## 4 Discussion  
The current method of associating local coordinates to each A-Scan is imprecise as it assumes an even distribution of scans along the entire survey line. As the GPR cart is triggered spatially by a survey wheel and the RealSense module is triggered temporally by the system clock, the two streams are not perfectly in sync and the association may become less accurate. This can be improved by tying the RealSense trigger to the survey wheel. In this arrangement, each pulse from the survey wheel causes both an A-Scan and a coordinate to be created simultaneously. The process by which 3D models are created and made available to the HoloLens has not yet been automated, and as such still requires human intervention. In the future, this process will become automated, along with the expansion of the processing techniques applied to the scan, such as background removal and back projection for 3-D image formation. Comparing the alternatives in the WLAN transmission of B-scan shows the advantage of using the Wi-Fi HaLow HAT setup for its low latency in comparison to the HTC and Orbit hotspots in conjunction with the single-board computer's onboard Wi-Fi module. However, it should be noted that the performance of the Wi-Fi hotspots is limited by the onboard Wi-Fi technology of the single-board computers, which is entirely replaced in the HaLow setup. Considering this fact, it is demonstrated that switching from the HTC Wi-Fi hotspot to the Orbit Wi-Fi hotspot lowers the mean latency values in both 2.4 and 5 GHz network cases, even though they are both restricted by the single-board computer's onboard wireless communication technology. The improvement of the Orbit hotspot over the HTC hotspot may be due to the increased load the HTC experiences while running Android OS. Figure 13: Comparison of mean latency time in each setup case using WLAN and cellular network transmission. While comparing the 5G network to its last generation counterpart, e.g., 4G LTE, the tests show slight performance improvements. It is worth noting that the carrier used in this experiment does not offer its highest performance service, 5G UWB, in this test area. Future experiments will include multiple test periods; additional Orbic stations, allowing for more data to be collected concurrently; optimization of processing times to better characterize round-trip times; and evaluation of the 5G coverage of the test area for comparison to previous literature. The proposed wireless communications methods satisfy the low latency data transfer requirements for near real-time edge computing and AR representation of the F-scans. Using this fast network, the operator can receive nearly real-time feedback from the experts and AR representation of the scan to adjust the path of the GPR scanning based on the new information. Furthermore, by edge computing of the F-scans, the operators do not need to scan the entire area, as they can identify the important targets through AR representation or expert feedback in the field. Therefore, they can focus their efforts on scanning the paths that give necessary information about the target rather than scanning the entire area. Comparing the WLAN and cellular network solutions presented here indicates comparable latency values between 5G and HaLow, but lower variance for 5G. While the performance is similar, it should be noted that the two systems are not interchangeable. To achieve the range allowed by cellular networks, multiple HaLow stations would be needed with each station increasing the total latency. This limitation is countered by the decentralized nature of HaLow technology. Further efforts to characterize and compare the performance of WLAN and cellular networks may be aimed at examining the effects of network congestion and saturation by measuring packet latency in diverse geographic locations and times. Additionally, the number of intermediaries between the sender and receiver in the cellular network should be characterized, allowing for more uniformly comparable results.