TAD NewsDesk, Russia: Cognitive Agro Pilot is a system designed by Sber and its ecosystem member Cognitive Pilot in Russia. It is an autonomous Artificial Intelligence-based driving system for farming equipment.
It has shown positive results and has been used in around 35 regions of Russia in the reaping of the 2020 harvest.
As a record from June to October 2020, over 350 New Holland, John Deere and CLAAS autonomous has associated with Cognitive Agro Pilot system and have shown great farm work in over 160,000 hectares of field and harvested more than 720,000 tonnes of crops.
Olga Uskova, CEO, Cognitive Pilot said,
“Controlled by the Cognitive Agro Pilot system, machines have worked over 230,000 hours, passing over 950,000 km this year. These high figures prove the setup is reliable and called-for among farmers. Partnership with Sberbank and leading agricultural holdings allows us not only to scale the use of technology efficiently but also guarantee that our clients enjoy high-quality local service.”
Moreover, Anatoly Popov, Deputy Chairman of the Executive Board, Sberbank said,
“A few years back, Artificial Intelligence (AI) in agriculture was a technology much talked about, but there were no practical examples of its widespread adoption in Russia. Now, once the first harvesting campaign with smart combines is over, we can say with confidence that the future is becoming a reality before our eyes, and what’s especially pleasing is that this is happening with the direct participation of Sber.”
Mr Popov also added,
“Russia is one of the leading countries in terms of agricultural production and is a key exporter of wheat, therefore, given the scale of production, the Cognitive Agro Pilot system has the potential to save the domestic agro-industrial complex millions of dollars.”
This AI-based system facilitates farming equipment such as grain combine harvesters, tractors, and sprayers. The system is equipped with the capability to take pictures from just one image of the video camera and by using a deep learning convolutional neural network fine-tuned for agronomic purposes. And hence it shows hope for some more technical advancements in the realm of agriculture.
Source: AgriculturePost.com
