Smart Farm Research and Analysis Platform Photo = Intelligent Spatial Information Service Consortium

It will accelerate the realization of smart agricultural technologies such as AI spatial information and food security

- Accumulation of 1 million AI learning data in precision agriculture succeeded

With the success of accumulating 1 million AI (Artificial Intelligence) learning data in the precision agricultural field, it is expected to be a successful model for overcoming challenges to identify crop problems, prescribe, and secure food in the future.

The Intelligent Spatial Information Service Consortium (Space Information Co., Ltd., Infinite Information Technology Co., Ltd., New Layer Co., Ltd., and Gyeongsang National University) announced on the 18th that it has completed the construction of 1 million AI learning data for 10 crops.

Sponsored by the Ministry of Science and ICT and organized by the Korea Intelligence and Information Society Agency, this construction project is. It has been promoted to analyze the impact of rapidly changing climate change and to solve the problem of safe food supply and demand by preparing countermeasures for the crop crisis.

In February last year, MUHANIT Co., Ltd. and Spatial Information Co., Ltd. formed a consortium of companies specializing in intelligent spatial information services and succeeded in commercializing SMART LEMS, an intelligent service model, in the land, environment, facilities, and disaster areas. It plans to prepare an AI inference model that collects and processes crop growth data by acquiring hyperspectral images of drones within this year.

"The agricultural sector was a field where there were countless microscopic variables such as soil, temperature, humidity, and soil that made up the growth environment of crops, and it was difficult to obtain data," said Bae Kyung-rok, CEO of MUHANIT. "We can expect innovative changes as ultra-spectral technology and avoidance technology can analyze the growth environment through drones."

(Omit)

MUHANIT has completed the construction of 1 million AI learning data for 10 types of field crops through the AI learning data construction project (2nd).

In artificial intelligence learning, the amount of data is more important than anything else, and we will strive for the development of K-Farm through 1 million completed learning data.

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