The term “digital age” refers to the 21st century, characterized by the widespread use of digital platforms for data and information sharing. This era is marked by critical technologies such as sensor networks, Machine Learning (ML), Deep Learning (DL), Predictive Maintenance (PDM), and the Internet of Things (IoT), which are pivotal in driving the Industry 4.0 revolution. Today, industrial operations encompass pre- and post-production, quality control, and supply chain management, all fully automated. Physical tasks are handled by intelligent robots equipped with machine learning capabilities, freeing humans to focus on cognitive activities. These robots perform diverse tasks while real-time sensor networks collect environmental data, ensuring efficient and adaptable industrial operations 3.5. This study aims to highlight the pivotal roles of ML, DL, and IoT within the framework of Industry 4.0, leveraging historical performance data for real-time decision-making. The chapter critically evaluates a multitude of tools, models, protocols, and cutting-edge technologies deployed in Industry 4.0 settings. It identifies areas requiring further investigation and provides recommendations to steer future advancements in Industry 4.0.
Keywords: Deep learning, Internet of Things, Industry 4.0, Machine learning, Predictive maintenance.
