Article
Computer Science, Information Systems
Cristina Paniagua, Jerker Delsing
Summary: The Internet of Things (IoT) is gaining popularity in industrial applications, requiring support from flexible and scalable systems. With the increasing number of available frameworks, selecting a suitable one for industrial applications has become difficult. Therefore, researching the characteristics of each framework to simplify the selection process is crucial.
IEEE SYSTEMS JOURNAL
(2021)
Article
Automation & Control Systems
Siya Xu, Yimin Li, Shaoyong Guo, Chenghao Lei, Di Liu, Xuesong Qiu
Summary: The industrial Internet of Things and 5G are key elements to support Industry 4.0. By integrating NFV technology with cloud computing and mobile edge computing, a collaborative IIoT architecture can efficiently provide flexible service for IIoT traffic. However, efficient cloud-edge collaboration, reasonable resource consumption, and different quality of services are still challenges. Therefore, a multiobjective deployment model and a deep-Q-learning-based algorithm are proposed to balance service quality and resource consumption.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2022)
Article
Computer Science, Information Systems
Prasad Ramesh Desai, S. Mini, Deepak K. Tosh
Summary: This article emphasizes the importance of using software-defined networking (SDN) and Internet of Things (IoT) to achieve efficient communication and proposes three optimized path algorithms to improve communication efficiency.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Computer Science, Information Systems
Cheng Qian, Wei Yu, Chao Lu, David Griffith, Nada Golmie
Summary: This article investigates the impact of insufficient data on machine learning model training and proposes a framework using GAN and continuous learning to address the issue. The experimental results demonstrate that new data greatly improves model accuracy, and the proposed defensive mechanism safeguards the model learning process.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Green & Sustainable Science & Technology
Hani Alshahrani, Attiya Khan, Muhammad Rizwan, Mana Saleh Al Reshan, Adel Sulaiman, Asadullah Shaikh
Summary: The Industrial Internet of Things (IIoT) is the use of IoT in industrial management, linking and synchronizing machines and devices through software programs and third platforms to improve productivity. Despite the benefits, security remains a major concern due to the lack of reliable security mechanisms and the magnitude of security features. Attacks exploiting vulnerabilities in IIoT networks have caused financial losses, reputational damage, and theft of important information. This paper proposes an SDN-based framework with machine learning techniques for intrusion detection in an industrial IoT environment, achieving an accuracy of 99.7% in detecting attacks.
Article
Computer Science, Information Systems
Henry Vargas, Carlos Lozano-Garzon, German A. Montoya, Yezid Donoso
Summary: This paper integrates Blockchain algorithms and Machine Learning techniques to create a comprehensive protection mechanism for IoT device networks, allowing for threat identification, activation of secure information transfer mechanisms, and adaptation to the computational capabilities of industrial IoT. The proposed solution achieves its objectives and is presented as a viable mechanism for detecting and containing intruders in an IoT network, surpassing traditional detection mechanisms such as an IDS in some cases.
Article
Computer Science, Interdisciplinary Applications
Xianyu Zhang, Xinguo Ming
Summary: With the development of industrial Internet environment and intelligent technology, enterprises are focusing more on system platform, information sharing, network collaboration, personalized customization and service recommendation in designing, implementing and operating Industrial Internet Platforms (IIP). However, there is a lack of a comprehensive framework for studying the high-level planning of IIP implementation and few studies on the detailed path and steps of IIP implementation in specific industries. The research aims to study the general model, reference architecture, service evaluation index system, implementation path and application verification for IIP to provide guidance for government and industry in planning, designing, implementing and promoting IIP.
COMPUTERS & INDUSTRIAL ENGINEERING
(2021)
Article
Automation & Control Systems
Jing Long, Wei Liang, Kuan-Ching Li, Yehua Wei, Mario Donato Marino
Summary: In this study, a semi-supervised ladder network model is proposed for intrusion detection in the Industrial IoT, taking into account the security issues and the challenge of limited labeled data. This model considers the manifold distribution of high-dimensional data and incorporates a manifold regularization constraint in the decoder. Additionally, a random attention-based data fusion approach is proposed to generate global features for intrusion detection. Experimental results on the CIC-IDS2018 dataset show that the proposed approach achieves a lower false alarm rate and is time efficient for training.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2023)
Article
Chemistry, Analytical
Yuri Santo, Roger Immich, Bruno L. L. Dalmazo, Andre Riker
Summary: Industrial production and manufacturing systems require automation, reliability, and low-latency intelligent control. The Industrial Internet of Things (IIoT) enables precise and low-latency intelligent computing and provides essential building blocks to drive manufacturing systems to higher productivity, efficiency, and safety. However, hardware failures and faults in IIoT present critical challenges. This article proposes the DASIF framework, which applies edge computing and machine learning to detect IIoT faults and trigger an alert state for improved communication reliability and efficient decision-making.
Article
Computer Science, Information Systems
Chaogang Tang, Chunsheng Zhu, Ning Zhang, Mohsen Guizani, Joel J. P. C. Rodrigues
Summary: In this article, the focus is on developing load balance aware task offloading strategies for IIoT devices in MEC using SDN technology. By formulating an optimization problem and proposing a greedy algorithm, the research aims to minimize response latency in the SDN-assisted MEC architecture. Simulation results show that the proposed approach outperforms others in terms of response latency.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Computer Science, Information Systems
Muna Al-Hawawreh, Elena Sitnikova, Neda Aboutorab
Summary: The Industrial Internet of Things (IIoT) is a high-value target for cyber attacks, and developing security solutions that fit its requirements is challenging due to the lack of accurate data. To address this, we propose X-IIoTID, an intrusion data set for IIoT that includes multi-view features of connectivity protocols, device activities, attack types, and protocols.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Computer Science, Information Systems
Wenjing Hou, Hong Wen, Ning Zhang, Jinsong Wu, Wenxin Lei, Runhui Zhao
Summary: This work proposes an online incentive-driven task allocation scheme to stimulate collaborative computing between EC servers and IIoT devices, aiming to accelerate task processing and reduce service latency. The proposed algorithm optimizes task assignment strategies to maximize system utility, promote faster computing, and stimulate collaborative computing. The results demonstrate superior performance and effectiveness of the proposed task allocation scheme.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Chemistry, Analytical
Alejandro Cortes-Leal, Carolina Del-Valle-Soto, Cesar Cardenas, Leonardo J. Valdivia, Jose Alberto Del Puerto-Flores
Summary: This article explores the application of Industry 4.0 technologies in network security, with a focus on the impact of energy consumption at the physical layer on operation and maintenance costs. Through simulations and experiments, the study reveals that the cooperative scheme is more efficient under normal operating conditions, while the collaborative scheme provides enhanced protection against jamming aggressiveness, making it safer and reducing costs. Additionally, the article presents an algorithm for real-time jamming detection and considers characteristics such as aggressor type, natural immunity of the WSN, and energy consumption during transmission.
Article
Automation & Control Systems
Zhenghao Xi, Yuhui Niu, Jieyu Chen, Xiu Kan, Huaping Liu
Summary: This study proposes a parallel neural network combining texture features to improve facial expression recognition, achieving a high accuracy of 98.14% compared to ResNet. The results demonstrate the effectiveness and robustness of the proposed method in facial expression classification.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2021)
Article
Automation & Control Systems
Kai Lin, Jian Gao, Guangjie Han, Haohua Wang, Chao Li
Summary: This article addresses the issue of adaptive resource scheduling in large-scale IIoT. It proposes a collaborative terminal-edge IIoT architecture that utilizes blockchain and AI technology to support dynamic resource scheduling in untrustworthy environments. A smart contract-based multidimensional resource transaction model and a distributed transaction learning resource scheduling algorithm are developed to improve efficiency and security. Extensive simulation experiments demonstrate that the proposed method outperforms existing algorithms in terms of scheduling decision delay, transaction generation ratio, and security.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2022)
Article
Engineering, Electrical & Electronic
Zhen Li, Changcheng Wu, Zhaozong Meng, Zhijun Chen, Fei Fei
Summary: A new microwave sensor system with a five-wire line configuration is developed for volumetric characterization of liquids. The sensor is low profile, low-cost, submersible, and easy to fabricate and implement. An analytical model is proposed for accurate permittivity determination, and the sensor is verified to be accurate with standard liquids of known permittivity. The sensor offers an alternative solution for assessing a wide range of liquids in various applications.
IEEE SENSORS JOURNAL
(2022)
Article
Engineering, Electrical & Electronic
Peng Liu, Zonghua Zhang, Zhaozong Meng, Nan Gao
Summary: Depth map super-resolution (DMSR) is an effective solution to improve the quality of depth maps captured by low-cost depth sensors. Most existing methods use RGB images as guidance to enhance the depth maps. In this research, we propose DEAF-Net, a novel convolutional neural network with deformable enhancement and adaptive fusion, to further improve the performance of DMSR. Experimental results demonstrate its effectiveness.
IEEE SIGNAL PROCESSING LETTERS
(2022)
Article
Engineering, Electrical & Electronic
Yadong Niu, Xuewen Lu, Xingyu Li, Wanyun Su, Zhaozong Meng, Sixiang Zhang
Summary: The article presents a study on the prediction methods of runway friction coefficient based on multivariable coupling, developing prediction models through finite element analysis and neural networks, with superior performance demonstrated.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2022)
Article
Engineering, Electrical & Electronic
Zhen Li, Changcheng Wu, Zhaozong Meng, Constantinos Soutis, Zhijun Chen, Ping Wang, Andrew Gibson
Summary: This study presents a new nondestructive microwave method using an open cavity resonator sensor for evaluating the multilayered coating thickness on carbon fiber-reinforced polymer composites. The resonance frequency shift caused by the coating perturbing the surface impedance is studied and a linear relationship between the frequency shift and the coating thickness change is revealed. The proposed sensor is insensitive to the conductivity anisotropy of the composite and offers efficient on-site evaluation of coatings on composite structures.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2022)
Article
Engineering, Electrical & Electronic
Kai Zhang, Zhen Li, Zhaozong Meng, Wei Zhou, Nan Gao, Zonghua Zhang
Summary: This study presents a surface mountable dual-mode Radio Frequency Identification (RFID) sensor, which can achieve product identification, sensing, and data integration, addressing the issues of complex sensor devices and inflexible integration with industrial processes. Experimental studies and exemplary applications demonstrate the feasibility of this technology in industrial integration.
IEEE SENSORS JOURNAL
(2022)
Article
Chemistry, Analytical
Yuzhuo Zhang, Yaqin Sun, Nan Gao, Zhaozong Meng, Zonghua Zhang
Summary: This study proposed a phase target method based on projector radial chromatic aberration measurement and calibration to improve the color fringing issue in a color fringe projection 3D measurement system. Experimental results showed that the proposed method effectively measured and calibrated the radial chromatic aberration of the projector, leading to improved projection quality.
Article
Engineering, Electrical & Electronic
Zhengyang Qin, Zhaozong Meng, Zhen Li, Nan Gao, Zonghua Zhang, Qingyi Meng, Dong Zhen
Summary: This study proposes a MEMS inertial measurement unit (MIMU)-assisted ultrawideband (UWB) localization system to handle non-line-of-sight (NLoS) occlusion errors and improve indoor localization accuracy. An NLoS occlusion detection method and occlusion compensation techniques are introduced using UWB transceiver channel information and variation pattern of anchor-to-node distance. Inertial navigation is achieved through extended Kalman filter (EKF)-based attitude computation and zero-velocity update (ZUPT)-based continuous gait segmentation during occlusion intervals. The integrated UWB and IMU parameters are compensated using an unscented Kalman filter (UKF) framework to improve accuracy and robustness. Experimental studies demonstrate the feasibility and effectiveness of the proposed techniques, providing a valuable reference for Internet of Things (IoT) applications.
IEEE SENSORS JOURNAL
(2023)
Article
Optics
Ziyu Li, Nan Gao, Zhaozong Meng, Zonghua Zhang, Feng Gao, Xiangqian Jiang
Summary: With the development of aerospace, high-speed train, and automotive industries, there is an increasing demand for measuring high-precision specular components. However, existing 3D measurement methods for specular surfaces are limited by the depth of field of camera lenses. This paper introduces a concave mirror into a phase measuring deflectometry (PMD) system and proposes an aided imaging PMD (AIPMD) based on a concave focusing mirror. The proposed system achieves clear imaging of encoded patterns and the surface under test within the camera lens depth of field, and a specular reconstruction algorithm is also studied based on this system. The feasibility and accuracy of the proposed method are verified through simulations and experiments.
Review
Instruments & Instrumentation
Qi Jin, Zhaozong Meng, Zhijun Chen, Zhen Li
Summary: A microwave microstrip line resonator sensor is developed for detecting adulteration in honey. By changing the permittivity of the honey, the adulteration can be detected, and the sensor offers the advantages of low cost, compact size, and easy fabrication. Simulation and experimental results demonstrate that the resonance frequency decreases with increasing water content, allowing for quantitative analysis of the adulteration.
REVIEW OF SCIENTIFIC INSTRUMENTS
(2023)
Article
Engineering, Electrical & Electronic
Ruowei Yin, Zhipeng Wu
Summary: The design of isolators is complicated and computationally intensive for reducing mutual coupling in large two-dimensional antenna arrays. This study applies different types of planar isolators in different orientations and experiments with two-element microstrip antenna arrays. By using U-shaped planar transmission line isolators, U-shaped planar transmission line-based destructive ground structure, and planar neutralization line structure, a mutual coupling reduction of approximately 6 dB is achieved. The effectiveness of the decoupling structures is confirmed through simulations and experimental measurements.
INTERNATIONAL JOURNAL OF ANTENNAS AND PROPAGATION
(2023)
Article
Computer Science, Information Systems
Hongpeng Li, Haichao Liu, Zhen Li, Chenxi Li, Zhaozong Meng, Nan Gao, Zonghua Zhang
Summary: This study proposes an adaptive threshold-based zero-velocity update (ZUPT) algorithm to address the issue of cumulative errors in continuous walking, improving localization accuracy with good adaptability.
IEEE INTERNET OF THINGS JOURNAL
(2023)
Review
Engineering, Electrical & Electronic
Jingren Xu, Zhen Li, Kai Zhang, Jingwen Yang, Nan Gao, Zonghua Zhang, Zhaozong Meng
Summary: This investigation provides an in-depth survey of the methods and the latest technical progress in RFID positioning, aiming to identify the underlying challenges. The main contributions include the theoretical model construction and parameter analysis, the classification of RFID positioning techniques and discussion of the latest progress, summary of potential applications and challenges, and prospects of emerging technologies. This investigation offers a comprehensive perspective on RFID positioning, serving as a reference for related research and practices.
IEEE JOURNAL OF RADIO FREQUENCY IDENTIFICATION
(2023)
Article
Computer Science, Information Systems
Wei Zhou, Wanyun Su, Xingyu Li, Zhaozong Meng, Shanshan Li
Summary: This paper proposes a feature extraction and classification method based on x-ray images to improve the defect recognition rate of thermal batteries. By combining the Gray Level Co-occurrence Matrix and Local Binary Pattern, the gray texture of the monomer is extracted and analyzed for serial feature fusion. The experimental results show that this method achieves a defect recognition rate of 98.9%.
Article
Engineering, Electrical & Electronic
Zhen Li, Zhaozong Meng, Changcheng Wu, Fei Fei, Andrew Gibson
Summary: This paper presents a microwave sensor based on a five-wire transmission line for simultaneous determination of liquid levels and complex permittivities. An analytical model is proposed using transmission line theory and transmission matrix technique. Numerical simulation demonstrates the feasibility and applicability of the sensor.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2022)
Article
Computer Science, Information Systems
Zeqing Yang, Mingxuan Zhang, Chao Li, Zhaozong Meng, Yue Li, Yingshu Chen, Libing Liu
Summary: The surface defect detection of automobile pipe joints based on computer vision faces technical challenges. This study proposes a new method that combines wavelet decomposition and reconstruction with the Canny operator for defect detection and uses a multi-channel fusion convolutional neural network for defect classification. Experimental results show that the method effectively eliminates interference and achieves high defect classification accuracy.
