Dergiler / International Journal of Environment and Geoinformatics / 2026 / Volume: 2 Issue: 2

Investigation of the Usability of Mobile Sensors for Weather Forecasting

Semih Dalğın(Istanbul Technical University, Department of Geomatics Engineering, Civil Engineering Faculty, Maslak, Istanbul)
A. Özgür Doğru(Istanbul Technical University, Department of Geomatics Engineering, Civil Engineering Faculty, Maslak, Istanbul)
Sayfa
—
Yayın Tarihi
2015-08-03
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⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

Therefore further studies should be executed for improving the accuracy of the mobile sensor data for scientific purposes.

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Temel Bulgular & Veri:However efficient use of the raw data provided by the sensors with different characteristics in order to obtain accurate results is not investigated in detail.   This study aims to investigate the data collected by mobile sensors integrated in the smartphones for scientific purposes such as weather forecasting.
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Sonuç & Katkı:Therefore further studies should be executed for improving the accuracy of the mobile sensor data for scientific purposes.
🔬Tür:Research Article
📍Kapsam:Genişletilmiş Akademik Örneklem
⚙️Değişkenler:Mobile sensors · weather forecast · accuracy assessment

Abstract

Normal 0 21 false false false TR X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Normal Tablo"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Times New Roman",serif; mso-ansi-language:EN-US; mso-fareast-language:EN-US;} Crowd sourcing is a popular method for providing data from people by the use of mobile sensor, internet and communication technologies. However efficient use of the raw data provided by the sensors with different characteristics in order to obtain accurate results is not investigated in detail.   This study aims to investigate the data collected by mobile sensors integrated in the smartphones for scientific purposes such as weather forecasting. In this context, accuracy of the data provided mobile humidity, pressure and temperature sensors was examined in this study. Data provided by 5 smart phones and 3 Bluetooth sensors were tested in this context. Accuracy assessment process was performed by calculating the Root Mean Square Errors of the data with respect to reference data collected by TST Sensor simultaneously. This study shows that accuracy of the data collected with the mobile sensors is affected by several external parameters such as climatic conditions, handling habits of the user, and etc. Although it is possible to calculate correction constant for each sensor separately, it is not possible to calculate a unique and universal correction constant in order to increase the accuracy of the raw data collected by the mobile sensors. Therefore further studies should be executed for improving the accuracy of the mobile sensor data for scientific purposes.

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Bu Makaleye Atıf Yap

Dalğın, S., Doğru, A. Ö. (2015). Investigation of the Usability of Mobile Sensors for Weather Forecasting. International Journal of Environment and Geoinformatics, Volume: 2 Issue: 2. https://doi.org/10.30897/ijegeo.303542

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Kaynakça (8)

  1. Ladd J.W. and Driscoll D.M. 1980. A Comparison of Objective and Subjective Means of Weather Typing: An Example from West Texas.J. Appl. Meteor., 19, 691–704.
  2. Liu M., 2013. A Study of Mobile Sensing Using Smartphones, International Journal of Distributed Sensor Networks Volume 2013, Article ID 272916, 11 pages.
  3. Murphy A.H., Brown B.G., 1984. A comparative evaluation of objective and subjective weather forecasts in the United States, Journal of Forecasting, Volume 3, Issue 4, pages 369–393.
  4. Sheth, A., Hensoni C., 2008. Semantic Sensor Web. Semantic & Services. IEEE Computer Society.
  5. URL 1: http://www.mgm.gov.tr/genel/sss.aspx?s=havatahmini
  6. URL 2: http://developer.android.com/guide/topics/sensors/sensors_overview.html
  7. URL 3: https://www.pressurenet.io/
  8. URL 4: http://cliffmass.blogspot.com.tr/2012/12/can-smartphone-observations.html