Precision Irrigation From Soil Sensor Networks: A Case Study of Water Saving Against Yield Risk
DOI:
https://doi.org/10.5281/zenodo.22661274Keywords:
Precision Irrigation From Soil Sensor Networks; Applied machine learning; Evidence synthesis; Production deployment; MLOpsAbstract
Precision Irrigation From Soil Sensor Networks is an area of active development in applied machine learning, with evidence that
has accumulated unevenly across its component questions. We review the current evidence base for precision irrigation from soil
sensor networks, spanning methodological, implementation, governance, and cost dimensions, focusing on where practice has
converged and where it continues to vary, and set out the practical considerations relevant to a team considering its adoption. We
conclude that selective, context-specific use is best supported by the evidence currently available, rather than uniform adoption or
avoidance
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