AP23489999 "Development of intelligent technology and a digital platform for adaptive zoning of territories in the context of climate dynamics"

Relevance

Based on the application of the developed methods and models for specific agricultural territories, practical recommendations will be proposed for their scientifically based adaptation zoning (selection of a territory for promising crops, or selection of plants and technological parameters of cultivation for the studied territory), which will ensure an increase in the productivity of the territory and crop yields. The practical implementation of the research results will contribute to increasing the level of competence of the country as a whole: the availability of specialists with new competencies and the development of interdisciplinary technologies, which is very important for the innovation-oriented sustainable development of the state.

Purpose

Creation of methods, models, algorithms, knowledge bases and a digital platform that implements them, providing assessment, spatial, temporal and structural analysis of existing and forecast levels of greenhouse gas distribution and impact, formation of adaptation scenarios for zoning territories with the choice of optimal conditions for sowing crops or carbon plants, taking into account and redistributing carbon quotas.

Expected and achieved results

An analysis of 123 scientific and methodological sources on climate impact modeling and data mining in the field of ecological and food security was conducted. This allowed for the clarification of research objectives and the justification of new approaches. A research strategy was formed based on a new adaptive zoning scheme for growing priority crops. This scheme includes modeling and decision support stages, enabling the assessment of eco-economic situations and forecasting plant growth, considering both technogenic and climatic impacts. A system of principles for agro-ecological zoning using AI, GIS, 3D modeling, and other technologies was developed. Original methods for assessing the distribution and impact of greenhouse gases based on situational models using geographic information systems and neural network technologies were proposed. An automated recommendation generation method for crop planting, determining optimal technological parameters, was created to increase productivity. A carbon quota method based on Blockchain for decarbonizing agricultural production by creating a specialized space for the implementation and redistribution of carbon quotas through smart contracts was proposed. A 3D model bank of priority agricultural crops (592 models) was formed for visualized assessments of plant condition dynamics.

Research team members with their identifiers (Scopus Author ID, Researcher ID, ORCID, if available) and links to relevant profiles