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Implementation of Industry 4.0 Solutions in the Agricultural Field of Ukraine

EasyChair Preprint no. 10354

10 pagesDate: June 7, 2023


This article is devoted to Industry 4.0 technologies implemented in the agricultural industry of Ukraine. For Ukraine, online services ensure a civilized use of land, increase the land value and market intelligence, reduce the risk of corruption to zero. The successful direction for Ukrainian farmers is trade with Europe. The Ukrainian team has been creating agricultural drones for farmers within the frames of the Kray Technologies startup since 2017. The introduction of innovations ensures the accuracy of measurements, the speed of data collection and processing. Drones allow to collect abundant photo data which is applied to estimate the biomass and crops’ growth parameters, their storage locations and the percentage of weed contamination. These data make it possible to carry out differentiated enrichment with fertilizers of different brands.

The agriculture was one of the first to feel the consequences of the full-scale Russian aggression in Ukraine, which began on the 24th of February. The war forced farmers to become food security guards. The Cabinet of Ministers of Ukraine with its order approved the action plan aimed to ensure food security in the conditions of martial law. Special attention is paid to the optimization of areas for certain crops. The scientific novelty of the present work consists in the application of the Lagrange multipliers method for solving the problem of optimizing the calendar plan for the sale of agricultural product stocks under price risk conditions. A price risk scenario with non-determined future market prices is considered.

Keyphrases: food security, Industry 4.0, Lagrange multipliers

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  author = {Tsesliv Olga},
  title = {Implementation of Industry 4.0 Solutions in the Agricultural Field of Ukraine},
  howpublished = {EasyChair Preprint no. 10354},

  year = {EasyChair, 2023}}
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