Application of the Raspberry Pi for In Situ Measurement Automation and Data Transfer and Storage

A. F. Rozvadovskiy

Marine Hydrophysical Institute of RAS, Sevastopol, Russia

e-mail: rozvadovsky@yandex.ru

Abstract

The paper considers issues of organization of remote workplaces for automation of in situ measurements of the marine environment. The workplace allows collection of data from a sensor system that measures characteristics of the marine environment in natural conditions; to transfer data to a remote data center via the Internet; to store and backup data. The paper presents algorithms for workplace organization based on modern technologies for data collection and transmission. The implementation of the workplace is detailed on the example of remote control of the weather station Davis Vantage Pro 2. This weather station was installed on the stationary oceanographic platform in Katsiveli to continuously measure parameters of the atmospheric surface layer. The remote control was organized on the basis of the hardware and software platform of a single-board personal computer Raspberry Pi. Two-year tests of the system allow concluding about its reliability and high efficiency. The proposed principles and algorithms can be applied to organization of remote workplaces for performing oceanological measurements in coastal areas with Internet access.

Keywords

automation, in situ measurements, marine environment, remote workplace, hardware and software platform, Raspberry Pi, weather station, Davis Vantage Pro 2, cloud storage, oceanographic platform, Katsiveli

Acknowledgments

The work was carried out under state assignment of MHI RAS FNNN-2024-0001 “Fundamental research of the processes determining the flows of matter and energy in the marine environment and at its borders, the state and evolution of the physical and biogeochemical structure of marine systems in modern conditions”.

For citation

Rozvadovskiy, A.F., 2024. Application of the Raspberry Pi for In Situ Measurement Automation and Data Transfer and Storage. Ecological Safety of Coastal and Shelf Zones of Sea, (4), pp. 117–130.

References

  1. Bondur, V.G., Ivanov, V.A., Vorobiev, V.E., Dulov, V.A., Dolotov, V.V., Zamshin, V.V., Kondratiev, S.I., Lee, M.E. and Malinovsky, V.V., 2020. Ground-to-Space Monitoring of Anthropogenic Impacts on the Coastal Zone of the Crimean Peninsula. Physical Oceanography, 27(1), pp. 95–107. https://doi.org/10.22449/1573-160X-2020-1-95-107
  2. Lavrova, O.Yu., Kostianoy, A.G., Lebedev, S.A., Mityagina, V. I., Ginzburg, A.I. and Sheremet, N.A., 2011. Complex Satellite Monitoring of the Russian Seas. Moscow: IKI RAN, 480 p. (in Russian).
  3. Smirnov, G.V., Eremeev, V.N., Ageev, M.D., Korotaev, G.K., Yastrebov, V.S. and Motyzhev, S.V., 2005. [Modern Means and Methods of Oceanological Research]. In: IO RAS, 2005. [Proceedings of IX International Scientific and Technical Conference Modern Methods and Means of Oceanological Research. Moscow]. Moscow: Izd-vo Instituta Okeanologii RAN. Part 1, 146 p. (in Russian).
  4. Veremyev, V.I., Kutuzov, V.M., Plotnitskaya, K.S., Kovalenko, V.V. and Telegin V.A., 2019. High-Frequency Radar for Coastal Areas Monitoring. Journal of the Russian Universities. Radioelectronics, 22(2), pp. 31–43. https://doi.org/10.32603/1993-8985-2019-22-2-31-43 (in Russian).
  5. Smolov, V.E. and Rozvadovskiy, A.F., 2020. Application of the Arduino Platform for Recording Wind Waves. Physical Oceanography, 27(4), pp. 430–441. https://doi.org/10.22449/1573-160X-2020-4-430-441
  6. Golovinov, E.E., Aminev, D.A., Kulakov, V.A., Bakirov, Sh.M. and Grigoriev, P.V., 2018. Analysis of System Solutions for Portable Weather Stations. Nanoindustry, (9), pp. 144–149. https://doi.org/10.22184/1993-8578.2018.82.144.149 (in Russian).
  7. Kusriyanto, M. and Putra, A.A., 2018. Weather Station Design Using IoT Platform Based on Arduino Mega. In: IEEE, 2018. International Symposium on Electronics and Smart Devices (ISESD), Bandung, Indonesia, 2018. IEEE, pp. 1–4. https://doi.org/10.1109/ISESD.2018.8605456
  8. Saini, H., Thakur, A., Ahuja, S., Sabharwal, N. and Kumar, N., 2016. Arduino Based Automatic Wireless Weather Station with Remote Graphical Application and Alerts. In: IEEE, 2016. 3rd International Conference on Signal Processing and Integrated Networks (SPIN), 11–12 February 2016, Noida, India. IEEE, pp. 605–609. https://doi.org/10.1109/SPIN.2016.7566768
  9. Singh, J., Mohammed, R., Kankaria, M., Panchal, R., Singh, S. and Sharma, R., 2018. Arduino-Based Weather Monitoring System. International Journal of Advanced in Management, Technology and Engineering Sciences, 8(3), pp. 1076–1079. Available at: https://www.ijamtes.org/gallery/29.%20mar%20ijamtes%20-%20317.pdf [Accessed: 28 November 2024].
  10. Gao, J., Ma, H., Liu, H., 2016. The Intelligent Weather Station System Based on Arduino. In: J. Kao and W.-P. Sung, eds., 2016. Proceedings of the 2016 International Conference on Engineering and Advanced Technology. Hong Kong, 22–23 December 2016. ICEAT. Vol. 82, pp. 300–308. https://doi.org/10.2991/iceat-16.2017.61
  11. Katyal, A., Yadav, R. and Pandey, M., 2016. Wireless Arduino Based Weather Station. International Journal of Advanced Research in Computer and Communication Engineering, 5(4), pp. 274–276. https://doi.org/10.17148/IJARCCE.2016.5470
  12. Kishorebabu, V. and Sravanthi, R., 2020. Real Time Monitoring of Environmental Parameters Using IOT. Wireless Personal Communications, 112(2), pp. 785–808. https://doi.org/10.1007/s11277-020-07074-y
  13. Rasal, M.V. and Rana, J.G., 2016. Raspberry Pi Based Weather Monitoring System. International Journal of Advanced Research in Computer and Communication Engineering, 5(10), pp. 119–122. Available at: https://ijarcce.com/wp-content/uploads/ 2016/10/IJARCCE-24.pdf [Accessed: 28 November 2024].
  14. Muck, P.Y. and Homam, M.J., 2018. IoT Based Weather Station Using Raspberry Pi 3. International Journal of Engineering and Technology, 7(4.30), pp. 145–148. https://doi.org/10.14419/ijet.v7i4.30.22085
  15. Vatsal, S. and Bhavin, M., 2017. Using Raspberry Pi to Sense Temperature and Relative Humidity. International Research Journal of Engineering and Technology, 4(2), pp. 380–385. Available at: https://www.irjet.net/archives/V4/i2/IRJET-V4I276.pdf [Accessed: 28 November 2024].
  16. Baste, P. and Dighe, D.D., 2017. Low Cost Weather Monitoring Station Using Raspberry Pi. International Research Journal of Engineering and Technology, 4(5). https://doi.org/10.5281/zenodo.2599637
  17. Vilayatkar, S.R., Wankhade, V.R., Wangekar, P.G. and Mundane, N.S., 2019. IoT Based Weather Monitoring System Using Raspberry Pi. International Research Journal of Engineering and Technology, 6(1), pp. 1187–1190. Available at: https://www.irjet.net/archives/V6/i1/IRJET-V6I1220.pdf [Accessed: 28 November 2024].
  18. Gheorghe, A.C. and Chiran, M.S., 2018. Raspberry Pi Based Weather Station. The Scientific Bulletin of Electrical Engineering Faculty, 18(2), pp. 63–66. https://doi.org/10.1515/sbeef-2017-0037
  19. Mathur, V., Saini, Y., Giri, V., Choudhary, V. Bharadwaj, U. and Kumar, V., 2021. Weather Station Using Raspberry Pi. In: IEEE, 2021. 2021 Sixth International Conference on Image Information Processing (ICIIP), India, Shimla, 26–28 November 2021. IEEE, pp. 279–283. https://doi.org/10.1109/ICIIP53038.2021.9702687
  20. Savić, T. and Radonjić, M., 2015. One Approach to Weather Station Design Based on Raspberry Pi Platform. In: IEEE, 2015. 2015 23rd Telecommunications Forum Telfor (TELFOR), Serbia, Belgrade, 24–26 November 2015. IEEE, pp. 623–626. https://doi.org/10.1109/TELFOR.2015.7377544
  21. Jenkins, G., 2014. A Comparison Between Two Types of Widely Used Weather Stations. Weather, 69(4), pp. 105–110. https://doi.org/10.1002/wea.2158
  22. Bharadwaj, A., Sudhir, A., Shekhar, H., Khandelwal, N. and Kishor, I., 2021. Raspberry Pi Based Weather Monitoring System. International Journal of Research in Engineering, Science and Management, 4(8), pp. 114–117. https://doi.org/10.13140/RG.2.2.23682.45763
  23. Tatarchuk, I.A., Mamrosenko, K.A. and Giatsintov, A.M., 2024. Graphical GLX-applications functioning ensuring on industrial equipment using the EGL API. Radioelectronics. Nanosystems. Information Technologies, 16(3), pp. 407–418. https://doi.org/10.17725/rensit.2024.16.407 (in Russian).

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