THE Fourth Industrial Revolution has set off a wave of technological innovation. New technologies, such as artificial intelligence, virtual reality, quantum information technology, unmanned technology, and biotechnolo...THE Fourth Industrial Revolution has set off a wave of technological innovation. New technologies, such as artificial intelligence, virtual reality, quantum information technology, unmanned technology, and biotechnology, have sprung up at an unprecedented rate, injecting new impetus into the development of the world economy and bringing the global economy into a new era.展开更多
IN September 2018,artificial intelligence(AI)scientist Dr.Kai-Fu Lee’s new book,AI Superpowers:China,Silicon Valley,and the New World Order,was released around the world.Soon,it was in the bestseller list on The New ...IN September 2018,artificial intelligence(AI)scientist Dr.Kai-Fu Lee’s new book,AI Superpowers:China,Silicon Valley,and the New World Order,was released around the world.Soon,it was in the bestseller list on The New York Times,USA Today,and The Wall Street Journal.展开更多
The ongoing expansion of the Industrial Internet of Things(IIoT)is enabling the possibility of effective Industry 4.0,where massive sensing devices in heterogeneous environments are connected through dedicated communi...The ongoing expansion of the Industrial Internet of Things(IIoT)is enabling the possibility of effective Industry 4.0,where massive sensing devices in heterogeneous environments are connected through dedicated communication protocols.This brings forth new methods and models to fuse the information yielded by the various industrial plant elements and generates emerging security challenges that we have to face,providing ad-hoc functions for scheduling and guaranteeing the network operations.Recently,the large development of SoftwareDefined Networking(SDN)and Artificial Intelligence(AI)technologies have made feasible the design and control of scalable and secure IIoT networks.This paper studies how AI and SDN technologies combined can be leveraged towards improving the security and functionality of these IIoT networks.After surveying the state-of-the-art research efforts in the subject,the paper introduces a candidate architecture for AI-enabled Software-Defined IIoT Network(AI-SDIN)that divides the traditional industrial networks into three functional layers.And with this aim in mind,key technologies(Blockchain-based Data Sharing,Intelligent Wireless Data Sensing,Edge Intelligence,Time-Sensitive Networks,Integrating SDN&TSN,Distributed AI)and improve applications based on AISDIN are also discussed.Further,the paper also highlights new opportunities and potential research challenges in control and automation of IIoT networks.展开更多
Industry 4.0 has become a reality by fusing the Industrial Internet of Things(IIoT)and Artificial Intelligence(AI),providing huge opportunities in the way manufacturing companies operate.However,the adoption of this p...Industry 4.0 has become a reality by fusing the Industrial Internet of Things(IIoT)and Artificial Intelligence(AI),providing huge opportunities in the way manufacturing companies operate.However,the adoption of this paradigm shift,particularly in the field of smart factories and production,is still in its infancy,suffering from various issues,such as the lack of high-quality data,data with high-class imbalance,or poor diversity leading to inaccurate AI models.However,data is severely fragmented across different silos owned by several parties for a range of reasons,such as compliance and legal concerns,preventing discovery and insight-driven IIoT innovation.Notably,valuable and even vital information often remains unutilized as the rise and adoption of AI and IoT in parallel with the concerns and challenges associated with privacy and security.This adversely influences interand intra-organization collaborative use of IIoT data.To tackle these challenges,this article leverages emerging multi-party technologies,privacy-enhancing techniques(e.g.,Federated Learning),and AI approaches to present a holistic,decentralized architecture to form a foundation and cradle for a cross-company collaboration platform and a federated data space to tackle the creeping fragmented data landscape.Moreover,to evaluate the efficiency of the proposed reference model,a collaborative predictive diagnostics and maintenance case study is mapped to an edge-enabled IIoT architecture.Experimental results show the potential advantages of using the proposed approach for multi-party applications accelerating sovereign data sharing through Findable,Accessible,Interoperable,and Reusable(FAIR)principles.展开更多
Part II on Best Practices in Construction 4.0 follows up on the previously published study Part I.This study examines corporate strategies from different angles,defines potential fields of application and works out ex...Part II on Best Practices in Construction 4.0 follows up on the previously published study Part I.This study examines corporate strategies from different angles,defines potential fields of application and works out existing empirical values and trends in the digitization process of the building sector.It highlights the unintended consequences of technological development and offers concrete practical approaches for responsible use.Using the qualitative research method,the study concludes that digital methods,such as Building Information Modelling(BIM)and Digital Twins,and Artificial Intelligence(AI)can add value,significantly reduce resources and increase sustainability.The study is part of a larger primary research on Corporate Digital Responsibility(CDR)in Construction 4.0;it identifies,analyzes and systematically evaluates the pillars of a sustainable digital transformation,especially in the Construction Industry.The holistic,interdisciplinary view of this study aims to provide orientation for small to medium-sized companies(SMEs)developing their individual digital strategy.An outline of the necessary prerequisites but also design options,as they result from the evaluation of expert interviews and literature research,supports companies in the design of Construction 4.0 that is in line with the needs of people,society and the environment and shaping more economically efficient building life cycles.It highlights that digital transformation has also reached the traditionally small-scale AEC industry(small-scale architecture,engineering and construction industry)and catalyzes the variety of innovations.展开更多
文摘THE Fourth Industrial Revolution has set off a wave of technological innovation. New technologies, such as artificial intelligence, virtual reality, quantum information technology, unmanned technology, and biotechnology, have sprung up at an unprecedented rate, injecting new impetus into the development of the world economy and bringing the global economy into a new era.
文摘IN September 2018,artificial intelligence(AI)scientist Dr.Kai-Fu Lee’s new book,AI Superpowers:China,Silicon Valley,and the New World Order,was released around the world.Soon,it was in the bestseller list on The New York Times,USA Today,and The Wall Street Journal.
基金This work was supported by the six talent peaks project in Jiangsu Province(No.XYDXX-012)Natural Science Foundation of China(No.62002045),China Postdoctoral Science Foundation(No.2021M690565)Fundamental Research Funds for the Cornell University(No.N2117002).
文摘The ongoing expansion of the Industrial Internet of Things(IIoT)is enabling the possibility of effective Industry 4.0,where massive sensing devices in heterogeneous environments are connected through dedicated communication protocols.This brings forth new methods and models to fuse the information yielded by the various industrial plant elements and generates emerging security challenges that we have to face,providing ad-hoc functions for scheduling and guaranteeing the network operations.Recently,the large development of SoftwareDefined Networking(SDN)and Artificial Intelligence(AI)technologies have made feasible the design and control of scalable and secure IIoT networks.This paper studies how AI and SDN technologies combined can be leveraged towards improving the security and functionality of these IIoT networks.After surveying the state-of-the-art research efforts in the subject,the paper introduces a candidate architecture for AI-enabled Software-Defined IIoT Network(AI-SDIN)that divides the traditional industrial networks into three functional layers.And with this aim in mind,key technologies(Blockchain-based Data Sharing,Intelligent Wireless Data Sensing,Edge Intelligence,Time-Sensitive Networks,Integrating SDN&TSN,Distributed AI)and improve applications based on AISDIN are also discussed.Further,the paper also highlights new opportunities and potential research challenges in control and automation of IIoT networks.
文摘Industry 4.0 has become a reality by fusing the Industrial Internet of Things(IIoT)and Artificial Intelligence(AI),providing huge opportunities in the way manufacturing companies operate.However,the adoption of this paradigm shift,particularly in the field of smart factories and production,is still in its infancy,suffering from various issues,such as the lack of high-quality data,data with high-class imbalance,or poor diversity leading to inaccurate AI models.However,data is severely fragmented across different silos owned by several parties for a range of reasons,such as compliance and legal concerns,preventing discovery and insight-driven IIoT innovation.Notably,valuable and even vital information often remains unutilized as the rise and adoption of AI and IoT in parallel with the concerns and challenges associated with privacy and security.This adversely influences interand intra-organization collaborative use of IIoT data.To tackle these challenges,this article leverages emerging multi-party technologies,privacy-enhancing techniques(e.g.,Federated Learning),and AI approaches to present a holistic,decentralized architecture to form a foundation and cradle for a cross-company collaboration platform and a federated data space to tackle the creeping fragmented data landscape.Moreover,to evaluate the efficiency of the proposed reference model,a collaborative predictive diagnostics and maintenance case study is mapped to an edge-enabled IIoT architecture.Experimental results show the potential advantages of using the proposed approach for multi-party applications accelerating sovereign data sharing through Findable,Accessible,Interoperable,and Reusable(FAIR)principles.
文摘Part II on Best Practices in Construction 4.0 follows up on the previously published study Part I.This study examines corporate strategies from different angles,defines potential fields of application and works out existing empirical values and trends in the digitization process of the building sector.It highlights the unintended consequences of technological development and offers concrete practical approaches for responsible use.Using the qualitative research method,the study concludes that digital methods,such as Building Information Modelling(BIM)and Digital Twins,and Artificial Intelligence(AI)can add value,significantly reduce resources and increase sustainability.The study is part of a larger primary research on Corporate Digital Responsibility(CDR)in Construction 4.0;it identifies,analyzes and systematically evaluates the pillars of a sustainable digital transformation,especially in the Construction Industry.The holistic,interdisciplinary view of this study aims to provide orientation for small to medium-sized companies(SMEs)developing their individual digital strategy.An outline of the necessary prerequisites but also design options,as they result from the evaluation of expert interviews and literature research,supports companies in the design of Construction 4.0 that is in line with the needs of people,society and the environment and shaping more economically efficient building life cycles.It highlights that digital transformation has also reached the traditionally small-scale AEC industry(small-scale architecture,engineering and construction industry)and catalyzes the variety of innovations.
