Advancing Smart Industries with Internet of Things and Artificial Intelligence: A Digital Ecosystem Perspective

Abstract

The digital transformation of industrial systems under the Industry 4.0 paradigm has introduced cyber-physical systems (CPS) as a core enabler of vertical integration and data-driven production environments. The convergence of Internet of Things (IoT) and Artificial Intelligence (AI) technologies has accelerated this transformation, fostering the development of the Industrial Internet of Things (IIoT) and creating smart industries characterized by real-time monitoring, automation, and human–robot collaboration (HRC). While these advancements establish a digital ecosystem capable of optimizing production through intelligent data analysis and decision-making, their practical implementation remains constrained by unresolved challenges and gaps in validation. With the emergence of Industry 5.0, the focus shifts toward human-centric, sustainable, and resilient industrial ecosystems, where AI-driven cognitive computing further enhances interaction between humans and machines. This review examines the application of AI–IoT integrated technologies across multiple industrial domains to identify their strengths, limitations, and recurring challenges. By categorizing existing literature into key application areas, the study highlights both the opportunities and risks inherent in current approaches, bridging the conceptual design of smart industries with their real-world realizations. The findings underscore the importance of scalable, secure, and efficient frameworks to ensure the safe and reliable adoption of AI–IoT in the industrial ecosystem.