Abstract
Around the world, producers across a variety of industries need tools and models for better measuring and monitoring water in order to guide decision making and improve productivity. Nowhere more is this the case than in irrigated agriculture. The purpose of this research is to develop a technology that integrates farmer costing data with on-site physical data provided by intelligent systems and technology to provide an account of on-farm water use. Currently, farm accounting technologies are not at the level of sophistication required to deeply consider the financial impacts of water use or loss. Water accounting technologies are not able to easily link to and integrate business systems and data to provide necessary monetary decision-making data, nor the context to support a smarter approach to cost-informed water management. Linking of soil moisture sensed data and local and remote weather station data to farm accounting in a potatoes case study demonstrates how smarter farm decision making can be supported by linking business systems and sensing technology.
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Acknowledgments
Great thanks to the very generous case study participants who graciously shared their time and knowledge. Thanks also to the University of South Australia for Research Themes Investment Funding.
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Tingey-Holyoak, J., Pisaniello, J.D., Buss, P., Wiersma, B. (2020). Cost-Informed Water Decision-Making Technology for Smarter Farming. In: Ahram, T., Karwowski, W., Vergnano, A., Leali, F., Taiar, R. (eds) Intelligent Human Systems Integration 2020. IHSI 2020. Advances in Intelligent Systems and Computing, vol 1131. Springer, Cham. https://doi.org/10.1007/978-3-030-39512-4_63
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