Hardware and software system for adaptive precision agriculture management within the consolidation of modern agrotechnologies in the crop production sector of the Kyrgyz Republic
Background Kyrgyzstan’s economy depends on agriculture. Of strategic importance are the natural conditions that form various ecosystems in different regions. The article highlights the problems that can be addressed by developing a unified software and hardware complex that ensures the fulfillment of the tasks associated with the agricultural production cycle. Materials and methods The comprehensive application of systems analysis, system engineering, and object-oriented design methods enabled the development of models for the software and hardware complex. These models were used during the development phase following the incremental life cycle model. Results The article presents models of the software and hardware structure, detailing the characteristics of each component and the categories of users along with their functionalities. Examples of user tasks and corresponding scenarios for using the digital system have been created. A prototype user interface has also been developed. Conclusion The use of this development fosters the creation of favorable conditions for crop cultivation in accordance with modern agricultural technology principles, allowing for ongoing and objective monitoring of plant health and farm facilities. The results can be used to create a national digital agri-food system that promotes sustainable development and food security.
Authors
- Oleg V. Dorofeev (ORCID: https://orcid.org/0000-0003-1868-0529)
- Irina Kulibaba (ORCID: https://orcid.org/0000-0002-8700-8763)
- Yana Beresneva (ORCID: https://orcid.org/0009-0009-1592-3995)
- Yuliya Smirnova
- Alex Karpov
Institutions
- Moscow University «Synergy» (RU)
- Moscow Polytechnic University (RU)
Publication Details
- Journal
- Frontiers in Computer Science
- Published
- 2026-03-03
- DOI
- https://doi.org/10.3389/fcomp.2026.1763420
- Primary Topic
- Smart Agriculture and AI
- Type
- article
- Field-Weighted Citation Impact
- 0.00