Earthquake Detection in a Static and Dynamic Environment Using Supervised Machine Learning and a Novel Feature Extraction Method [PDF]
Sensors, 2020 Detecting earthquakes using smartphones or IoT devices in real-time is an arduous and challenging task, not only because it is constrained with the hard real-time issue but also due to the similarity of earthquake signals and the non-earthquake signals ...
Irshad Khan +2 more
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BLESeis: Low-Cost IoT Sensor for Smart Earthquake Detection and Notification [PDF]
Sensors, 2020 The Internet of Things (IoT) has been implemented to provide solutions for certain event detection because of ease of installation, computing and communication capability, and cost-effectiveness. Seismic event detection, however, is still a challenge due
Jongbin Won +3 more
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Earthquake Detection Using Stacked Normalized Recurrent Neural Network (SNRNN)
Applied Sciences, 2023 Earthquakes threaten people, homes, and infrastructure. Earthquake detection is a complex task because it does not show any specific pattern, unlike object detection from images.
Muhammad Atif Bilal +4 more
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Convolutional neural network for earthquake detection and location. [PDF]
Sci Adv, 2018 ConvNetQuake is the first neural network for detection and location of earthquakes from seismograms.
Perol T, Gharbi M, Denolle M.
europepmc +7 more sources
Hybrid Validation of a Quality-Controlled, Waveform-Centered AI Framework with Optional Multi-Sensor Support for Seismic Monitoring [PDF]
SensorsRapid and reliable seismic monitoring requires accurate waveform inference, together with robustness to noise, incomplete sensing, and unstable predictions.
Askar Abdykadyrov +5 more
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Unsupervised anomaly detection for earthquake detection on Korea high-speed trains using autoencoder-based deep learning models [PDF]
Scientific ReportsWe propose a method for detecting earthquakes for high-speed trains based on unsupervised anomaly-detection techniques. In particular, we utilized autoencoder-based deep learning models for unsupervised learning using only normal training vibration data.
Jeonguk Seo +5 more
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Early Earthquake Detection Using Batch Normalization Graph Convolutional Neural Network (BNGCNN)
Applied Sciences, 2022 Earthquake is a major hazard to humans, buildings, and infrastructure. Early warning systems should detect an earthquake and issue a warning with earthquake information such as location, magnitude, and depth.
Muhammad Atif Bilal +4 more
doaj +3 more sources
Detection of Earthquake-Induced Building Damages Using Polarimetric SAR Data
Remote Sensing, 2020 Remote sensing, particularly using synthetic aperture radar (SAR) systems, can be an effective tool in detecting and assessing the area and amount of building damages caused by earthquake or tsunami.
Sang-Eun Park, Yoon Taek Jung
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Time-Frequency-Based Separation of Earthquake and Noise Signals on Real Seismic Data: EMD, DWT and Ensemble Classifier Approaches [PDF]
SensorsEarthquakes are sudden and destructive natural events caused by tectonic movements in the Earth’s crust. Although they cannot be predicted with certainty, rapid and reliable detection is essential to reduce loss of life and property.
Yunus Emre Erdoğan, Ali Narin
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Twitter earthquake detection: earthquake monitoring in a social world
Annals of Geophysics, 2011 The U.S. Geological Survey (USGS) is investigating how the social networking site Twitter, a popular service for sending and receiving short, public text messages, can augment USGS earthquake response products and the delivery of hazard information ...
Daniel C. Bowden +2 more
doaj +4 more sources