Abstract
In aquaculture, fishery workers and researchers strong require to visualize water temperature. This is because knowing the water temperature makes it possible to take measures against fish diseases and predict the occurrence of red tide. In collaboration with fishery researchers, we constructed a multi-depth sensor network consisting of 17 water temperature observation devices over the Uwa Sea in Ehime Prefecture. In addition, we developed a Web system that can instantly visualize the water temperature measured on this network and provide it to fishery workers in the Uwa Sea. However, the water temperature information provided by this Web system is only current or past information, and fishery workers are requiring the provision of near-future water temperature forecasts for about 3 days. Therefore, in this research, as a new function of this Web system, we will implement a function to predict the water temperature in the near future from the past water temperature information and provide the forecast information. This paper examines the steps to be solved for the prediction of seawater temperature, which is the current problem in this system. Moreover, among the steps, this paper reports on the solution method and its evaluation experiment for improving the accuracy of water temperature interpolation.
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Agusa, Y., Endo, K., Kuroda, H., Kobayashi, S. (2022). Examination of Water Temperature Interpolation Method for Prediction. In: Choraś, M., Choraś, R.S., Kurzyński, M., Trajdos, P., Pejaś, J., Hyla, T. (eds) Progress in Image Processing, Pattern Recognition and Communication Systems. CORES IP&C ACS 2021 2021 2021. Lecture Notes in Networks and Systems, vol 255. Springer, Cham. https://doi.org/10.1007/978-3-030-81523-3_33
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DOI: https://doi.org/10.1007/978-3-030-81523-3_33
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