# Low-Cost Digitalization Solution through Scalable IIoT Prototypes
## 2 State of the Art  
The authors wanted to find support in the literature for their assumption that one of the main culprits of the low adoption rate is the lack of motivation. [PERSON] and [PERSON] [19] have been investigating low levels of Industry 4.0 adoption in SMEs, especially with regards to IIoT in the scope of \"Industrie 4.0\" and \"Made in China 2025\" [27] programs. They interviewed a large number of Chinese and German SME stakeholders (predominately CEOs) and they observed their confidence levels in their respective programs. The stakeholders felt that these programs are more suited to large enterprises rather than SMEs. Furthermore, [PERSON] et al. [28] noted that companies remain unconvinced about the benefits of the new technologies, having in mind they are untested, and that old technology still has better cost-benefit ratios. [PERSON] and [PERSON] [8] also identified through a survey that most SMEs struggle with the implementation of Industry 4.0 technologies, both from the financial point of view as well as from the lack of expertise and knowledge of those technologies. [PERSON] et al. [29] also noted that for SMEs to not only exploit but to explore new business opportunities through Industry 4.0, they require implementation support and financial security to experiment, as they have limited resources and have to avert risks because of their limited size. The authors, therefore, presume that there is a motivation issue and that there is a need to develop a solution that takes this into account. In the search for the appropriate digitization techniques, the authors focused on the various approaches toward digitization in the literature. In their work, [PERSON] et al. [30] state that to utilize the full potential of Industry 4.0, all entities in the supply chain must be able to communicate with each other. They suggest that different layers must have standardized technical communication that is also supported by the Reference Architectural Model for Industry 4.0 (RAMI 4.0) [31]. There are different approaches to the digital transformation of the manufacturing SME. In most cases, old machines do not provide a level of connectivity and digitization necessary for the ensuing process. There are two choices, either the acquisition of new machines or the retrofitting of the old ones. The analysis [32] showed that the retrofitting solutions were more cost-effective than the purchasing solutions, and that strong retrofitting in particular was the best in terms of sustainability. [PERSON] et al. [33] demonstrated that the adoption of the Industry 4.0 in SMEs can be achieved through retrofitting existing equipment using mostly open hardware and software, and that it does not imply a high investment in new equipment and technologies. Retrofitting old industrial machines to adhere to Industry 4.0 paradigms has been subject to intensive scientific research in recent years [34; 35; 36; 37; 38]. Industrial IoT is seen as an ideal tool for machine digitization. [PERSON] et al. [39] conducted a literature review that focused on the digitalization of the machine tools in the Industry 4.0. They observed that the IIoT topics have seen a rise in the research articles. Actually, the only Industry 4.0 technology in manufacturing that had more published articles is Artificial Intelligence/Machine Learning. [PERSON] et al. [34] focus on retrofitting in their work, where they noted that for automated industrial equipment to reach Industry 4.0 level of modernization, they need integration with the IoT sensors. The leading companies in the automation field have recognized the benefits of retrofitting old machines, and several studies have utilized those solutions. [PERSON] et al. [40] on the other hand, have proposed a retrofit solution using the Siemens IoT-2040 gateway and the data transmission to the Mindsphere Cloud from Siemens and GRV Software to monitor the energy data in real-time. [PERSON] and [PERSON] [41] have performed a retrofit of a CNC machine with an accelerometer using the Bosch XDK sensor prototyping platform.