Abstract: Distributed fiber optic sensing (DFOS) systems, methods and structures for determining the proximity of vibration sources located perpendicular to a sensor fiber that is part of the DFOS system that may potentially threaten/damage or otherwise compromise the sensor fiber itself. Systems, methods, and structures according to aspects of the present disclosure employ Artificial Intelligence (AI) methodology(ies) that use as input a fundamental physical understanding of wave propagation and attenuation in the ground along with Bayesian inference and Maximum Likelihood Estimation (MLE) techniques for estimating/determining the proximity of potentially damaging vibration sources to the optical sensor fiber.

Abstract: Aspects of the present disclosure describe systems, methods and structures for determining any location on a deployed fiber cable from an optical time domain reflectometry (OTDR) curve using a movable mechanical vibration source to stimulate tiny vibration of fiber in deployed fiber cable along the cable route and a fiber sensing system at a central office to detect the vibration(s). Latitude and longitude of the location(s) of the vibration source is measured with a GPS device and a dynamic-OTDR distance is measured at central office (CO) simultaneously. The collected GPS location data and corresponding dynamic-OTDR distance data are paired and saved into a database. This saved data may be processed to graphically overlie a map thereby providing exact cable location on the map thereby providing carriers/service providers the ability to improve fiber fault location on a deployed fiber cable much faster and more accurately than presently possible using methods available in the art.

Abstract: A device may receive, from a fiber sensor device, sensing data associated with a fiber optic cable, the sensing data being produced by an activity that poses a threat of damage to the fiber optic cable, and the sensing data identifying: amplitudes of vibration signals, frequencies of the vibration signals, patterns of the vibration signals, times associated with the vibration signals, and locations along the fiber optic cable associated with the vibration signals. The device may process, with a machine learning model, the sensing data to determine a threat level of the activity to the fiber optic cable, the machine learning model having been trained based on historical information regarding detected vibrations, historical information regarding sources of the detected vibrations, and historical information regarding threat levels to the fiber optic cable. The device may perform one or more actions based on the threat level to the fiber optic cable.

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.

Abstract: Aspects of the present disclosure describe distributed fiber optic sensing (DFOS) systems, methods, and structures that advantageously enable anomaly detection resulting from construction—or other activity based on image processing that may advantageously detect/notify/prevent damage to a fiber optic network infrastructure before such damage occurs.

Abstract: Aspects of the present disclosure describe single mode fiber distributed temperature sensing (DTS) with improved noise characteristics employing superluminescent emitting diodes (SLEDs) and/or amplified spontaneous emission (ASE) light sources.

Abstract: Methods and systems for training a neural network include generate an image of a mask. A copy of an image is generated from an original set of training data. The copy is altered to add the image of a mask to a face detected within the copy. An augmented set of training data is generated that includes the original set of training data and the altered copy. A neural network model is trained to recognize masked faces using the augmented set of training data.

Abstract: Aspects of the present disclosure describe physical layer security in optical telecommunications networks wherein a filtering-based physical security is provided by a wavelength tunable distributed fiber optical sensing (DFOS) system operating simultaneously on the telecommunications network.

Abstract: Aspects of the present disclosure describe distributed fiber optic sensing (DFOS) systems, methods, and structures that advantageously enable smart refrigeration systems including retail.

Abstract: An advance in the art is made according to aspects of the present disclosure directed to distributed fiber optic sensing systems (DFOS), methods, and structures that advantageously monitor and identify—in real-time—roadway traffic and patterns across a multiple-lane highway by employing a multiple-transverse fiber optic cable arrangement of optical fiber cable positioned under the highway/roadway to detect, monitor, and/or identify traffic.

Abstract: Aspects of the present disclosure describe distributed fiber optic sensing (DFOS) systems, methods, and structures that advantageously are employed in smart stadium or other venue applications, such applications including: parking lot security and management; intrusion detection; social sensing; air quality monitoring and early fire detection—among others.

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.

Abstract: Aspects of the present disclosure describe hybrid distributed fiber optic sensing systems, methods, and structures that advantageously are extensions of existing fiber optic infrastructure and provide distributed fiber optic sensing (DFOS) functionality to the existing infrastructure.

Abstract: Aspects of the present disclosure describe distributed fiber optic sensing systems, methods, and structures that advantageously are employed to determine the location and depth of underground fiber-optic facilities that may be carrying telecommunications traffic.

Abstract: Aspects of the present disclosure describe distributed fiber optic sensing (DFOS) systems, methods, and structures that advantageously measure wind speed at utility poles that support fiber optic cables and—in many applications—electrical and/or other communications cables (i.e., cable television).

Abstract: Aspects of the present disclosure describe optical fiber sensing systems, methods and structures disclosing a distributed optical fiber sensor network constructed on a switched optical fiber telecommunications infrastructure to detect temperatures, acoustic effects, and vehicle traffic—among others—demonstrated with a number of different network topologies.

Abstract: Aspects of the present disclosure describe systems, methods and structures providing detection and localization of disaster-related indoor events via hybrid ethernet/optical fiber cable.

Abstract: A device may receive, from a sensor device, cable distance data identifying cable distances along a fiber cable to vibrations experienced by the fiber cable, and may receive location data identifying locations associated with the vibrations. The device may correlate the cable distance data and the location data to generate correlated location data, and may store the correlated location data in a data structure. The device may receive, from the sensor device, data identifying a cable distance along the fiber cable to an alarm condition associated with the fiber cable, and may determine a location of the alarm condition based on the correlated location data and the data identifying the cable distance along the fiber cable to the alarm condition. The device may perform actions based on the alarm location.

Abstract: Aspects of the present disclosure describe single mode fiber distributed temperature sensing (DTS) with improved noise characteristics employing superluminescent emitting diodes (SLEDs) and/or amplified spontaneous emission (ASE) light sources.

Abstract: Aspects of the present disclosure describe systems, methods and structures providing non-destructive localization of underground optical fiber cables utilizing distributed fiber optic sensing (DFOS) and time difference of arrival techniques.