Комп’ютерно-інтегровані технології автоматизації технологічних процесів на транспорті та у виробництві

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Adaptive learning with ai: analysis of existing solutions and development prospects
(Харківський національний автомобільно-дорожній універститет, 2024) Altynali, N.
In the context of rapid technological development, adaptive learning systems are becoming important innovations that can transform the educational process through personalization and interactivity. This article analyzes existing solutions in the field of adaptive learning using artificial intelligence (AI) and discusses the prospects for their further development. Key technologies such as natural language processing, machine learning and recommendation systems that allow content to be adapted to the individual needs of students are being explored. The advantages of such systems in increasing student engagement, academic performance and motivation, as well as their limitations related to ethical aspects and technical barriers, are shown. Based on the analysis of modern research, directions for improving adaptive systems are proposed, including improving scalability, developing inclusive solutions and ensuring data security. The article focuses on the importance of an interdisciplinary approach in the development of educational technologies to create an inclusive and effective learning experience.
Analysis of ai-driven approaches to professional selfdetermination: a focus on psychology, skills, and market trends
(Харківський національний автомобільно-дорожній універститет, 2024) Zhaxygeldiyeva, K.
Artificial Intelligence (AI) is increasingly transforming career guidance by offering personalized recommendations based on psychological profiles, skill mapping, and labor market trends. This paper examines the current and potential applications of AI in career development, particularly in the fields of psychology, skill mapping, and market trend analysis. By leveraging AI-driven tools, career counselors can provide personalized advice by assessing individual personality traits, cognitive abilities, and professional skills. Additionally, AI systems use real-time labor market data to align individual capabilities with emerging job opportunities, helping people navigate an ever-evolving workforce landscape. This study also explores AI’s integration into career counseling tools, such as chatbots, and its role in skill mapping to match personal abilities with career demands. A systematic literature review (SLR) was conducted, including primary studies retrieved from databases such as ScienceDirect, IEEE Xplore, ResearchGate, and ASICT. The findings highlight the growing role of AI in shaping career decisions, offering new opportunities for career development in a competitive job market. Despite being in early stages, AI's potential for revolutionizing career guidance is significant, with the promise of improving decision-making accuracy and aligning skills with market needs.
Analysis of blockchain technology
(Харківський національний автомобільно-дорожній універститет, 2024) Kashaganova, G. B.; Sekushin, N. S.
This article provides a brief overview of blockchain technology. Blockchain is a decentralized distributed database that ensures secure and transparent transactions. It allows transactions to occur without the need for third parties. The article gives an example of blockchain technology, explains its basic principles, types, and examples of its use in IT products.
Analysis of cloud authentication systems for biometric data
(Харківський національний автомобільно-дорожній універститет, 2024-10) Assylbek, D. O.
This article analyzes cloud authentication systems that use biometric data to enhance security. Cloud technologies enable efficient management of biometric data, providing high security and user convenience. However, these systems face challenges related to data storage security, privacy, and infrastructure reliability.
Analysis of the thermal characteristics of a solar heat supply system with thermosiphon circulation
(Харківський національний автомобільно-дорожній універститет, 2024) Tolepberdinova, A.; Nugmanova, S.; Ormanbekova, A. A.
Blockchain in education: studying smart contracts to create a decentralized system
(Харківський національний автомобільно-дорожній універститет, 2024) Koshkinbayeva, B.; Kalpeyeva, Z.
Recently, blockchain technology has been actively studied and used by both researchers and practitioners. This is due to its unique features, such as decentralization, security, reliability, and data integrity. The article is devoted to the possibility of introducing blockchain technology into the educational environment through smart contracts. To achieve this goal, the following tasks were set: to study blockchain technologies for their applicability in the educational environment; to justify the need for using smart contracts in the educational process; to develop an algorithm for implementing smart contracts for storing educational information and using it for further analysis. The Ethereum platform was chosen for the development of smart contracts. The program code of the smart contract was compiled in the Remix compiler.
Description of the conceptual-architectural model of the smart city
(Харківський національний автомобільно-дорожній універститет, 2024) Togzhanova, K. O.; Rametov, N.
Today, cities have become the main drivers of economic development, standing at the forefront of production and consumption networks. They shape social and economic relations and contribute a significant portion of the gross domestic product (GDP) in many countries. Cities play a central role in national, regional, and global development, and the quality of life for people depends on them. As a result, there are growing demands on cities that were unprecedented in the past, including the need for accessible urban infrastructure, high mobility, urban security, environmental cleanliness, and the development of local self-government.
Development of robotic systems for autonomous control in smart cities and industry 4.0
(Харківський національний автомобільно-дорожній універститет, 2024) Zhaskairatov, K.; Aliyeva, Marta
Digital technologies for control of heat cooling supply systems at industrial facilities: increasing efficiency, economy and reliability
(Харківський національний автомобільно-дорожній універститет, 2024) Mashchanova, T. R.; Ormanbekova, A. A.; Nugmanova, S. A.
Currently, industrial facilities are facing increasing demands on the efficiency, reliability and cost-effectiveness of heat and cooling systems. The article discusses the use of modern digital technologies to control such systems. SCADA systems, IoT sensors and predictive analytics play an important role in optimizing heat and cold supply management processes at industrial facilities.
Iot air exchange control system
(Харківський національний автомобільно-дорожній універститет, 2024) Sultanbay, A. J.
The article is devoted to the research and development of an intelligently controlled air exchange system based on IoT technologies for use in urban environments. With increasing urbanization and environmental degradation, traditional ventilation systems cannot cope with changing conditions that require the development of new air quality management solutions. This study proposes a system that uses air quality sensors to monitor pollution, temperature and humidity in real time, as well as IoT technology to automatically adjust air flow. During the research, the system was modeled and experimental tests were carried out. The results showed that the introduction of an intelligent system will significantly improve indoor air quality by reducing pollution levels by 15-25% compared with traditional air exchange methods. The system also helps to save energy and reduce operating costs. This solution has significant potential for use in urban infrastructure, contributing to the improvement of the environment and quality of life.
Medical robots in Kazakhstan: current state and prospects for development
(Харківський національний автомобільно-дорожній універститет, 2024) Aigerim, A. N.; Erikzhan, A. A.; Ulbala, B. K.; Ulan, D. A.; Anargul, A. S.
Overview of computer vision areas application for inspection and quality control
(Харківський національний автомобільно-дорожній універститет, 2024) Khalimonov, Y. I.; Sotnik, S. V.
Overview of digital locks with artificial intelligence
(Харківський національний автомобільно-дорожній універститет, 2024) Lvov, А. А.; Sotnik, S. V.
Predictive maintenance using artificial intelligence and machine learning
(Харківський національний автомобільно-дорожній універститет, 2024) Tleuova, A. A.; Beketova, G. S.
Predictive maintenance is a method that helps predict potential equipment failures and avoid unexpected breakdowns. Recently, artificial intelligence (AI) and machine learning (ML) technologies have increasingly been used for predictive maintenance. These technologies allow significant reductions in emergency repair costs and extend the lifespan of equipment. This article explores how these technologies can be applied in Kazakhstan to improve maintenance processes in industries. The aim of the work is to investigate predictive maintenance methods and adapt them to the conditions of Kazakhstan's industry. The following methods are used in the study: Analysis of historical data on failures to predict future breakdowns; Use of sensors to analyze equipment status in real time; Development of hybrid models combining different approaches to improve prediction accuracy. The results of the study showed that using AI and ML for predictive maintenance can help reduce repair and maintenance costs and improve equipment performance. Data analysis from sensors allows timely detection of faults, which helps avoid prolonged downtimes. During the study, failure prediction models were developed, showing prediction accuracy of up to 98.7% with low error rates. These models can be useful not only for large enterprises but also in other sectors of Kazakhstan's economy, such as energy, agriculture, and transportation, which will improve the overall efficiency of the industrial sector.
Remote monitoring using the keras library
(Харківський національний автомобільно-дорожній універститет, 2024) Kashaganova, G. B.; Ilakhunov, P. Kh.
This article discusses the use of modern technologies, including mobile applications and neural networks, for remote patient monitoring. Various applications of artificial intelligence in medicine are described, such as real-time monitoring, diagnostics, personalized treatment, and remote consultation. Particular attention is paid to the use of mobile device cameras in medical applications for video consultations, symptom recognition, disease monitoring, and patient response analysis. An example code for image classification using deep neural networks is provided. The final part of the article discusses the importance of using mobile health with neural networks for remote patient monitoring and predicting possible complications.
Research and development of a mobile reconnaissance robot
(Харківський національний автомобільно-дорожній універститет, 2024) Tokbayev, S.; Zhumahan, N.
Research and development of an intelligent controlled air exchange system for use in standard conditions based on iot
(Харківський національний автомобільно-дорожній універститет, 2024) Dzhumabekova, Z. A.; Fazylov, N. N.
The article discusses the basic principles of the Internet of Things (IoT) and embedded systems, as well as their interconnection and application in various fields such as smart homes, healthcare, industry and transport. The role of these technologies in improving the quality of life and increasing the efficiency of various processes is emphasized. Particular attention is paid to the prospects for the development of IoT in the context of the introduction of 5G technology, which is expected to contribute to a sharp increase in the number of connected devices and reduce energy consumption. It is expected that by 2021, the number of IoT devices in the world will reach 16 billion. The research is aimed at analyzing modern achievements in the field of IoT and identifying the challenges faced by these technologies, as well as considering their prospects in the context of digital transformation of society. The article also describes research methods, including theoretical analysis, comparative analysis, modeling and experimental testing. The results of the study show that the introduction of IoT and 5G technologies will lead to fundamental changes in society, business and production processes, opening up new opportunities for automation and optimization of various fields of activity.
Research on the characteristics of criminal offenses in the field of information and communications
(Харківський національний автомобільно-дорожній універститет, 2024) Yuldashev, R.; Kalpeyeva, Z.
The rapid development of digital technologies and the expansion of internet access in Kazakhstan have led to a surge in cybercrimes, which pose significant risks to society and individuals. This research investigates the characteristics of criminal offenses in the area of information and communications, highlighting trends, legislation, and the role of cybersecurity measures in mitigating these risks. By analyzing data from various sources and evaluating criminal statistics, the paper explores the need for enhanced laws and technological frameworks to address these crimes.
Review of methods for determining obstacles in the way of vehicles
(Харківський національний автомобільно-дорожній універститет, 2024) Togzhanova, K. O.; Nokerova, S. O.
As regions develop, it becomes important to adapt the transport system to the changing socio-economic dynamics of municipal districts, industrial centers, urban areas, and transportation networks. This includes improving cargo flow management and traffic control systems. Today, vision systems are widely used, especially in road safety and logistics, to address various challenges.
Robotics and automation: challenges and prospects for industrial production
(Харківський національний автомобільно-дорожній універститет, 2024) Ormanbekova, A. A.; Bakyt, Zh. A.