An intelligent and secure internet of robotic things: A review and conceptual framework

Abstract

Robots are increasingly being deployed across various fields and applications, including agriculture, manufacturing, transportation, surveillance, and rescue missions. The integration of technologies such as Artificial Intelligence (AI) and the Internet of Things (IoT) with robotics significantly enhances their capabilities and expands their range of applications. Rapid advancements in these technologies have driven notable progress in robotics research, particularly in the domain of AI-enabled Internet of Robotic Things (IoRT). However, our extensive literature study finds that there is a growing need for the development of big data–enabled secure IoRT systems capable of handling vast amounts of data generated by large-scale heterogeneous, homogeneous robots and multiple stakeholders. Addressing this need is essential to meet modern industrial and societal demands. Therefore, this paper presents a conceptual framework for AI-enabled, big data analytics–driven secure and reliable IoRT, based on a comprehensive review of the literature. The framework emphasizes key enabling technologies, including connectivity, cloud and edge computing, big data analytics, and cybersecurity systems, with the ultimate aim of supporting the transition to Industry 5.0. Furthermore, we explore several promising research directions that could enhance the intelligence and security of future IoRT systems. Before concluding, we provide an in-depth discussion of the benefits, limitations, and challenges associated with IoRT. We hope this work will serve as a valuable resource for researchers and practitioners in advancing next-generation intelligent robotic systems for the betterment of society.