## 1 Introduction  
In the last decade, Internet of Things (IoT) and Cyber Physical Systems (CPS) have become pervasive and made an impact on many aspects of everyday life [1; 2]: concepts such as Smart Home, Smart Car and Smart City have become familiar also to non-technical users. The integration of embedded systems, ubiquitous Internet access and Machine-to-Machine (M2M) communications have paved the way for IoT and CPS to be introduced also in industrial environments [3], under the forms of Industrial Internet of Things (IIoT or I2 oT) [4; 5] and Cyber-Physical Production Systems (CPPS) [6]. As a consequence, the fourth industrial revolution, namely Industry 4.0 [7], is rapidly reshaping traditional industrial processes.  
The first three industrial revolutions were characterised by technical innovations that aimed to improve production efficiency: the first industrial revolution was triggered by water and steam power; electricity and assembly lines enabled mass production in the second industrial revolution; in the third industrial revolution, the introduction of control automation and Programmable Logic Controllers (PLCs) gave a boost to factory production [8; 9]. The fourth industrial revolution is mainly enabled by three innovation elements [3]: ubiquitous Internet access, M2M communications and advanced data analysis. The objective is not only improving production efficiency but also enabling the so-called mass customization [10], i.e., the mass production of personalised products by making use of modularised product design and flexible processes.  
One of the keys to customer satisfaction is providing services and products with a high level of customisation. This is enabled by production processes that are increasingly corresponding to customers' expectations and needs, both in terms of timeliness and quality [11]. In order to fulfill these requirements, industry-related processes, from production to delivery, from warehousing to stock replenishment, need to be adequately designed so that resource usage is optimised, and faults and system downtimesare minimised. Furthermore, workplace health and safety, as well as the quality of working conditions, need to be ensured to improve work-life balance and, therefore, workers' happiness, according to the assumption that happier workers are more productive.  
In this paper, all of these aspects will be analysed by considering how the use of new technologies related to IIoT and CPPs can enhance industrial processes. Since the main difference of this industrial revolution with respect to the previous ones is the focus on humans and how their perceptions affect industrial processes, this aspect will be thoroughly analysed. In Industry 4.0, workers and customers are an integral part and the core of most of the decision processes, both in terms of objective measurements of their activities and subjective feedback gathering. In this context, the use of crowdsensing and crowdsourcing introduces many advantages [12]. In crowdsensing and crowdsourcing, data are collected collaboratively by exploiting the pervasive presence of Internet-connected geolocated devices. This enables the collection of impressive amounts of data and the opportunity of analysing them to perform more advanced processes and applications.  
The remainder of the paper is organised as follows. In Section 2, the background of the main enabling technologies that enabled the fourth industrial revolution are examined. Section 3 describes the applications that are expected to characterise Industry 4.0, subdivided into five application domains. Section 4 provides a discussion about the challenges that current technologies will have to face for being effectively integrated into industrial processes, despite their stringent requirements. The section ends with an overview of the opportunities that will be created. Section 5 focuses on the use of crowdsensing and crowdsourcing to enable the applications that characterise Industry 4.0. Finally, Section 6 draws final conclusions.