Figure 1: Rainfall intensities in mm per hour detected and estimated using signals from telecom lines (coloured lines in the image at different frequencies and lengths) and satellite data for an area in the Kenyan Rift Valley
Figure 1: Rainfall intensities in mm per hour detected and estimated using signals from telecom lines (coloured lines in the image at different frequencies and lengths) and satellite data for an area in the Kenyan Rift Valley - UT researcher Kingsley Kumah optimised a machine learning algorithm to improve the resolution of rainfall predictions using satellite data. To train his algorithm, Kumah used rainfall information gathered with phone signals. This technology enables measurements in places that are difficult to access. In the Netherlands and other European countries, you just have to open an app on your telephone to get a fairly accurate prediction of the rainfall in the coming few hours. This is possible thanks to radar that can detect rainfall with a very high resolution. In many areas of the world, such as rural Africa, no such weather technologies are available. This makes rainfall predictions difficult.
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