Articles | Volume 20, issue 4
https://doi.org/10.5194/nhess-20-921-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-20-921-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Design and implementation of a mobile device app for network-based earthquake early warning systems (EEWSs): application to the PRESTo EEWS in southern Italy
Simona Colombelli
CORRESPONDING AUTHOR
Department of Physics “Ettore Pancini”, University of Naples
Federico II, Naples, Italy
Francesco Carotenuto
Department of Physics “Ettore Pancini”, University of Naples
Federico II, Naples, Italy
Luca Elia
Department of Physics “Ettore Pancini”, University of Naples
Federico II, Naples, Italy
Aldo Zollo
Department of Physics “Ettore Pancini”, University of Naples
Federico II, Naples, Italy
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Cited
18 citations as recorded by crossref.
- Support Vector Machine-Based Rapid Magnitude Estimation Using Transfer Learning for the Sichuan–Yunnan Region, China J. Zhu et al. 10.1785/0120210232
- Hybrid Deep-Learning Network for Rapid On-Site Peak Ground Velocity Prediction J. Zhu et al. 10.1109/TGRS.2022.3230829
- Design and implementation of earthquake early warning dissemination mobile app for Uttarakhand (India) G. Rathore et al. 10.1007/s10950-022-10124-6
- Real-Time Seismic Intensity Measurements Prediction for Earthquake Early Warning: A Systematic Literature Review Z. Cheng et al. 10.3390/s23115052
- Design and implementation of Internet-of-Things software monitoring and early warning system based on nonlinear technology H. Ma et al. 10.1515/nleng-2022-0036
- Earthquake Early Warning (EEW) System: System Architecture, Data Modelling, and User Interface Design H. Noprisson 10.32628/CSEIT2173136
- Magnitude Estimation for Earthquake Early Warning Using a Deep Convolutional Neural Network J. Zhu et al. 10.3389/feart.2021.653226
- Magnitude Estimation for Earthquake Early Warning with Multiple Parameter Inputs and a Support Vector Machine J. Zhu et al. 10.1785/0220210144
- Actionable and understandable? Evidence-based recommendations for the design of (multi-)hazard warning messages I. Dallo et al. 10.1016/j.ijdrr.2022.102917
- Earthquake Event Recognition on Smartphones Based on Neural Network Models M. Chen et al. 10.3390/s22228769
- Magnitude estimation and ground motion prediction to harness fiber optic distributed acoustic sensing for earthquake early warning I. Lior et al. 10.1038/s41598-023-27444-3
- Insights into Mechanical Properties of the 1980 Irpinia Fault System from the Analysis of a Seismic Sequence G. Festa et al. 10.3390/geosciences11010028
- On-site instrumental seismic intensity prediction for China via recurrent neural network and transfer learning J. Zhu et al. 10.1016/j.jseaes.2023.105610
- A Communication, Management and Tracking Mobile Application for Enhancing Earthquake Preparedness and Situational Awareness in the Event of an Earthquake P. Kirci et al. 10.3390/su15020970
- Multilevel Assessment of Seismic Damage and Vulnerability of Masonry Buildings (MUSE-DV) in Historical Centers: Development of a Mobile Android Application L. Sbrogiò et al. 10.3390/su14127145
- Chinese Nationwide Earthquake Early Warning System and Its Performance in the 2022 Lushan M6.1 Earthquake C. Peng et al. 10.3390/rs14174269
- Early detection of earthquake magnitude based on stacked ensemble model A. Joshi et al. 10.1016/j.jaesx.2022.100122
- MEANet: Magnitude estimation via physics-based features time series, an attention mechanism, and neural networks J. Song et al. 10.1190/geo2022-0196.1
18 citations as recorded by crossref.
- Support Vector Machine-Based Rapid Magnitude Estimation Using Transfer Learning for the Sichuan–Yunnan Region, China J. Zhu et al. 10.1785/0120210232
- Hybrid Deep-Learning Network for Rapid On-Site Peak Ground Velocity Prediction J. Zhu et al. 10.1109/TGRS.2022.3230829
- Design and implementation of earthquake early warning dissemination mobile app for Uttarakhand (India) G. Rathore et al. 10.1007/s10950-022-10124-6
- Real-Time Seismic Intensity Measurements Prediction for Earthquake Early Warning: A Systematic Literature Review Z. Cheng et al. 10.3390/s23115052
- Design and implementation of Internet-of-Things software monitoring and early warning system based on nonlinear technology H. Ma et al. 10.1515/nleng-2022-0036
- Earthquake Early Warning (EEW) System: System Architecture, Data Modelling, and User Interface Design H. Noprisson 10.32628/CSEIT2173136
- Magnitude Estimation for Earthquake Early Warning Using a Deep Convolutional Neural Network J. Zhu et al. 10.3389/feart.2021.653226
- Magnitude Estimation for Earthquake Early Warning with Multiple Parameter Inputs and a Support Vector Machine J. Zhu et al. 10.1785/0220210144
- Actionable and understandable? Evidence-based recommendations for the design of (multi-)hazard warning messages I. Dallo et al. 10.1016/j.ijdrr.2022.102917
- Earthquake Event Recognition on Smartphones Based on Neural Network Models M. Chen et al. 10.3390/s22228769
- Magnitude estimation and ground motion prediction to harness fiber optic distributed acoustic sensing for earthquake early warning I. Lior et al. 10.1038/s41598-023-27444-3
- Insights into Mechanical Properties of the 1980 Irpinia Fault System from the Analysis of a Seismic Sequence G. Festa et al. 10.3390/geosciences11010028
- On-site instrumental seismic intensity prediction for China via recurrent neural network and transfer learning J. Zhu et al. 10.1016/j.jseaes.2023.105610
- A Communication, Management and Tracking Mobile Application for Enhancing Earthquake Preparedness and Situational Awareness in the Event of an Earthquake P. Kirci et al. 10.3390/su15020970
- Multilevel Assessment of Seismic Damage and Vulnerability of Masonry Buildings (MUSE-DV) in Historical Centers: Development of a Mobile Android Application L. Sbrogiò et al. 10.3390/su14127145
- Chinese Nationwide Earthquake Early Warning System and Its Performance in the 2022 Lushan M6.1 Earthquake C. Peng et al. 10.3390/rs14174269
- Early detection of earthquake magnitude based on stacked ensemble model A. Joshi et al. 10.1016/j.jaesx.2022.100122
- MEANet: Magnitude estimation via physics-based features time series, an attention mechanism, and neural networks J. Song et al. 10.1190/geo2022-0196.1
Latest update: 22 Sep 2023
Short summary
We developed a mobile app for Android devices which receives the alerts generated by a network-based early warning system, predicts the expected ground-shaking intensity and the available lead time at the user position, and provides customized messages to inform the user about the proper reaction to the alert. The app represents a powerful tool for informing in real time a wide audience of end users and stakeholders about the potential damaging shaking in the occurrence of an earthquake.
We developed a mobile app for Android devices which receives the alerts generated by a...
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