Presentation + Paper
3 March 2022 AI-driven applications over telecom networks by distributed fiber optic sensing technologies
Author Affiliations +
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.
Conference Presentation
© (2022) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Ming-Fang Huang, Shaobo Han, Chaitanya Narisetty, Milad Salemi, Yuheng Chen, and Ting Wang "AI-driven applications over telecom networks by distributed fiber optic sensing technologies", Proc. SPIE 12028, Next-Generation Optical Communication: Components, Sub-Systems, and Systems XI, 120280K (3 March 2022); https://doi.org/10.1117/12.2613499
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KEYWORDS
Fiber optics sensors

Artificial intelligence

Roads

Networks

Safety

Sensing systems

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