## 1 Introduction  
The Fourth Industrial Revolution (Industry 4.0) pertains to contemporary trends in automation and information exchange within manufacturing technologies. It encompasses various innovative technologies, including the Internet of Things (IoT), artificial intelligence, cyber-physical systems (CPSs), big data analytics, digital twin, cloud computing, additive manufacturing, etc., as shown in Figure 1. It leverages these technologies to transform traditional manufacturing into highly interconnected, smart manufacturing systems [1; 2]. The primary aim of Industry 4.0 is to establish smart factories in which CPSs oversee physical operations, generate digital replicas of the tangible environment, and take actions rooted in real-time information. The significance of Industry 4.0 lies in the interconnected systems, increased efficiency, personalized customization, resource efficiency, and safety and security [3; 4]. As IoT technology becomes a prominent field of communication, the scope of its applications is expanding into the industrial sector. Hence, the novel approach of connecting industrial equipment to the internet has led to an extension of the IoT called Industrial IoT (IIoT). Thus, IoT and IIoT are integral and pivotal components of the Industry 4.0 paradigm, offering less expensive, robust, and practical solutions to manufacturing paradigms. IoT comprises interconnected computing devices, such as electronic systems, objects, and living organisms that are capable of communicating data across a network without requiring human or human-machine interaction [5]. Similarly, IIoT is a subset of the broader concept of the IoT but tailored specifically for industrial environments. It refers to the interconnection of industrial equipment, devices, and systems to collect, exchange, and analyze data to optimize industrial and manufacturing processes [6]. Linking diverse technological platforms offers the capability to interact with remotely situated manufacturing machinery, regardless of the user's geographical location. Consequently, product designers can transmit their product designs for manufacturing to a broader range of potential production facilities. This evolution within the manufacturing sector results in a more adaptable yet finely tuned production setting, presenting a flexible and optimized manufacturing environment. Figure 1: Components of Industry 4.0. IoT is changing the lives of humans and making them more comfortable [7; 8; 9]. IoT communications take place with a set of predefined models and protocols, such as ad hoc on-demand distance vector (AODV) routing, destination-sequenced distance vector vector (DSDV) routing, optimized link state routing (OLSR), dynamic source routing (DSR), routing protocol for low power and lossy networks (RPL), constrained application protocol (CoAP), and 6 LoWPAN (Ipv6 over low-power wireless personal area networks). IoT communications occur in four layers, i.e., the perceptual layer, support layer, application layer, and network layer. The IoT nodes can connect with their neighbors and proceed with data among other nodes [10; 11; 12; 13]. Thus, the IoT plays a tremendous role in the manufacturing sector, in regard to enabling smart manufacturing. In addition, IoT-enabled mobile industrial robots (MiRs) are significantly contributing to smart manufacturing by leveraging IoT to enhance their capabilities. By collecting real-time data, performing predictive maintenance, navigating autonomously, collaborating with human operators, and enabling remote monitoring and control, these robots are helping manufacturers improve efficiency, reduce costs, and enhance product quality. MiRs are designed to be flexible and easily programmable, so they can be adapted to different tasks and workflows. They can be programmed to enable smart manufacturing, e.g., by transporting materials from one location to another, picking up and delivering materials to specific workstations, or assisting with inventory management tasks [14; 15].