The economic component of the principles of building synthetic nervous systems

Abstract

Introduction. The digital economy, which the Russian Federation has embarked on, consists of a set of automated control systems, the effectiveness of each of which determines the effectiveness of the entire digital economy. Therefore, one of the main tasks that needs to be solved on the way to its construction is the creation of a fundamentally new, cost-effective architecture for building automated control systems.Purpose. This scientific study pursues the fundamental objective of systematizing and precisely formulating the postulates for constructing automated control systems (ACS) based on synthetic nervous systems (SNS). It represents a logical extension of the authors' publication series dedicated to a comprehensive assessment of the economic efficiency of this paradigm in developing data acquisition automation and process control systems. The proclaimed economic advantages, thoroughly analyzed in prior research, are attainable exclusively through strict and unwavering adherence to these postulates; their violation entirely nullifies or substantially diminishes the positive economic effect of SNS implementation.Methods. The methodological foundation encompasses a systematic and comprehensive analysis of an extensive corpus of technical and scientific literature on ACS development and optimization. Building on this, the authors consolidated the identified principles under the unified designation "SNS construction postulates", providing detailed descriptions of each alongside quantitative evaluations of their economic impacts. The approach leverages simple yet universal engineering practices, which despite their evident nature to specialists have previously lacked clear and consolidated formulation in available publications.Results. As the key result, postulates are formulated, positioned as fundamental directives and imperatives of design. Thorough assimilation and application of the postulates is declared mandatory for every automation system integration engineer, guaranteeing the achievement of economic efficiency in automation systems. The formulated postulates will not surprise qualified specialists due to their obvious logical simplicity and practical validity. Conclusions. Synthetic nervous systems are a new direction in the development of automated control systems. Russia could become a leader in their production and the birthplace of this technology. It is obvious that the economy of the future is not a digital economy or even a knowledge economy, but, above all, an economy of high, knowledge–intensive technologies. One of the ways the Russian Federation can succeed in the world of the economic future is to find new, more effective methods of using the technologies available to it, even if they are foreign. The development of synthetic nervous system technology is one such way.