# Low-Cost Digitalization Solution through Scalable IIoT Prototypes
## 1 Introduction
The acquisition of all the necessary data play a fundamental role, and it is especially challenging when dealing with originally disconnected machines. Most machines of the latest generation possess new sensor technology and can easily be connected in order to provide production data. In contrast, SMEs, especially in the manufacturing industry, mostly have machines that belong to Industry 3.0. Industry 3.0 is defined by the rise of Information and Communication Technology, and the use of robots, actuators, and servomotors became a major part of the manufacturing industry [12]. These machines are considered disconnected, and thus, cannot seamlessly integrate into Industry 4.0. According to [PERSON] et al. [13] machines can be classified as talking or mute with regard to their level of connectivity. It is thus necessary to teach machines to \"talk\", to enable them to provide the data. As mentioned before, the data provide insight into the entire factory operation. This will, in turn, provide tools to make informed and smarter data-driven decisions. The process of getting the data from analog machines is the process of machine digitization. Digitization is one of the first steps in transforming Industry 3.0 to Industry 4.0. The authors would like here to differentiate between the terms digitization and digitalization. According to [PERSON], digitalization is \"the use of digital technologies to change a business model and provide new revenue and value-producing opportunities\" [14]. Machine digitization enables the creation of the digital twin, a virtual representation of a physical system. It is a closed-loop system with the information being exchanged in both directions between the virtual and physical counterparts. Once the digital twin is created, it presents a way to simulate the system operations and to orchestrate the production system in an optimal way [15]. Digital twins of manufacturing systems show great promise in diverse applications, according to [PERSON] et al. [16]. However, [PERSON] et al. [17] does not consider a complete digital twin to be feasible, due to the massive amount of data that the virtual replica would require. They propose the use of a digital shadow, which, in their view, represents reality in a more compact fashion and with better performance than a fully integrated digital twin. The authors, therefore, have chosen the digital shadow as a preferable option to the digital twin, especially considering the requirements for the solution. The \"downgrade\" from the digital twin additionally makes sense from a business perspective, especially in cases where even a limited number of information can create enough value for the different internal or external stakeholders. The authors extrapolated a set of requirements the digitization solution for SME shop floors machine should fulfill. The solution should enable the creation of the digital shadow and therefore provide the necessary data, and in extension, the insight that will benefit the decision-makers. These requirements are:  
1. **Cost effectiveness --**A low initial cost of investment for the digitization of a single machine or manufacturing unit decreases the entrepreneurial risk, and hence the hesitation of a company [18; 19; 20]. After seeing immediate improvements, the company can gradually upgrade the entire machinery. Furthermore, the benefits grow progressively with the degree of digitization. 2. **Implementation simplicity--**A lower complexity increases the speed of development and implementation. The increase in speed provides the results quickly, thus increasing the confidence of the decision-makers that the entire process can be finished quickly. Many authors have identified a high complexity and a lack of qualified workforce as big barrier towards the Industry 4.0 adoption process [21; 22]. 3. **Security--**Security is the focus of any IoT development, the industrial setting only emphasizes this. It is one of the main challenges faced by companies in the context of the Industrial Internet of Things (IIoT) [23]. 4.