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Manufacturers have seen noteworthy variations as a result of Industry 5.0 in recent years. They have seen firsthand the growth of robotics, cloud computing, and the Net of Things (NoT) in driving automation and data technology. Thanks to the seamless integration of software, hardware, and staff, smart factories are becoming increasingly prevalent, and an increasing number of manufacturers are experiencing success with “as-a-Service” business models. Industry 5.0 is now significantly more accessible to small and medium-sized businesses due to its growing maturity. Utilizing technology that gathers, organizes, and combines data with information from your ERP to improve your shop floor efficiency and provide insights is now a lot simpler. These days, it costs much less time, money, and effort for businesses of all sizes to gain realworld experience.

These days, there's a shift away from the industry 5.0 model's emphasis on efficiency towards the realization that mechanized, smart plants must nevertheless prioritize people. More and more people are emerging to believe that social and technical systems can coexist to increase resilience, sustainability, and customization. Restoring people to the centre of industrial production will allow Industry 5.0 to make better use of their skills in creativity, critical thinking, and problem-solving.

This work focuses on how Industry 5.0 uses contemporary technology (Industrial Net of Things (INoT), AI, and Cloud Computing) in significant ways. It intends to investigate the possible uses, advantages, and difficulties related to the implementation of the technologies in smart industries. This survey's contributions include giving a thorough summary of the body of research on the applications, procedures, technologies, and prospects around the usage of INoT, AI, and cloud computing in industry V.0. It pays close attention to several concerns linked to Synthetic Intelligence (SI) and big data in smart sectors, such as security and privacy issues with data, challenges related to interpretation, and adversarial attacks on AI models. This chapter also gives an overview of INoTs, a crucial component of Industry 5.0, and examines the methods used by AI and big data approaches to extract insights from the data created in INoTs.