In this work,Digital Twins based on Neural Networks for the steady state production of styrene were generated.Thus,both the Aspen Technology AI Model Builder(alternative 1)and a homemade MS Excel VBA code connected to...In this work,Digital Twins based on Neural Networks for the steady state production of styrene were generated.Thus,both the Aspen Technology AI Model Builder(alternative 1)and a homemade MS Excel VBA code connected to Aspen HYSYS and Aspen Plus(alternative 2)were used with this same aim.The raw data used for generating the Digital Twins were obtained from process simulations using Aspen HYSYS and/or Aspen Plus,which were connected through a recycle-like stream via automation for solving the entire simulation flowsheet.Aspen HYSYS was used for solving the pre-heating,reaction,and stabilization sections of the process whereas Aspen Plus ensured the computing of the separation and purification columns.Both alternatives led to an excellent prediction showing the capability of creating Digital Twins from and for process simulation.展开更多
In order to improve the comprehensive defense capability of data security in digital twins(DTs),an information security interaction architecture is proposed in this paper to solve the inadequacy of data protection and...In order to improve the comprehensive defense capability of data security in digital twins(DTs),an information security interaction architecture is proposed in this paper to solve the inadequacy of data protection and transmission mechanism at present.Firstly,based on the advanced encryption standard(AES)encryption,we use the keystore to expand the traditional key,and use the digital pointer to avoid the key transmission in a wireless channel.Secondly,the identity authentication technology is adopted to ensure the data integrity,and an automatic retransmission mechanism is added for the endogenous properties of the wireless channel.Finally,the software defined radio(SDR)platform composed of universal software radio peripheral(USRP)and GNU radio is used to simulate the data interaction between the physical entity and the virtual entity.The numerical results show that the DTs architecture can guarantee the encrypted data transmitted completely and decrypted accurately with high efficiency and reliability,thus providing a basis for intelligent and secure information interaction for DTs in the future.展开更多
To understand the current application and development of 3D modeling in Digital Twins(DTs),abundant literatures on DTs and 3D modeling are investigated by means of literature review.The transition process from 3D mode...To understand the current application and development of 3D modeling in Digital Twins(DTs),abundant literatures on DTs and 3D modeling are investigated by means of literature review.The transition process from 3D modeling to DTs modeling is analyzed,as well as the current application of DTs modeling in various industries.The application of 3D DTs modeling in theelds of smartmanufacturing,smart ecology,smart transportation,and smart buildings in smart cities is analyzed in detail,and the current limitations are summarized.It is found that the 3D modeling technology in DTs has broad prospects for development and has a huge impact on all walks of life and even human lifestyles.At the same time,the development of DTs modeling relies on the development and support capabilities of mature technologies such as Big Data,Internet of Things,Cloud Computing,Articial Intelligence,and game technology.Therefore,although some results have been achieved,there are still limitations.This work aims to provide a good theoretical support for the further development of 3D DTs modeling.展开更多
At present,the interpretation of regional economic development(RED)has changed from a simple evaluation of economic growth to a focus on economic growth and the optimization of economic structure,the improvement of ec...At present,the interpretation of regional economic development(RED)has changed from a simple evaluation of economic growth to a focus on economic growth and the optimization of economic structure,the improvement of economic relations,and the change of institutional innovation.This article uses the RED trend as the research object and constructs the RED index to conduct the theoretical analysis.Then this paper uses the attention mechanism based on digital twins and the time series network model to verify the actual data.Finally,the regional economy is predicted according to the theoretical model.The specific research work mainly includes the following aspects:1)This paper introduced the development status of research on time series networks and economic forecasting at home and abroad.2)This paper introduces the basic principles and structures of long and short-term memory(LSTM)and convolutional neural network(CNN),constructs an improved CNN-LSTM model combined with the attention mechanism,and then constructs a regional economic prediction index system.3)The best parameters of the model are selected through experiments,and the trained model is used for simulation experiment prediction.The results show that the CNN-LSTM model based on the attentionmechanism proposed in this paper has high accuracy in predicting regional economies.展开更多
Backgrounds This work emphasizes the current research status of the urban Digital Twins to establish an intelligent spatiotemporal framework.A Geospatial Artificial Intelligent(GeoAI)system is developed based on the G...Backgrounds This work emphasizes the current research status of the urban Digital Twins to establish an intelligent spatiotemporal framework.A Geospatial Artificial Intelligent(GeoAI)system is developed based on the Geographic Information System and Artificial Intelligence.It integrates multi-video technology and Virtual City in urban Digital Twins.Methods Besides,an improved small object detection model is proposed:YOLOv5-Pyramid,and Siamese network video tracking models,namely MPSiam and FSSiamese,are established.Finally,an experimental platform is built to verify the georeferencing correction scheme of video images.Result The MultiplyAccumulate value of MPSiam is 0.5B,and that of ResNet50-Siam is 4.5B.Besides,the model is compressed by 4.8times.The inference speed has increased by 3.3 times,reaching 83 Frames Per Second.3%of the Average Expectation Overlap is lost.Therefore,the urban Digital Twins-oriented GeoAI framework established here has excellent performance for video georeferencing and target detection problems.展开更多
Digital twins for wide-areas(DT-WA)can model and predict the physical world with high fidelity by incorporating an artificial intelligence(AI)model.However,the AI model requires an energy-consuming updating process to...Digital twins for wide-areas(DT-WA)can model and predict the physical world with high fidelity by incorporating an artificial intelligence(AI)model.However,the AI model requires an energy-consuming updating process to keep pace with the dynamic environment,where studies are still in infancy.To reduce the updating energy,this paper proposes a distributed edge cooperation and data collection scheme.The AI model is partitioned into multiple sub-models deployed on different edge servers(ESs)co-located with access points across wide-area,to update distributively using local sensor data.To reduce the updating energy,ESs can choose to become either updating helpers or recipients of their neighboring ESs,based on sensor quantities and basic updating convergencies.Helpers would share their updated sub-model parameters with neighboring recipients,so as to reduce the latter updating workload.To minimize system energy under updating convergency and latency constraints,we further propose an algorithm to let ESs distributively optimize their cooperation identities,collect sensor data,and allocate wireless and computing resources.It comprises several constraint-release approaches,where two child optimization problems are solved,and designs a largescale multi-agent deep reinforcement learning algorithm.Simulation shows that the proposed scheme can efficiently reduce updating energy compared with the baselines.展开更多
Digital twins have emerged as a promising technology for maintenance applications,enabling organizations to simulate and monitor physical assets to improve their performance.In Operation and Maintenance(O&M),digit...Digital twins have emerged as a promising technology for maintenance applications,enabling organizations to simulate and monitor physical assets to improve their performance.In Operation and Maintenance(O&M),digital twin facilitates the diagnosis and prognosis of critical assets,forming the basis for smart maintenance planning and reducing downtime.However,there is a lack of standardized approaches for the qualifications of digital twins in maintenance,leading to low trustworthiness and limiting its application.This paper proposes a novel framework for the qualifications of digital twins in maintenance based on five pillars,namely fidelity,smartness,timeliness,integration,and standard compliance.We demonstrate the effectiveness of the framework through two case studies,showing how it can be implemented on digital twins for preventive maintenance and condition-based maintenance.Our proposed framework can help organizations across different industrial domains develop and implement digital twins in maintenance more effectively and efficiently,leading to significant benefits in terms of cost reduction,performance improvement,and sustainability.展开更多
Despite advances in intelligent medical care,difficulties remain.Due to its complicated governance,designing,planning,improving,and managing the cardiac system remains difficult.Oversight,including intelligent monitor...Despite advances in intelligent medical care,difficulties remain.Due to its complicated governance,designing,planning,improving,and managing the cardiac system remains difficult.Oversight,including intelligent monitoring,feedback systems,and management practises,is unsuccessful.Current platforms cannot deliver lifelong personal health management services.Insufficient accuracy in patient crisis warning programmes.No frequent,direct interaction between healthcare workers and patients is visible.Physical medical systems and intelligent information systems are not integrated.This study introduces the Advanced Cardiac Twin(ACT)model integrated with Artificial Neural Network(ANN)to handle real-time monitoring,decision-making,and crisis prediction.THINGSPEAK is used to create an IoT platform that accepts patient sensor data.Importing these data sets into MATLAB allows display and analysis.A myocardial ischemia research examined Health Condition Tracking’s(HCT’s)potential.In the case study,75%of the training sets(Xt),15%of the verified data,and 10%of the test data were used.Training set feature values(Xt)were given with the data.Training,Validation,and Testing accuracy rates were 99.9%,99.9%,and 99.9%,respectively.General research accuracy was 99.9%.The proposed HCT system and Artificial Neural Network(ANN)model gather historical and real-time data to manage and anticipate cardiac issues.展开更多
Developments in new-generation information technology have enabled Digital Twins to reshape the physical world into a virtual digital space and provide technical support for constructing the Metaverse.Metaverse object...Developments in new-generation information technology have enabled Digital Twins to reshape the physical world into a virtual digital space and provide technical support for constructing the Metaverse.Metaverse objects can be at the micro-,meso-,or macroscale.The Metaverse is a complex collection of solid,liquid,gaseous,plasma,and other uncertain states.Additionally,the Metaverse integrates tangibles with social relations,such as interpersonal(friends,partners,and family)and social relations(ethics,morality,and law).This review introduces some principles and laws,such as broken windows theory,small-world phenomenon,survivor bias,and herd behavior,for constructing a Digital Twins model for social relations.Therefore,from multiple perspectives,this article reviews mappings of tangible and intangible real-world objects to the Metaverse using the Digital Twins model.展开更多
The industrial Internet of Things (IIoT) is an important engine for manufacturingenterprises to provide intelligent products and services. With the development of IIoT, moreand more attention has been paid to the appl...The industrial Internet of Things (IIoT) is an important engine for manufacturingenterprises to provide intelligent products and services. With the development of IIoT, moreand more attention has been paid to the application of ultra-reliable and low latency communications(URLLC) in the 5G system. The data analysis model represented by digital twins isthe core of IIoT development in the manufacturing industry. In this paper, the efforts of3GPP are introduced for the development of URLLC in reducing delay and enhancing reliability,as well as the research on little jitter and high transmission efficiency. The enhancedkey technologies required in the IIoT are also analyzed. Finally, digital twins are analyzedaccording to the actual IIoT situation.展开更多
To realize high-accuracy physical-cyber digital twin(DT)mapping in a manufacturing system,a huge amount of data need to be collected and analyzed in real-time.Traditional DTs systems are deployed in cloud or edge serv...To realize high-accuracy physical-cyber digital twin(DT)mapping in a manufacturing system,a huge amount of data need to be collected and analyzed in real-time.Traditional DTs systems are deployed in cloud or edge servers independently,whilst it is hard to apply in real production systems due to the high interaction or execution delay.This results in a low consistency in the temporal dimension of the physical-cyber model.In this work,we propose a novel efficient edge-cloud DT manufacturing system,which is inspired by resource scheduling technology.Specifically,an edge-cloud collaborative DTs system deployment architecture is first constructed.Then,deterministic and uncertainty optimization adaptive strategies are presented to choose a more powerful server for running DT-based applications.We model the adaptive optimization problems as dynamic programming problems and propose a novel collaborative clustering parallel Q-learning(CCPQL)algorithm and prediction-based CCPQL to solve the problems.The proposed approach reduces the total delay with a higher convergence rate.Numerical simulation results are provided to validate the approach,which would have great potential in dynamic and complex industrial internet environments.展开更多
Background All recent technological findings can be collectively used to strengthen the industrial Internet of things(IIoT)sector.The novel technology of multi-access edge computing or mobile edge computing(MEC)and di...Background All recent technological findings can be collectively used to strengthen the industrial Internet of things(IIoT)sector.The novel technology of multi-access edge computing or mobile edge computing(MEC)and digital twins have advanced rapidly in the industry.MEC is the middle layer between mobile devices and the cloud,and it provides scalability,reliability,security,efficient control,and storage of resources.Digital twins form a communication model that enhances the entire system by improving latency,overhead,and energy consumption.Methods The main focus in this study is the biggest challenges that researchers in the field of IIoT have to overcome to obtain a more efficient communication environment in terms of technology integration,efficient energy and data delivery,storage spaces,security,and real-time control and analysis.Thus,a distributed system is established in a local network,in which several functions operate.In addition,an MEC-based framework is proposed to reduce traffic and latency by merging the processing of data generated by IIoT devices at the edge of the network.The critical parts of the proposed IIoT system are evaluated by using emulation software.Results The results show that data delivery and offloading are performed more efficiently,energy consumption and processing are improved,and security,complexity,control,and reliability are enhanced.Conclusions The proposed framework and application provide authentication and integrity to end users and IoT devices.展开更多
Background Digital twins are virtual representations of devices and processes that capture the physical properties of the environment and operational algorithms/techniques in the context of medical devices and tech-no...Background Digital twins are virtual representations of devices and processes that capture the physical properties of the environment and operational algorithms/techniques in the context of medical devices and tech-nologies.Digital twins may allow healthcare organizations to determine methods of improving medical processes,enhancing patient experience,lowering operating expenses,and extending the value of care.During the present COVID-19 pandemic,various medical devices,such as X-rays and CT scan machines and processes,are constantly being used to collect and analyze medical images.When collecting and processing an extensive volume of data in the form of images,machines and processes sometimes suffer from system failures,creating critical issues for hospitals and patients.Methods To address this,we introduce a digital-twin-based smart healthcare system in-tegrated with medical devices to collect information regarding the current health condition,configuration,and maintenance history of the device/machine/system.Furthermore,medical images,that is,X-rays,are analyzed by using a deep-learning model to detect the infection of COVID-19.The designed system is based on the cascade recurrent convolution neural network(RCNN)architecture.In this architecture,the detector stages are deeper and more sequentially selective against small and close false positives.This architecture is a multi-stage extension of the RCNN model and sequentially trained using the output of one stage for training the other.At each stage,the bounding boxes are adjusted to locate a suitable value of the nearest false positives during the training of the different stages.In this manner,the arrangement of detectors is adjusted to increase the intersection over union,overcoming the problem of overfitting.We train the model by using X-ray images as the model was previously trained on another dataset.Results The developed system achieves good accuracy during the detection phase of COVID-19.The experimental outcomes reveal the efficiency of the detection architecture,which yields a mean average precision rate of 0.94.展开更多
We are in the midst of a significant transformation regarding the way we produce products and deliver services thanks to the digitization of manufacturing and new connected supply-chains and co-creation systems.This a...We are in the midst of a significant transformation regarding the way we produce products and deliver services thanks to the digitization of manufacturing and new connected supply-chains and co-creation systems.This article elaborates Digital Twins Approach to the current challenges of knowledge management when Industry 4.0 is emerging in industries and manufacturing.Industry 4.0 approach underlines the importance of Internet of Things and interactions between social and physical systems.Internet of Things(and also Internet of Services and Internet of Data)are new Internet infrastructure that marries advanced manufacturing techniques and service architectures with the I-o-T,I-o-S,and I-o-D to create manufacturing systems that are not only interconnected,but communicate,analyze,and use information to drive further intelligent action back in the physical world.This paper identifies four critical domains of synergy challenge:(1)man-to-man interaction;(2)man-to-machine interaction;(3)machine-to-man interaction;and finally(4)machine-to-machine interaction.Key conclusion is that new knowledge management challenges are closely linked to the challenges of synergic interactions between these four key interactions and accurate measurements of synergic interaction.展开更多
Background Digital twins offer rich potential for exploration in virtual reality(VR).Using interactive molecular simulation approaches,they enable a human operator to access the physical properties of molecular object...Background Digital twins offer rich potential for exploration in virtual reality(VR).Using interactive molecular simulation approaches,they enable a human operator to access the physical properties of molecular objects and to build,manipulate,and study their assemblies.Integrative modeling and drug design are important applications of this technology.Methods In this study,head-mounted virtual reality displays connected to mole-cular simulation engines were used to create interactive and immersive digital twins.They were used to perform tasks relevant to specific use cases.Results Three areas were investigated,including model building,rational design,and tangible models.Here,we report several membrane-embedded systems of ion channels,viral com-ponents,and artificial water channels.We were able to improve and create molecular designs based on digital twins.Conclusions The molecular application domain offers great opportunities,and most of the technical and tech-nological aspects have been solved.Wider adoption is expected once the onboarding of VR is simplified and the technology gains wider acceptance.展开更多
Product assembly simulation is considered as one of the key technologies in the process of complex product design and manufacturing.Virtual assembly realizes the assembly process design,verification,and optimization o...Product assembly simulation is considered as one of the key technologies in the process of complex product design and manufacturing.Virtual assembly realizes the assembly process design,verification,and optimization of complex products in the virtual environment,which plays an active and effective role in improving the assembly quality and efficiency of complex products.In recent years,augmented reality(AR)and digital twin(DT)technology have brought new opportunities and challenges to the digital assembly of complex products owing to their characteristics of virtual reality fusion and interactive control.This paper expounds the concept and connotation of AR,enumerates a typical AR assembly system structure,analyzes the key technologies and applications of AR in digital assembly,and notes that DT technology is the future development trend of intelligent assembly research.展开更多
Background The advancements of Artificial Intelligence,Big Data Analytics,and the Internet of Things paved the path to the emergence and use of Digital Twins(DTs)as technologies to“twin”the life of a physical entity...Background The advancements of Artificial Intelligence,Big Data Analytics,and the Internet of Things paved the path to the emergence and use of Digital Twins(DTs)as technologies to“twin”the life of a physical entity in different fields,ranging from industry to healthcare.At the same time,the advent of eXtended Reality(XR)in industrial and consumer electronics has provided novel paradigms that may be put to good use to visualize and interact with DTs.XR technologies can support human-to-human interactions for training and remote assistance and could transform DTs into collaborative intelligence tools.Methods We here present the Human Collaborative Intelligence empowered Digital Twin framework(HCLINT-DT)integrating human annotations(e.g.,textual and vocal)to allow the creation of an all-in-one-place resource to preserve such knowledge.This framework could be adopted in many fields,supporting users to learn how to carry out an unknown process or explore others’past experiences.Results The assessment of such a framework has involved implementing a DT supporting human annotations,reflected in both the physical world(Augmented Reality)and the virtual one(Virtual Reality).Con-clusions The outcomes of the interface design assessment confirm the interest in developing HCLINT-DT-based applications.Finally,we evaluated how the proposed framework could be translated into a manufacturing context.展开更多
The emerging field of City Digital Twins has advanced in recent years with the help of digital infrastructure and technologies connected to the Internet of Things(IoT).However,the evolution of this field has been so f...The emerging field of City Digital Twins has advanced in recent years with the help of digital infrastructure and technologies connected to the Internet of Things(IoT).However,the evolution of this field has been so fast that a gap has opened in relation to systematic reviews of the relevant literature and the maturation of City Digital Twins on an urban scale.Our work bridges this gap by highlighting maturity in the field.We conducted a systematic literature review with bibliometric and content analysis of 41 selected papers published in Web of Science and Scopus data-bases,covering five areas:data types and sources,case studies,applied technologies and methods,maturity spectrum,and appli-cations.Based on maturity indicators,the majority of the reviewed studies(90%)were at initial to medium stages of maturity(up to element 3),most of them focused on 3D modelling,monitoring and visualisation.However,digital twins cannot be limited to 3D models,monitoring and visualisation,for they can be developed to include two-directional interactions between humans and com-puters.Such a high level of maturity,which was not found in the reviewed studies,requires advanced technologies and methods such as cloud computing,artificial intelligence,BIM and GIS.We also found that further studies are essential if the field is to handle the complex urban challenges of multidisciplinary digital twins.While City Digital Twins extend by definition beyond mere 3D city modelling,some studies involving 3D city models still refer to their subjects as City Digital Twins.Among the research gaps we identified,we’d like to highlight the need for near-real-time data analytics algorithms,which could furnish City Digital Twins with big data insights.Other opportunities include public participation capabilities to increase social collaboration,integrating BIM and GIS technologies and improving storage and computation infrastructure.展开更多
The transition to low carbon energy systems poses challenges in terms of energy efficiency.In building refur-bishment projects,efficient technologies such as smart controls and heat pumps are increasingly being used a...The transition to low carbon energy systems poses challenges in terms of energy efficiency.In building refur-bishment projects,efficient technologies such as smart controls and heat pumps are increasingly being used as a substitute for conventional technologies with the aim of reducing carbon emissions and determining operational energy and cost savings,together with other benefits.Measured building performance,however,often reveals a significant gap between the predicted energy use(design stage)and actual energy use(operation stage).For this reason,lean and interpretable digital twins are needed for building energy monitoring aimed at persistence of savings and continuous performance improvement.In this research,interpretable regression models are built with data at multiple temporal resolutions(monthly,daily and hourly)and seamlessly integrated with the goal of verifying the performance improvements due to Smart thermostatic radiator valves(TRVs)and gas absorption heat pumps(GAHPs)as well as giving insights on the performance of the building as a whole.Further,as part of modelling research,time of week and temperature(TOWT)approach is reformulated and benchmarked against its original implementation.The case study chosen is Hale Court sheltered housing,located in the city of Portsmouth(UK).This building has been used for the field-testing of innovative technologies such as TRVs and GAHPs within the EU Horizon 2020 project THERMOSS.The results obtained are used to illustrate possible extensions of the use of energy signature modelling,highlighting implications for energy management and innovative building technologies development.展开更多
The concept of the digital twin,also known colloquially as the DT,is a fundamental principle within Industry 4.0 framework.In recent years,the concept of digital siblings has generated considerable academic and practi...The concept of the digital twin,also known colloquially as the DT,is a fundamental principle within Industry 4.0 framework.In recent years,the concept of digital siblings has generated considerable academic and practical interest.However,academia and industry have used a variety of interpretations,and the scientific literature lacks a unified and consistent definition of this term.The purpose of this study is to systematically examine the definitional landscape of the digital twin concept as outlined in scholarly literature,beginning with its origins in the aerospace domain and extending to its contemporary interpretations in the manufacturing industry.Notably,this investigationwill focus on the research conducted on Industry 4.0 and smartmanufacturing,elucidating the diverse applications of digital twins in fields including aerospace,intelligentmanufacturing,intelligent transportation,and intelligent cities,among others.展开更多
基金V.R.F.thanks to the Aspen Technology Inc.the possibility to participate in the training course“EHM 101:Introduction to Aspen Hybrid Models for Engineering”,where,during the trial time available for AIMB he carried out the case presented in the current paper.
文摘In this work,Digital Twins based on Neural Networks for the steady state production of styrene were generated.Thus,both the Aspen Technology AI Model Builder(alternative 1)and a homemade MS Excel VBA code connected to Aspen HYSYS and Aspen Plus(alternative 2)were used with this same aim.The raw data used for generating the Digital Twins were obtained from process simulations using Aspen HYSYS and/or Aspen Plus,which were connected through a recycle-like stream via automation for solving the entire simulation flowsheet.Aspen HYSYS was used for solving the pre-heating,reaction,and stabilization sections of the process whereas Aspen Plus ensured the computing of the separation and purification columns.Both alternatives led to an excellent prediction showing the capability of creating Digital Twins from and for process simulation.
基金supported in part by the Intergovernmental International Cooperation in Science and Technology Innovation Program under Grants 2019YFE0111600in part by National Natural Science Foundation of China under Grants 62122069,62072490,62201507,and 62071431+2 种基金in part by Science and Technology Development Fund of Macao SAR under Grants 0060/2019/A1 and 0162/2019/A3in part by FDCT-MOST Joint Project under Grant 0066/2019/AMJin part by Research Grant of University of Macao under Grant MYRG2020-00107IOTSC。
文摘In order to improve the comprehensive defense capability of data security in digital twins(DTs),an information security interaction architecture is proposed in this paper to solve the inadequacy of data protection and transmission mechanism at present.Firstly,based on the advanced encryption standard(AES)encryption,we use the keystore to expand the traditional key,and use the digital pointer to avoid the key transmission in a wireless channel.Secondly,the identity authentication technology is adopted to ensure the data integrity,and an automatic retransmission mechanism is added for the endogenous properties of the wireless channel.Finally,the software defined radio(SDR)platform composed of universal software radio peripheral(USRP)and GNU radio is used to simulate the data interaction between the physical entity and the virtual entity.The numerical results show that the DTs architecture can guarantee the encrypted data transmitted completely and decrypted accurately with high efficiency and reliability,thus providing a basis for intelligent and secure information interaction for DTs in the future.
文摘To understand the current application and development of 3D modeling in Digital Twins(DTs),abundant literatures on DTs and 3D modeling are investigated by means of literature review.The transition process from 3D modeling to DTs modeling is analyzed,as well as the current application of DTs modeling in various industries.The application of 3D DTs modeling in theelds of smartmanufacturing,smart ecology,smart transportation,and smart buildings in smart cities is analyzed in detail,and the current limitations are summarized.It is found that the 3D modeling technology in DTs has broad prospects for development and has a huge impact on all walks of life and even human lifestyles.At the same time,the development of DTs modeling relies on the development and support capabilities of mature technologies such as Big Data,Internet of Things,Cloud Computing,Articial Intelligence,and game technology.Therefore,although some results have been achieved,there are still limitations.This work aims to provide a good theoretical support for the further development of 3D DTs modeling.
文摘At present,the interpretation of regional economic development(RED)has changed from a simple evaluation of economic growth to a focus on economic growth and the optimization of economic structure,the improvement of economic relations,and the change of institutional innovation.This article uses the RED trend as the research object and constructs the RED index to conduct the theoretical analysis.Then this paper uses the attention mechanism based on digital twins and the time series network model to verify the actual data.Finally,the regional economy is predicted according to the theoretical model.The specific research work mainly includes the following aspects:1)This paper introduced the development status of research on time series networks and economic forecasting at home and abroad.2)This paper introduces the basic principles and structures of long and short-term memory(LSTM)and convolutional neural network(CNN),constructs an improved CNN-LSTM model combined with the attention mechanism,and then constructs a regional economic prediction index system.3)The best parameters of the model are selected through experiments,and the trained model is used for simulation experiment prediction.The results show that the CNN-LSTM model based on the attentionmechanism proposed in this paper has high accuracy in predicting regional economies.
基金Supported by Key R&D Program of the Ministry of Science and Technology (2019YFC0810704)Key R&D Program of Guangdong Province (2019B111102002)Shenzhen Science and Technology Program (KCXFZ202002011007040)。
文摘Backgrounds This work emphasizes the current research status of the urban Digital Twins to establish an intelligent spatiotemporal framework.A Geospatial Artificial Intelligent(GeoAI)system is developed based on the Geographic Information System and Artificial Intelligence.It integrates multi-video technology and Virtual City in urban Digital Twins.Methods Besides,an improved small object detection model is proposed:YOLOv5-Pyramid,and Siamese network video tracking models,namely MPSiam and FSSiamese,are established.Finally,an experimental platform is built to verify the georeferencing correction scheme of video images.Result The MultiplyAccumulate value of MPSiam is 0.5B,and that of ResNet50-Siam is 4.5B.Besides,the model is compressed by 4.8times.The inference speed has increased by 3.3 times,reaching 83 Frames Per Second.3%of the Average Expectation Overlap is lost.Therefore,the urban Digital Twins-oriented GeoAI framework established here has excellent performance for video georeferencing and target detection problems.
基金supported by National Key Research and Development Program of China(2020YFB1807900).
文摘Digital twins for wide-areas(DT-WA)can model and predict the physical world with high fidelity by incorporating an artificial intelligence(AI)model.However,the AI model requires an energy-consuming updating process to keep pace with the dynamic environment,where studies are still in infancy.To reduce the updating energy,this paper proposes a distributed edge cooperation and data collection scheme.The AI model is partitioned into multiple sub-models deployed on different edge servers(ESs)co-located with access points across wide-area,to update distributively using local sensor data.To reduce the updating energy,ESs can choose to become either updating helpers or recipients of their neighboring ESs,based on sensor quantities and basic updating convergencies.Helpers would share their updated sub-model parameters with neighboring recipients,so as to reduce the latter updating workload.To minimize system energy under updating convergency and latency constraints,we further propose an algorithm to let ESs distributively optimize their cooperation identities,collect sensor data,and allocate wireless and computing resources.It comprises several constraint-release approaches,where two child optimization problems are solved,and designs a largescale multi-agent deep reinforcement learning algorithm.Simulation shows that the proposed scheme can efficiently reduce updating energy compared with the baselines.
文摘Digital twins have emerged as a promising technology for maintenance applications,enabling organizations to simulate and monitor physical assets to improve their performance.In Operation and Maintenance(O&M),digital twin facilitates the diagnosis and prognosis of critical assets,forming the basis for smart maintenance planning and reducing downtime.However,there is a lack of standardized approaches for the qualifications of digital twins in maintenance,leading to low trustworthiness and limiting its application.This paper proposes a novel framework for the qualifications of digital twins in maintenance based on five pillars,namely fidelity,smartness,timeliness,integration,and standard compliance.We demonstrate the effectiveness of the framework through two case studies,showing how it can be implemented on digital twins for preventive maintenance and condition-based maintenance.Our proposed framework can help organizations across different industrial domains develop and implement digital twins in maintenance more effectively and efficiently,leading to significant benefits in terms of cost reduction,performance improvement,and sustainability.
文摘Despite advances in intelligent medical care,difficulties remain.Due to its complicated governance,designing,planning,improving,and managing the cardiac system remains difficult.Oversight,including intelligent monitoring,feedback systems,and management practises,is unsuccessful.Current platforms cannot deliver lifelong personal health management services.Insufficient accuracy in patient crisis warning programmes.No frequent,direct interaction between healthcare workers and patients is visible.Physical medical systems and intelligent information systems are not integrated.This study introduces the Advanced Cardiac Twin(ACT)model integrated with Artificial Neural Network(ANN)to handle real-time monitoring,decision-making,and crisis prediction.THINGSPEAK is used to create an IoT platform that accepts patient sensor data.Importing these data sets into MATLAB allows display and analysis.A myocardial ischemia research examined Health Condition Tracking’s(HCT’s)potential.In the case study,75%of the training sets(Xt),15%of the verified data,and 10%of the test data were used.Training set feature values(Xt)were given with the data.Training,Validation,and Testing accuracy rates were 99.9%,99.9%,and 99.9%,respectively.General research accuracy was 99.9%.The proposed HCT system and Artificial Neural Network(ANN)model gather historical and real-time data to manage and anticipate cardiac issues.
文摘Developments in new-generation information technology have enabled Digital Twins to reshape the physical world into a virtual digital space and provide technical support for constructing the Metaverse.Metaverse objects can be at the micro-,meso-,or macroscale.The Metaverse is a complex collection of solid,liquid,gaseous,plasma,and other uncertain states.Additionally,the Metaverse integrates tangibles with social relations,such as interpersonal(friends,partners,and family)and social relations(ethics,morality,and law).This review introduces some principles and laws,such as broken windows theory,small-world phenomenon,survivor bias,and herd behavior,for constructing a Digital Twins model for social relations.Therefore,from multiple perspectives,this article reviews mappings of tangible and intangible real-world objects to the Metaverse using the Digital Twins model.
文摘The industrial Internet of Things (IIoT) is an important engine for manufacturingenterprises to provide intelligent products and services. With the development of IIoT, moreand more attention has been paid to the application of ultra-reliable and low latency communications(URLLC) in the 5G system. The data analysis model represented by digital twins isthe core of IIoT development in the manufacturing industry. In this paper, the efforts of3GPP are introduced for the development of URLLC in reducing delay and enhancing reliability,as well as the research on little jitter and high transmission efficiency. The enhancedkey technologies required in the IIoT are also analyzed. Finally, digital twins are analyzedaccording to the actual IIoT situation.
基金supported by 2019 Industrial Internet Innovation Development Project of Ministry of Industry and Information Technology of P.R. China “Comprehensive Security Defense Platform Project for Industrial/Enterprise Networks”Research on Key Technologies of wireless edge intelligent collaboration for industrial internet scenarios (L202017)+1 种基金Natural Science Foundation of China, No.61971050BUPT Excellent Ph.D. Students Foundation (CX2020214)。
文摘To realize high-accuracy physical-cyber digital twin(DT)mapping in a manufacturing system,a huge amount of data need to be collected and analyzed in real-time.Traditional DTs systems are deployed in cloud or edge servers independently,whilst it is hard to apply in real production systems due to the high interaction or execution delay.This results in a low consistency in the temporal dimension of the physical-cyber model.In this work,we propose a novel efficient edge-cloud DT manufacturing system,which is inspired by resource scheduling technology.Specifically,an edge-cloud collaborative DTs system deployment architecture is first constructed.Then,deterministic and uncertainty optimization adaptive strategies are presented to choose a more powerful server for running DT-based applications.We model the adaptive optimization problems as dynamic programming problems and propose a novel collaborative clustering parallel Q-learning(CCPQL)algorithm and prediction-based CCPQL to solve the problems.The proposed approach reduces the total delay with a higher convergence rate.Numerical simulation results are provided to validate the approach,which would have great potential in dynamic and complex industrial internet environments.
文摘Background All recent technological findings can be collectively used to strengthen the industrial Internet of things(IIoT)sector.The novel technology of multi-access edge computing or mobile edge computing(MEC)and digital twins have advanced rapidly in the industry.MEC is the middle layer between mobile devices and the cloud,and it provides scalability,reliability,security,efficient control,and storage of resources.Digital twins form a communication model that enhances the entire system by improving latency,overhead,and energy consumption.Methods The main focus in this study is the biggest challenges that researchers in the field of IIoT have to overcome to obtain a more efficient communication environment in terms of technology integration,efficient energy and data delivery,storage spaces,security,and real-time control and analysis.Thus,a distributed system is established in a local network,in which several functions operate.In addition,an MEC-based framework is proposed to reduce traffic and latency by merging the processing of data generated by IIoT devices at the edge of the network.The critical parts of the proposed IIoT system are evaluated by using emulation software.Results The results show that data delivery and offloading are performed more efficiently,energy consumption and processing are improved,and security,complexity,control,and reliability are enhanced.Conclusions The proposed framework and application provide authentication and integrity to end users and IoT devices.
文摘Background Digital twins are virtual representations of devices and processes that capture the physical properties of the environment and operational algorithms/techniques in the context of medical devices and tech-nologies.Digital twins may allow healthcare organizations to determine methods of improving medical processes,enhancing patient experience,lowering operating expenses,and extending the value of care.During the present COVID-19 pandemic,various medical devices,such as X-rays and CT scan machines and processes,are constantly being used to collect and analyze medical images.When collecting and processing an extensive volume of data in the form of images,machines and processes sometimes suffer from system failures,creating critical issues for hospitals and patients.Methods To address this,we introduce a digital-twin-based smart healthcare system in-tegrated with medical devices to collect information regarding the current health condition,configuration,and maintenance history of the device/machine/system.Furthermore,medical images,that is,X-rays,are analyzed by using a deep-learning model to detect the infection of COVID-19.The designed system is based on the cascade recurrent convolution neural network(RCNN)architecture.In this architecture,the detector stages are deeper and more sequentially selective against small and close false positives.This architecture is a multi-stage extension of the RCNN model and sequentially trained using the output of one stage for training the other.At each stage,the bounding boxes are adjusted to locate a suitable value of the nearest false positives during the training of the different stages.In this manner,the arrangement of detectors is adjusted to increase the intersection over union,overcoming the problem of overfitting.We train the model by using X-ray images as the model was previously trained on another dataset.Results The developed system achieves good accuracy during the detection phase of COVID-19.The experimental outcomes reveal the efficiency of the detection architecture,which yields a mean average precision rate of 0.94.
文摘We are in the midst of a significant transformation regarding the way we produce products and deliver services thanks to the digitization of manufacturing and new connected supply-chains and co-creation systems.This article elaborates Digital Twins Approach to the current challenges of knowledge management when Industry 4.0 is emerging in industries and manufacturing.Industry 4.0 approach underlines the importance of Internet of Things and interactions between social and physical systems.Internet of Things(and also Internet of Services and Internet of Data)are new Internet infrastructure that marries advanced manufacturing techniques and service architectures with the I-o-T,I-o-S,and I-o-D to create manufacturing systems that are not only interconnected,but communicate,analyze,and use information to drive further intelligent action back in the physical world.This paper identifies four critical domains of synergy challenge:(1)man-to-man interaction;(2)man-to-machine interaction;(3)machine-to-man interaction;and finally(4)machine-to-machine interaction.Key conclusion is that new knowledge management challenges are closely linked to the challenges of synergic interactions between these four key interactions and accurate measurements of synergic interaction.
文摘Background Digital twins offer rich potential for exploration in virtual reality(VR).Using interactive molecular simulation approaches,they enable a human operator to access the physical properties of molecular objects and to build,manipulate,and study their assemblies.Integrative modeling and drug design are important applications of this technology.Methods In this study,head-mounted virtual reality displays connected to mole-cular simulation engines were used to create interactive and immersive digital twins.They were used to perform tasks relevant to specific use cases.Results Three areas were investigated,including model building,rational design,and tangible models.Here,we report several membrane-embedded systems of ion channels,viral com-ponents,and artificial water channels.We were able to improve and create molecular designs based on digital twins.Conclusions The molecular application domain offers great opportunities,and most of the technical and tech-nological aspects have been solved.Wider adoption is expected once the onboarding of VR is simplified and the technology gains wider acceptance.
基金the National Natural Science Foundation of China(51875517,51490663 and 51821093)and Key Research and Development Program of Zhejiang Province(2017C01045).
文摘Product assembly simulation is considered as one of the key technologies in the process of complex product design and manufacturing.Virtual assembly realizes the assembly process design,verification,and optimization of complex products in the virtual environment,which plays an active and effective role in improving the assembly quality and efficiency of complex products.In recent years,augmented reality(AR)and digital twin(DT)technology have brought new opportunities and challenges to the digital assembly of complex products owing to their characteristics of virtual reality fusion and interactive control.This paper expounds the concept and connotation of AR,enumerates a typical AR assembly system structure,analyzes the key technologies and applications of AR in digital assembly,and notes that DT technology is the future development trend of intelligent assembly research.
基金Supported by the University of Bologna Alma Attrezzature 2017 grantAEFFE S.p.a.+1 种基金the Golinelli FoundationElettrotecnica Imolese S.U.R.L.。
文摘Background The advancements of Artificial Intelligence,Big Data Analytics,and the Internet of Things paved the path to the emergence and use of Digital Twins(DTs)as technologies to“twin”the life of a physical entity in different fields,ranging from industry to healthcare.At the same time,the advent of eXtended Reality(XR)in industrial and consumer electronics has provided novel paradigms that may be put to good use to visualize and interact with DTs.XR technologies can support human-to-human interactions for training and remote assistance and could transform DTs into collaborative intelligence tools.Methods We here present the Human Collaborative Intelligence empowered Digital Twin framework(HCLINT-DT)integrating human annotations(e.g.,textual and vocal)to allow the creation of an all-in-one-place resource to preserve such knowledge.This framework could be adopted in many fields,supporting users to learn how to carry out an unknown process or explore others’past experiences.Results The assessment of such a framework has involved implementing a DT supporting human annotations,reflected in both the physical world(Augmented Reality)and the virtual one(Virtual Reality).Con-clusions The outcomes of the interface design assessment confirm the interest in developing HCLINT-DT-based applications.Finally,we evaluated how the proposed framework could be translated into a manufacturing context.
文摘The emerging field of City Digital Twins has advanced in recent years with the help of digital infrastructure and technologies connected to the Internet of Things(IoT).However,the evolution of this field has been so fast that a gap has opened in relation to systematic reviews of the relevant literature and the maturation of City Digital Twins on an urban scale.Our work bridges this gap by highlighting maturity in the field.We conducted a systematic literature review with bibliometric and content analysis of 41 selected papers published in Web of Science and Scopus data-bases,covering five areas:data types and sources,case studies,applied technologies and methods,maturity spectrum,and appli-cations.Based on maturity indicators,the majority of the reviewed studies(90%)were at initial to medium stages of maturity(up to element 3),most of them focused on 3D modelling,monitoring and visualisation.However,digital twins cannot be limited to 3D models,monitoring and visualisation,for they can be developed to include two-directional interactions between humans and com-puters.Such a high level of maturity,which was not found in the reviewed studies,requires advanced technologies and methods such as cloud computing,artificial intelligence,BIM and GIS.We also found that further studies are essential if the field is to handle the complex urban challenges of multidisciplinary digital twins.While City Digital Twins extend by definition beyond mere 3D city modelling,some studies involving 3D city models still refer to their subjects as City Digital Twins.Among the research gaps we identified,we’d like to highlight the need for near-real-time data analytics algorithms,which could furnish City Digital Twins with big data insights.Other opportunities include public participation capabilities to increase social collaboration,integrating BIM and GIS technologies and improving storage and computation infrastructure.
文摘The transition to low carbon energy systems poses challenges in terms of energy efficiency.In building refur-bishment projects,efficient technologies such as smart controls and heat pumps are increasingly being used as a substitute for conventional technologies with the aim of reducing carbon emissions and determining operational energy and cost savings,together with other benefits.Measured building performance,however,often reveals a significant gap between the predicted energy use(design stage)and actual energy use(operation stage).For this reason,lean and interpretable digital twins are needed for building energy monitoring aimed at persistence of savings and continuous performance improvement.In this research,interpretable regression models are built with data at multiple temporal resolutions(monthly,daily and hourly)and seamlessly integrated with the goal of verifying the performance improvements due to Smart thermostatic radiator valves(TRVs)and gas absorption heat pumps(GAHPs)as well as giving insights on the performance of the building as a whole.Further,as part of modelling research,time of week and temperature(TOWT)approach is reformulated and benchmarked against its original implementation.The case study chosen is Hale Court sheltered housing,located in the city of Portsmouth(UK).This building has been used for the field-testing of innovative technologies such as TRVs and GAHPs within the EU Horizon 2020 project THERMOSS.The results obtained are used to illustrate possible extensions of the use of energy signature modelling,highlighting implications for energy management and innovative building technologies development.
基金This research is supported by National Natural Science Foundation of China(No.61902158).
文摘The concept of the digital twin,also known colloquially as the DT,is a fundamental principle within Industry 4.0 framework.In recent years,the concept of digital siblings has generated considerable academic and practical interest.However,academia and industry have used a variety of interpretations,and the scientific literature lacks a unified and consistent definition of this term.The purpose of this study is to systematically examine the definitional landscape of the digital twin concept as outlined in scholarly literature,beginning with its origins in the aerospace domain and extending to its contemporary interpretations in the manufacturing industry.Notably,this investigationwill focus on the research conducted on Industry 4.0 and smartmanufacturing,elucidating the diverse applications of digital twins in fields including aerospace,intelligentmanufacturing,intelligent transportation,and intelligent cities,among others.
