## 3 Multi-Sensor Platform: Layout and Use Cases  
The MSP prototype is shown in Figure 1[12]. The prototype has dimensions of 100 mm \(\times\) 100 mm, and the housing is realized in blackened ionized aluminum. Figure 1: MSP prototype. The lateral section with three circular connectors for the external sensors interfaces is provided on the left. The top side of the device shows the printed 5G-SMART logo. In the aperture of the housing, the board with the main electronic components is visible. The aperture will be covered with a plastic panel, under which a flat radio antenna is attached to prevent signal disturbances. An accelerometer is mounted on an integrated support to detect and measure device vibrations without distortion. The 6800 mAh lithium-ion battery is placed in the lower part of the board, with dimensions of 90 mm \(\times\) 60 mm. On the right, the circular connector to the external ancillary communication module is provided. The MSP use cases tested at the Aachen shop floor trial site are highlighted in Figure 2[13]. The MSP device will be mainly used in the following manufacturing applications:  
* Condition monitoring of machine tools used in milling machines, grinding machines, and electro-erosion machines;
* Condition monitoring of workpieces;
* Infrastructure monitoring, such as for heatmap of labs and shop floors. The measured data are collected by sensors and processed in real time. The measurement data stream (A) is the path through which the information is transferred from the sensors to the network. The information reaches the 5G base station and the 5G core. Once data are processed, they are sent to the factory cloud. Parallel computing and virtualization are the basis for big data processing, enabling virtual machines and digital twins of physical devices. Data processing pipelines are realized through Kubernetes clusters. Sensor data are transferred through the 5G network and processed inside the clusters[13]. The 5G network ensures the interaction between sensors, machines, and workpieces. Configuration data are sent in downlink from the factory cloud via 5G to the MSP sensors (B) for MSP measurement customization for the different applications. The MARPOSS ARTIS Genior(tm) modular monitoring system (GEM-VM)[14] is a virtualized monitoring system applied within the communication stream of the MSP. It is mainly applied for predictive maintenance purposes. Data are processed by the software platform and sent to the cloud for data analytics. In the cloud predictive algorithms based on mathematical models identify variations from the optimal values. This reduces latency  
Figure 2: MSP use cases. before a failure happens, saving time and cost to extend machinery lifetime and improve performance. Thanks to sensor monitoring, the MSP applications benefit from the presence of GEM-VM; repairs and replacements are carried out only when strictly necessary. This technology is based on spectral analysis of the vibration signal. The vibration condition is always present in the machinery; therefore, its monitoring allows for detection of problems in a predictive way, avoiding breakdowns. The GEM-VM receives process signals from machine tools and performs fast Fourier transform (FFT), power spectral density (PSD), and noise spectral density (NSD) analysis. Acceleration, gravity, temperature, and velocity signals are analyzed in time and frequency. Constant vibration and temperature monitoring allows a quick stop signal to be sent within 1 ms of receiving a discordant value in order to prevent damage. The machine-to-machine (M2M) communication (C) is the wired connection that enables a data stream between the factory cloud and the numerical control unit (NCU) in machinery. This is achieved through a hardware gateway installed in the form of a Genior(tm) modular central processing unit (CPU) via PROFINET. Feedback control is provided by transferring the information from the factory cloud to the physical machine.