A Weather Prediction and Earthquake Monitoring System

Abayon, Renalyn C.; Apilado, Joenilyn R.; Pacis, Daryl B.; Chua, Marissa G.; Aguilar, Arfel V.; Calim, Jeffrey; Padilla, Sheenrod Meitzler A.; Puno, James Christopher S.; Apsay, Mary Regina B.; Bustamante, Ricky V.

doi:10.1109/spc.2018.8704138

Cited by 2 publications

(2 citation statements)

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“…Beberapa tanda atau gejala awal akan datangnya gempa bumi adalah fenomena Total Electron Content pada lapisan ionosfer [4][5] [6] Akibat pergerakan lempeng, terjadi rekahan yang memengaruhi gaya berat dan mineral magnetis di dalam bumi sehingga mengganggu kestabilan gaya medan elektromagnetik. Gangguan ini bisa sampai radius 400 kilometer di atas permukaan bumi pada lapisan ionosfer dan peningkatan geomagnetism pada permukaan bumi dalam waktu tertentu sebelum terjadinya gempa [7] [8] [9] dan geomagnetism dapat dideteksi menggunakan sensor MAG3110 [10] [11] Selain itu juga sensor DHT11 dapat digunakan untuk memonitor gempa melalui perubahan suhu tanah yang terjadi seperti yang telah dilakukan oleh [12] .…”

Section: Pendahuluanunclassified

Gempa Bumi : Hubungan Data Sensor MAG3110 dengan Data Sensor ADXL345 Berbasis IoT

et al. 2021

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The earthquake early warning system was built by implementing the IoT-based telemetry method to measure the earth's magnetic flux and vibrations at the latitude coordinates and longitude coordinates (-5.640274, 104.3050093), (-5.600941, 104.7788183) through the MAG3110 and ADXL345 sensors that were integrated in the raspberry pi3 as a server and applications on Android phones used for measurement data display. The result of the measurement data was that the average impact of the arising earth anomaly and vibration at the same coordinates took 400 seconds in the anomaly range of 395 μT to 404 μT. The conclusion of this study was that the study was able to be used as a basic to design the real-time earthquake warning system.

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Section: Pendahuluanunclassified

Gempa Bumi : Hubungan Data Sensor MAG3110 dengan Data Sensor ADXL345 Berbasis IoT

et al. 2021

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“…Reference [22] collected geographical information to pass through six different membership functions for measuring land sliding susceptibility using NFES. Many researchers have analysed combination of artificial neural network and fuzzy inference system [29][30][31][32]. Earthquake attribute such as magnitude, depth, longitude and latitude has been studied in [33] to provide input to NFES for computation of the future earthquake.…”

Section: Neuro Fuzzy Expert System (Nfes)mentioning

confidence: 99%

Earthquake Prediction Using Expert Systems: A Systematic Mapping Study

2020

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Earthquake is one of the most hazardous natural calamity. Many algorithms have been proposed for earthquake prediction using expert systems (ES). We aim to identify and compare methods, models, frameworks, and tools used to forecast earthquakes using different parameters. We have conducted a systematic mapping study based upon 70 systematically selected high quality peer reviewed research articles involving ES for earthquake prediction, published between January 2010 and January 2020.To the best of our knowledge, there is no recent study that provides a comprehensive survey of this research area. The analysis shows that most of the proposed models have attempted long term predictions about time, intensity, and location of future earthquakes. The article discusses different variants of rule-based, fuzzy, and machine learning based expert systems for earthquake prediction. Moreover, the discussion covers regional and global seismic data sets used, tools employed, to predict earth quake for different geographical regions. Bibliometric and meta-information based analysis has been performed by classifying the articles according to research type, empirical type, approach, target area, and system specific parameters. Lastly, it also presents a taxonomy of earthquake prediction approaches, and research evolution during the last decade.

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A Weather Prediction and Earthquake Monitoring System

Cited by 2 publications

References 1 publication

Gempa Bumi : Hubungan Data Sensor MAG3110 dengan Data Sensor ADXL345 Berbasis IoT

Gempa Bumi : Hubungan Data Sensor MAG3110 dengan Data Sensor ADXL345 Berbasis IoT

Earthquake Prediction Using Expert Systems: A Systematic Mapping Study

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