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NquiringMinds have been working with local farmers to apply IoT sensor technology to the grain harvesting process. The task is a complex challenge as there are several variables to account for which affect the process. The agricultural environment is just one of the many applications of the platform, and this case study is a good example of the flexibility of the technology in true open source solutions.

The aim of the project is to lower the moisture content to just below the acceptable level. The grain is sold by weight and the closer to the upper limit, the more the grain will sell for. Above the limit and the seller has to pay a levy. By applying real time sensors and machine learning it will be possible to confidently dry the grain to just below the threshold. And sell the grain for several pounds a tonne more than would otherwise be possible. With one grain dryer processing thousands of tonnes a harvest the additional revenue can quickly add up.
The sensors are cheap and the value is added by knowing how to operate an IOT network in extreme conditions of up to 100 degrees centigrade and then apply machine learning and real time responses to a dynamic system. As with everything we do the platform is hardware neutral and so can be easily integrated onto any existing equipment.