The latest technologies in agribusiness include a range of IT solutions that reduce manual intervention with the top priority tasks to improve, develop, and implement projects based on smart agriculture, which operates on the principles of automation and robotization of production. The aim of the study is to develop a system of automated control of business processes for an agricultural enterprise. The system allows for remote collection and processing of data on technical and economic performance of the farming enterprise. It proves to be a low-cost solution due to the use of affordable and available equipment. When designing the system, the authors described its back end, as well as the connectivity architecture between sensors and modules on one side, and the microcontroller on the other. The paper features modules for monitoring and controlling electrical energy consumption, lighting, temperature, and humidity written in C ++ programming language. Test modules that were controlled by the Arduino microcontroller were analyzed. Further development of the system may involve devising and introducing IoT technologies based on the use of various architectural platforms for practical application.

The article is devoted to the application of economic and mathematical models of business planning management based on the use of the feedback principle. As the objective function (evaluation toolkit) of the task, the value of the execution time of the entire business project, which must be minimized, is considered. To solve this problem, it is proposed to form a class of admissible strategies for optimal adaptive control of the implementation process; as well as a specific business project using network economic and mathematical modeling is worked out. Within the limits of these strategies, the method of achieving optimal self-adjusting control of business planning processes is determined. the optimal execution time and the optimal timetable for the implementation of the project are determined. The main feature of the proposed new method is the ability to take into account the real conditions for the implementation works of the concrete project, which makes it possible to timely adjust the process of management of business planning and prevent disruptions in its implementation. This method also serves as the basis for constructing numerical algorithms for developing and creating the automated systems for realization of optimal adaptive control of business planning processes. The results obtained are illustrated on a specific business project for opening a public catering enterprise and show a high degree of efficiency in using the new method.

The article discusses the problem of optimizing the adaptive control of business planning processes by an economic entity. The results of the work are based on a new method of network formalization and optimization of adaptive project management, using network economic and mathematical modeling and the principles of adaptive control. The paper describes a new optimization network economic and mathematical model. This model takes into account the possibilities of monitoring the states of the process under consideration and adaptive control of the implementation of a business project. Within the framework of the formed network model, a new method for solving the task of network formalization and optimization of adaptive control of business planning processes is proposed. When implementing the proposed method, a strategy for optimal adaptive control of business planning processes is formed. On its basis, the optimal time for the implementation of a business project and the optimal schedule for its implementation in general are calculated. The article describes the practical application of the proposed method for solving the considered optimization problem on a specific example of the implementation of business planning processes in the development of new dishes at a public catering enterprise. The results obtained in the work show the sufficient efficiency of the developed new method of formalization and optimization of adaptive control of business planning processes. Further development of this area of research can be associated with the development of an intelligent computer system for optimizing the adaptive control of business planning processes and the creation of appropriate tools to support the adoption of management decisions by business entities during their implementation.

The article describes the functionality developed by the authors of an intelligent software system for optimizing adaptive control of business planning processes in the face of uncertainty. The results are based on a new method for optimizing adaptive project management using network economic and mathematical modeling. Based on this method, a methodology has been developed for solving the problem of optimizing adaptive control of business planning processes, which in the proposed intelligent software decision support system uses a block containing an adaptive control optimization model. As the objective function (evaluation functional) in the method used, the value of the length of the time period for the execution of the business plan, which needs to be minimized, is considered. The method used allows you to create a class of acceptable strategies for adaptive control of the implementation process for the business plan in question. Within the framework of this class of strategies, an optimal adaptive control strategy for the implementation of business planning processes is formed, the optimal time for its implementation and the optimal schedule for implementing the business plan as a whole, and the corresponding optimal adaptive control strategies are calculated. Application of the proposed new method in an intelligent software system allows for feedback and optimal time for the implementation of the business project as a whole. The developed intelligent system is designed to automate the modeling of business planning processes and optimize adaptive decision-making control during their implementation on the basis of network economic and mathematical modeling, as well as methods and tools for developing intelligent soft systems. The created system takes into account the existing specific technical and economic conditions and information support. The results obtained in this work can serve as the basis for creating intelligent instrumental systems for supporting managerial decision-making in the implementation of business planning processes in the face of information uncertainty and risks.