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Smart city article details
| Title | Ai-Driven Applications Over Telecom Networks By Distributed Fiber Optic Sensing Technologies |
|---|---|
| ID_Doc | 7015 |
| Authors | Huang M.-F.; Han S.; Narisetty C.; Salemi M.; Chen Y.; Wang T. |
| Year | 2022 |
| Published | Proceedings of SPIE - The International Society for Optical Engineering, 12028 |
| DOI | http://dx.doi.org/10.1117/12.2613499 |
| Abstract | By employing distributed fiber optic sensing (DFOS) technologies, field deployed fiber cables can be utilized as not only communication media for data transmissions but also sensing media for continuously monitoring of the physical phenomenon along the entire route. The fiber can be used to monitor ambient environment along the route covering a wide geographic area. With help of artificial intelligence and machine learning (AI/ML) technologies on information processing, many applications can be developed over telecom networks. We review the recent field results and demonstrate how DFOS can work with existing communication channels and provide holistic view of road traffic monitoring included vehicle counts and average vehicle speeds. A long-term wide-area road traffic monitoring system is an efficient way of gathering seasonal vehicle activities which can be applied in future smart city applications. Additionally, DFOS also offers cable cut prevention functions such as cable self-protection and cable cut threat assessment. Detection and localization of abnormal events and evaluating the threat to the cable are realized to protect telecom facilities. © 2022 SPIE |
| Author Keywords | artificial intelligence; cable cut prevention; Distributed fiber optic sensing; traffic monitoring |
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