Thesis supervisor: Anikó Éva Nyéki
Location of studies (in Hungarian): SZE-AKMK Department of Biological Systems and Precision Technology Mosonmagyaróvár Vár square 2. building "V" Abbreviation of location of studies: AKMK
Description of the research topic:
Farm and in situ observations (Internet of Things databases from sensors) together with existing databases provide the opportunity to both predict yields using "simpler" statistical methods or decision support systems that are already used as an extension, and also enable the potential use of artificial intelligence. The latter has the advantage of being able to handle many parameters indefinitely in time and space, i.e., big data databases created using precision management tools and data collection capabilities can be used in the areas of the meteorology, technology, and soil-related information, including characterizing different plant species.
Keywords: crop models, artificial intelligence, deep learning and machine learning, big data, database of IoT, remote sensing, data fusion, Inter season forecast, sustainable crop production (prediction of water and nutrient deficiencies), yield influencing variables, automated crop production
Number of students who can be accepted: 1
Deadline for application: 2024-05-31
2024. IV. 17. ODT ülés Az ODT következő ülésére 2024. június 14-én, pénteken 10.00 órakor kerül sor a Semmelweis Egyetem Szenátusi termében (Bp. Üllői út 26. I. emelet).
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