Fiber sensing can detect physical parameters such as phase and polarization changes in optical signals. This optical data needs to be interpreted into human-understandable events and scene information for real-world applications.
Our research and development focus on innovative applied machine learning and signal processing algorithms that convert low-level sensory inputs into high-level information, providing solutions for real-world sensing applications in safety, security, smart city, infrastructure health monitoring, power & energy industry, and more. We have developed multiple AI prototypes and high-performance computation platforms for real-time perception of the physical world and validated them through numerous world- and industry-first field trials.
Publication Tags: physics informed, fiber sensing