Prediction of Earthquake Using 3 Axis Accelerometer Sensor (ADXL335) and ARDUINO UNO
International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
Call for Papers | Fully Refereed | Open Access | Double Blind Peer Reviewed

ISSN: 2319-7064


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Research Proposals or Synopsis | Electronics & Communication Engineering | India | Volume 6 Issue 9, September 2017 | Popularity: 6.5 / 10


     

Prediction of Earthquake Using 3 Axis Accelerometer Sensor (ADXL335) and ARDUINO UNO

Veenu Grover, Aman Sharma


Abstract: Seismology is that branch of Science that deals with the study of Earthquake and Seismic wave through the body and Surface of Earth. Today, Detection of Earthquake is carried out everywhere but a need to predict it is urgent to prevent deterioration to both life and property! In this paper, we have given brief information about what is earthquake and designed a model to predict it. A brief introduction has been given to different types of seismic waves with their respective frequencies. The Accelerometer ADLX335 has been used in combination with Arduino Uno (ATMega 328) at the earthquake prone areas which are connected with the Data Centers by a wireless network. ADLX335 is capable of sensing vibrations from all the directions X, Y as well as Z. The ADXL335 is a low power, complete 3-axis accelerometer with signal conditioned voltage outputs and can measure static and dynamic accelerations. Programming for the controller is carried out using the software Arduino 1.8.3 By which we obtain the graphical data of seismic waves in X, Y, Z directions.


Keywords: Earthquake, Seismic Waves, Seismic data Acquisition, ATMega 328, Accelerometer, ADC, XBee S1, Minicom GUI


Edition: Volume 6 Issue 9, September 2017


Pages: 1044 - 1047



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Veenu Grover, Aman Sharma, "Prediction of Earthquake Using 3 Axis Accelerometer Sensor (ADXL335) and ARDUINO UNO", International Journal of Science and Research (IJSR), Volume 6 Issue 9, September 2017, pp. 1044-1047, https://www.ijsr.net/getabstract.php?paperid=ART20176803, DOI: https://www.doi.org/10.21275/ART20176803

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