Role of Mechatronics in Industry 4.0/5.0 Transitions: IoT, AI-driven Robotics, and Autonomous Control Strategies

Abstract

The global manufacturing landscape is undergoing an unprecedented paradigm shift driven by the convergence of cyber-physical systems, artificial intelligence (AI), and advanced robotics, collectively catalysed by the Fourth Industrial Revolution (Industry 4.0) and its emerging successor, Industry 5.0. Mechatronics, as an integrative engineering discipline that synergises mechanical engineering, electronics, computer science, and control theory, occupies a pivotal role at the intersection of these revolutions. This study presents a comprehensive review of the evolving role of mechatronics in facilitating and accelerating the industry 4.0 to 5.0 transition, with particular emphasis on three critical technological pillars: the internet of things (IoT), AI-driven robotics, and autonomous control strategies. Through a systematic survey of literature published between 2015 and 2025, this review examines how IoT-enabled mechatronic systems achieve real-time sensing, edge computing, and bidirectional data exchange across heterogeneous industrial networks. The study critically analyses the deployment of machine learning algorithms, including deep reinforcement learning (DRL), convolutional neural networks (CNNs), and transformer-based architectures in intelligent robotic platforms and flexible manufacturing systems. Furthermore, it investigates autonomous control paradigms such as model predictive control (MPC), adaptive control, multi-agent coordination, and digital twin frameworks that enable self-organising, fault-tolerant manufacturing ecosystems. The review identifies key challenges encompassing interoperability standards, cybersecurity vulnerabilities, energy efficiency, human-robot collaboration (HRC), and ethical considerations in autonomous decision-making. It delineates the conceptual boundary between Industry 4.0 (efficiency-centric, data-driven automation) and Industry 5.0 (human-centric, resilient, and sustainable co-creation), mapping how mechatronic innovations bridge these paradigms. Case studies from automotive, aerospace, pharmaceutical, and smart logistics sectors are synthesised to illustrate real-world deployment trajectories. The paper concludes with a forward-looking research agenda identifying open problems, emerging technologies such as neuromorphic computing and soft robotics, and strategic recommendations for researchers, engineers, and policymakers.