Bangalore – March 11, 2026 – VIAVI Solutions has announced the launch of next-generation fiber test head for distributed acoustic sensing (FTH-DAS) to enhance their NITRO Fiber Sensing solution. The FTH-DAS is a true-phase DAS interrogator with embedded AI and machine learning (ML) engine. Designed for the network edge, the FTH-DAS interrogator enables multi-event detection and localization with real-time event classification across multiple fibers directly on the device.
“By combining on-device Machine Learning alongside a patented true-phase DAS technique, the VIAVI FTH-DAS delivers the enhanced measurement accuracy and interpretation needed for real-time intelligence,” said Kevin Oliver, Vice President and General Manager, Fiber and Access Solutions, VIAVI. “To put this into context, a gas pipeline operator would not only be able to detect leaks, but also nearby digging, vehicles and even footsteps, with the AI allowing for instantaneous and true alerts to prevent accidental damage before it happens. Classic OTDR, temperature, strain and acoustic monitoring is now possible in a single fiber core for both dark and in-service fiber links.”
DAS fiber sensing uses traditional optical fibers as a continuous microphone to detect and locate damage and potential threats over long distances. The number of applications for DAS technology has risen significantly in recent years, and now includes threat identification for data centers and telecom network cables, security surveillance of borders and sensitive perimeters, as well as monitoring of critical infrastructure ranging from identifying pipeline leaks to detecting undersea power cable wear.
VIAVI’s AI/ML event detection and classification models have been developed based on decades of historical data. The tools and models are run and automatically updated at the edge on the FTH-DAS without the need for external, remote and centralized processing or manual intervention. The AI/ML engine analyzes data in real time from the fiber links under test, allowing minimal commissioning time while enhancing event identification, classification and tracking over time. Continuous, scalable model adaptation is implemented for automatic improvement in a private or VIAVI-managed cloud-based ecosystem.
The true-phase DAS adopts a VIAVI-patented phase-stepping interferometry technique to recover the optical phase from Rayleigh backscatter. Beyond just detecting disturbances, this approach allows for true measurements of physical quantities such as strain, vibration amplitude, frequency and true acoustic power. Results are repeatable, objective and comparable across deployments, enabling applications beyond simple event detection and allowing robust ML training and inference.
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