NETWORK SENSING TOPOLOGIES FOR FIBER OPTIC SENSING

    公开(公告)号:US20210314681A1

    公开(公告)日:2021-10-07

    申请号:US17221820

    申请日:2021-04-04

    Abstract: Aspects of the present disclosure describe distributed fiber optic sensing (DFOS) systems, methods, and structures that advantageously utilize existing telecommunications facilities that serve as not only to convey telecommunications traffic—but as a sensor medium providing useful sensory information. In sharp contrast to the prior art—a DFOS system when so deployed may advantageously exploit network topologies and optical switches to provide novel sensing features including the detection of environmental events including acoustic, temperature, and vibrational events that may be indicative of societal activity including traffic and/or emergency events.

    APPARATUS, METHODS, AND SYSTEMS FOR MONITORING FIRE EXTINGUISHER OPERATIONAL READINESS

    公开(公告)号:US20170209725A1

    公开(公告)日:2017-07-27

    申请号:US15412406

    申请日:2017-01-23

    Abstract: Aspects of the present disclosure describe apparatus, methods and systems for monitoring the operational status of fire extinguishers through the utilization of optically sensed, color profile determinations of a pressure gauge positioned on the fire extinguisher as well as the utilization of vibrational, and location sensing devices. Advantageously, monitoring apparatus according to the present disclosure are networkable, and a number of their operational characteristics may be configured via the network and associated servers. Furthermore, monitoring apparatus according to the present disclosure may employ vibrational, acceleration, GPS, RFID, and ultrasonic sensors to detect movement, location, and obstructions. In sharp contrast to the prior art, apparatus, methods and systems according to the present disclosure operate with existing fire extinguishers and provide a convenient, cost effective, and highly functional upgrade path for deployed fire extinguishers.

    Deep Learning and Language Model Enhanced System for Wind Turbine Monitoring Using DistributedFiber Optic Sensing (DL-LM-DFOS)

    公开(公告)号:US20250148427A1

    公开(公告)日:2025-05-08

    申请号:US18935512

    申请日:2024-11-02

    Abstract: Disclosed is a deep learning and language model enhanced system and method for wind turbine monitoring using distributed fiber optic sensing (DL-LM-DFOS) which combines advantages of distributed fiber optic sensing with the power of deep learning and large language models. Our system and method automatically learns and extracts useful features from raw sensor data, detects complex patterns indicating potential issues, and incorporates and learns from a wide range of data, including textual data such as maintenance logs, operational notes, or alarm messages. As a result, our inventive system and method provide comprehensive, efficient, and predictive monitoring of wind turbines.

    OptiSenseGPT: Context-Aware Anomaly Detection with Natural Language Alerts and ActionableRecommendations for Distributed Fiber Optic Sensing Applications

    公开(公告)号:US20250147992A1

    公开(公告)日:2025-05-08

    申请号:US18935495

    申请日:2024-11-02

    Abstract: Disclosed are integrated systems and methods providing intelligent anomaly detection for DFOS systems and applications, the systems and methods utilizing a natural language processing model, such as ChatGPT, to generate real-time alerts with actionable recommendations and potential consequences based on detected anomalies. Our innovative solution—OptiSenseGPT—solves problems left uncured by traditional methods by delivering easily understandable alerts in natural language, enabling timely response by relevant personnel. Our integrated OptiSenseGPT systems and methods disclosed provide context-aware recommendations and consequences, enhancing decision-making and improving overall performance and safety of a monitored infrastructure or environment. Our OptiSenseGPT systems and methods advantageously provide integration of natural language processing; context-aware recommendations; presentation of potential consequences; adaptability and customization; and seamless integration.

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