GPR Sensing and Visual Mapping Through 4G-LTE, 5G, Wi-Fi HaLow, and Wi-Fi Hotspots with Edge Computing and AR Representation
Source abstract
Abstract
In this study, we demonstrate an application for 5G networks in mobile and remote GPR scanning situations to detect buried objects by experts while the operator is performing the scans. Using a GSSI SIR-30 system in conjunction with the RealSense camera for visual mapping of the surveyed area, subsurface GPR scans were created and transmitted for remote processing. Using mobile networks, the raw B-scan files were transmitted at a sufficient rate, a maximum of 0.034 ms mean latency, to enable near real-time edge processing. The performance of 5G networks in handling the data transmission for the GPR scans and edge computing was compared to the performance of 4G networks. In addition, long-range low-power devices, namely Wi-Fi HaLow and Wi-Fi hotspots, were compared as local alternatives to cellular networks. Augmented reality headset representation of the F-scans is proposed as a method of assisting the operator in using the edge-processed scans. These promising results bode well for the potential of remote processing of GPR data in augmented reality applications.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Geophysical Methods and Applications · Indoor and Outdoor Localization Technologies · Microwave Imaging and Scattering Analysis
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Mechanical Engineering, University of Vermont, Burlington, VT 05405, USA
Computer Science, University of Vermont, Burlington, VT 05405, USA
Electrical and Biomedical Engineering, University of Vermont, Burlington, VT 05405, USA
Funding
U.S National Science Foundation
References (34)
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