A New Scheduling Challenge for Real-World Human-Robot Collaboration in Internet of Things Applications

Abstract

Cloud computing, robotics, the Internet of Things (IoT), artificial intelligence (AI), and machine learning (ML) are some of the technologies that make up the Internet of Robotic Things (IoRT). Transportation, industry, healthcare, and security all heavily rely on IoRT. IoRT has the potential to significantly accelerate human growth. Robots can send and receive data to and from other people and devices thanks to IoRT. This study reviews IoRT in terms of comparable architectures, methodologies, and capabilities. The associated research difficulties are so outlined. When creating robotic systems and objects, IoRT architectures are crucial. Human-robot cooperation, or HRC, is quickly emerging as a crucial element of smart manufacturing, healthcare, and service sectors due to the rapid integration of Internet of Things technology. However, real-world implementation of such systems poses challenging scheduling challenges due to the dynamic, diverse, and resource-constrained nature of IoT contexts. This paper presents a novel scheduling problem for real-world human–robot collaboration in Internet of Things applications, which aims to balance communication disruptions, computation demands, and safety-critical interactions. In contrast to traditional scheduling methods, which primarily deal with deterministic scenarios, the proposed perspective emphasizes flexibility in response to erratic human behavior, changing network conditions, and diverse device capabilities. The challenge is increased by the need to guarantee energy efficiency, real-time responsiveness, and secure data exchange across scattered IoT nodes. This scheduling problem needs to be fixed to improve system productivity and human safety, reduce job execution latency, and accomplish seamless coordination. This work lays the foundation for exploring new scheduling models that bridge the gap between theoretical frameworks and the practical requirements of IoT-enabled human–robot collaboration.