TY - GEN
T1 - A Smart Device Using Low-Cost Sensors to Detect Earthquakes
AU - Lee, Jangsoo
AU - Kim, Jae Seon
AU - Choi, Seonhwa
AU - Kwon, Young Woo
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/4/1
Y1 - 2019/4/1
N2 - 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.
AB - 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.
KW - accelerometer
KW - Earthquake
KW - earthquake early warning
KW - internet of things
KW - machine learning
UR - http://www.scopus.com/inward/record.url?scp=85064713024&partnerID=8YFLogxK
U2 - 10.1109/BIGCOMP.2019.8679190
DO - 10.1109/BIGCOMP.2019.8679190
M3 - Conference contribution
AN - SCOPUS:85064713024
T3 - 2019 IEEE International Conference on Big Data and Smart Computing, BigComp 2019 - Proceedings
BT - 2019 IEEE International Conference on Big Data and Smart Computing, BigComp 2019 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2019 IEEE International Conference on Big Data and Smart Computing, BigComp 2019
Y2 - 27 February 2019 through 2 March 2019
ER -