## 8 Conclusions  
The limitations of state-of-the-art industrial sensors and multi-sensor devices have been presented and discussed. Low-flexibility and real-time control capabilities, wired connections, and high latency limit industrial production. With the advent of 5G technology and its high reliability and low latency characteristics, the possibility of designing 5G devices for smart manufacturing has emerged.  
In this paper, we presented an MSP prototype equipped with both internal and external sensors capable of collecting different types of information, i.e., acceleration, humidity and temperature, and vibrations. Its modular architecture and the presence of interfaces for external sensors allow it to be placed on any workpiece, in any machine tool, or the infrastructure present on the shop floor of a factory. The connection with an external ancillary communication module allows for various types of 5G communication modules to become available on the market either now or in the future. The MSP realizes the idea of a 5G device that is, at the same time, flexible, reliable, and modular. Changing of the communication module for a more recent one, e.g., when switching from 3 GPP Rel. 15 to Rel. 16, can be achieved without redesigning the whole prototype. This guarantees market-wide flexibility and reliability.  
These characteristics were first analyzed from a hardware point of view. The main components were introduced and described. Starting from the hardware components, a hardware abstraction layer was created, the building blocks of which serve as the basis for the final operating firmware. Three device-testing commands were presented and described. Additionally, general-purpose commands were introduced.  
As a state-of-the-art project, the device was tested at a prototype level. Future developments consist of actual study at a trial site and verification in real situations for the described application use cases. Several benefits are expected with the use of such prototypes, such as optimization of production processes, increased automation, better control of diagnostic processes, and fault detection, which will be achieved by an improvement in connectivity, flexibility, and applicability.  
Conceptualization, A.P., E.Z. and R.P.; methodology, A.P. and E.Z.; software, P.M. and A.P.; validation, P.M., A.P. and R.P.; investigation, P.M. and A.P.; resources, P.M., A.P. and R.P.; data curation, P.M. and A.P.; writing--original draft preparation, P.M. and A.P.; writing--review and editing, A.P., E.Z., R.P. and N.K.; visualization, N.K.; supervision, E.Z., R.P., N.K. and R.H.S.;  
Figure 4: Experimental setup with MSP, wired sensor, and visualization PC.  
project administration, N.K.; funding acquisition, R.H.S. All authors have read and agreed to the published version of the manuscript.  
This work was performed under the framework of the H2020 project 5G-SMART co-funded by the EU. The authors would like to acknowledge the contributions of their colleagues. This information reflects the consortium's view, but the consortium is not liable for any use that may be made of any of the information contained herein. The 5G-SMART project received funding from the European Union's Horizon 2020 research and innovation program under grant agreement no. 857008.  
Not applicable.  
The authors declare no conflict of interest.