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Applied Sciences
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Advances in Intelligent Communication System
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Advances in Intelligent Communication System

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".

Deadline for manuscript submissions: 30 October 2024 | Viewed by 12946

Special Issue Editors

Prof. Dr. Wei Chen

E-Mail Website
Guest Editor
School of Computer Science and Technology, China University of Mining and Technology, Xuzhou 221116, China
Interests: mine communication; artificial intelligence; industrial Internet of Things; safety monitoring
Prof. Dr. Tak-Shing Yum

E-Mail Website
Guest Editor
Department of Information Engineering, The Chinese University of Hong Kong, Hongkong 999077, China
Interests: wireless communications; probability models, artificial intelligence; wireless and internet

Special Issue Information

Dear Colleagues,

The mine communication system consists of an originating device, a receiving device and a transmission medium. It relies on the high-speed network covering the underground mines to build a mine sensor network, connecting the mine environment, equipment and personnel through a variety of ubiquitous transmission mediums, and can conduct real-time monitoring, perception, communication and control of mine signs (mine disaster environment, equipment running status, personnel safety situation). Mine communication systems are widely used in coal mines and non-coal mine industries, especially mine safety monitoring, unmanned mining and emergency rescue.

However, basic mine communication systems have been unable to meet the requirements of modern intelligent mine construction. Smart mine systems such as mine safety monitoring, equipment health diagnosis and personnel safety situational awareness have various complex functions of hybrid communication networks. The modern applications of mine communication systems must be assisted by powerful intelligent technology to process and analyze big data and deal with the problems of finding an optimal solution, making the best decision, detecting events, and fault diagnosis. Artificial intelligence (AI) simulates the natural intelligence exhibited by humans or animals, enabling systems to perform tasks without the assistance of humans, or even better than humans. Modern AI technology usually utilizes evolutionary computation, nature-inspired algorithms, machine learning, or deep learning to solve the problems of optimization, decision-making, event analysis and fault diagnosis. The integration of mine communication systems and AI technology is very suitable for enhancing network intelligence, to realize the intelligence of mine communication, which enables the establishment of innovative communication systems and applications scenarios for modern smart mines.

Prof. Dr. Wei Chen
Prof. Dr. Tak-Shing Yum
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • intelligence communication
  • smart mine
  • artificial intelligence
  • sensor network
  • transmission medium

Published Papers (6 papers)

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Research

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19 pages, 10274 KiB  
Article
Research on New Greenable Class Gravity Retaining Wall Structure Technology Based on Video Monitoring
by Zengle Li, Huimei Zhang, Bin Zhi, Xin Li and Shiguan Chen
Appl. Sci. 2023, 13(21), 12066; https://doi.org/10.3390/app132112066 - 06 Nov 2023
Viewed by 901
Abstract
As the most common geological disaster problem in mines, slope geological disasters have become a focus of research, along with the difficulty of mine safety and ecological environment protection together with the ecological restoration of open-pit mines. At present, a large number of [...] Read more.
As the most common geological disaster problem in mines, slope geological disasters have become a focus of research, along with the difficulty of mine safety and ecological environment protection together with the ecological restoration of open-pit mines. At present, a large number of slope-retaining wall structures lack research on safety monitoring, real-time acquisition, and intelligent early warning. Therefore, this paper combines cement-modified loess with gravity retaining wall structures and puts forward a new type of greening gravity retaining wall structure. From the perspective of “the Internet of Things + construction”, a video monitoring system is established to monitor the retaining wall structure in real time. Finally, based on video image processing technology, the deformation of the retaining wall surface is identified and the inclination angle of the wall surface is calculated, so as to improve the real-time and intelligent monitoring of the new greening gravity retaining wall. The results show that the new greening gravity retaining wall based on video monitoring proposed in this paper has the characteristics of a gravity retaining wall and ecological retaining wall, which are conducive to improving the real-time and intelligent monitoring of the new greening gravity retaining wall. Cement-modified loess is used as the planting matrix, and the cement mixing ratio should not exceed 10%. Considering the requirements of economy and shear strength, the cement mixing ratio should be selected from 5% to 12%. Full article
(This article belongs to the Special Issue Advances in Intelligent Communication System)
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18 pages, 14460 KiB  
Article
An Improved High-Resolution Network-Based Method for Yoga-Pose Estimation
by Jianrong Li, Dandan Zhang, Lei Shi, Ting Ke and Chuanlei Zhang
Appl. Sci. 2023, 13(15), 8912; https://doi.org/10.3390/app13158912 - 02 Aug 2023
Cited by 2 | Viewed by 1267
Abstract
In this paper, SEPAM_HRNet, a high-resolution pose-estimation model that incorporates the squeeze-and-excitation and pixel-attention-mask (SEPAM) module is proposed. Feature pyramid extraction, channel attention, and pixel-attention masks are integrated into the SEPAM module, resulting in improved model performance. The construction of the model involves [...] Read more.
In this paper, SEPAM_HRNet, a high-resolution pose-estimation model that incorporates the squeeze-and-excitation and pixel-attention-mask (SEPAM) module is proposed. Feature pyramid extraction, channel attention, and pixel-attention masks are integrated into the SEPAM module, resulting in improved model performance. The construction of the model involves replacing ordinary convolutions with the plug-and-play SEPAM module, which leads to the creation of the SEPAMneck module and SEPAMblock module. To evaluate the model’s performance, the YOGA2022 human yoga poses teaching dataset is presented. This dataset comprises 15,350 images that capture ten basic yoga pose types—Warrior I Pose, Warrior II Pose, Bridge Pose, Downward Dog Pose, Flat Pose, Inclined Plank Pose, Seated Pose, Triangle Pose, Phantom Chair Pose, and Goddess Pose—with a total of five participants. The YOGA2022 dataset serves as a benchmark for evaluating the accuracy of the human pose-estimation model. The experimental results demonstrated that the SEPAM_HRNet model achieved improved accuracy in predicting human keypoints on both the common objects in context (COCO) calibration set and the YOGA2022 calibration set, compared to other state-of-the-art human pose-estimation models with the same image resolution and environment configuration. These findings emphasize the superior performance of the SEPAM_HRNet model. Full article
(This article belongs to the Special Issue Advances in Intelligent Communication System)
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18 pages, 3569 KiB  
Article
Pointer Meter Recognition Method Based on Yolov7 and Hough Transform
by Chuanlei Zhang, Lei Shi, Dandan Zhang, Ting Ke and Jianrong Li
Appl. Sci. 2023, 13(15), 8722; https://doi.org/10.3390/app13158722 - 28 Jul 2023
Cited by 1 | Viewed by 1448
Abstract
The current manual reading of substation pointer meters wastes human resources, and existing algorithms have limitations in accuracy and robustness for detecting various pointer meters. This paper proposes a method for recognizing pointer meters based on Yolov7 and Hough transform to improve their [...] Read more.
The current manual reading of substation pointer meters wastes human resources, and existing algorithms have limitations in accuracy and robustness for detecting various pointer meters. This paper proposes a method for recognizing pointer meters based on Yolov7 and Hough transform to improve their automatic readability. The proposed method consists of three main contributions: (1) Using Yolov7 object detection technology, which is the latest Yolo technology, to enhance instrument recognition accuracy. (2) Providing a formula for calculating the angle of a square pointer meter after Hough transformation. (3) Applying OCR recognition to the instrument dial to obtain the model and scale value. This information helps differentiate between meter models and determine the measuring range. Test results demonstrate that the proposed algorithm achieves high accuracy and robustness in detecting different types and ranges of instruments. The map of the Yolov7 model on the instrument dataset is as high as 99.8%. Additionally, the accuracy of pointer readings obtained using this method exceeds 95%, indicating promising applications for a wide range of scenarios. Full article
(This article belongs to the Special Issue Advances in Intelligent Communication System)
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11 pages, 5551 KiB  
Article
Intelligent Blasthole Detection of Roadway Working Face Based on Improved YOLOv7 Network
by Shan Pan, Zijian Tian, Yifeng Qin, Zhongwen Yue and Ting Yu
Appl. Sci. 2023, 13(11), 6587; https://doi.org/10.3390/app13116587 - 29 May 2023
Cited by 2 | Viewed by 992
Abstract
Blasthole detection is crucial but challenging in tedious underground mining processes, given the diversity of surrounding rock backgrounds and uneven light intensity. However, existing algorithms have limitations in extracting image features and identifying differently sized objects. This study proposes a cascade-network-based blasthole detection [...] Read more.
Blasthole detection is crucial but challenging in tedious underground mining processes, given the diversity of surrounding rock backgrounds and uneven light intensity. However, existing algorithms have limitations in extracting image features and identifying differently sized objects. This study proposes a cascade-network-based blasthole detection method. The proposed method includes a blasthole feature extract transformation (BFET) module and a blasthole detection (BD) module. Firstly, we constructed the BFET module on the improved Cycle Generative Adversarial Network (CycleGAN) by multi-scale feature fusion. Then, we fused the convolution features of the generators in CycleGAN to obtain the enhanced feature map of the blasthole images. Secondly, the BD module was cascaded with the BFET module to accomplish the task of detecting blastholes. Results indicated that the detection accuracy of the blasthole image was significantly improved by strengthening the contrast of the image and suppressing over-exposure. The experimental results also showed that the proposed method enhanced the contrast of the image and could improve the accuracy of blasthole detection in real time. Compared with the YOLOv7 and CycleGAN+YOLOv7 methods, the detection accuracy of our method was improved by 5.34% and 2.38%, respectively. Full article
(This article belongs to the Special Issue Advances in Intelligent Communication System)
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33 pages, 1016 KiB  
Article
Digital Technology for Good: Path and Influence—Based on the Study of ESG Performance of Listed Companies in China
by Jingyong Wang, Zixiang Song and Lida Xue
Appl. Sci. 2023, 13(5), 2862; https://doi.org/10.3390/app13052862 - 23 Feb 2023
Cited by 8 | Viewed by 2716
Abstract
The relationship between digital technology and enterprise management is becoming increasingly close. Whether the application of new digital technology can guide enterprises and even the social economy to good governance is an urgent problem to be solved. This paper selects the data of [...] Read more.
The relationship between digital technology and enterprise management is becoming increasingly close. Whether the application of new digital technology can guide enterprises and even the social economy to good governance is an urgent problem to be solved. This paper selects the data of listed companies from 2011 to 2020 as a sample to empirically test the impact of digital transformation on ESG performance. The methodology is as follows: (1) Using the least squares method to do the main regression test. (2) Using Heckman’s two-step method, Lag 1 and 2, instrumental variable method: two-stage regression, PSM-OLS and PSM-DID estimation, robust analysis to do endogenous treatment to ensure that the main regression test is persuasive. (3) Using mediating effect to test the mechanism of action. (4) Using the least squares method for further research. The results show that: (1) Digital transformation is conducive to ESG performance. (2) In industries with high monopolies, digital transformation is not conducive to ESG performance. (3) Further analysis shows that due to the influence of peer effect, the concept of technological goodness is transmitted through network relationships to support other enterprises in the market. This study provides a new perspective for studying the influencing factors of enterprise ESG performance and also provides a theoretical reference for enterprises to use digital technology to achieve good governance. The scope of our research, the purpose of which is to help enterprises manipulate technology better, focuses on the effect on enterprises brought by digital technology. Full article
(This article belongs to the Special Issue Advances in Intelligent Communication System)
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Review

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31 pages, 3580 KiB  
Review
A Review of Image Inpainting Methods Based on Deep Learning
by Zishan Xu, Xiaofeng Zhang, Wei Chen, Minda Yao, Jueting Liu, Tingting Xu and Zehua Wang
Appl. Sci. 2023, 13(20), 11189; https://doi.org/10.3390/app132011189 - 11 Oct 2023
Cited by 1 | Viewed by 4004
Abstract
Image Inpainting is an age-old image processing problem, with people from different eras attempting to solve it using various methods. Traditional image inpainting algorithms have the ability to repair minor damage such as scratches and wear. However, with the rapid development of deep [...] Read more.
Image Inpainting is an age-old image processing problem, with people from different eras attempting to solve it using various methods. Traditional image inpainting algorithms have the ability to repair minor damage such as scratches and wear. However, with the rapid development of deep learning in the field of computer vision in recent years, coupled with abundant computing resources, methods based on deep learning have increasingly highlighted their advantages in semantic feature extraction, image transformation, and image generation. As such, image inpainting algorithms based on deep learning have become the mainstream in this domain.In this article, we first provide a comprehensive review of some classic deep-learning-based methods in the image inpainting field. Then, we categorize these methods based on component optimization, network structure design optimization, and training method optimization, discussing the advantages and disadvantages of each approach. A comparison is also made based on public datasets and evaluation metrics in image inpainting. Furthermore, the article delves into the applications of current image inpainting technologies, categorizing them into three major scenarios: object removal, general image repair, and facial inpainting. Finally, current challenges and prospective developments in the field of image inpainting are discussed. Full article
(This article belongs to the Special Issue Advances in Intelligent Communication System)
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