## 4 Perspectives on Embedded AIoT Devices for SMEs Based on Identified Attributes
### Verification of the Designed Devices Considering the Identified Essential Attributes
#### 4.2.2 Jetson Xavier NX  
An order of magnitude higher than the Jetson Nano is the Jetson Xavier NX. The Jetson Xavier NX has a powerful 384-core NVIDIA GPU based on the Volta architecture, and additionally features 48 tensor cores. The Jetson NX Xavier is powered by an input voltage of 19 V, which is a higher than that of the Jetson Nano. This is due to the more powerful hardware; hence, the overall power consumption of the Nano is lower than that of the Xavier. The higher power consumption is due to more powerful hardware, which provides the possibility to implement more complex neural network models, especially machine vision, allowing for applications such as robots or drones, etc. It is important to mention that development kits even in the case of the NX module are defined by the manufacturer as a non-production device. Still, it is ideal for prototyping and testing various deep learning techniques to solve defined problems. For comparison, the Jetson Nano has 472 GFLOPs and the Xavier NX has 21 TOPs.  
There are several differences between Nano and Xavier in carrier board (kit) design, despite the fact that visually they are two similar products. At first glance, the use of active cooling is obvious in the case of the Xavier module. The Nano has a passive heatsink, but it is possible to attach additional active cooling to it or to replace it completely with an ICE Tower Cooling Fan [69]. The NX carrier board version has two M.2 Key slots--E,M--and the Nano has only one M.2 Key E socket to have the ability to connect via an external Wi-Fi card. This means that the Xavier has the option to attach fast, M.2 NVMe SSD external memory for running source code or just expanding storage. Unfortunately, you cannot use this drive to install an operating system image and boot from this drive. This is strictly possible only for the SD card--you must boot the operating system from it.  
In terms of performance, the fundamental difference between Nano and Xavier is the use of INT8 precision tensor cores and the cumulative number of CUDA and tensor cores. Xavier has a Wi-Fi adapter installed from the factory, and the antennas are built-in on the underside of the plate carrier [70]. Thanks to this design, there is no need to additionally attach antennas, and they do not take up excess space outside the case as in the Jetson. Table 4 gives all necessary information about Jetsons.  
One of the weaknesses of the abovementioned models is that, although it is possible to use these devices after certain modifications, use in industry is not recommended by the manufacturer. This is the problem with most of the current cheap solutions that could be used as a basic solution for SMEs. While the Jetson Nano and Jetson Xavier pins, Asus T-inker, excel in prototyping solutions, their use in a real industrial environment is not recommended and would be done at users' own risk. In the case of production systems, such an experimental setup would require its own long-term testing of the reliability of the system in question.  
\begin{table}
\begin{tabular}{c c c} \hline
**Parameters** & **Jetson Nano B01** & **Jetson Xavier NX** \\ \hline GPU & 128-core Maxwell & 384 CUDA cores and 48 tensor cores \\ \hline CPU & Quad-core ARM A57 1.43 GHz & 6-core NVIDIA Carmel ARM 64-bit CPU \\ \hline Memory & 4 GB 64-bit LPDDR4 25.6 GB/s & 8 GB 128-bit LPDDR4x 51.2 GB/s \\ \hline Storage & MicroSD & MicroSD, M.2 \\ \hline Video Encoder & 4 K @ 30 1 4 \(\times\) 1080 p–30 fps & 2 \(\times\) 4 K 30 fps, 6 \(\times\) 1080 p–60 fps \\ \hline Camera & 2 \(\times\) MIPI CSI-2 & 2 \(\times\) MIPI CSI-2 \\ \hline Connectivity & Ethernet, M.2 Key E & Ethernet, M.2 Key E, M.2 Key M \\ \hline Others & GPIO, I2C, I2S, SPI, UART & HDMI_4_\(\times\) USB 3.1, USB 2.0 Micro-B, GPIO, I2C, I2S, SPI, UART \\ \hline \end{tabular}
\end{table}
Table 4: Jetson Nano and Jetson Xavier NX technical specifications.