# Emerging Trends in Hybrid Wireless Communication and Data Management for the Industry 4.0
## 1 Introduction  
In the Industry 4.0 paradigm, the core of distributed industrial automation and manufacturing systems is essentially the reliable exchange of information. Any attempt to steer processes independently of continuous human interaction requires, in a very wide sense, the flow of information between sensors, controllers, and actuators [1]. The industrial automation sector was always a pioneer of innovation and most industrial systems come equipped with hundreds or thousands installed smart devices. Wearable and smart devices will allow to interconnect, track, and integrate humans in the production process while, at the same time, the data generated will help engineers in increasingly complex decision-making processes [2]. Consequently, there are many connectivity options and data management techniques that can be used today. However, it is not rare that only limited kinds of data are used, while the great amount of other available data is simply dropped [3], especially in completely centralized industrial settings. Current models for cloud-enabled manufacturing propose architectures that are organizationally centralized: operation of the entire cloud network is guided and controlled by a single or a small group of automated organizational nodes, which connect the demandfor manufacturing services with their supply [4]. Such centralized operation of the manufacturing network poses a potential problem from the perspectives of the system's critical requirements, such as latency and reliability. According to this vision, the next generation of smart factories will very likely be a system of combined networks relying on diverse Internet of Things (IoT) components [5]. Compared to the traditional industrial environments, in IoT-enabled smart factories all relevant data including first, the massive electronic data generated in numeric control units or programmable logic controllers, second, operation status data from add-on sensors and measuring instruments on processing units, and third, environmental data from sensors surrounding processing units, should be collected and transmitted to form for example a cyber processing unit mirroring the physical processing units to realize intelligent-machine applications such as the optimization of processing parameters and the safe functioning of processing units [6]. This transformation comes hand in hand with new challenges for the interplay between IoT and industrial manufacturing [7]; it also imposes a new set of critical and non-critical requirements that need to be addressed. 5G networks are also being designed to support industrial wireless networks. In fact, 5G is being designed to support several verticals, including the factories of the future, in an optimized way, either using low-band spectrum below 1 GHz, mid-band frequencies from 1 GHz to 6 GHz, or high-band spectrum above 6 GHz [8]. 5G is currently attracting extensive research interest from both industry and academia, but there are many challenges that need to be resolved, such as network coexistence among different radio access technologies, resource sharing and access with legacy devices, Quality of Experience (QoE) for users in the unlicensed band, environmental and propagation issues, and power and cost issues [9]. Research activities focusing on radio interface(s) and their interoperability, and access network related issues, traffic characteristics, and spectrum related issues are then encouraged for the development of 5G networks supporting the factories of the future [10]. Some industrial use cases impose stringent requirements on wireless IoT and 5G networks. These requirements include robustness, low latency, energy efficiency, constrained data rates and flexible management and heterogeneity [11]. A basic enabler for satisfying those industrial requirements is the identification and control of the autonomous, interconnected entities within the production system and their operation without the change of the control applications in the rest of the production system [12].