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The animation industry is currently undergoing significant transformations fueled by technological advancements. Emerging technologies such as Artificial Intelligence, Big Data Analytics, Cloud Computing, the Internet of Things, Virtual and Augmented Reality, and Blockchain are reshaping the animation industry's value chain. This paper explores the impact of Industry 4.0 technologies on various stages of the animation industry's value chain, including conceptualization, pre-production, production, post-production, distribution, and consumption. Through a combination of literature review and semi-structured interviews, the paper identifies key capabilities of Industry 4.0 technologies in the animation industry. Subsequently, experts from different countries were engaged to validate and evaluate these capabilities, scoring them based on their importance and effectiveness in production and marketing activities. Analysis of data from 60 experts resulted in the identification of the most critical capabilities, which were categorized into four groups based on their relation to either the production or marketing of animation products. Furthermore, the analysis of questionnaires enabled the development of four scenarios depicting the potential future trajectories of animation companies based on their adoption of Industry 4.0 capabilities. The paper delves deeper into each scenario, elucidating their underlying factors and characteristics. Ultimately, it is predicted that companies leveraging Industry 4.0 technologies for both production and marketing activities will emerge as the leaders of the animation industry. This paper offers valuable insights into the evolving landscape of the animation sector and provides a roadmap for companies seeking to harness the potential of Industry 4.0 advancements for sustained leadership and success. • Industry 4.0 can profoundly transform the animation industry through its production-oriented and marketing-oriented capabilities. • Artificial intelligence can generate facial expressions and lip-sync animations based on audio input or text transcripts. • Big Data Analytics provides the opportunity for personalizing animation products. • Cloud Computing provides new ways of delivering products such as streaming animations. • Digital twins enable animators to visualize and iterate on their designs before production begins. [ABSTRACT FROM AUTHOR]

• Revealing the concept, connotation, and state-of-the-art architecture of HSM. • A comprehensive survey on key enablers and applications of HSM. • Identification of challenges and future research directions towards HSM. • Enhancing the research, implementation, and application of HSM. As businesses started to embrace Industry 4.0, along came the Fifth Industrial Revolution. Industry 5.0 complements the existing Industry 4.0 paradigm for the not-too-distant future by highlighting research and innovation as drivers for a transition to a sustainable, human-centric, and resilient industry. The core values of Industry 5.0 including human-centricity, sustainability, and resilience have prompted formal discussions that manufacturing should be human-centric. Human-centric smart manufacturing (HSM) takes full advantage of human flexibility, machine precision, and new-generation information technologies to construct a super smart, sustainable, and resilient manufacturing system. Nowadays, extensive research on the concept, architecture, enabling technologies, and applications of smart manufacturing have been conducted. However, research on HSM is relatively lacking, yet starting to gain traction rapidly. Hence, this paper primarily carries out a systematic literature review on HSM to identify promising research topics with high potential for further investigations. Firstly, this paper reveals the concept and connotation of HSM, on which the state-of-the-art architecture of HSM is introduced. Then, several promising Industry 4.0 technologies are identified as the key enablers that can continue to support the construction and operation of HSM, where a comprehensive survey and discussion on these technologies are conducted. Thirdly, what's new in HSM applications and how HSM will reshape the entire lifecycle of industrial products are explored. Finally, this paper identifies limitations, barriers, and challenges that will be encountered during the developing, operating, and maintaining HSM, and provides valuable research directions to continuously improve HSM. [ABSTRACT FROM AUTHOR]

• A review of COVID-19 guidelines ensures the need of disruptive technologies. • COVID-19 enforces healthcare system to find alternatives for patients' treatment. • The disruptive technologies used to analyze and to restrict the spread of COVID-19. • The study aids healthcare team to detect the plan of treatment remotely and safely. • The analysis of COVID-19 patients ensures the importance of intelligent framework. This paper describes a framework using disruptive technologies for COVID-19 analysis. Disruptive technologies include high-tech and emerging technologies such as AI, industry 4.0, IoT, Internet of Medical Things (IoMT), big data, virtual reality (VR), Drone technology, and Autonomous Robots, 5 G, and blockchain to offer digital transformation, research and development and service delivery. Disruptive technologies are essential for Industry 4.0 development, which can be applied to many disciplines. In this paper, we present a framework that uses disruptive technologies for COVID-19 analysis. The proposed framework restricts the spread of COVID-19 outbreaks, ensures the safety of the healthcare teams and maintains patients' physical and psychological healthcare conditions. The framework is designed to deal with the severe shortage of PPE for the medical team, reduce the massive pressure on hospitals, and track recovered patients to treat COVID-19 patients with plasma. The study provides oversight for governments on how to adopt technologies to reduce the impact of unprecedented outbreaks for COVID-19. Our work illustrates an empirical case study on the analysis of real COVID-19 patients and shows the importance of the proposed intelligent framework to limit the current outbreaks for COVID-19. The aim is to help the healthcare team make rapid decisions to treat COVID-19 patients in hospitals, home quarantine, or identifying and treating patients with typical cold or flu. [ABSTRACT FROM AUTHOR]

Data-driven models for industrial energy savings heavily rely on sensor data, experimentation data and knowledge-based data. This work reveals that too much research attention was invested in making data-driven models, as supposed to ensuring the quality of industrial data. Furthermore, the true challenge within the Industry 4.0 is with data communication and infrastructure problems, not so significantly on developing modelling techniques. Current methods and data infrastructures for industrial energy savings were comprehensively reviewed to showcase the potential for a more accurate and effective digital twin-based infrastructure for the industry. With a few more development in enabling technologies such as 5G developments, Internet of Things (IoT) standardization, Artificial Intelligence (AI) and blockchain 3.0 utilization, it is but a matter of time that the industry will transition towards the digital twin-based approach. Global government efforts and policies are already inclining towards leveraging better industrial energy efficiencies and energy savings. This provides a promising future for the development of a digital twin-based energy-saving system in the industry. Foreseeing some potential challenges, this paper also discusses the importance of symbiosis between researchers and industrialists to transition from traditional industry towards a digital twin-based energy-saving industry. The novelty of this work is the current context of industrial energy savings was extended towards cutting-edge technologies for Industry 4.0. Furthermore, this work proposes to standardize and modularize industrial data infrastructure for smart energy savings. This work also serves as a concise guideline for researchers and industrialists who are looking to implement advanced energy-saving systems. Image 1 • Various countries transitioning towards Industry 4.0 via industrial analytics and energy savings. • Enabling technologies can lead to the deployment of new industrial data infrastructures. • Advances in digital twins, AI, blockchain and IoT can serve as enabling technologies. • Global policies are inclining towards improving industrial energy efficiency. • Communication between researchers and industrialist is crucial for implementation. [ABSTRACT FROM AUTHOR]

The adoption of emerging technological trends and applications of the Internet of Things (IoT) in the industrial systems is leading towards the development of Industrial IoT (IIoT). IIoT serves as a new vision of IoT in the industrial sector by automating smart objects for sensing, collecting, processing and communicating the real-time events in industrial systems. The major objective of IIoT is to achieve high operational efficiency, increased productivity, and better management of industrial assets and processes through product customization, intelligent monitoring applications for production floor shops and machine health, and predictive and preventive maintenance of industrial equipment. In this paper, we present a new and clear definition of IIoT, which can help the readers to understand the concept of IIoT. We have described the state-of-the-art research efforts in IIoT. Finally, we have highlighted the enabling technologies for IIoT and recent challenges faced by IIoT. [ABSTRACT FROM AUTHOR]