Artificial Intelligence-Based IoT-Edge Environment for Industry 5.0

Industry 5.0 represents a major shift in manufacturing, emphasizing the integration of human-centered processes alongside cutting-edge technologies. The deployment of artificial intelligence (AI) in edge contexts, which includes bringing computer resources closer to the location where data is generated, is a critical aspect in this advancement. This chapter discusses the creation and deployment of an artificial intelligence (AI)-powered edge environment specifically built for Industry 5.0. The goal is to improve industrial operations’ efficiency, adaptability, and reactivity. The chapter uses artificial intelligence to manage and study real-time data at the network’s edge, reducing latency and promoting faster decision-making. This integration of AI and IoT and edge allows for the deployment of predictive maintenance, effective quality control, and the optimization of manufacturing processes, all of which contribute to a more proactive and adaptive industrial environment. The application of AI algorithms in collaborative robotics dramatically enhances workforce efficiency and safety. Furthermore, the edge environment serves as a platform for the seamless and efficient interaction of cyber-physical systems and human operators, resulting in the creation of a connected and highly responsive industrial ecosystem. Edge computing significantly mitigates the security and privacy risks inherent in AI applications by minimizing the need for huge data transfers to centralized cloud servers. Edge-based artificial intelligence (AI) solutions offer a decentralized technique for improving data privacy and reducing vulnerability to cyber threats. This chapter especially suited to firms looking to capitalize on the disruptive prospects presented by Industry 5.0 with integration of AI and Edge. Using real-world case studies and simulations, this chapter demonstrates the usefulness and practicality of the proposed AI-based edge environment in encouraging innovation and competitiveness in the manufacturing industry. However, the true value of IoT devices is realized through the utilization of edge computing, which provides the necessary resources. Artificial intelligence algorithms are essential for inferring information in edge computing. In addition, the data collected from IoT applications is typically unstructured and requires additional analysis. AI-based models are utilized to extract pertinent information. In addition, when exchanging data between devices, there is a possibility of harmful attacks. Therefore, this chapter delves into the concept of Industry 5.0, the architecture of the Internet of Things (IoT) and AI-driven edge devices. We thoroughly examine the technical aspects of IoT networks and the technologies that facilitate communication. Next, we explored a range of AI-driven technologies that are incorporated into Edge environments, including AI-powered tools, edge computing, and trust models for edge devices.