# Interoperability of the Time of Industry 4.0 and the Internet of Things
## 1 Introduction  
The manufacturing industry is currently moving towards more connected and smarter manufacturing chains with optimized supply processes [1]. Smart manufacturing networks integrate heterogeneous data collected across the supply chain for achieving business goals. This trend is, amongst others, captured in the vision of the Industry 4.0 that is focusing on creating intelligent products and production processes [2]. Ultimately, it represents a convergence of information technology and operational technology: supply and production chains will dynamically adjust themselves in order to provide on-demand customization of manufacturing of on-demand customer-driven products. From a business point of view, Industry 4.0 fosters permanent (or temporal) cooperation among end-to-end, geographically-disperse manufacturing systems. This cooperation is centered on a shared value-chain built by sharing and coordinating (i) people, (ii) manufacturing data, (iii) operational processes, and (iv) sensors and actuators [3]. The production of physical products should also be integrated with supply chain(s) in order to foster optimal distribution [1]. In this context, both production lines and supply chains are trying to take advantage of the sparse collection of sensors and actuators for optimizing their value chain. Consequently, devices are playing a central role in these production lines, which are becoming more and more complex and extremely difficult (if not impossible) to monitor and control by humans. This trend fosters the creation of devices that are capable of dynamically sensing and adjusting themselves in order to optimize the production processes. The Internet of Things (IoT) and Web of Things research is trying to implement such devices, and consequently, these research domains may serve as a technology enabler for (i) collecting, (ii) storing, (iii) elaborating, and (iv) acting upon the information that is produced and shared among all the value chains. Nevertheless, devices without the capability to adjust themselves to the environment cannotdynamically participate in the production line in Industry 4.0 due to the increasing complexity, which is beyond human reach. Consequently, \"intelligent interoperability\" plays a critical role in \"enabling the enabler\" in ensuring the central role that research initiatives in the area of IoT should play in Industry 4.0. In other words, devices should be equipped with the capability of describing themselves in a way that is understandable by both machines and humans; thus, fostering an implicit or explicit semantic description of themselves. Industry 4.0 academics and practitioners commonly accept this need, and a set of case studies and best practices was first introduced by [PERSON] et al. [4]. This paper intends to survey and categorize the efforts of academics and practitioners to enrich the interoperability of devices as described by the IoT domain with a semantic description of the device itself in order to foster dynamic readjustments of themselves with the respect to the system in which they are. This autonomous behavior will play a critical role in designing the production lines fostered by the Industry 4.0 vision due to the increasing complexity, which is beyond human reach. The research domain of IoT is presenting itself as a scattered collection of activities in several different venues. The terminology used reflects this reality; in particular: sensor network, mobile sink, mobile agent, and mobile data collectors usually mean the same thing. In addition, some researchers borrow terms like actuator or invent specific new terms like \"mole\" for similar things. This is engthnized by the fact that the various sub-communities do not share a single vision, and the term interoperability has a different meaning, which includes: (i) protocol efficiency in terms of data lengths and energy consumption, (ii) methods and functionalities, (iii) interoperability with computational infrastructure, and (iv) the use of meta information for enabling some reasoning.