Concept of forming individualization of smart village methodology using AI cognitive processes

The study examines the role of digital agriculture in rural transformation and optimization of agricultural production, especially in the context of Russia. The article discusses the application of advanced sensors for soil and fertility analysis, which helps in determining potential yields and effective fertilizer application. Digital agriculture is presented as a tool to improve efficiency and productivity in rural areas, contributing to their economic growth. In addition, the study emphasizes the importance of adequate use of data and modern technology in farming. The analyses presented are based on extensive use of statistical and mathematical methods using various Python software packages. The conclusions of the study emphasize the need to integrate digital technologies in agriculture for sustainable rural development

Fundamentals of smart Village modeling in the context of integration of cognitive processes of artificial intelligence in the era of modern infrastructure challenges

The study focuses on the stages of implementation and development of smart villages, which are digital technologies for agriculture that increase efficiency and productivity in this area. We uncovered the stages of development of smart villages, then we looked at what is included in the Internet of Things within a smart village. After that, we looked at the specific digital solutions for agriculture and the purpose of smart village. As part of the study, we analyzed a number of indicators characterizing the development of the sphere of agriculture and its prospects. As the results of the study, we constructed and analyzed correlation matrices of indicators

Big data and analytics for crop yield forecasting: Empirical research and development prospects

The study provides a comprehensive analysis of the role and prospects of applying big data technologies in agriculture. It covers a wide range of issues related to the implementation and use of Big Data in the agro-industrial sector, exploring both the theoretical foundations and practical aspects of their application. Special attention is given to the examination of current trends, identification of key challenges, and opportunities associated with the use of these technologies in agriculture. The authors investigate how big data technologies are transforming approaches to managing agrarian processes, improving crop yields, and optimizing resources. Various aspects are analyzed, including the development of data processing technologies, their application for analysis and forecasting in agriculture, and discussions on issues related to the adoption and dissemination of these technologies in the Russian context. Specific examples of successful projects and initiatives demonstrating the potential of Big Data in agribusiness are presented

Robotics in agriculture: Advanced technologies in livestock farming and crop cultivation

This article provides an analysis of the impact of robotic systems on modern agriculture. Key aspects of integrating advanced technologies, such as automation of feeding processes, pasture management, and automated crop harvesting, are highlighted. Examples of successful implementation of innovative solutions on farms are discussed, including mobile feed mixers, automated calf feeding systems, smart soil sample collectors, and flying autonomous garden robots. Special attention is given to the analysis of the economic efficiency and sustainability of applying these technologies, as well as their impact on improving working conditions and reducing environmental impact. Challenges and problems related to high initial investments, the need for qualified personnel, and the adaptation of old farm structures to new technologies are also discussed. Conclusions are drawn regarding the prospects and opportunities that robotics opens up for agriculture, emphasizing its role in achieving sustainability and increasing productivity in the face of growing global challenges

Concept of forming individualization of smart village methodology using AI cognitive processes

The study examines the role of digital agriculture in rural transformation and optimization of agricultural production, especially in the context of Russia. The article discusses the application of advanced sensors for soil and fertility analysis, which helps in determining potential yields and effective fertilizer application. Digital agriculture is presented as a tool to improve efficiency and productivity in rural areas, contributing to their economic growth. In addition, the study emphasizes the importance of adequate use of data and modern technology in farming. The analyses presented are based on extensive use of statistical and mathematical methods using various Python software packages. The conclusions of the study emphasize the need to integrate digital technologies in agriculture for sustainable rural development

Fundamentals of smart Village modeling in the context of integration of cognitive processes of artificial intelligence in the era of modern infrastructure challenges

The study focuses on the stages of implementation and development of smart villages, which are digital technologies for agriculture that increase efficiency and productivity in this area. We uncovered the stages of development of smart villages, then we looked at what is included in the Internet of Things within a smart village. After that, we looked at the specific digital solutions for agriculture and the purpose of smart village. As part of the study, we analyzed a number of indicators characterizing the development of the sphere of agriculture and its prospects. As the results of the study, we constructed and analyzed correlation matrices of indicators