Network Communication Technology Research Articles

Symmetric Collaborative Fault-Tolerant Control of Multi-Intelligence under Long-Range Transmission in Air–Ground Integrated Wireless High-Mobility Self-Organizing Networks

With the continuous development and progress of wireless self-organizing network communication technology, how to carry out long-distance cooperative control of multiple intelligences under the framework of an air–ground integrated wireless high-mobility self-organizing network has become a hot and difficult topic that needs to be solved urgently. This paper takes the air–ground integrated wireless high-mobility self-organizing network system as the basic framework and focuses on solving the long-distance cooperative fault-tolerant control of multi-intelligent bodies and the topological stability of a wireless mobile self-organizing network. To solve the above problems, a direct neural network with a robust adaptive fault-tolerant controller is designed in this paper. By constructing a symmetric population neural network model and combining it with the Lyapunov stabilization criterion, the system feedback matrix K has the ability of autonomous adaptive learning, and symmetrically distorts, rotates, or scales the training data to instantly adjust the system’s fault-tolerant corrections and adaptive adjusting factors to resist the unknown disturbances and faults, to achieve the goals of multi-intelligent body stable control and the stable operation of a wireless high-mobility self-organizing network topology. Simulation results show that with the feedback adjustment of the multi-system under the designed controller, the multi-system as a whole has good fault-tolerant performance and autonomous learning approximation performance, and the tracking error asymptotically converges to zero. The experimental results show that the multi-flight subsystems fly stably, the air–ground integrated wireless high-mobility self-organizing network topology has good stability performance, and the maximum relative improvement of the topology stability performance is 50%.

Evaluating the integration of traditional gong methods in smart home environment for the recovery of health functions of stroke patients

Since the 21st century, network and mobile communication technology are gradually entering the medical and health services field. Combining body area networks, broad-generation mobile communications, and cloud platforms has made various medical applications for large-scale populations possible. The development of digital medical technology, especially digital telemedicine, is increasingly proving to be an important means of significantly reducing the cost of medical care and access, changing the distribution of medical resources, and improving the overall level of care. To observe the effects of traditional Chinese medicine gongfu combined with rehabilitation therapy on mild depression, anxiety, and functional recovery of activities of daily living (ADL) in patients recovering from stroke, and to provide new treatment methods to improve the function and daily living ability of the group who develop mild depression and anxiety after stroke. In this paper, the digital medical engineering application combining information technology and medical treatment integrates various high-end information technologies such as body domain network and cloud computing to solve the difficulties in the current application one by one, to provide the national people with the system provides “timely”, “local” and “bottomless” remote digital health services to the Chinese people.

An ameliorated localization algorithm for compensating stratification effect based on improved underwater salp swarm optimization technique

SummaryThe underwater acoustic sensor network is a fundamental source for ocean exploration. The potential applications of underwater acoustic sensor network (UASN) include seismic imaging, disaster prevention, mine reconnaissance, pollution monitoring, exploration of natural resources, and military surveillance. To acquire accurate results, implementing all applications of underwater sensor networks requires an adequate network connection and communication technology. The precise placement of underwater sensor nodes needs to be identified in order to achieve effective communication. To accomplish the requirement, the paper presents an efficient localization algorithm to compensate the stratification effect based on an improved underwater salp swarm optimization technique (LAS‐IUSSOT). To compute the location of sensor nodes with high accuracy, the nodes are initially randomly deployed in three‐dimensional underwater acoustic sensor network (3D‐UASN). After that, the hybridization of centroid‐based localization and the ray theory technique is used, and then, the degree of coplanarity is analyzed among the underwater sensor nodes. Then, the computation of the location of unknown nodes is performed using improved underwater salp swarm optimization technique (IUSSOT) to obtain the optimized location and compensate the impact of the stratification. The comparison of the simulation results of the existing algorithm and the proposed algorithm is performed. The LAS‐IUSSOT achieves 40.46% and 28.00% accuracy in terms of localization of underwater sensor nodes for both the sparse and dense regions in 3D‐UASN. The LAS‐IUSSOT achieves 49.39% and 62.57% accuracy in terms of ranging of underwater sensor nodes for both the sparse and dense regions in 3D‐UASN. Simulation results illustrate that the proposed algorithm outperforms the existing algorithm in terms of localization and ranging accuracy in both sparse and dense regions in 3D‐UASN, root mean square error (RMSE), normalized localization error (NLE), computation time, and convergence rate.

An approach for offloading with multi-hop considerations in an RSU signal overlay setting

In recent years, significant advancements in vehicle technology have spurred growing interest in Vehicular Ad hoc Networks (VANETs). This interest is driven by concerns for road safety and the need to alleviate network congestion, leading to the emergence of Intelligent Transport Systems (ITS). ITS focuses on improving road traffic management and safety through the utilization of wireless and mobile network communication technologies. VANETs play a pivotal role within the realm of ITS, facilitating tasks such as enhancing road safety, traffic monitoring, and ensuring passenger comfort by mitigating accidents and congestion. These objectives rely on the timely and accurate delivery of data to vehicle agents and relevant authorities, facilitated by reliable VANETs and Road Signal Units (RSUs). Achieving this necessitates identifying optimal routes with minimal distance, high radio access, and quality-awareness levels. To address these objectives, this study proposes the utilization of the Congestion Network with Predicted K-means multi-hop RSU algorithm (CN-MHMR) to enhance vehicular networking and communication. This algorithm facilitates efficient node transfer from base nodes to destination nodes via the shortest and energy-efficient paths, thereby enabling viable and reliable vehicular communications. The performance of the proposed model was evaluated based on various metrics, including energy consumption, throughput, delay, packet delivery ratio, accuracy, precision, and recall values.

Warehouse Management Information System Technology Review

With the rapid development of information technology, warehouse management information systems are playing an increasingly important role in modern logistics management. This paper first elaborates on the importance of warehouse management information systems and the impact of technological development on warehouse management, and then reviews the development process of warehouse management information systems. Next, it focuses on introducing the application of key technologies such as barcode technology, RFID technology, UWB high-precision positioning technology, wireless network communication technology, cloud computing technology, and big data analysis technology in warehouse management. In addition, this paper also analyzes the current problems faced by warehouse management information systems and discusses the application prospects of emerging technologies such as artificial intelligence, Internet of Things, blockchain, automation, and robotics in warehouse management. Finally, it summarizes the main findings of the review and proposes insights and suggestions for the development of warehouse management information systems and future research directions.

Development and Research of Safety Video Monitoring System for Loading and Unloading of Chemical Products in Railway Transportation

As the important position of chemical railroad transportation in modern logistics is becoming more and more prominent, its safety problem has attracted wide attention. To improve the safety of transporting chemicals by rail, this paper strives to develop an advanced safety monitoring system. The main background of this paper is the serious potential results of chemical products railroad transportation accidents which require an effective monitoring method to prevent. The purpose of this research is to design and realize an efficient and reliable video monitoring system to monitor the loading and unloading of chemicals transported by railroads in real-time. To achieve this goal, we adopted comprehensive methods, including video image recognition technology, data analysis technology, communication network technology, etc., which have significant meaning in preventing railroad accidents of chemical product transportation and safeguarding people’s life and property.

Interactive design of intelligent wearable products based on network communication technology

At this stage, network communication technology is increasingly mature, and intelligent wearable products are also widely used in human daily life. Wearable products are popular with users because of their numerous types, complete functions and convenient services. Wearable products integrate interaction technology, and users can interact with products. However, how to improve the user’s interaction experience and reduce the user’s cognitive burden on the interaction interface is an urgent problem in the current product interaction design. Therefore, based on the analysis of the types and related technologies of wearable products, this paper made a specific analysis of the interaction design of wearable products, and established an interaction design model. At the same time, the wearable fall detection system was also tested by machine learning algorithm. The experimental results showed that the average test result of the algorithm in this paper was 87.39%, while the average test result of the traditional algorithm was 83.79%. In terms of the missed alarm rate of fall detection, the average test result of this algorithm was 6.4%, while the average test result of the traditional algorithm was 12.33%. In terms of fall detection sensitivity, the average test result of this algorithm was 92.50%, while the average test result of the traditional algorithm was 88.24%. Compared with traditional algorithms, this method performs better, with lower missed detection rate and higher sensitivity. Innovative combination of machine learning algorithm, through three-dimensional coordinate system, differentiation and vector sum formula, improves the accuracy and reliability of fall detection. In conclusion, the algorithm in this paper can effectively optimize the relevant performance of the system, thus improving the accuracy of the system’s fall detection.

Leveraging the Synergy of IPv6, Generative AI, and Web Engineering to Create a Big Data-driven Education Platform

The rapid advancement of network technology in China has significantly accelerated the implementation of information technology in higher education. Through the utilization of computer technology, multimedia technology, big data technology, artificial intelligence technology, and network communication technology, the integration of these technologies in university teaching has become widespread. This paper presents an analysis and discussion on the utilization of the latest IPv6 network transmission protocol technology to enhance the application of data collection in university education, with a specific focus on gathering information related to university faculties. By leveraging web engineering and multimedia technology as fundamental components, the network facilitates the sharing of educational resources among students, thereby enabling the reform of management approaches, fostering educational progress in China, and establishing a comprehensive big data-driven education platform specifically tailored to colleges and universities. Additionally, the incorporation of big data visualization and analysis tools allows for easy retrieval of existing university educational information, facilitates the creation of data charts, and expedites the utilization of data for its inherent value. Finally, the proposed approach employs generative AI to collect and analyze feedback from students and educators, followed by the application of web engineering techniques to continuously enhance the online education platform based on this feedback.

Inheritance of Intangible Culture Based on Wireless Communication Network in College Dance Teaching

Intangible cultural heritage is an important part of Chinese excellent traditional culture, and college dance teaching is paid more attention by researchers of physical education and computer technology. In order to help the inheritance and development of non-legacy culture in college dance teaching, this paper analyzes the influencing factors of wireless communication network in college dance teaching, constructs an interactive platform for non-legacy digital dance teaching based on wireless communication network technology, and applies it in the dance teaching process of a university in Henan province to highlight the role of wireless communication technology in dance teaching. The results show that the interactive platform can effectively reduce teachers' physical energy consumption and has certain reliability and practicality. Through artificial intelligence algorithm, the traditional dance teaching method has been changed, and a new exploration of non-legacy dance teaching has been realized.

Application of building BIM technology based on sensor systems and 5G cloud computing

At present, the technology of artificial intelligence has been developing, making people's life more convenient and production more efficient. As the artificial intelligence software Siri is accepted and used by more and more people, some voice assistant software with similar functions gradually appear in people's vision, such as Sogou voice assistant, Xiaoai, Xiaodu and so on. ASR is the entrance of Siri and other software systems. The quality of software is directly affected by ASR. If there is no good ASR, it is impossible to have high-quality voice assistant applications. Therefore, we must correctly understand the important value of ASR and deeply study this technology in order to achieve better human-computer interaction. In recent years, the development of communication network technology is changing rapidly, from 2G to 5G, technology has been in progress. Compared with the previous 4G, 5G has a higher technical level, whether in network equipment or in data computing technology. For 5 g network, cloud computing technology is very important and has a great impact on it, so we need to focus on the research to realize the optimization and innovation development of 5G network. The construction sector constitutes a crucial segment of China's economy, exerting a significant influence on its overall growth trajectory. Given the prevailing developmental context, this document provides a concise overview of the BIM (Building Information Modeling) Technology, encompassing its fundamental concept, distinguishing attributes, and core principles. Furthermore, it delves into the manifold junctures where BIM Technology finds application across the entire construction life cycle. By employing an actual project as an illustrative instance, this study compiles a synopsis of BIM Technology's utilization at each phase, conducting a comprehensive evaluation of the project through the lens of the accrued experience and outcomes. This assessment lays the groundwork for an extensive exploration of potential expansion and application avenues, culminating in the eventual advancement of BIM Technology's achievements.

Chinese expert consensus on the process of 5G+ helicopter aviation medical rescue (2024 edition)

To address the lagging status of aviation medical rescue in China compared to developed countries, the focus is on critical weaknesses such as the inadequate aviation rescue communication network and communication technology. The team has established an efficient network among rescue helicopters, emergency centers, and hospitals using 5G technology, achieving millisecond-level speed and real-time data transmission. The Professional Committee of Emergency Resuscitation and Disaster Medicine of Chinese Medical Doctor Association integrated emergency experts, medical institutions, and emergency rescue teams to jointly draft Chinese expert consensus on 5G+ helicopter aviation medical rescue (2024 edition). The consensus recommends the widespread application of 5G technology in aviation medical rescue, utilizing 5G technology for warning and dispatch during the initiation of aviation medical rescue, and using 5G technology for real-time transmission of vital signs and high-definition videos to emergency centers and receiving hospitals during rescue operations and flight. Successful cases fully demonstrate the potential of 5G technology in aviation medical rescue. The consensus aims to standardize and guide 5G+ helicopter medical rescue, ultimately achieving the goal of patients being "admitted upon boarding".

Device authentication for 5G terminals via Radio Frequency fingerprints

The development of wireless communication network technology has provided people with diversified and convenient services. However, with the expansion of network scale and the increase in the number of devices, malicious attacks on wireless communication are becoming increasingly prevalent, causing significant losses. Currently, wireless communication systems authenticate identities through certain data identifiers. However, this software-based data information can be forged or replicated. This article proposes the authentication of device identity using the hardware fingerprint of the terminal’s Radio Frequency (RF) components, which possesses properties of being genuine, unique, and stable, holding significant implications for wireless communication security. Through the collection and processing of raw data, extraction of various features including time-domain and frequency-domain features, and utilizing machine learning algorithms for training and constructing a legal fingerprint database, it is possible to achieve close to a 97% recognition accuracy for Fifth Generation (5G) terminals of the same model. This provides an additional and robust hardware-based security layer for 5G communication security, enhancing monitoring capability and reliability.

Federated learning enables 6 G communication technology: Requirements, applications, and integrated with intelligence framework

The 5 G networks are effectively deployed worldwide, and academia and industries have begun looking at 6 G network communication technology for consumer electronics applications. 6 G will be built on pervasive artificial intelligence (AI) to enable data-driven Machine Learning (ML) applications in massively scalable and heterogeneous networks. Conventional ML technique involves centralizing train data in data centers where centralized ML algorithms can be employed for data inference and analysis. The data inference and analysis are frequently inconvenient or impracticable for the devices to submit information to the preset sever because of privacy concerns and inadequate communication capabilities in wireless networks. However, privacy limitations and restrictions in wireless network communication capacity are frequently impractical or undesirable for the devices to acquiesce data to the parameter server. Federated learning (FL) enables the devices to train a practical and standard model while needing data exchange and transfer, which might solve these issues. This paper presents an overview of FL, 6 G, and FL enables 6 G communication technology. In particular, 6 G requirements and applications, and the proposed FL framework algorithm with evaluation are described. Finally, FL-enabling 6 G communication technologies open challenges, and research directions are discussed to help future researchers improve the FL-enabled 6 G network.

Generic IoT for Smart Buildings and Field-Level Automation—Challenges, Threats, Approaches, and Solutions

Smart home and building systems are popular solutions that support maintaining comfort and safety and improve energy efficiency in buildings. However, dynamically developing distributed network technologies, in particular the Internet of Things (IoT), are increasingly entering the above-mentioned application areas of building automation, offering new functional possibilities. The result of these processes is the emergence of many different solutions that combine field-level and information and communications technology (ICT) networks in various configurations and architectures. New paradigms are also emerging, such as edge and fog computing, providing support for local monitoring and control networks in the implementation of advanced functions and algorithms, including machine learning and artificial intelligence mechanisms. This paper collects state-of-the-art information in these areas, providing a systematic review of the literature and case studies with an analysis of selected development trends. The author systematized this information in the context of the potential development of building automation systems. Based on the conclusions of this analysis and discussion, a framework for the development of the Generic IoT paradigm in smart home and building applications has been proposed, along with a strengths, weaknesses, opportunities, and threats (SWOT) analysis of its usability. Future works are proposed as well.

Design of the Temperature and Humidity Intelligent Home Control System Based on PLC

With the improvement of people's living standards, smart home is becoming more and more popular. Smart home is based on the residential, integrated a variety of modern advanced technologies such as wiring technology, centralized processing technology, network communication and other technologies will achieve integrated processing of various facilities in life. In contemporary society, people have higher and higher requirements for the quality of life, and the use of Programmable logic controller (PLC) to control smart homes has become popular. This paper draws on the traditional use of PLC to control the temperature and humidity of the greenhouse and the concentration of carbon dioxide, and considers the use of PLC to realize the control of smart home. The design uses PLC programmable controller to control the temperature and humidity of smart home life, making life more intelligent.

Knowledge and ICT based networks: towards a taxonomy

Abstract Purpose The article proposes a taxonomy of knowledge-based and information and communication technology (ICT) networks based on a systematic literature review. The specific objectives focus on (1) presenting knowledge-based and ICT network models, indicating their theoretical context (trends); (2) identifying proposals for knowledge-based network models in the literature (based on SLR); (3) developing a taxonomy of knowledge-based network models; and (4) indicating the directions of their development. Design/methodology/approach The systematic literature review (SLR) methodology was used, which allows not only for a formalized and objectified synthesis of the existing scientific achievements or for the evaluation of previous research. In addition, the “snowball” method was used, and its application was supported by the use of the ResearchRabbit tool. In addition, the taxonomy method (typological analysis, typological approach) was used. Findings The results of SLR were presented: a list of selected types of knowledge-based and ICT networks along with a discussion of the results, and the author’s proposals for a taxonomy of knowledge-based and ICT networks were presented along with a synthetic description of the leading models. The directions of their development were also indicated. Practical implications (*if any, optional). The practical usefulness of the proposal contained in the study is related to the possibility of using the proposed concept to evaluate various types of network models, which will enable the formulation of diagnostic findings and conducting comparative and dynamic research in the field of analysis and evaluation of knowledge-based and ICT-based network models. Originality/value The added value of the article is related to the development of a proprietary taxonomy of knowledge- and ICT-based networks and, consequently, to the organization and systematization of models of these networks. This taxonomy is a valuable tool for organizing and categorizing information systematically. When it comes to knowledge and ICT-based networks, a taxonomy can help classify and understand the different types and components involved in starting point division into network models that were created as a result of the virtualization process and models that were created as a result of exchange processes and the flow of intangible assets. The added value is also related to the practical usefulness of the developed taxonomy.

Research progress of space laser communication networking technology

Research progress of space laser communication networking technology

Fake News in Virtual Community, Virtual Society, and Metaverse: A Survey

In the trend of the accelerated progression of communication network technology, the emergence of virtual communities (VCs), virtual societies (VSs), metaverse, and other technologies not only makes data access and sharing easier but also leads to the proliferation of fake news (FN). To effectively monitor and identify FN in VC, VS, and metaverse, and to create a safer virtual space, this work takes FN in VC, VS, and metaverse as objects. First, the content and display methods of FN are reviewed and explained, and it is understood that FN is mainly displayed by single-modal and multimodal representations. Second, the application scenarios in many important fields such as transportation are reviewed and analyzed, so as to further understand the impact and detection effect of FN in different scenarios. Finally, an intelligent outlook and summary analysis are carried out on the detection and information security of FN, which provides theoretical reference and new opportunities for the detection and identification of FN in the virtual cyberspace.

Application of BIM+IoT technology in the design and operation and maintenance stages of smart buildings

With the continuous emergence of new technologies and the efficient and convenient development of people’s daily life and work, the topic of intelligent building is becoming more and more hot. There are two kinds of data in intelligent building, namely static data and dynamic data. The digital expression of intelligent building is realized through the fusion and interaction of these two kinds of data. The building information model (BIM) stores a large amount of static data, including size, material, color and other data, while the Internet of Things (IoT) collects real-time dynamic data, including temperature, humidity, light and other data, through sensors in every space within the building. The related problems of building data management in the design and operation and maintenance stages mainly include data collection relying on manual work, low data processing efficiency, scattered and disorderly data storage, difficult data interaction, slow speed, and low data visualization. In order to solve these problems, this paper combines the characteristics and advantages of BIM and IoT technology, analyzes the interaction and application value of BIM and IoT technology in the design and operation and maintenance stage of intelligent buildings, and constructs a data management system based on the Internet of things, a 3D visualization technology based on BIM, and an operation and maintenance management platform based on BIM and IoT. The application of BIM and IoT technology in the design and operation and maintenance stage of intelligent buildings has promoted the development of the construction industry. The Internet of Things can provide many functional services, such as real-time monitoring, remote tracking, automatic update, plan management and a series of personalized services and management, to achieve the management, control and detection of various things, and ensure the high-speed and effective operation of the system. The emergence of the building system of modern communication network technology has brought many conveniences to people, and there is still a broad space for development. The combination of new Internet of Things technology and intelligent buildings will certainly be an important development direction.

Retracted: Research on Cultural Communication in College English Teaching Based on Wireless Communication and Multimedia Network Technology

Retracted: Research on Cultural Communication in College English Teaching Based on Wireless Communication and Multimedia Network Technology