Abstract
Early crop yield prediction can address one of the most important agricultural challenges—feeding a growing population. The results of this prediction can be used to maximize crop yields. Crop growth is determined by a variety of weather, soil, and other micro-climatic variables. In addition, one of the most important parameters affecting crop growth, and over which the farmer has a large influence, is the selection of a sowing date. There are a few different models and simulators for predicting crop yields. However, they are rarely user-friendly. This paper focuses on developing a user-friendly mobile client that uses a simulator in the background to determine the sowing date which results in the highest crop yield. In the mobile application, a user selects the fixed interval of sowing dates and a crop type to obtain the sowing date that gives the highest predicted yield.
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Commonwealth Scientific and Industrial Research Organisation, https://www.csiro.au/en/.
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Acknowledgements
This work has been supported by the project IoT-field: An Ecosystem of Networked Devices and Services for IoT Solutions Applied in Agriculture funded by European Union from the European Regional Development Fund.
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Kralj, I., Skocir, P., Jezic, G. (2022). Mobile Client for Crop Yield Prediction Based on Weather Data. In: Jezic, G., Chen-Burger, YH.J., Kusek, M., Šperka, R., Howlett, R.J., Jain, L.C. (eds) Agents and Multi-Agent Systems: Technologies and Applications 2022. Smart Innovation, Systems and Technologies, vol 306. Springer, Singapore. https://doi.org/10.1007/978-981-19-3359-2_4
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DOI: https://doi.org/10.1007/978-981-19-3359-2_4
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