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The purpose of this paper is to investigate the current situation of China's local valve industry, the maturity of intelligent manufacturing and the way to promote intellectual development.

Firstly, a macro analysis of the valve market environment from the domestic and international perspective was conducted. Secondly, online surveys and in-depth interviews were administered to understand the current status of IM development and future development goals. Finally, case studies were conducted to demonstrate whether the hypothesis of the development approach is feasible.

This study finds that the overall maturity level of the local valve industry is still in the planning stage since the local valve industry lacks concentration and is relatively scattered. In addition, the feasible development approach is dependent on smart devices to improve production efficiency, ensure quality management and effectively control costs.

The research is conducted and focused on the Yangtze River Delta region instead of the whole country, and the size of the sample is small. Therefore, there may be some characteristics omitted in the analysis.

Manufacturers can upgrade to smart manufacturing through intelligent software platforms in order to complete an automatic interaction of data and devices. In addition, manufacturers should complete cross-regional collaborative development through the industrial Internet of things.

There is little or none of research work completed for the development strategy of the valve industry internationally. Therefore, research findings of this area can provide a fundamental understanding of China's local valve industry and contribute to the existing knowledge.

Purpose: With this study, the authors aim to highlight the application of machine learning in smart appliances used in our day-to-day activities. This chapter focuses on analysing intelligent devices used in our daily lives to examine various machine learning models that can be applied to make an appliance ‘intelligent’ and discuss the different pros and cons of the implementation.

Methodology: Most smart appliances need machine learning models to decrypt the meaning and functioning behind the sensor’s data to execute accurate predictions and come to appropriate conclusions.

Findings: The future holds endless possibilities for devices to be connected in different ways, and these devices will be in our homes, offices, industries and even vehicles that can connect each other. The massive number of connected devices could congest the network; hence there is necessary to incorporate intelligence on end devices using machine learning algorithms. The connected devices that allow automatic control appliance driven by the user’s preference would avail itself to use the Network to communicate with devices close to its proximity or use other channels to liaise with external utility systems. Data processing is facilitated through edge devices, and machine learning algorithms can be applied.

Significance: This chapter overviews smart appliances that use machine learning at the edge. It highlights the effects of using these appliances and how they raise the overall living standards when smarter cities are introduced by integrating such devices.

The purpose of this paper is to ensure the anonymity and security of health data and improve the integrity and authenticity among patients, doctors and insurance providers. Simulation and validation algorithms are proposed in this work to ensure the proper implementation of the distributed system to secure and manage healthcare data. The author also aims to examine the methodology of Wireless Body Area Networks and how it contributes to the health monitoring system.

Wireless Body Area Network (WBAN) plays an important role in patient health data monitoring. In this paper, a novel framework is designed and proposed to generate data by the sensor machines and be stored in the cloud, and the transactions can be secured by blockchain. DNA cryptography is used in the framework to encrypt the hashes of the blocks. The proposed framework will ensure the anonymity and security of the health data and improve the integrity and authenticity among the patients, doctors and insurance providers.

Cloud Computing and Distributed Networking have transformed the IT industry and their amalgamation with intelligent systems would revolutionize the Healthcare Industry. The data being generated by devices is huge and storing it in the cloud environment would be a better decision. However, the privacy and security of healthcare data are still a concern because medical data is very confidential and desires to be safe and secure. The blockchain is a promising distributed network that ensures the security aspect of the data and makes the transactions authentic and transparent. In this work, the data is collected using various sensor devices and is transmitted to the cloud through the WBAN via the blockchain network.

In this paper, a framework for securing and managing the healthcare data generated by intelligent systems is proposed. As the data generated by these devices are heterogeneous and huge in nature, the cloud environment is chosen for its storage and analysis. Therefore, the transactions to and from the cloud are secured by using the blockchain-based distributed network.

The target end-users of our system are the patients to keep themselves informed and healthy, healthcare providers to monitor the conditions of their patients virtually, and the health insurance providers to have a track of the history of the patients, so that no fraudulent claims can be made.

The target end-users of our system are the patients for keeping themselves informed and healthy, healthcare providers for monitoring the conditions of their patients virtually and the health insurance providers to have a track of the history of the patients, so that no fraudulent claims can be made.

Questioning gender is about taking an active, critical role in the technological design of our daily behaviour. It is a deconstruction of the oppositions that exist in the discourses of Ambient Intelligence designers, the ICT industry and computer scientists. What underlies the assumption that Ambient Intelligence will, by disappearing into our environment, bring humans both an easy and entertaining life? The gender perspective can uncover power relations within the promotion and realisation of Ambient Intelligence that satisfy an obvious wish for a technological heaven. The deconstruction of the promise of progress and a better life reveals what is overvalued, what is undervalued and what is ignored. This paper is a deconstruction of the view, currently prevalent in the discourses of Ambient Intelligence; a view of humans and the way they live. A view that will influence the way women and men will be allowed to construct their lives.

The purpose of this paper is to provide an in-depth overview of the security requirements and challenges for Internet of Things (IoT) and discuss security solutions for various enabling technologies and implications to various applications.

Security requirements and solutions are analysed based on a four-layer framework of IoT on sensing layer, network layer, service layer, and application layer. The cross-layer threats are analysed followed by the security discussion for the enabling technologies including identification and tracking technologies, WSN and RFID, communication, networks, and service management.

IoT calls for new security infrastructure based on the new technical standards. As a consequence, new security design for IoT shall pay attention to these new standards. Security at both the physical devices and service-applications is critical to the operation of IoT, which is indispensable for the success of IoT. Open problems remain in a number of areas, such as security and privacy protection, network protocols, standardization, identity management, trusted architecture, etc.

The implications to various applications including supervisory control and data acquisition, enterprise systems, social IoT are discussed. The paper will serve as a starting point for future IoT security design and management. The security strategies for IoT should be carefully designed by managing the tradeoffs among security, privacy, and utility to provide security in multi-layer architecture of IoT.

The paper synthesizes the current security requirements for IoT and provides a clear framework of security infrastructure based on four layers. Accordingly, the security requirements and potential threats in the four-layer architecture are provided in terms of general devices security, communication security, network security, and application security.

This paper aims to study different possibilities for implementing easy-to-use and cost-effective micro-systems to detect and trace expelled gases from rotten food. The paper covers various radio-frequency identification (RFID) technologies and gas sensors as the two promoting feasibilities for the tracing of packaged food. Monitoring and maintaining quality and safety of food in transport and storage from producer to consumer are the most important concerns in food industry. Many toxin gases, even in parts per billion ranges, are produced from corrupted and rotten food and can endanger the consumers’ health. To overcome the issues, intelligent traceability of food products, specifically the packaged ones, in terms of temperature, humidity, atmospheric conditions, etc., has been paid attention to by many researchers.

Food poisoning is a serious problem that affects thousands of people every year. Poisoning food must be recognized early to prevent a serious health problem.

Contaminated food is usually detectable by odor. A small gas sensors and low-cost tailored to the type of food packaging and a communication device for transmitting alarm output to the consumer are key factors in achieving intelligent packaging.

Conducting polymer composite, intrinsically conducting polymer and metal oxide conductivity gas sensors, metal–oxide–semiconductor field-effect transistor (MOSFET) gas sensors offer excellent discrimination and lead the way for a new generation of “smart sensors” which will mould the future commercial markets for gas sensors.

Small size, low power consumption, short response time, wide operating temperature, high efficiency and small area are most important features of introduced system for using in package food.

Describes the evolution of industrial control systems from PLC to PC based systems including the use of the DeviceNet fieldbus standard. Also includes a case study of automotive gearbox assembly.

Examines the thirteenth published year of the ITCRR. Runs the whole gamut of textile innovation, research and testing, some of which investigates hitherto untouched aspects. Subjects discussed include cotton fabric processing, asbestos substitutes, textile adjuncts to cardiovascular surgery, wet textile processes, hand evaluation, nanotechnology, thermoplastic composites, robotic ironing, protective clothing (agricultural and industrial), ecological aspects of fibre properties – to name but a few! There would appear to be no limit to the future potential for textile applications.

Introduction: Healthcare facilities have witnessed deterioration, limited employee engagement, and communication gaps due to a lack of wireless technology. The Internet makes work and life quicker and more intelligent. The Internet of Things (IoT) is a scheme of interconnection equipped with unique identifiers in recent years. Artificial intelligence (AI) and IoT advancement allow employees to develop competent and predictive services and solutions in human resource (HR) practices. This chapter has been formulated to summarise and classify the existing research and better understand the past, present, and future of employee engagement by improving IoT interrelated devices in the healthcare industry.

Purpose: This study aims to categorise and overcome the challenges involved in HR practices. Effectively embracing IoT application-connected devices in the healthcare industry can enhance human resources management’s (HRM) role and measure performance assessment to improve employee engagement and productivity.

Methodology: In this study, the authors develop propositions dependent on a theory-based review. A systematic analysis was applied to minimise the challenges of HRM. The subject-related articles from different journal sources, like Scopus, Emerald, Web of Science, Springer, etc., were analysed based on engagement criteria. It was graphically recorded in a collective and informative way to emphasise the review outcomes. The study has presented the positive impacts of AI and IoT on engagement in health care.

Summary: This chapter accumulated theory-based knowledge about healthcare employee engagement and how IoT-based technology like AI can optimise employees’ engagement effectively. Further, it draws comparative benefits for a workforce to execute performance advancements and create future progressive aspects for healthcare employees.