An information-oriented model of risk prediction in food and environmental security based on artificial intelligence in the context of martial law

Work number - M 13 AWARDED

Presented Dnipro University of Technology

Authors:
1. LAKTIONOV Ivan – Dr.Sc. (Tech.), Professor of the Department of Computer Systems Software, Dnipro University of Technology
2. KASHTAN Vita – Cand.Sc. (Tech.), Associate Professor of the Department of Information Technologies and Computer Engineering, Dnipro University of Technology
3. DIACHENKO Grygorii – Cand.Sc. (Tech.), Associate Professor of the Department of Electric Drive, Dnipro University of Technology

The software and hardware for the practical implementation of an information-oriented model for predicting the risks of man-made and natural disasters in the food and environmental security of Ukraine in the context of martial law are proposed. The hardware and software basis of the model is an information technology based on satellite monitoring, wireless sensors, methods of machine learning and fuzzy logic. The developed technology is different from the existing ones in that it provides comprehensive predictive monitoring of critical parameters of natural and artificial ecosystems and infrastructure facilities in real-time with decision-making support. The assessment of the actual and anticipated state of the analysed objects and processes is conducted by software tools for processing time- and space-distributed measurement data based on artificial intelligence. This makes it possible to plan and implement an algorithm for preventing and neutralising threats to national interests.

The socio-economic effect is in the creation of a domestic IT product that is globally competitive in terms of its technical and functional characteristics and is the foundation for the innovative development of domestic industry, agriculture and infrastructure. The main results have been introduced into the production facilities of the National Academy of Agrarian Sciences of Ukraine and the International Scientific and Research Centre for Cyber Physical Technologies (Dnipro University of Technology, Reutlingen University). As a result of the implementation and use of the developed information technology, it has been found that the accuracy of detecting damage to infrastructure facilities reaches 98.1 %; the percentage of correct identification of burnt-out areas of natural ecosystems ranges from 92 % to 96 %; the accuracy of predicting the probability of grain crop diseases ranges from 95 % to 96.5 %.

Number of publications: 1 collective monograph in a Ukrainian edition, 1 chapter of a monograph in a foreign edition, 2 textbooks, 43 articles (20 – indexed in Scopus / WoS), 7 conference proceedings in Scopus / WoS, 6 single-authored conference papers. The total number of citations to the publications of the authors/h-index for the submission: Web of Science – 15/2, Scopus – 95/5, Google Scholar – 146/6. 3 patents of Ukraine for invention and 2 patents for utility model were obtained

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