How Data Will Transform Industrial Processes: Crowdsensing, Crowdsourcing and Big Data as Pillars of Industry 4.0

Abstract

We are living in the era of the fourth industrial revolution, namely Industry 4.0. This paper presents the main aspects related to Industry 4.0, the technologies that will enable this revolution, and the main application domains that will be affected by it. The effects that the introduction of Internet of Things (IoT), Cyber-Physical Systems (CPS), crowdsensing, crowdsourcing, cloud computing and big data will have on industrial processes will be discussed. The main objectives will be represented by improvements in: production efficiency, quality and cost-effectiveness; workplace health and safety, as well as quality of working conditions; products' quality and availability, according to mass customisation requirements. The paper will further discuss the common denominator of these enhancements, i.e., data collection and analysis. As data and information will be crucial for Industry 4.0, crowdsensing and crowdsourcing will introduce new advantages and challenges, which will make most of the industrial processes easier with respect to traditional technologies.

Society 5.0 and Social Development: Contributions to a Discussion

“…The article ends with a brief conclusion. and will bring as a new productive paradigm with application in several activity areas (Abreu, 2018;Morrar, Arman, & Mousa, 2017;Liu, Cao, Yang, & Jiang, 2018;Shamim et al, 2017;Liao et al, 2017;Fraga-Lamas, Noceda-Davila, Fernández-Caramés, Díaz-Bouza, & Vilar-Montesinos, 2016;Ang et al, 2017;Pilloni, 2018).…”

“…This concept of Industry 4.0 emerged in Germany in 2011, in the search to apply digital technologies to production (Abreu, 2018;Morrar et al, 2017;Pilloni, 2018;Ang et al, 2017;Hayashi, Sasajima, Takayanagi, & Kanamaru, 2017).…”

“…According to Müller et al (2018), Industry 4.0's attention is too focused on the economic and technological dimensions (Pfeiffer, 2016;Pilloni, 2018). Its social impact must also be taken into account, as well as, obviously, the technological impact (Morrar et al, 2017;Moniz & Krings, 2016).…”

Development of User-Participatory Crowdsensing System for Improved Privacy Preservation

“…Therefore, personal information protection is essential in crowdsensing services, and related research should be based on the possible service types. Spatiotemporal [22] Non-spatiotemporal [23] We classify crowdsensing services according to the classification criteria in Reference [24], and we present threats and countermeasures against personal information disclosure in each type of service. Table 1 shows the types of crowdsensing services according to various classification criteria.…”

“…Moreover, crowdsensing services involving spatiotemporal data (e.g., vehicle trajectory) are vulnerable in terms of location or trace privacy [22]. Closed crowdsensing services irrelevant to spatiotemporal characteristics, such as industrial management [23], are resistant to privacy exposure.…”