Due to modern microcomputers and platforms based on microprocessors such as, for example, Raspberry Pi, Orange Pi, Nano Pi, Rock Pi, Banana Pi, Asus Tinker Board – the development of prototypes of em-bedded systems is possible in a «design» mode. The software part is implemented on the basis of operat-ing systems and standard technologies based on well-known programming languages such as C / C++, Python, C#, Java, etc. In such case the control channel for the embedded system can be either imple-mented via a web service separated by a communication channel or controlled independently. It is im-portant to understand that creating an embedded system on a standard platform is much more expensive than buying a ready-made mass-produced device with the same functionality. Therefore, it makes sense to use platforms like the Raspberry Pi mainly for individual artificial devices. If it is necessary to build a project of embedded systems and there is a problem with choosing a hardware platform for the client side, then currently there is a wide range of boards and solutions for building an efficient and inexpen-sive system using ready-made modules. The number of expansion cards and various sensors, video cam-eras, internet connection via Ethernet, Wi-Fi and Bluetooth provides a wide range of opportunities for building almost any solution based on this component base. The foundation can be made within a small budget, with minimal time spent, using large blocks and ready-made libraries for programming embed-ded systems. This article presents the results of research and development work on the creation of a software and hardware infrastructure of a terrestrial platform with the elements of artificial intelligence. Based on the actual results of the research, a deployment diagram and a component diagram of such an infrastructure have been constructed.

У роботі розглянуто спосіб підвищення ефективності обміну структурованими даними, який може застосовуватися під час розробки програмного забезпечення. Як засоби вирішення проблеми представлено власний формат серіалізації даних, спеціально розроблений з врахуванням специфіки сутностей у реляційній моделі, та механізм програмної обробки даних при десеріалізації, що дозволяє значно підвищити продуктивність роботи застосунку. Фактичним результатом дослідження є побудова концепції експериментального формату та варіант реалізація запропонованого методу обробки даних.