Prospera

Prospera, the company founded two years ago by group of IT specialists and agronomists created one very interesting technology in which center there is a monitoring of cultivation of a harvest for the purpose of optimization of this process. Though certain data, for example, weather information and satellite images of low resolution are available to farmers long ago, it appears, it is not enough. Even in the presence of weather data from the state meteorological station which can be in 30 km from real location of agricultural grounds they do not reflect uzkolokalny climatic conditions which play a crucial role^[1].

However at large scales of agriculture the geographical dispersion of grounds complicates their detour and manual data collection. In rural areas it is also difficult to bring electricity and equipment cables necessary for data collection.

Today inexpensive sensors can obtain data on temperature and humidity, and inexpensive cameras can measure the illumination and solar radiation and transfer valuable images. Devices can be reported through Wi-Fi or 3G and in many cases can work at solar energy. This approach which allowed to use very effectively technology at cultivation of plants in the closed soil is even more often applied also in agriculture under the open sky now.

It is necessary to notice that Prospera considers itself not the supplier of sensors, and the company specializing in data. And its purpose — not only to help clients to collect data and in compliance with them to work, but also to create intelligence for work with data and to accumulate experience in this data domain.

In other words, there is a crowdsourcing element: though the detailed picture of data remains in secret, all of them (their volume in total can reach hundreds of thousands of indications of sensors a day) help to build, test and specify predictive models. These models help to keep track of the correlations between specific values in collected data relating to growth of a harvest and an exit of agricultural products. Understanding of these correlations and formation on this basis of forecasts just also makes in what Prospera sees gold grain of the value proposition.

In addition to predictive applications also the applications generating instructions are used here. In the considered area computer vision and work with images as in combination with a sensing technology of images diseases of crops can help to reveal capture of images are of great importance and to automatically direct personnel for carrying out the corresponding processing. It can also timely help to warn farmers about need of cutting of plants or the beginning of harvesting. Therefore in terms of economic effect not only data collection, but also their methodical analysis based on which it is possible to undertake adequate measures is necessary and to give instructions to workers.

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