Smart manufacturing, preventive maintenance, and the distribution of water are just a few of the numerous operations and procedures that the internet of things (IoT) has made feasible. This approach has led to the development of cyber-physical humancentered systems (CPHSs), which leverage operator capabilities to assist complicated manufacturing processes in achieving their goals of adaptability, sustainability, and human-centricity. The suggested CPHS employs smart mist computing nodes and hybrid edge computing architecture to assess thermal pictures and mitigate industrial security concerns. The conducted research indicates that the suggested CPHS methods might recognise human presence in the chosen real-world scenario far too quickly and accurately (in maximum of twelve ms with 98.89% accuracy) using devices with low power (a Raspberry Pi 3B). The research ends with some recommendations to assist managers and developers in the future in overcoming the difficulties associated with implementing the forthcoming wave of CPHSs for intelligent and eco-friendly manufacturing.
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Industry can now create complex circular supply chains and competitive, innovative business models thanks to the current digital transformation. However, this shift also has a lot of ramifications for sustainability because the information and communications technology (ICT) industry has a significant impact on the environment. The objectives that must be fulfilled in order to bring the principles of the circular economy to reality are outlined in the UN Agenda for Sustainable Development (Assembly, U. G. 2015). To do this, solutions must be provided in a way that is sustainable over their entire life cycle. The (IoT, edge computing, and artificial intelligence (AI) are the three main technologies that enable these kinds of sustainable digital revolutions that are moving towards a smart circular economy.
According to Yao et al. (2017), there has been a shift from Intelligent Manufacturing to Smart Manufacturing. They highlight that the prior model did not leverage AI to incorporate “human intelligence/wisdom in manufacturing”. In both the Smart and Intelligent Manufacturing models, Wang et al. emphasise how important it is to comprehend human capacities. Their findings suggest that rather than being replaced by machinery, humans can work in tandem with robots. The European Union regards to this paradigm shift as Industry 5.0, which is the movement away from the current factory automation and towards innovation that is more accommodating of humans (Breque et al., 2021).
According to Teh and Rana (2023), the IoT and Industrial IoT (IIoT) platforms are predicted to generate USD 13 trillion in economic value for the world economy till 2030. These systems enable ubiquitous interaction among physical objects. However, these estimates only account for industrial applications. Furthermore, during the past 20 years, IoT technologies have converged, opening the door for the so-called Internet of Everything (Miraz et al., 2015). This is because the conventional understanding of the Internet Protocol (IP) and the Internet of People has grown (Miranda et al., 2015). The goal of this is to enhance people's lives through the integration of people, objects, procedures, and data.
It is noteworthy that there are various definitions of Industry 5.0 available in the literature due to its open and changing nature. The European Commission established the Industry 5.0 foundation (Alves et al., 2023) with the goal of balancing economic development and sustainability while taking into account the future of European industry. These foundations are mentioned in this article. In any event, given the current global crises such as the ongoing coronavirus epidemic, global warming, and the ongoing confrontation among Russia and Ukraine industry 5.0 is becoming increasingly significant. Industry 5.0 seeks to overcome the shortcomings of Industry 4.0 while also taking these contemporary social trends such as equal opportunity and numerous of the UN Sustainable Development Goals (SDGs)—into account (Fraga-Lamas & Fernández-Caramés, 2020).
Numerous technological advances in Industry 4.0 right now applied to robotics can be greatly modified in numerous instances to assist human workers in more efficient production processes, while also increasing their level of expertise and innovation and supplementing any skills that may be lacking. In the future, high-tech and technologically advanced manufacturing scenarios may involve more workers, but these digitally interconnected networks might also meet human the centre and ecological objectives in terms of goods manufacturing operations and customer base. In the realm of human factors, the development of robotics and production line technology is becoming increasingly significant, as robots are designed to collaborate with humans to complete tasks (Tuner et al., 2019; Welfare et al., 2019; Ostheimer et al., 2021; Panagou et al 2021). A portion of this investigation that is attracting a lot of attention is cooperative robots, or Cobots (Li et al., 2021; Doyle-Kent, M. 2021).