Weather Forecasting in Agriculture

The farmers must take into account a variety of factors when farming including but not limited to the soil, irrigation systems, and most importantly- weather conditions. Weather forecasting is a crucial factor that farmers must take into account to ensure healthy produce. 

Extreme weather conditions such as heavy rains, storms, or floods can lead to the loss of life and livelihoods, reduced crop yield, destruction of the infrastructure for distributing electricity, and disruption of water supply.

The whole yield of the crop is greatly dependent upon the weather conditions, so a farmer must be well-prepared and informed of impending weather conditions or climatic changes in order to produce a profitable crop.

IoT and AI are combined including weather prediction. Artificial intelligence algorithms can be used to process available weather data from your IoT sensors, and when combined with analytics, statistics, and machine learning capabilities, you can obtain a forthcoming weather forecast. 

You can also merge previous weather data from other sources because the more data there is, the more accurate the predictions will be. 

When your local field data, such as information about your specific crop kind, is included, this data becomes even more important and pertinent. The forecast predictions will then be improved to make them more useful and suitable for your local application. They can also take into account the particular developmental stage of your crop in addition to other local environmental aspects.

Although weather forecasting is nothing new, it can be made more accurate with the help of AI systems. In fact, a recent study found that the artificial intelligence system can predict the weather with the highest degree of accuracy up to a year in advance.