Artificial intelligence in agriculture
Автор: Alferev Dmitrii Aleksandrovich
Журнал: АгроЗооТехника @azt-journal
Рубрика: Механизация, автоматизация и информатизация сельскохозяйственного производства
Статья в выпуске: 4 т.1, 2018 года.
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Agriculture and the agro-industrial complex are key sectors of the national economy; they provide people with food required for any human activity. In the context of population growth and limited territories, the problem of shortage of final products of the agricultural sector, as well as ensuring its high quality for all end users, comes to the fore. Modern breakthrough artificial intelligence technologies can help solve this problem to a large extent. Nowadays this tool is widely implemented in all economic sectors and, accordingly, there are no special obstacles to its use in the field of agriculture. This technology helps automate production and management processes to a large extent, as well as detect interrelations in large amounts of unstructured data. Thus, the goal of our paper is to generalize and systematize the knowledge about perspective technologies of artificial intelligence in agriculture which will help provide the population with qualitative food, and will also give the chance to the enterprises that implement these technologies to gain the corresponding competitive advantages. The article systematizesscientific knowledge about modern technologies of the agricultural sector, which successfully introduces artificial intelligence technologies: robotics, photography and local fixation of indicators, and audio and video analysis. A list of positive effects from their implementation and dissemination has been developed and presented. This publication will be useful for specialists in the agricultural sector, as well as scientists and researchers dealing with issues and problems of computer programming and modeling of artificial intelligent systems.
Agro-industry, artificial intelligence, robotics, photo, audio and video recording, big data analysis
Короткий адрес: https://sciup.org/147225580
IDR: 147225580 | DOI: 10.15838/alt.2018.1.4.5