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

Deadline for manuscript submissions: closed (31 August 2023) | Viewed by 65506

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Prof. Dr. Zhigeng Pan

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Digital Media & Interaction Research Center, Hangzhou Normal University, Hangzhou 310012, China
Interests: learning (artificial intelligence); albedo; computer vision; convolutional neural nets; expectation-maximisation algorithm; feature extraction; haptic interfaces; human computer interaction; image classification; image colour analysis; image matching; image reconstruction; image sequences; image watermarking; lighting; motion estimation; multi-agent systems; object detection; object tracking; pattern classification; rendering (computer graphics); sensor fusion; stereo image processing; ubiquitous computing; video signal processing
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Dr. Zhihan Lv

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Guest Editor

Department of Game Design, Uppsala University, SE-751 05 Uppsala, Sweden
Interests: virtual/augmented reality; multimedia; human–computer interaction; networks; geographic information; digital twins; Internet of Things; blockchain
Special Issues, Collections and Topics in MDPI journals

Prof. Dr. Kai Xu

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Guest Editor

School of Computer Science Cellphone, National University of Defense Technology, Changsha 410128, China
Interests: computer graphics; 3D vision; data-driven geometry modeling
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

With the rapid development of modern society, the demand for practicability and intelligence increases daily, and more application technologies are focusing on the development of digital intelligence. The development of smart manufacturing, smart industry, smart medical, and other fields is the only way to build a smart city in the future. Eventually, it will expand beyond the level of cities and countries to realize intelligent research on the entire universe, exploring its origin and development from a more intelligent perspective.

Virtual reality (VR) contains a variety of information technologies, among which simulation technology has developed in a more extensive direction in recent years. The demand for virtual reality technology in various industries and fields is increasing, and pursuit of a more extreme sense of immersion and interactivity is the mainstream of current research.

Digital twin (DT) provides a broader application space for virtual reality whilst simultaneously providing higher requirements for technological progression. In the future, various objects in the virtual world will have more abundant intelligence, allowing them to evolve independently and to map each other with objects in the real world. For existing applications and their future developments, the integration of real-world data into the virtual world is critical to the evolution of digital twin technology.

The exhibition of a variety of virtual achievements indicates that the development of the metaverse is no longer limited to the conceptual level, and digital twin provides a fundamentally effective method of improvement. The expansion of VR, DT, and the Metaverse promote each other, forming a closed-loop mutual push development method.

This Special Issue involves a wide range of multidisciplinary themes and realizes more systematic intelligent and digital development in multiple fields, such as industry, manufacturing, education, aerospace, medical and health, and urban development.

Prof. Dr. Zhigeng Pan
Dr. Zhihan Lv
Prof. Dr. Kai Xu
Guest Editors

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Keywords

virtual reality
augmented reality
digital twins
Metaverse
dynamic modeling
3D technology
system integration technology
geographic information system
medical healthcare
Industry 4.0
industrial manufacturing
intelligent manufacturing
smart manufacturing
BIM
building information modeling

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Published Papers (11 papers)

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Research

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20 pages, 5611 KiB

Open AccessArticle

Using WebXR Metaverse Platforms to Create Touristic Services and Cultural Promotion

by Ana Martí-Testón, Adolfo Muñoz, Luis Gracia and J. Ernesto Solanes

Appl. Sci. 2023, 13(14), 8544; https://doi.org/10.3390/app13148544 - 24 Jul 2023

Cited by 19 | Viewed by 2792

Abstract

In recent years, there has been a surge of Metaverse applications and tools striving to capture the attention of both the general public and businesses, with a particularly strong potential within the tourism sector. However, there has been significant criticism towards major corporations for marketing a concept of the Metaverse that fails to align with reality. On the other hand, smaller entities such as Spatial-io, which is an innovative metaverse platform, are introducing a different style of the Metaverse, one that is highly accessible from contemporary devices like smartphones, tablets, VR headsets, and traditional PCs via WebXR platforms. This article delves into and scrutinizes various methodologies of a tourism-oriented Metaverse, considering its prospective utility as a vehicle to attract more visitors. A virtual tourist information center was established on the Spatial-io Metaverse platform to promote Valencia, Spain. This research scrutinizes the navigation, accessibility, and usability of the service from a conventional PC browser, contrasting it with the experience offered by the Meta Quest 2 virtual reality headset. The study’s quantitative and qualitative data analysis indicates that these innovative services are highly regarded, particularly when a real person (not a bot) provides information, fostering trust and offering details about various tourist attractions within the promoted city. The comparison of user inquiries’ time and depth aligns with the immersion level, demonstrating more positive feedback when the service is accessed through the VR system rather than a standard PC browser. Full article

(This article belongs to the Special Issue Virtual Reality, Digital Twins and Metaverse)

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16 pages, 1357 KiB

Open AccessArticle

A Visual Analysis Method for Predicting Material Properties Based on Uncertainty

by Qikai Chu, Lingli Zhang, Zhouqiao He, Yadong Wu and Weihan Zhang

Appl. Sci. 2023, 13(8), 4709; https://doi.org/10.3390/app13084709 - 8 Apr 2023

Cited by 2 | Viewed by 2109

Abstract

The traditional way of studying fluorinated materials by adjusting parameters throughout multiple trials can no longer meet the needs of the processing and analysis of multi-source, heterogeneous, and numerous complex data. Due to the high confidentiality of fluorinated materials’ data, it is not convenient for the plant to trust the data to third party professionals for processing and analysis. Therefore, this paper introduces a visual analysis method for material performance prediction supporting model selection, MP²-method, which helps with researchers’ independent selection and comparison of different levels of prediction models for different datasets and uses visual analysis to achieve performance prediction of fluorinated materials by adjusting control parameters. In addition, according to the Latin hypercube Markov chain (LHS-MC) model of uncertainty for visual analysis proposed in this paper, the uncertainty of the control-parameter data is reduced, and their prediction accuracy is improved. Finally, the usefulness and reliability of MP²-method are demonstrated through case studies and interviews with domain experts. Full article

(This article belongs to the Special Issue Virtual Reality, Digital Twins and Metaverse)

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14 pages, 4405 KiB

Open AccessArticle

Multi-Channel Expression Recognition Network Based on Channel Weighting

by Xiuwen Lu, Hongying Zhang, Qi Zhang and Xue Han

Appl. Sci. 2023, 13(3), 1968; https://doi.org/10.3390/app13031968 - 2 Feb 2023

Cited by 2 | Viewed by 1894

Abstract

Accurate expression interpretation occupies a huge proportion of human-to-human communication. The control of expressions can facilitate more convenient communication between people. Expression recognition technology has also been transformed from relatively mature laboratory-controlled research to natural scenes research. In this paper, we design a multi-channel attention network based on channel weighting for expression analysis in natural scenes. The network mainly consists of three parts: Multi-branch expression recognition feature extraction network, which combines residual network ResNet18 and ConvNeXt network ideas to improve feature extraction and uses adaptive feature fusion to build a complete network; Adaptive Channel Weighting, which designs adaptive weights in the auxiliary network for feature extraction, performs channel weighting, and highlights key information areas; and Attention module, which designs and modifies the spatial attention mechanism and increases the proportion of feature information to accelerate the acquisition of important expression feature information areas. The experimental results show that the proposed method achieves better recognition efficiency than existing algorithms on the dataset FER2013 under uncontrolled conditions, reaching 73.81%, and also achieves good recognition accuracy of 89.65% and 85.24% on the Oulu_CASIA and RAF-DB datasets, respectively. Full article

(This article belongs to the Special Issue Virtual Reality, Digital Twins and Metaverse)

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20 pages, 4753 KiB

Open AccessArticle

Relative Pose Estimation between Image Object and ShapeNet CAD Model for Automatic 4-DoF Annotation

by Soon-Yong Park, Chang-Min Son, Won-Jae Jeong and Sieun Park

Appl. Sci. 2023, 13(2), 693; https://doi.org/10.3390/app13020693 - 4 Jan 2023

Cited by 3 | Viewed by 3070

Abstract

Estimating the three-dimensional (3D) pose of real objects using only a single RGB image is an interesting and difficult topic. This study proposes a new pipeline to estimate and represent the pose of an object in an RGB image only with the 4-DoF annotation to a matching CAD model. The proposed method retrieves CAD candidates from the ShapeNet dataset and utilizes the pose-constrained 2D renderings of the candidates to find the best matching CAD model. The pose estimation pipeline consists of several steps of learned networks followed by image similarity measurements. First, from a single RGB image, the category and the object region are determined and segmented. Second, the 3-DoF rotational pose of the object is estimated by a learned pose-contrast network only using the segmented object region. Thus, 2D rendering images of CAD candidates are generated based on the rotational pose result. Finally, an image similarity measurement is performed to find the best matching CAD model and to determine the 1-DoF focal length of the camera to align the model with the object. Conventional pose estimation methods employ the 9-DoF pose parameters due to the unknown scale of both image object and CAD model. However, this study shows that only 4-DoF annotation parameters between real object and CAD model is enough to facilitates the projection of the CAD model to the RGB space for image-graphic applications such as Extended Reality. In the experiments, performance of the proposed method is analyzed by using ground truth and comparing with a triplet-loss learning method. Full article

(This article belongs to the Special Issue Virtual Reality, Digital Twins and Metaverse)

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22 pages, 2491 KiB

Open AccessArticle

Sequential Characteristics Based Operators Disassembly Quantization Method for LSTM Layers

by Yuejiao Wang, Zhong Ma and Zunming Yang

Appl. Sci. 2022, 12(24), 12744; https://doi.org/10.3390/app122412744 - 12 Dec 2022

Cited by 4 | Viewed by 1928

Abstract

Embedded computing platforms such as neural network accelerators deploying neural network models need to quantize the values into low-bit integers through quantization operations. However, most current embedded computing platforms with a fixed-point architecture do not directly support performing the quantization operation for the LSTM layer. Meanwhile, the influence of sequential input data for LSTM has not been taken into account by quantization algorithms. Aiming at these two technical bottlenecks, a new sequential-characteristics-based operators disassembly quantization method for LSTM layers is proposed. Specifically, the calculation process of the LSTM layer is split into multiple regular layers supported by the neural network accelerator. The quantization-parameter-generation process is designed as a sequential-characteristics-based combination strategy for sequential and diverse image groups. Therefore, LSTM is converted into multiple mature operators for single-layer quantization and deployed on the neural network accelerator. Comparison experiments with the state of the art show that the proposed quantization method has comparable or even better performance than the full-precision baseline in the field of character-/word-level language prediction and image classification applications. The proposed method has strong application potential in the subsequent addition of novel operators for future neural network accelerators. Full article

(This article belongs to the Special Issue Virtual Reality, Digital Twins and Metaverse)

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20 pages, 4545 KiB

Open AccessArticle

Adaptive Feature Fusion for Small Object Detection

by Qi Zhang, Hongying Zhang and Xiuwen Lu

Appl. Sci. 2022, 12(22), 11854; https://doi.org/10.3390/app122211854 - 21 Nov 2022

Cited by 15 | Viewed by 3708

Abstract

In order to alleviate the situation that small objects are prone to missed detection and false detection in natural scenes, this paper proposed a small object detection algorithm for adaptive feature fusion, referred to as MMF-YOLO. First, aiming at the problem that small object pixels are easy to lose, a multi-branch cross-scale feature fusion module with fusion factor was proposed, where each fusion path has an adaptive fusion factor, which can allow the network to independently adjust the importance of features according to the learned weights. Then, aiming at the problem that small objects are similar to background information and small objects overlap in complex scenes, the M-CBAM attention mechanism was proposed, which was added to the feature reinforcement extraction module to reduce feature redundancy. Finally, in light of the problem of small object size and large size span, the size of the object detection head was modified to adapt to the small object size. Experiments on the VisDrone2019 dataset showed that the mAP of the proposed algorithm could reach 42.23%, and the parameter quantity was only 29.33 MB, which is 9.13% ± 0.07% higher than the benchmark network mAP, and the network model was reduced by 5.22 MB. Full article

(This article belongs to the Special Issue Virtual Reality, Digital Twins and Metaverse)

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34 pages, 23857 KiB

Open AccessArticle

Protocols for the Graphic and Constructive Diffusion of Digital Twins of the Architectural Heritage That Guarantee Universal Accessibility through AR and VR

by Pablo Alejandro Cruz Franco, Adela Rueda Márquez de la Plata and Elena Gómez Bernal

Appl. Sci. 2022, 12(17), 8785; https://doi.org/10.3390/app12178785 - 31 Aug 2022

Cited by 30 | Viewed by 4365

Abstract

The objective of this article is to generate and validate a workflow that allows us to use virtual twins obtained from unique buildings of our architectural heritage. These twins will guarantee the preservation and dissemination of cultural assets and will promote universal accessibility through new technologies, such as databases, metaverses, virtual reality, augmented reality or gamification. This universal accessibility is based on new metaverses to offer experiences that allow us to overcome physical barriers and reach any user regardless of their economic or physical condition or their location. To obtain this workflow, we worked with digital twins obtained by photogrammetry. Different databases and metaverses were studied, understanding them as new systems for the representation and dissemination of architecture. These metaverses were critically assessed and screened, looking for the most suitable one to be integrated into an effective workflow that satisfies a series of imposed premises, such as being suitable for use in virtual reality and augmented reality environments. The ultimate goal is the aforementioned universal accessibility. Full article

(This article belongs to the Special Issue Virtual Reality, Digital Twins and Metaverse)

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14 pages, 3826 KiB

Open AccessArticle

Building Better Digital Twins for Production Systems by Incorporating Environmental Related Functions—Literature Analysis and Determining Alternatives

by Daniela Popescu, Mihai Dragomir, Sorin Popescu and Diana Dragomir

Appl. Sci. 2022, 12(17), 8657; https://doi.org/10.3390/app12178657 - 29 Aug 2022

Cited by 24 | Viewed by 3533

Abstract

The digital twin solution is an industry 4.0 specific tool that has grown in the past decade, stemming from the modelling and simulation approaches that existed before, complemented by new sensor capabilities, cloud processing, big data analytics, and implementation mechanisms. As it is being used mostly in the present by manufacturing companies, the primary focus of the solution is to enhance productivity and reduce costs by optimizing processes and enabling real-time problem-solving, sometimes based on decision-making systems and artificial intelligence. However, as companies are being faced with an increasingly steep list of environmental requirements and regulations, ranging from the classical pollution control and waste recycling to full-scale economic models based on circular economy and transformative carbon dioxide elimination programs, the features of the manufacturing digital twins must also evolve to provide an appropriate answer to these challenges. In this paper, the authors propose a framework for building better digital twins for production systems by incorporating environmental-related functions. The demarches start from analysing existing solutions presented in literature from the point of view of environmental suitability, based on the use of the MoSCoW method for differentiating attributes (into Must have, Should have, Could have, Will not have elements) and determining development alternatives based on the employment of Multi-Criteria Decision Analysis (MCDA) for feature selection, and the TRIZ method (Theory of Inventive Problem-Solving) for application guidelines. The MCDA was performed within a focus group of nine production specialists from regionally successful sectors. We arrive at the conclusion that environmental-related functions are poorly implemented in the digital twins of the present (although more so in integrated solutions and custom-built applications) and that the development of the proper tools, databases, and interpretation keys should proceed immediately in the fields of production engineering, industrial ecology, and software development to support them. Full article

(This article belongs to the Special Issue Virtual Reality, Digital Twins and Metaverse)

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10 pages, 380 KiB

Open AccessArticle

Options for and Challenges of Employing Digital Twins in Construction Management

by Tareq Salem and Mihai Dragomir

Appl. Sci. 2022, 12(6), 2928; https://doi.org/10.3390/app12062928 - 13 Mar 2022

Cited by 66 | Viewed by 8408

Abstract

The notions of smart construction and smart or digital cities include many modern concepts that are advocated today, especially in countries with advanced economies, and depend on using information technology and the Internet of Things as a basis to automate processes and activate digital systems to manage activities and services related to the operation of buildings and urban structures. In light of the spread of digital technology and modern managerial approaches, the concept of a digital twin is being used on a large scale with the current trend and direction to digitalize activities providing many economic, social and technical advantages. A digital twin is a system in which a virtual representation of a real entity or physical system is used continuously by being fed with data and deriving outputs in the form of decisions and actions that are generated through the processes of machine learning, simulation, development and lifecycle management. This study aims to review the literature on construction project management through the lens of digital twins and ways to use them in the field to improve operational results. The authors propose a framework for analyzing and supervising the development of digital twins that uses three main stages: the commonly encountered Building Information Modeling (BIM); the existing monitoring and actuation digital twins; and an envisioned third stage that makes use of artificial intelligence, complex visualization instruments and advanced controls with the capability to exact change within a construction project on the building site. Full article

(This article belongs to the Special Issue Virtual Reality, Digital Twins and Metaverse)

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Review

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22 pages, 1911 KiB

Open AccessReview

Impact of Digital Twins and Metaverse on Cities: History, Current Situation, and Application Perspectives

by Zhihan Lv, Wen-Long Shang and Mohsen Guizani

Appl. Sci. 2022, 12(24), 12820; https://doi.org/10.3390/app122412820 - 14 Dec 2022

Cited by 59 | Viewed by 7883

Abstract

To promote the expansion and adoption of Digital Twins (DTs) in Smart Cities (SCs), a detailed review of the impact of DTs and digitalization on cities is made to assess the progression of cities and standardization of their management mode. Combined with the technical elements of DTs, the coupling effect of DTs technology and urban construction and the internal logic of DTs technology embedded in urban construction are discussed. Relevant literature covering the full range of DTs technologies and their applications is collected, evaluated, and collated, relevant studies are concatenated, and relevant accepted conclusions are summarized by modules. First, the historical process and construction content of a Digital City (DC) under modern demand are analyzed, and the main ideas of a DC design and construction are discussed in combination with the key technology of DTs. Then, the metaverse is the product of the combination of various technologies in different scenes. It is a key component to promote the integration of the real world and the digital world and can provide more advanced technical support in the construction of the DC. DTs urban technology architecture is composed of an infrastructure terminal information center terminal and application server end. Urban intelligent management is realized through physical urban data collection, transmission, processing, and digital urban visualization. The construction of DTs urban platform can improve the city’s perception and decision-making ability and bring a broader vision for future planning and progression. The interactive experience of the virtual world covered by the metaverse can effectively support and promote the integration of the virtual and real, and will also greatly promote the construction of SCs. In summary, this work is of important reference value for the overall development and practical adoption of DTs cities, which improves the overall operation efficiency and the governance level of cities. Full article

(This article belongs to the Special Issue Virtual Reality, Digital Twins and Metaverse)

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28 pages, 2109 KiB

Open AccessReview

Deep Learning for Intelligent Human–Computer Interaction

by Zhihan Lv, Fabio Poiesi, Qi Dong, Jaime Lloret and Houbing Song

Appl. Sci. 2022, 12(22), 11457; https://doi.org/10.3390/app122211457 - 11 Nov 2022

Cited by 74 | Viewed by 20723

Abstract

In recent years, gesture recognition and speech recognition, as important input methods in Human–Computer Interaction (HCI), have been widely used in the field of virtual reality. In particular, with the rapid development of deep learning, artificial intelligence, and other computer technologies, gesture recognition and speech recognition have achieved breakthrough research progress. The search platform used in this work is mainly the Google Academic and literature database Web of Science. According to the keywords related to HCI and deep learning, such as “intelligent HCI”, “speech recognition”, “gesture recognition”, and “natural language processing”, nearly 1000 studies were selected. Then, nearly 500 studies of research methods were selected and 100 studies were finally selected as the research content of this work after five years (2019–2022) of year screening. First, the current situation of the HCI intelligent system is analyzed, the realization of gesture interaction and voice interaction in HCI is summarized, and the advantages brought by deep learning are selected for research. Then, the core concepts of gesture interaction are introduced and the progress of gesture recognition and speech recognition interaction is analyzed. Furthermore, the representative applications of gesture recognition and speech recognition interaction are described. Finally, the current HCI in the direction of natural language processing is investigated. The results show that the combination of intelligent HCI and deep learning is deeply applied in gesture recognition, speech recognition, emotion recognition, and intelligent robot direction. A wide variety of recognition methods were proposed in related research fields and verified by experiments. Compared with interactive methods without deep learning, high recognition accuracy was achieved. In Human–Machine Interfaces (HMIs) with voice support, context plays an important role in improving user interfaces. Whether it is voice search, mobile communication, or children’s speech recognition, HCI combined with deep learning can maintain better robustness. The combination of convolutional neural networks and long short-term memory networks can greatly improve the accuracy and precision of action recognition. Therefore, in the future, the application field of HCI will involve more industries and greater prospects are expected. Full article

(This article belongs to the Special Issue Virtual Reality, Digital Twins and Metaverse)

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