A Holonic Human Cyber-Physical System in Healthcare.

Mechanical and Mechatronic Engineerin

Smart Meter Development Using Digital Twin Technology for Green Energy Distribution Optimization

This study proposes a digital twin (DT) approach and technical framework for smart meters to solve potential implementation and development problems and adapt to the new energy revolution trend and increase smart grid network security. DT models were deployed in the cloud and edge using a smart meter DT demonstration system. This paper evaluates the DT system's communication performance in real-time smart grid application through three dimensions: remote application service for smart grid user side, P2P transaction on the user side, and user real-time request service. This study's container-based decision tree strategy for smart meters meets the smart grid's real-time communication requirements for user-side applications

Enactive manufacturing through cyber-physical systems: a step beyond cognitive manufacturing

Cognitive manufacturing, as a paradigm for providing intelligence to manufacturing systems and enabling interaction with operators presents limitations. Manufacturing system requires to be adaptive to machine tools, manufacturing environments and operators. In this line, the enactive approach to cognitive science provides a paradigm for the design of new biologically inspired cognitive architectures. Likewise, the advantages of Key Enabling Technologies and the concept of Industry 4.0 reveal new opportunities for increasing industrial innovation and developing sustainable industrial environments. These technologies are appropriated to overcome the limitations of cognitive manufacturing, because they can achieve the integration of physical and digital systems focused on cyber-physical systems. In this work, an architecture for the sustainable development of enactive manufacturing systems based on holonic paradigm is proposed and its main associated informational model is described

A Review on MPC Based Self Recovering Intelligent Advance Meter for Smart Grid: Scheme and Challenges

The Model Predict Control (MPC) based Intelligent Advance Metering (IAM) is a core maneuver of future smart grids (SG). SG is the advanced generation of electric power and utility system that improve operation technology (OT) and information technology (IT) to provide nonstop, self-recovery, self-configuration, low-cost, and security-based electricity to the consumer in real-time. Smart metering (SM) allows SG to connect the electric, gas, and oil utilities through sensors. Power plants, consumers, and utility companies will be received real-time wireless control IAM with fifth generation (5G) network technology. The aim of 5G network technology is to enable power grid digitalization (PGD) and facilitate the (IOT) Internet of Things for the future advance SG with benefits such as high-rate public safety, low latency, ultra-high speed, large number of connectivity, and reliability. In this paper, we analyze future predictions about energy needs by using MPC, fast self-recovery system, self-configuration, and upgradation, better performance of service provider, faster power connecting after an outage, control electric theft, minimize electric leakage, a large number of wireless connecting of IAM home-based, and real-time monitoring via human machine interface (HMI) and for customer end IAM operation over 5G networks to reduce billing price, reduce meter cost, lower outage cost, and as well as personalized control over electricity consumption and future challenge in this area

Review and perspectives on driver digital twin and its enabling technologies for intelligent vehicles

Digital Twin (DT) is an emerging technology and has been introduced into intelligent driving and transportation systems to digitize and synergize connected automated vehicles. However, existing studies focus on the design of the automated vehicle, whereas the digitization of the human driver, who plays an important role in driving, is largely ignored. Furthermore, previous driver-related tasks are limited to specific scenarios and have limited applicability. Thus, a novel concept of a driver digital twin (DDT) is proposed in this study to bridge the gap between existing automated driving systems and fully digitized ones and aid in the development of a complete driving human cyber-physical system (H-CPS). This concept is essential for constructing a harmonious human-centric intelligent driving system that considers the proactivity and sensitivity of the human driver. The primary characteristics of the DDT include multimodal state fusion, personalized modeling, and time variance. Compared with the original DT, the proposed DDT emphasizes on internal personality and capability with respect to the external physiological-level state. This study systematically illustrates the DDT and outlines its key enabling aspects. The related technologies are comprehensively reviewed and discussed with a view to improving them by leveraging the DDT. In addition, the potential applications and unsettled challenges are considered. This study aims to provide fundamental theoretical support to researchers in determining the future scope of the DDT system

The Operator 4.0: Human Cyber-Physical Systems & Adaptive Automation towards Human-Automation Symbiosis Work Systems

A vision for the Operator 4.0 is presented in this paper in the context of human cyber-physical systems and adaptive automation towards human-automation symbiosis work systems for a socially sustainable manufacturing workforce. Discussions include base concepts and enabling technologies for the development of human-automation symbiosis work systems in Industry 4.0