Intelligent System Architecture Research Articles

Research on the Intelligent System Architecture and Control Strategy of Mining Robot Crowds

Despite the pressure of carbon emissions and clean energy, coal remains the economic backbone of many developing countries due to its abundant resources and widespread distribution. The stable supply of coal is also vital for the global economy and remains irreplaceable in the future global energy structure. China has been a major contributor to annual coal output, accounting for nearly 50% worldwide since 2014. However, despite implementing intelligent coal mining technology, China’s coal mining industry still employs over 1.5 million underground miners, posing significant safety risks associated with underground mining operations. Therefore, the introduction of coal mining robots in underground mines is an urgently needed scientific and technological solution for upgrading China’s and even the world’s coal energy industry. The working face needs a shearer, hydraulic support, a scraper conveyor, and other equipment for coordination. The deep integration of intelligent technology with factors such as “humans, machines, the environment, and management” in the workplace is the core content of intelligent coal mines. This paper puts forward an advanced framework for robot technology systems in coal mining, including single robots, robotized equipment, robot crowds, and unmanned systems. The framework clarifies the common key technologies of coal mining robot research and development and the cross-integration with new technologies such as 5G, the industrial internet, big data, artificial intelligence, and digital twins to improve the autonomous and intelligent application of coal mining robots. By establishing a scientific and complete standard system for coal mining robots, we aim to achieve the customized research and development and standardized production of various types of robot. A specific analysis is conducted on the research progress of common key technologies such as the explosion-proof design, mechanical system innovation, power drive, intelligent sensing, positioning and navigation, and underground communication of coal mining robots. The current research and application status of various types of coal mining robots in China are summarized. A new direction for future coal mining robot research and development is proposed. Robotic mining systems should be promoted to enhance the overall intelligence level and efficiency of mining equipment. To develop human–machine environment-integrated robots to improve the autonomy and collaboration level of coal mining robots, the digital twinning of the entire mine robot system should be accelerated; the normalized operation level of coal mine robots should be improved; research on coal mining robots, shield support robots, and transportation robots should be performed; intelligence should be achieved in fully mechanized mining faces; and equipment shield support for fully mechanized mining faces should be provided. The practical process of implementing coal mining robotization is summarized in this paper, and the technical and engineering feasibility of the coal mining machine population is verified.

РАЗВИТИЕ АРХИТЕКТУРЫ ИНТЕЛЛЕКТУАЛЬНЫХ ТРАНСПОРТНЫХ СИСТЕМ

The paper analyzes the role of a complete architecture of intelligent transport systems (ITS) in ensuring their effectiveness. Many countries or groups of countries have ITS architecture with successful results of its application in practice. It is shown that the ITS architecture is constantly being updated and this is a characteristic trend. The paper proposes new approaches to the formation of the architecture of the integration platform within ITS. The scheme of organisation of data flows in different loops of software tools of the integration platform is developed. It is proposed to separate the control loops proper transport system data and identification data, which describe a partisipant of the ITS (digital object) with the expansion of capabilities in a cooperative ITS. It is possible to organise linked chains of identification of ITS digital objects, to participate in the formation of network structures for ITS work processes, describing the behaviour of digital objects during ITS processes and the behaviour of end users in accordance with the properties of network structures.

Processing method for multi-source data fabric system based on intelligent system architecture

Currently, the data management of power enterprises faces the need to analyze data sources from multiple places. However, traditional multi-source data fabric systems have problems such as low analysis efficiency and high error rates, which brings great inconvenience to the data analysis of power enterprises. In order to improve the accuracy and efficiency of data analysis in data structure systems, the intelligent system architecture is applied to the construction of source data structure systems. The main modules are data collection, data matching, data integration, and data analysis. This article uses simulated annealing genetic algorithm to perform high-performance calculations on system timing data, thus achieving data matching. This article conducted data level data integration, feature level data integration, and decision level data integration. The access survey method was used to analyze the current data management problems faced by power companies. The evaluation and analysis of general multi-source data fabric systems and multi-source data fabric systems based on intelligent system architecture were conducted using the evaluation panel evaluation method. The analysis results showed that the operational convenience of the multi-source data fabric system based on intelligent system architecture could reach 60%–80%, which greatly improved compared to general multi-source data fabric systems; the information sharing of multi-source data fabric systems based on intelligent system architecture was greatly improved; the data processing efficiency of general multi-source data fabric systems was much lower than that of multi-source data fabric systems based on intelligent system architecture; however, the symmetry of data collection and matching in the multi-source data fabric system based on intelligent system architecture was slightly insufficient, and further improvement was still needed. In order to benefit more power companies through the intelligent system architecture based multi-source data fabric system, it was necessary to strengthen the management of data collection and matching symmetry.

ОСОБЕННОСТИ МЕТОДОВ РАЗРАБОТКИ АРХИТЕКТУРЫ ИНТЕЛЛЕКТУАЛЬНЫХ ТРАНСПОРТНЫХ СИСТЕМ В КИТАЙСКОЙ НАРОДНОЙ РЕСПУБЛИКЕ

This paper considers the development steps and key points of China's intelligent transportation system architecture, and, at the same time, explains the transformation between the stages and the integration of the logical architecture, thus forming a data flow diagram of the logical architecture. The physical architecture is formed on the basis of the logical architecture, and provides the basis for the proposed application system with Chinese characteristics.

Medical decision support in the light of interactive granular computing: Lessons from the Ovufriend project

The main aim of the paper is to discuss the architecture for the future Intelligent Systems (IS's) and Decision Support Systems (DS's) dealing with complex phenomena such as supporting medical decisions (diagnosis and therapy) and to emphasize challenges in designing such systems. More precisely, the paper presents arguments for developing a specialized computing model based on the interactive granular computing paradigm which can help to design IS's and DS's more close to the prototypes of real life decision making. In this regard, the paper brings to the fore different experiences faced during designing other medical IS's or DS's.As a starting step, the paper considers the experience of developing the OvuFriend platform and outlines some possible extension of it in the framework of the proposed architecture on the basis of Interactive Granular Computing (IGrC) model. Specifically, our attempt is to analyze a scheme, which is being used in the platform of OvuFriend for determining health risks and possibilities of a woman to conceive a child, from the perspective of IGrC. The target of the paper is two fold. Firstly, to show how the underlying AI algorithm of this scheme can be related with the notion of computing in the context of IGrC. Secondly, to identify possible extensions of the existing scheme so that it becomes more dynamic, interactive, and close to personalized medicine.

Deep reinforcement learning for solving steelmaking-continuous casting scheduling problems under time-of-use tariffs

This paper proposes a novel intelligent scheduling method based on deep reinforcement learning (DRL) to solve the multi-objective steelmaking-continuous casting (SCC) scheduling problem, under time-of-use (TOU) tariffs for the first time. The intelligent scheduling system architecture is designed, and a mathematical model is established to minimise the total sojourn time and electricity cost. To effectively reduce production costs by avoiding peak periods of electricity consumption, the ‘start time’ of the system is generated based on the Markov Decision Process (MDP), and heuristic scheduling rules related to power cost are used as the action space, with corresponding reward functions designed according to the characteristics of these two objectives. To satisfy the continuous casting which is a particular SCC constraint, a backward strategy is developed. Additionally, a branching duelling double deep Q-network (BD3QN) is adapted to guide action selection and avoid blind search in the iteration process, and then applied to real-time scheduling. Numerical experiments demonstrate that the proposed method outperforms comparison algorithms in terms of solution quality and CPU times by a large margin.

Operation and Maintenance System Architecture Design and Practice for Cloud-network Integration

As cloud-network integration, 5G and 6G, all-optical network, and IP-based services evolve, operational systems of operators face new challenges. The current operational systems suffer from inconsistent technical architecture, insufficient data sharing, lack of decoupling capability, and inadequate intelligence, leading to a high maintenance workload and poor customer experience. This paper analyzes the requirements of intelligent operation systems for operators and innovatively proposes an architecture and design scheme for intelligent operational systems based on cloud-network integration. The paper summarizes the practical experience of the new generation of cloud-network operation and maintenance systems and proposes improvements and outlooks for the development of the next generation of operational management systems.

An architecture for the dynamic adaptation of an intelligent multi-tutoring system

The articulation between machine tutoring and human tutoring remains a productive research within in the context of Intelligent Tutoring Systems (ITS), particularly in the context of e-learning where the dropout rate is high. We explore an innovative approach, the automation of tutoring as it is done in the classroom to respond to the difficulties of the learner. We propose a generic Intelligent Multi-Tutoring System (IMTS) architecture composed of two modules COMES and MAT. The Communication Entry Service (COMES) module manages communications between the IMTS and a Learning Management System (LMS). The module Multi-Agent Tutoring (MAT) is the multi-agent system developed with JADE, which allows the dynamic adaptation of tutoring (Machine, Peer, Teacher) according to the profile of the learner. We offer a configurable system to customize tutoring to the individual needs of each learner. It can be grafted onto any learning platform, making it multidisciplinary and easy to integrate into existing learning environments. The teacher will be able to devote more time to learners which need greater his intervention.The peer will develop human and relational qualities linked to their know-how, transversal skills sought by recruiters. To validate this architecture, we provide an application and results that integrate the elements of the described model. The results of the experiment prove the feasibility and reliability of our approach.

Use of cognitive load measurements to design a new architecture of intelligent learning systems

In the context of learning environments, the learner’s attention and mental effort are of primary interest in the process of acquiring knowledge. Due to the skills and abilities of each learner, there is a growing need for generic and adaptive environments. In this work, we introduce a new architecture for such environments to assist the learner with a multi-agent-based approach. Using Electroencephalogram, this architecture generates learning content and interactions adapted for each learner. Moreover, this work presents a new unsupervised approach to estimate and recognize the learner’s cognitive load based on the Standardized Euclidean Distance (SED) and the Power Spectral Density (PSD) of brain rhythms within low frequencies, namely Theta[4–7 Hz] (θ) and Alpha [8–11 Hz] (α). The learner’s outcomes and estimated mental efforts are combined in the evaluation process using a fuzzy logic-based approach. Three experimental protocols are adopted in order to validate our study. These protocols are based on cognitive tasks with different difficulty levels. Experimental results show that PSD in θ and α bands in the occipital lobe accurately describe changes in the learner’s mental efforts and cognitive load according to the cognitive task difficulty level. Based on the Cohen Kappa coefficient, our cognitive load estimation approach, using α, is compared to an existing cognitive load index from the literature. This performance assessment process revealed large values (k≥0.48) in the occipital lobe, which reflects the efficiency of the proposed approach. Results from this study are mainly used in educational engineering and reeducation in order to subjectively assess the approaches and treatments offered in these contexts.

Intelligent Transport Systems as the Basis of de Lege Ferenda of the Transport System of the Russian Federation

Objective: to research the trends of legal regulation of using intelligent transport systems under digital transformation of the transport sector of economy, namely, the growing importance of intelligent transport systems in the future transport system of the Russian Federation.Methods: systemic-structural method is the basis for researching intelligent transport systems. It enables to study the architecture of intelligent transport systems as a complex structural unity. Also, comparative-legal method was used, aimed at illustrating the differences and similarities in the legal regulation of intelligent transport systems. Methods of legal modeling and forecasting, as well as formal-logic method, served as secondary methods to comprehensively study the legal regulation of intelligent transport systems.Results: the article presents conceptual approaches to defining the notion of “intelligent transport systems” and outlining the hierarchy of intelligent transport systems, which play a fundamental role in building the transport sector. Based on the analysis, conclusions are made about the vectors of forming transport legislation, aimed at regulating the use of intelligent transport systems.Scientific novelty: the article provides a conceptual approach to forming the legal regulation of intelligent transport systems. To this end, the issue is considered about the essential content of the notion of “intelligent transport systems” at legal and scientific levels; the current terminological problems in building the legal regulation are shown. Analysis of the architecture of intelligent transport systems allowed for the first time to formulate the basic approaches to shaping the legal regulation of its individual elements (including highly automated and fully automated transport means, “smart” infrastructure, etc.) not in isolation but as constituent parts of the whole matter.Practical significance: the presented materials and conclusions facilitate the development of legal regulation of transport industry under digital transformation. The article accentuates the legal regulation of intelligent transport systems taking into account their technical and technological features. It is the intelligent transport systems that are de lege ferenda of the transport system, which determines the vector of transformation of transport legislation. In turn, development of the legal bases allows broadening the geography of introducing technical novelties and making their application much more large-scale.

A Microservices-Based Approach to Designing an Intelligent Railway Control System Architecture

The symmetry between customer expectations and operator goals, on one hand, and the digital transition of the railways, on the other hand, is one of the main factors affecting green transport sustainability. The European Train Control System (ETCS) was created to improve interoperability between different railway signaling systems and increase safety and security. While there are a lot of ETCS Level 2 deployments all over the world, the specifications of ETCS Level 3 are under development. ETCS Level 3 is expected to have a significant impact on automatic train operation, protection, and supervision. In this paper, we present an innovative control system architecture that allows the incorporation of artificial intelligence (AI)/machine learning (ML) applications. The architecture features control function virtualization and programmability. The concept of an intelligent railway controller (IRC) is introduced as being a piece of cloud software responsible for the control and optimization of railway operations. A microservices-based approach to designing the IRC’s functionality is presented. The approach was formally verified, and some of its performance metrics were identified.

Cyber resilience and cyber security issues of intelligent cloud computing systems

It is necessary to provide the cyber security of cloud computing according to the components that constitute its structure. The first step in advancing the cyber security of this technology is to accurately identify its threats. In this paper, a new cyber security reference model of the cloud system, which consists of components making up separate layers of cloud computing is proposed. Available reference models of cloud computing security do not describe the virtualization and service layers and the important components for providing the cyber security of cloud computing in detail, do not consider the social media IoT sensor layer, which collects the text data typed by attackers to carry out cyber attacks on the cloud infrastructure, and the cyber resilience issues of the cloud computing at all In addition, this paper studies the cyber security issues of cloud computing service models, and constructs an attack model to provide security of cloud systems. It gives an interpretation of standards and legislative acts on the cyber security of cloud computing. According to security aspects, clarification of the cyber security and cyber resilience concepts of cloud systems is provided. The cyber resilience architecture of intelligent cloud systems is developed. The advantage of developed cyber resilience model over available one is that, it determines the information security and cyber security aspects of cloud computing and combines them to form the cyber resilience aspects of cloud systems.

Integration of the Wang & Mendel Algorithm into the Application of Fuzzy Expert Systems to Intelligent Clinical Decision Support Systems

The use of intelligent systems in clinical diagnostics has evolved, integrating statistical learning and knowledge-based representation models. Two recent works propose the identification of risk factors for the diagnosis of obstructive sleep apnea (OSA). The first uses statistical learning to identify indicators associated with different levels of the apnea-hypopnea index (AHI). The second paper combines statistical and symbolic inference approaches to obtain risk indicators (Statistical Risk and Symbolic Risk) for a given AHI level. Based on this, in this paper we propose a new intelligent system that considers different AHI levels and generates risk pairs for each level. A learning-based model generates Statistical Risks based on objective patient data, while a cascade of fuzzy expert systems determines a Symbolic Risk using symptom data from patient interviews. The aggregation of risk pairs at each level involves a fuzzy expert system with automatically generated fuzzy rules using the Wang-Mendel algorithm. This aggregation produces an Apnea Risk indicator for each AHI level, allowing discrimination between OSA and non-OSA cases, along with appropriate recommendations. This approach improves variability, usefulness, and interpretability, increasing the reliability of the system. Initial tests on data from 4400 patients yielded AUC values of 0.74–0.88, demonstrating the potential benefits of the proposed intelligent system architecture.

Implementation of a Hybrid Intelligence System Enabling the Effectiveness Assessment of Interaction Channels Use in HMI.

The article presents a novel idea of Interaction Quality Sensor (IQS), introduced in the complete solution of Hybrid INTelligence (HINT) architecture for intelligent control systems. The proposed system is designed to use and prioritize multiple information channels (speech, images, videos) in order to optimize the information flow efficiency of interaction in HMI systems. The proposed architecture is implemented and validated in a real-world application of training unskilled workers-new employees (with lower competencies and/or a language barrier). With the help of the HINT system, the man-machine communication information channels are deliberately chosen based on IQS readouts to enable an untrained, inexperienced, foreign employee candidate to become a good worker, while not requiring the presence of either an interpreter or an expert during training. The proposed implementation is in line with the labor market trend, which displays significant fluctuations. The HINT system is designed to activate human resources and support organizations/enterprises in the effective assimilation of employees to the tasks performed on the production assembly line. The market need of solving this noticeable problem was caused by a large migration of employees within (and between) enterprises. The research results presented in the work show significant benefits of the methods used, while supporting multilingualism and optimizing the preselection of information channels.

Flexible handover solution for vehicular ad-hoc networks based on software defined networking and fog computing

<p>Vehicular ad-hoc networks (VANET) suffer from dynamic network environment and topological instability that caused by high mobility feature and varying vehicles density. Emerging 5G mobile technologies offer new opportunities to design improved VANET architecture for future intelligent transportation system. However, current software defined networking (SDN) based handover schemes face poor handover performance in VANET environment with notable issues in connection establishment and ongoing communication sessions. These poor connectivity and inflexibility challenges appear at high vehicles speed and high data rate services. Therefore, this paper proposes a flexible handover solution for VANET networks by integrating SDN and fog computing (FC) technologies. The SDN provides global knowledge, programmability and intelligence functions for simplified and efficient network operation and management. FC, on the other hand, alleviates the core network pressure by providing real time computation and transmission functionalities at edge network to maintain the demands of delay sensitive applications. The proposed solution overcomes frequent handover challenges and reduces the processing overhead at core network. Moreover, the simulation evaluation shows significant handover performance improvement of the proposed solution compared to current SDN based schemes, especially in terms of handover latency and packet loss ratio under various simulation environments.</p>

Development of an approach to the creation of an intellectual system of national security management

The object of the research is intelligent systems for collecting, processing and analyzing information about the state of national security.
 Investigated problem: The problem that is solved in the research is the problem of building intelligent systems for collecting, processing and analyzing information about the state of national security with limitations on the available computing resources, reliability and given speed of processing of various types of data circulating in it. The main scientific results obtained during the study by the authors are:
 proposed approach to the development of intelligent systems for the collection, processing and analysis of information on the state of the state's national security. The proposed approach takes into account the security of the system, available forces and means, purpose, system effect, method of formation, resource composition, structure, management, the process of functioning according to the purpose, resource consumption and the specified efficiency criterion. This will allow to justify the requirements for software and hardware of intelligent systems for collecting, processing and analyzing information about the state of the state's national security.
 proposed architecture of intelligent systems for collecting, processing and analyzing information about the state of national security of the state. Its approximate composition, functional purpose and structure of the database management system are substantiated.
 The area of practical use of the research results: It is advisable to use the proposed scientific results when conducting research and development works on the creation of intelligent systems for collecting, processing and analyzing information about the state of national security of the state, and developing requirements for hardware and software of this type of systems.
 Field of application: software, information systems, decision support systems.

Architectures of Intelligent Systems in Engineering

Architectures of Intelligent Systems in Engineering

Research on Active Safety Methodologies for Intelligent Railway Systems

Safety is essential when building a strong transportation system. As a key development direction in the global railway system, the intelligent railway has safety at its core, making safety a top priority while pursuing the goals of efficiency, convenience, economy, and environmental friendliness. This paper describes the state of the art and proposes a system architecture for intelligent railway systems. It also focuses on the development of railway safety technology at home and abroad, and proposes the active safety method and technology system based on advanced theoretical methods such as the in-depth integration of cyber–physical systems (CPS), data-driven models, and intelligent computing. Finally, several typical applications are demonstrated to verify the advancement and feasibility of active safety technology in intelligent railway systems.

Smart Governance of Urban Ecological Environment Driven by Digital Twin Technology: A Case Study on the Ecological Restoration and Management in S island of Chongqing

China is undergoing rapid urbanization, which has caused undesirable urban sprawl and ecological deterioration. Combining information technology for ecological environment governance is an effective measure to improve governance efficiency. In this paper, based on the analysis of the ecological restoration and governance case of S Island in Chongqing, an ecological intelligent governance system architecture based on the integration of multiple information technologies such as digital twin is extracted. The research shows that the S Island is based on the technical concept of the digital twin, and integrates a variety of information technology integration, collects and processes a large amount of data generated in the whole process of S Island repair and operation, and builds it based on the digital twin concept and accurately maps the physical space. This system model can be stored and processed based on the integrated data, realize knowledge graph visualization, algorithm optimization, and iterative integration for different objects and application scenarios, and finally serve different functional modules in ecological governance, which can be used to support Smart governance of cities.

Fleet management and control system for developing countries implemented with Intelligent Transportation Systems (ITS) services

Fleet Management Control Systems (FMCS) monitor vehicles in real-time and help assessing schedule compliance. Transit services in developing countries must improve in aspects such as information about routes, schedules and users; and compliance with traffic regulations, to achieve an increase in their demand. Although a FMCS can deal with these issues, currently implemented systems have some limitations related to communications technology, associated costs, interoperability and standardization. This paper includes the following: 1) The Intelligent Transportation System (ITS) architecture designed for the FMCS; 2) The development of a FMCS prototype for developing countries, considering the proposed architecture, using the Long Range communication technology and Intelligent Transportation Systems services; 3) A validation and testing of the FMCS prototype, using transit vehicles in a city. The developed prototype was successfully tested. The ideal operating parameters of the FMCS in terms of communications technology were identified in one of the four routes used in the tests. The results in such route were validated with additional tests, using the same parameters, and reaching similar operating values. A data set with the information of the performed tests was generated. With the results obtained in the FMCS, a better control of the transit service can be achieved, helping to improve upon the problems identified for developing countries (especially in medium-sized cities) related to route and schedule compliance, speeding, safety, standardization and helpful information for users. Additionally, service operation costs are reduced by using cutting-edge communications technology and promoting interoperability with other mobility services created for these cities.