# Context-Aware Systems Architecture in Industry 4.0: A Systematic Literature Review
## 5 Analysis and Discussion
### Architecture Technologies, Norms, Models, and Standards  
#### 5.3.1 Technologies  
The software architect designs the architecture to meet functional and non-functional needs. From this perspective, most current systems are based on monolithic software solutions that restrict the flexibility, adaptability, and scalability and add complexity to the maintenance task [86]. The multiplicity of technologies associated with I4.0 and incorporated into the solution means that, according to [PERSON] et al. [90], it takes a technology-agnostic approach to architectural design. According to Figure 4, and regarding the technologies that guided the development of the architectures identified in the 25 articles, the first grouping includes CPS (64%), IoT (56%), and cloud computing (52%). Another grouping includes CPPS (28%) and edge computing (28%) and, finally, IIoT (24%), digital twins (16%), and fog computing (12%). This is an expected result given that the inclusion criteria only allowed articles whose titles or abstracts contained concepts associated with I4.0 as identified by [PERSON] et al. [29]. Figure 3: Comparative list of context inference techniques. CPS and other technologies, such as IoT, are considered the key to achieving the convergence of the physical and digital worlds, increasing the quality and personalisation of production [75]. Researchers identify and discuss IIoT and CPPS because IoT devices are integrated into the industrial environment and CPS support production processes. On the other hand, [PERSON] et al. [98], cited by [PERSON] et al. [55], states that 14.0 relies on the combination and interaction of many existing and new technologies around these two concepts, IIoT and CPPS. CPS incorporates decentralisation, modularity, and scalability as fundamental attributes, intending to enhance the effectiveness of production processes, both internal and external [75]. It is a critical element of I4.0, as the central infrastructure for the development of solutions based on decentralised networks of cyber-physical entities [91]. In the analysis of the selected studies, we can observe the broad application of CPS, since the effective control of the industrial space also requires characteristics associated with context services, which are essential to enable flexible systems, according to [PERSON] et al. [83]. Instead of ISA-95, the CPS concept provides a series of features, such as flexibility, scalability, and adaptability, to respond promptly to changes in customer requirements. However, according to [PERSON] et al. [92], the development of such a system remains a challenge. One of these challenges concerns the need for programmers to foresee all possible scenarios. Another prominent trend in autonomous systems for Gartner is DT, which represents an essential part of CPS and can provide decision support to improve product life cycle management workflows [87]. [PERSON] et al. [55] present an example of this concept in an architecture that includes a layer to mirror and synchronise the real factory space in the digital space. [PERSON] et al. [94] present three characteristics listed by [PERSON] et al. [99] and associated with the DT to enable mirroring and ensure synchronisation between the physical and digital: (i) it must be synchronised with its physical twin, (ii) there must be active data acquisition, and (iii) there must be some executable models. In the physical space, sensors transmit data in real time via IoT systems, using established communication protocols to ensure the reliability and consistency of the information. As the volume of data generated grows exponentially, cloud computing and edge computing techniques are used to process sensor information before storing it in databases for future analysis [87]. According to the literature, this is the layered organisation model, proposed in 13 papers [39; 55; 73; 75; 80; 81; 82; 84; 86; 87; 90; 91; 93], and only three papers [86; 90; 91]  
Figure 4: Comparative list of technologies referenced in examined papers.