International Scientific Journals
of Scientific Technical Union of Mechanical Engineering "Industry 4.0"

The present study examines autonomous factories as a contemporary manifestation of digital transformation in the manufacturing sector. Unlike traditional automation, autonomous systems demonstrate cognitive capabilities through the integration of artificial intelligence, machine learning, and cyber-physical systems. The technological architecture includes the Internet of Things, digital twins, advanced robotics, and blockchain technologies, functioning in synergy. The implementation process follows a phased evolution through five maturity levels. The analysis reveals multiple challenges – technical, financial, ethical, and regulatory. Empirical data shows that the primary difficulties stem from psychological resistance and organizational adaptation, rather than from technological limitations. The research examines the economic effects, changes in employment structure, and the social dimensions of the transformation. In conclusion, the necessity for a balanced approach is emphasized, integrating technological capabilities with human needs in the context of Industry 5.0 philosophy.

Artificial Intelligence (AI) is revolutionising the preservation and conservation of cultural artefacts by introducing innovative, noninvasive and highly efficient solutions. The integration of AI has transformed traditional approaches to the preservation, documentation and restoration of artefacts. Contemporary AI-based technologies and applications vary from computer vision and machine learning to natural language processing and high-fidelity digital surrogates. Applications such as AI-assisted imaging, 3D reconstruction, environmental data analytics and semantic metadata linking enhance both the physical and digital safeguarding of cultural assets. AI-driven platforms support provenance verification, forgery detection and adaptive preventive conservation, ensuring sustainable stewardship of heritage collections. This paper reviews current AI tools and applications in heritage institutions and fine-art contexts, highlighting their role in improving conservation accuracy, accessibility and long-term resilience of artefacts.

The report analyses AI-enhanced decision support architectures for multi-domain unmanned systems in defence operations. It examines how data from aerial, ground, surface and underwater platforms can be fused and processed through AI models to improve situational awareness and decision-making. The study outlines a layered architectural framework, highlights practical examples from recent conflicts and identifies key challenges related to data reliability, system resilience and human-machine interaction. The findings emphasise the need for robust, transparent and human-centred AI integration.

The article provides an insight into the analysis of trends in contemporary HR in the era of Industry 4.0, with an emphasis on the role of artificial intelligence (AI) in managers’ decision-making processes. The study addresses the opportunities and threats associated with the implementation of AI within HR and its impact on organizational effectiveness and human resource management. Using secondary data analysis and literature synthesis, we offer a deeper insight into modern HR management approaches and discuss the potential risks associated with digital transformation. The aim of the study is to provide practical recommendations for managers on how to deal with the challenges of the current Industry 4.0 era.

The application of artificial intelligence (AI) in medicine has emerged as a topic of global interest. Since the introduction of the term in the mid of 20th century, there has been considerable progress in the development of computer systems, leading into their integration into healthcare. At present, AI is increasingly being adopted across a growing number of medical specialties, where it contributes not only to diagnostic processes but also to the selection of appropriate treatments and the prediction of patient outcomes. AI prediction is particularly useful in the management of chronic conditions. Furthermore, AI demonstrates significant potential to expedite routine procedures, thereby allowing healthcare professionals to dedicate more time to cognitively demanding tasks, in which AI systems continue to present certain limitations. Nevertheless, despite notable advancements in recent years, several challenges must still be addressed in future research. These include the formulation of standards and guidelines for AI implementation, the assurance of cybersecurity to safeguard sensitive data, and the continuous education and training of healthcare practitioners. In conclusion, AI holds considerable promise for enhancing the quality and efficiency of healthcare delivery. Its role is not to replace human professionals, but rather to augment their performance and optimize the use of their time and expertise.

The rapid advancement of Industry 4.0 technologies has significantly transformed manufacturing environments, necessitating the adoption of intelligent and scalable solutions. MESWARM is a modern platform designed to digitize and optimize manufacturing processes, offering industrial enterprises a means to enhance efficiency, reliability, and sustainability. By integrating traditional Manufacturing Execution System functionalities with cutting-edge technologies such as Artificial Intelligence and the Internet of Things, MESWARM provides a flexible, modular system tailored to specific production needs. It’s architecture and key functionalities are outlined, highlighting its core modules such as Configuration, Production Management, and IoT. The potential of future modules, including Service Management, Adaptive Logic, Energy Management, Document Management, and AI-driven analytics, is also explored. By leveraging real-time data collection and analysis through MQTT-based communication, MESWARM facilitates precise production monitoring and predictive maintenance, minimizing downtime and enhancing operational decision-making. Real-world implementations are examined, showcasing its impact on production efficiency and system scalability.

This article presents the development process of Custom GPT based on GPT-4o for paid users and GPT-4 for non-paid users to promote and explain climate analysis and the use of GIS technologies in scientific projects. The bot’s work will be as a communication system, offering detailed scientific explanations on the topic, navigation and pointing to additional resources such as web pages, reports and visualizations. The article examines the planning of the bot, the structure and volume of the submitted information, as well as the possibilities of expanding its functions in the future. Potential additional tasks that the bot could take on, such as automating processes and assisting with data work, are being explored. The conclusions highlight the benefits of using GPT for the promotion of scientific results and the possibilities for future development of its functionalities.

New technological capabilities are becoming an increasingly important part of our daily lives. If we want to be sustainable and competitive, we as a society must take advantage of them. The huge volume of data cannot be used effectively without the implementation of artificial intelligence algorithms. And to be effective and useful, data must be protected and secure.

A review and analysis of methods for the detection and recognition of unmanned aerial vehicles (UAVs) has been carried out. UAV detection channels were considered – acoustic, optical, radar, infrared, radio reconnaissance channel. The advantages and disadvantages of the channels used are compared and evaluated. In the case of small UAVs, there are a number of significant difficulties and limitations. One of the directions in UAV detection is acoustic observations. The noise created by the UAV’s power plant and propeller is an important unmasking feature. The creation and improvement of methods for the detection, direction-finding and recognition of small UAVs by receiving and processing their sound signals is an urgent task. In the implementation of this method of detection of UAVs are used frequency spectra, spectrograms, normalized autocorrelation functions and phase portraits of acoustic signals. Information features of the UAV sound image can be estimates of spectral coefficients determined from a discrete implementation containing a given number of samples, as well as parameters of autoregressive models.

The use of artificial intelligence systems in public administration is of great importance and has great prospects. Artificial intelligence facilitates the interaction of various structures of the state system and the implementation of the direct activities of these structures. For public administration, it is important to analyze the mechanisms of behavior of a mass gathering of people. Since experimental analysis of crowd behavior is impossible, the creation of mathematical models with their subsequent software implementation is of particular importance.

This paper explores the pivotal role of technology and innovation in enhancing the resilience of Bulgaria’s critical infrastructure. It examines the integration of advanced technologies such as artificial intelligence, Internet of Things (IoT), blockchain, digital twins, unmanned aerial vehicles (UAVs), cyber-physical systems (CPS), and big data analytics in sectors like hazardous waste management, border security, and airport security. By analyzing case studies and current implementations, the paper highlights the successes and challenges faced in adopting these technologies. The study also discusses the importance of public-private partnerships and regulatory frameworks in fostering an environment conducive to technological innovation. The findings underscore the necessity for continuous investment in technology to safeguard critical infrastructure against emerging threats and to ensure long-term sustainability.

In the digital era, radical changes occur in all processes, under the influence of the dynamic development and application of intelligent technologies, including of artificial intelligence. The report explains the specific areas of application of artificial intelligence in human resource management processes, as well as the corresponding changes in these processes. Based on their own research, the authors indicate the specific benefits of applying artificial intelligence to HR processes.