NEC Laboratories America celebrates Women’s History Month and International Women’s Day by recognizing the women researchers, engineers, and interns whose work in artificial intelligence, optical networking, cybersecurity, and data science is helping shape the future of technology.
NEC Laboratories America’s Optical Networking & Sensing team will participate in OFC 2026 in Los Angeles, March 15–19, contributing to panels, workshops, and courses focused on optical sensing, multicore fibers, and next-generation high-capacity optical communication systems.
We present methods and field trial results demonstrating an integrated distributed acoustic sensing (DAS) and distributed temperature sensing (DTS) system for manhole localization, condition diagnostics, and anomaly detection in pre-deployed telecommunication fiber networks. The proposed system leverages ambient environmental signals, such as vibrational patterns from traffic and day-night temperature fluctuations, and machine learning techniques for automated detection. By combining DAS waterfall traces with temperature measurements from DTS, we achieve improved classification accuracy. Experimental results from three real-world testbeds in Texas and New Jersey show a significant improvement in classification accuracyfrom 78.9% and 89.5% using DAS and DTS alone, respectively, to 94.7% via cross-referenced analysis. We propose a structured prediction formulation for manhole localization based on a U-Net architecture with a gated attention mechanism, where the label of each fiber location in the waterfall image is predicted using both its neighboring context and within-patch discriminative features. The method also supports cross-route generalization for manhole localization and enables condition diagnostics, identifying issues such as cable exposure and water ingress. These results highlight the potential for scalable deployment of fiber sensing solutions for real-time, continuous monitoring of telecom infrastructure.
Distributed fiber-optic sensing combined with machine learning enables continuous monitoring of telecom infrastructure. We employ generative modeling for event classification, supporting semi supervised learning, uncertainty calibration, and noise resilience. Our approach offers a scalable, data-efficient solution for real-world deployment in complex environments.
NEC Laboratories America (NECLA) was proud to join the European Conference on Optical Communication (ECOC 2025) in Copenhagen, Denmark, from September 28 to October 2. Our researchers presented cutting-edge work in distributed acoustic sensing, AI-driven fiber optics, and optical networking. From generative models for event classification to digital twins and entomological observations using telecom fibers, these sessions highlighted NECLA’s role in shaping the future of intelligent and resilient communication systems. In addition, NECLA’s Fatih Yaman co-organized a workshop on emerging frontiers in optical communication.
Distributed fiber optics sensing is applied for traffic management in the intersection. The high-definition fiber sensing data streaming is applied as source and YOLO computer vision model isemployed for event detection classification and localization.
We demonstrate real-time fiber risk assessment and dynamic network routing in live metro networks using deployed DASs, satellite imagery, and large-scale AI, achieving the first significantreduction in fiber failures in four years
Field trials of ambient noise-based automated methods for manhole localization and condition diagnostics using a real-time DAS/DTS integrated system were conducted. Crossreferencingmultiple sensing data resulted in a 94.7% detection rate and enhanced anomaly identification.
This study demonstrates an AI-driven method for detecting road deformations using Distributed Acoustic Sensing (DAS) over existing telecom fiber networks. Utilizingambient traffic noise, it enables real-time, long-term, and scalable monitoring for road safety.
Publication Date: 4/3/2025 Event: OFC 2025 Reference: Th4C.2: 1-3, 2025 Authors: Jian Fang, NEC Laboratories America, Inc.; Ming-Fang Huang, NEC Laboratories America, Inc.; Scott Kotrla, Verizon; Tiejun J. Xia, Verizon; Glenn A. Wellbrock, Verizon; Jeffrey A Mundt, Verizon; Ting Wang, NEC Laboratories America, Inc.; Yoshiaki Aono, NEC Corporation Abstract: We demonstrated a high-sensitivity forwarding-transmission vibration […]
