In the Industry 4.0 model, the integration of Internet of Things (IoT) and Cyber-Physical Systems (CPS) revolutionizes manufacturing processes. Consider a smart factory scenario where all four layers of Industry 4.0 are interconnected and optimized for efficiency.Application Layer (Smart Factory):The smart factory is equipped with advanced sensors and actuators embedded in machinery and production lines.Real-time data collection and analysis enable predictive maintenance and process optimization.Automated workflows manage inventory, production scheduling, and quality control.Cyber-Physical Systems (CPS):CPS components include sensors, actuators, embedded systems, and control algorithms.These systems monitor physical processes, adjust machine parameters, and ensure safety and reliability.CPS coordinates with IoT devices to implement adaptive manufacturing strategies.Internet of Things (IoT):IoT devices such as RFID tags, wearable sensors, and smart tools track assets, monitor environmental conditions, and collect operational data.Cloud-based IoT platforms process massive data streams, apply machine learning algorithms, and facilitate remote monitoring and control.Edge computing devices near production lines provide low-latency processing for time-sensitive applications.Internet Services Layer:Wired and wireless networks connect devices and systems within the smart factory.Cloud and edge computing services support data storage, analytics, and application deployment.Cybersecurity protocols safeguard sensitive information and prevent unauthorized access.Collaboration Between IoT and CPS:The collaboration between IoT and CPS enhances manufacturing capabilities but also introduces certain risks:Benefits:Improved efficiency and productivity through data-driven insights and automation.Enhanced safety measures with real-time monitoring and predictive maintenance.Greater flexibility and adaptability to market demands through agile manufacturing processes.Risks:Cybersecurity vulnerabilities due to increased connectivity and data exchange.Dependency on complex technologies leading to potential system failures or malfunctions.Privacy concerns regarding the collection and usage of sensitive data from IoT devices.In conclusion, the synergistic integration of IoT and CPS in Industry 4.0 facilitates intelligent manufacturing systems but necessitates careful consideration of security and operational challenges.This report provides an overview of a smart factory scenario within the Industry 4.0 framework, highlighting the roles of IoT and CPS components and discussing potential collaborations and risks.

Discuss the importance of the Internet of things in Industry 4.0 with a simple sketch

Which of the following is not the key features and characteristics of the core progress from traditional manufacturing toward Industry 4.0?A.The impact of exponential technologiesB.Produces stronger and lighter materialsC.Horizontal integration through a new generation of global value chain networksD.Vertical networking of smart manufacture schemesE.Through-life engineering across the entire value chain

Introduction to the Special Section:Convergence of Automation Technology,Biomedical Engineering, and Health InformaticsToward the Healthcare 4.0Zhibo Pang , Senior Member, IEEE, Geng Yang , Member, IEEE, Ridha Khedri, Member, IEEE,and Yuan-Ting Zhang, Fellow, IEEEAbstract—Industry 4.0 is spilling out from manufacturingto healthcare. In this article, we provide a brief history andkey enabling technologies of Industry 4.0, and its revolu-tion in healthcare—Healthcare 4.0—and its reshaping of thelandscape of the entire healthcare value chain. We discussthe shift in the system design paradigm from open, small,and single loop to closed, large, and multiple loops. We pro-vide the example of a Caregiving Home, and discuss emerg-ing research topics and challenges, including healthcare bigdata, automated medical production, healthcare robotics,and human–robot symbiosis. Relevant papers published inthis special section are also presented.Index Terms—Caregiving Home, convergence, Health-care 4.0, healthcare robotics, human–robot symbiosis,Industry 4.0.I. I NTRODUCTIONTHE FOURTH REVOLUTION of industry (Industry 4.0)is reshaping all the segments of industries. Pulled bygrand social challenges, automation technologies are dramat-ically “spilling out” from traditional scenarios, such as factoriesand workshops, to everyday life. The traditional research areasof biomedical engineering and health informatics for the agingThis work was supported in part by Open Foundation of the StateKey Laboratory of Fluid Power and Mechatronic Systems at ZhejiangUniversity under the Grant GZKF-201703, in part by the FundamentalResearch Funds for the Central Universities, in part by the Open Foun-dation of the State Key Laboratory of Fluid Power and Mechatronic Sys-tems, in part by the Science Fund for Creative Research Groups of theNational Natural Science Foundation of China under Grant 51521064, inpart by NSFC-Zhejiang Joint Fund for the Integration of Industrializationand Informatization under Grant U1509204, and in part by the NaturalSciences and Engineering Research Council of Canada (NSERC) underGrant RGPIN 2014-06115. (Corresponding author: Geng Yang.)Z. Pang is with the ABB AB, Corporate Research, V ¨aster ˚as 72178,Sweden (e-mail: [email protected]).G. Yang is with the State Key Laboratory of Fluid Power and Mecha-tronic Systems, School of Mechanical Engineering, Zhejiang University,Hangzhou 310027, China (e-mail: [email protected]).R. Khedri is with the Department of Computing and Software, Facultyof Engineering, McMaster University, Hamilton, ON L8S 4L8, Canada(e-mail: [email protected]).Y.-T. Zhang is with the Department of Mechanical and Biomedical En-gineering, City University of Hong Kong, Hong Kong (e-mail: [email protected]).Digital Object Identifier 10.1109/RBME.2018.2848518population have gained unprecedented interest from the automa-tion industry. The research landscape in both academia and in-dustry is significantly reshaped with the cross-disciplinary syn-ergy of expertise and the deep convergence of automation tech-nology, biomedical engineering, and health informatics. Thistrend has been driving the rapid development of health engi-neering, an emerging interdisciplinary field for the predictive,preventive, precise, and personalized medicine. More powerfultools from process or factory automation, such as distributedcontrol systems and robotics, are penetrating into biomedicineand healthcare applications [1], [2]. For example, research ac-tivities related to robotics for biomedicine and healthcare havebeen largely intensified in the recent years [3], [4].The goal of this special section is threefold: 1) to reviewthe advancement in the convergence of automation technology,biomedical engineering, and health informatics; 2) to identifythe gap between the state-of-the-art of research and industrialdemands; and 3) to envision the directions for future research.The application scenarios can cover single or multiple scenariosof health engineering, such as primary care, preventive care,predictive technologies, hospitalization, home care, and occu-pational health. We focus on the cross-disciplinary approaches,solutions, and initiatives rather than single disciplinary ones.II. I MPACT OF I NDUSTRY 4.0 TO HEALTHCAREA. Industry 4.0 Basics and Key TechnologiesIndustry 4.0 (also sometimes spelled as Industrie 4.0) is avision for a new industrial revolution put forward by the Com-munication Promoters Group of the Industry–Science ResearchAlliance to further enhance Germsany’s manufacturing industry[5]. Several other countries, such as China and India, followedby articulating similar visions. The current advances in the fol-lowing areas trigger the Industry 4.0 vision.Cyber-physical systems (CPS) refers to the area where sys-tems incorporate computation and physical processes. Thesophistication that is reached in harnessing machine controlthrough computing provides unprecedented efficiency in thephysical processes and gives levels of performance neverreached before. As early as the 1970s, we started to designsystems where we embedded the computing driven control into

Decentralization entails having a more agile,flexible, and autonomous approach to productionvia decentralized intelligence to address the com-plexity of the integrated processes [14]. Under thisprinciple, smart components of the Industry 5.0ecosystem should operate autonomously andmake independent yet informed decisions whennecessary [61]. Decentralization relies on data trans-parency and the interconnectedness of objects andpeople across value chains. Thus, IoE, cloud data,and C-CPS are crucial to decentralization as theystreamline the monitoring and control of the physi-cal world based on which decentralized decisionsare made [62].

Throughout this successfully enduring yet turbulent history, today fashion industry approaches the4.0 age with many learned lessons and a great potential of being transformed into a more sustainableand truly customer-driven sector.The following sections will introduce the main paradigmatic changes which are affecting fashion,embracing the concept of I4.0 as the combination of “smart factories” + “smart networks” + “smartproducts”. As already anticipated, this synthesis into a tripartite model can be considered an emergingvision coming from the study of architectural models which are able to exploits all potentials offeredby current I4.0 paradigm (Platform 4.0, 2015).Based on this assumption, Figure 2 integrates into this triple structure all major processes, businessunits and components charactering fashion industry. Therefor the “Factory” sphere is populated withPrototyping and collection Sampling, Production and Logistic; the Networks sphere is populated withSupply-chains Management, Retail and Communication; the Products sphere is populated withPackaging, Products and their Surplus Management and finally, Research, Design and ProductDevelopment, centrally positioned, function as the ideal connection among the three components.Figure 2 framework then connects the main technologies and applications supporting 4.0 modelimplementation to each sphere. As the nature of current technologies is open and multipurpose, theaim of the model is to point out the specific relevance of certain set of solutions in enabling 4.0innovation with respect to specific processes and business units, knowing that almost all of them canfind application in any sphere. As, for example, Digital Manufacturing, that is used for severalapplications in speeding up the Sampling and Prototyping processes within the production sphere;but it is already showing a great potential in what is a futuristic model of distributed manufacturing,where it will be a diffused networks to receive manufacturing data and produce the right quantity ofgoods close to each markets. Or, for example, Internet of Things (IoT) technology, that is alreadytransforming Production in many advanced factories where sensors, robots and humans areexchanging data; but it is already finding application in Retail where sensors in spaces arecommunicating with customers’ mobile devices or with respect to products, tracking their lifecycle.Figure 2 model is completed by linking Smart Factories, Networks and Products, characterized bytheir key processes, business units and components and related set of set technologies, to six designprinciples –Interoperability, Virtualization, Decentralization, Modularity, Service Orientation, RealTime Capability – which can enable the implementation of I4.0 eco-system (Pentek, 2016).The integrated architectural model represented in Figure 2 can support a deeper analysis of what isemerging within the fashion industry as examples and practices innovating the field, but also to detectcriticalities and slowness of adoption within this business. Using it as a reference, the followingsections will try to provide few insights on the current state of the art and major trends of the "FourthIndustrial Revolution", possibly identifying its impacts on the textile and apparel industry, usingdescriptive cases and examples