Fiber sensing on roadside applications

    公开(公告)号:US12154007B2

    公开(公告)日:2024-11-26

    申请号:US16229676

    申请日:2018-12-21

    Abstract: A fiber-based roadside condition sensing system is provided. The system includes a fiber optic cable arranged in various roadside locations for Distributed Vibration Sensing (DVS) and Distributed Acoustic Sensing (DAS) at the various roadside locations. The system further includes a machine-learning-based analyzer for selectively providing any of an early warning and a prevention of various detected conditions responsive to a machine-learning-based analysis of results from the DVS and the DAS.

    Intent-based network computing job assignment

    公开(公告)号:US12047242B2

    公开(公告)日:2024-07-23

    申请号:US18481988

    申请日:2023-10-05

    CPC classification number: H04L41/0896 H04L41/122

    Abstract: Described is a novel framework, we call intent-based computing jobs assignment framework, for efficiently accommodating a clients' computing job requests in a mobile edge computing infrastructure. We define the intent-based computing job assignment problem, which jointly optimizes the virtual topology design and virtual topology mapping with the objective of minimizing the total bandwidth consumption. We use the Integer Linear Programming (ILP) technique to formulate this problem, and to facilitate the optimal solution. In addition, we employ a novel and efficient heuristic algorithm, called modified Steiner tree-based (MST-based) heuristic, which coordinately determines the virtual topology design and the virtual topology mapping. Comprehensive simulations to evaluate the performance of our solutions show that the MST-based heuristic can achieve an efficient performance that is close to the optimal performance obtained by the ILP solution.

    FAST OPTICAL CABLE IDENTIFICATION USING ACOUSTIC PEN

    公开(公告)号:US20240235668A1

    公开(公告)日:2024-07-11

    申请号:US18485198

    申请日:2023-10-11

    CPC classification number: H04B10/073 G01H9/004

    Abstract: A fast optical fiber identification system and method employing an acoustic pen that is connected to a portable device (such as a laptop, a smartphone, an iPad). The pen generates acoustic signals under the control of the portable device. The portable device interacts with a DFOS (Distributed Fiber Optic Sensor, e.g., a DAS or DVS) interrogator to notify the interrogator about the generated signals and receives a detection result from the interrogator. The result is either illustrated using a graph on the portable device, or as a tone of different volume, to indicate the strength of the pen's signal detected by the interrogator. As the pen touches/excites vibrationally/acoustically each of the fibers, the portable device notifies the user about the detected signal's strength or presence/no-presence, which allows a technician to quickly identify the fiber of interest.

    Distributed fiber optic sensor placement

    公开(公告)号:US12028110B2

    公开(公告)日:2024-07-02

    申请号:US17713171

    申请日:2022-04-04

    CPC classification number: H04B10/27 H04Q11/0062 H04Q2011/009

    Abstract: A procedure to solve the DFOS placement problem that uses a genetic algorithm to achieve a global optimization of sensor placement. First, our procedure according to aspects of the present disclosure defines a fitness function that counts the number of DFOS sensors used. Second, the procedure uses a valid DFOS placement assignment to model an individual in the genetic algorithm. Each individual consists of N genes, where N is the number of nodes in the given network infrastructure, e.g., N=|V|. Each gene has two genomes: (1) a list of 0s and/or 1s, in which is represent the network nodes that are equipped with DFOS sensors, and 0s represent the nodes that are not equipped with DFOS sensors; (2) a list of sensing fiber routes. An individual that has smallest number of is in their genes will be considered as the strongest individual. Thirdly, the procedure randomly generates a population of individuals. After a certain number of generations of population, the strongest individual in the last generation will be the global optima for the DFOS placement assignment.

    Contrastive learning of utility pole representations from distributed acoustic sensing signals

    公开(公告)号:US11698290B2

    公开(公告)日:2023-07-11

    申请号:US17714091

    申请日:2022-04-05

    CPC classification number: G01H9/004

    Abstract: Systems and methods for operating a distributed fiber optic sensing (DFOS)/distributed acoustic sensing (DAS) system include a length of optical sensing fiber suspended aerially by a plurality of utility poles and in optical communication with a DFOS interrogator/analyzer. The method includes operating the DFOS/DAS system while manually exciting more than one of the poles to obtain frequency response(s) of the excited poles; contrastively training a convolutional neural network (CNN) with the frequency responses obtained; classifying the utility poles using the contrastively trained CNN; and generating a profile map of the excited poles indicative of the classified utility poles.

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