, it is not only costly to use a smartphone for merely detecting earthquakes, but also a waste of computing resources because smartphones comes with a powerful CPU, plentiful memory, and other auxiliary sensors. Also, a smartphone always needs to be connected to Internet. In this paper, we introduce a stand-alone earthquake detection device equipped with an acceleration sensor and Wi-Fi, First, we systematically evaluated a set of acceleration sensors by assessing their performance and accuracy to select the most suitable acceleration sensor, and then developed an designated device that can detect earthquakes and send alerts to nearby devices. Furthermore, to distinguish earthquakes from daily motions, we employed a Artificial Neural Network(ANN) technique with the earthquake dataset obtained from the Pohang earthquake in South Korea, 2017. Our result shows that a low-cost acceleration sensor can be used to detect an earthquake, thereby enhancing the public safety of communities vulnerable to earthquakes.
机译:由于移动和嵌入式计算中硬件和软件技术的重大发展,小型手持设备(如智能手机)已用于检测地震。在过去的几年中,人们一直在努力使用智能手机内部的低成本加速度传感器来检测地震。但是,由于智能手机带有强大的CPU,充足的内存和其他辅助传感器,因此使用智能手机仅检测地震不仅成本高昂,而且浪费了计算资源。此外,智能手机始终需要连接到Internet。在本文中,我们介绍了一种配备有加速度传感器和Wi-Fi的独立地震检测设备,首先,我们通过评估其性能和准确性来系统地评估一组加速度传感器,以选择最合适的加速度传感器,然后开发可以检测地震并将警报发送到附近设备的指定设备。此外,为了将地震与日常运动区分开来,我们采用了人工神经网络(ANN)技术,并从2017年韩国浦项地震中获得了地震数据集。我们的结果表明,低成本的加速度传感器可用于检测地震波。地震,从而增强了易受地震影响社区的公共安全。

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