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- W4308756426 abstract "Decisions in agriculture are frequently based on weather. With an increase in the availability and affordability of off-the-shelf weather stations, farmers able to acquire localised weather information. However, with uncertainty in the sensor and installation quality, farmers are at risk of making poor decisions based on incorrect data. We present an automated approach to perform quality control on weather sensors. Our approach uses time-series modelling and data fusion with Bayesian principles to provide predictions with uncertainty quantification. These predictions and uncertainty are used to estimate the validity of a sensor observation. We test on temperature, wind, and humidity data and achieve error hit rates above 80% and false negative rates below 11%." @default.
- W4308756426 created "2022-11-15" @default.
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- W4308756426 date "2022-11-08" @default.
- W4308756426 modified "2023-09-24" @default.
- W4308756426 title "Quality Control in Weather Monitoring with Dynamic Linear Models" @default.
- W4308756426 doi "https://doi.org/10.48550/arxiv.2211.04528" @default.
- W4308756426 hasPublicationYear "2022" @default.
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