We report the distributed-fiber-sensing field trial results over a 5G-transport-network. A standard communication fiber is used with real-time AI processing for cable self-protection, cable-cut threat assessment and road traffic monitoring in a long-term continuous test.
We demonstrate a new application of fiber-optic-sensing and machine learning techniques for vehicle run-off-road events detection to enhance roadway safety and efficiency. The proposed approach achieves high accuracy in a testbed under various experimental conditions.
We report the field trial results of monitoring abnormal activities near deployed cable with fiber-optic-sensing technology for cable protection. Detection and position determination of abnormal events and evaluating the threat to the cable is realized.
We demonstrate fiber optic sensing systems in a distributed fiber sensor network built on existing telecom infrastructure to detect temperature, acoustic effects, vehicle traffic, etc. Measurements are also demonstrated with different network topologies and simultaneously sensing four fiber routes with one system.
To the best of our knowledge, we present the first underground fiber cable position detection methods using distributed fiber optic sensing (DFOS) technology. Meter level localization accuracy is achieved in the results.
In this study, we explored surface-enhanced Raman spectroscopy (SERS) for analyzing red wine through several facile sample preparations. These approaches involved the direct analysis of red wine with Raman spectroscopy and the direct incubation of red wine with silver nanoparticles (i.e., AgNPs) and a reproducible SERS substrate, the AgNP mirror, previously developed by our group. However, as previously reported for red wine analysis, the signals obtained through these approaches were either due to interference of the fluorescence exhibited by pigments or mainly attributed to a DNA fraction, adenine. Therefore, an innovative approach was developed using solvent extraction to provide more characteristic information that is beneficial for wine chemical profiling and discrimination. Signature peaks in the wine extract spectra were found to match those of condensed tannins, resveratrol, anthocyanins, gallic acid, and catechin, which indicated that SERS combined with extraction is an innovative method for profiling wine chemicals and overcoming well-known challenges in red wine analysis. Based on this approach, we have successfully differentiated three red wines and demonstrated the possible relation between the overall intensity of wine spectra and the ratings. Since the wine chemical profile is closely related to the grape species, wine quality, and wine authentication, the SERS approach to obtain rich spectral information from red wine could advance wine chemical analysis.
We demonstrated for the first time that geographic locations on deployed fiber cables can be determined accurately by using OTDR distances. The method involves vibration stimulation near deployed cables and distributed fiber optical sensing technology.
To the best of our knowledge, we present the first field trial of distributed fiber optical sensing (DFOS) and high-speed communication, comprising a coexisting system, over an operation telecom network. Using probabilistic-shaped (PS) DP-144QAM, a 36.8 Tb/s with an 8.28-b/s/Hz spectral efficiency (SE) (48-Gbaud channels, 50-GHz channel spacing) was achieved. Employing DFOS technology, road traffic, i.e., vehicle speed and vehicle density, were sensed with 98.5% and 94.5% accuracies, respectively, as compared to video analytics. Additionally, road conditions, i.e., roughness level was sensed with >85% accuracy via a machine learning based classifier.
For the first time, we demonstrate detection of vehicle speed, density, and road conditions using deployed fiber carrying high-speed data transmission, and prove carriers’ large-scale fiber infrastructures can also be used as ubiquitous sensing networks.
