Abstract: According to one example embodiment, an optical fiber sensor includes an optical fiber cable and a device body configured to cause an optical pulse signal to be incident on the optical fiber cable and identify, from intensity change of backscattered light of the incident optical pulse signal and an arrival time of the backscattered light, a prescribed environmental change having occurred in a vicinity of the optical fiber cable and an occurrence location of the environmental change, in which the device body performs correction of a sensing location on the optical fiber cable, based on environmental change information including the identified occurrence location and installation location information of the optical fiber cable.

Abstract: An AI-driven cable mapping system that employs distributed fiber optic sensing (DFOS) fiber sensing and machine learning that provides autonomous determination of fiber optic cable location and mapping of same. Designed Al algorithms operating within our inventive systems and methods provide an easy solution for cable mapping in a GIS system; automatically maps using landmarks and manhole locations; and employs a supervised learning algorithm. A vehicle-assist operation is employed wherein a vehicle carries a Global Positioning System (GPS) device and drives along a roadway thereby following the fiber optic cable route; data paring that provides further significant locational information wherein time synchronizes between the DFOS system and vehicle GPS device from which we automatically pair the data of fiber length from traffic trajectories and GPS coordinates by time series.

Abstract: A structure deterioration detection system includes an optical fiber cable that is placed along the longitudinal direction of a structure and continuously detects any vibration along the longitudinal direction of the structure, and a signal processing unit including a vibration measurement unit that measures the strength of a detected vibration, a per unit time integration unit that integrates the vibration strength for a specified period of time, an information storage unit that stores the integrated vibration strength, and a deterioration determination unit that makes a determination about whether deterioration of the structure has occurred by comparing the integrated vibration strengths at different times.

Abstract: A traffic monitoring apparatus includes: at least one memory storing instructions; and at least one processor. The processor is configured to execute the instructions to; acquire waterfall data from a distributed acoustic sensor (DAS), wherein the waterfall data includes a generation position of a vibration on a roadway adjacent to the DAS, a generation time of the vibration and an amplitude of the vibration; preprocess the waterfall data; estimate at least one enhancement of the processed waterfall data, wherein an enhancement corresponds to a traffic flow property; and estimate at least one traffic flow property of the roadway from the enhancements of the processed waterfall data.

Abstract: The present disclosure provides a traffic prediction apparatus, system, method and program capable of predicting the number of vehicles and the speed of vehicles in a predetermined time and in a predetermined range based on waterfall data of vehicles. The traffic prediction apparatus comprises acquisition means for acquiring waterfall data comprising a generation position of a vibration, a generation time of the vibration and an amplitude of the vibration generated by a vehicle traveling on a road, pre-processing means for transforming the acquired waterfall data, generation means for training a portion of the plurality of processed waterfall data and at least one corresponding ground truth traffic property used as plurality of labels to generate a trained model, wherein the ground truth may be obtained from a secondary acquisition means, and prediction means for predicting at least one traffic property for a processed waterfall data.

Abstract: According to one example embodiment, an optical fiber sensor includes an optical fiber cable and a device body configured to cause an optical pulse signal to be incident on the optical fiber cable and identify, from intensity change of backscattered light of the incident optical pulse signal and an arrival time of the backscattered light, a prescribed environmental change having occurred in a vicinity of the optical fiber cable and an occurrence location of the environmental change, in which the device body performs correction of a sensing location on the optical fiber cable, based on environmental change information including the identified occurrence location and installation location information of the optical fiber cable.

Abstract: Provided are a structure deterioration detection system and a structure deterioration detection method capable of detecting deterioration of a structure at low cost. In one example embodiment, a structure deterioration detection system includes an optical fiber cable that is placed along the longitudinal direction of a structure and continuously detects any vibration along the longitudinal direction of the structure, and a signal processing unit including a vibration measurement unit that measures the strength of a detected vibration, a per unit time integration unit that integrates the vibration strength for a specified period of time, an information storage unit that stores the integrated vibration strength, and a deterioration determination unit that makes a determination about whether deterioration of the structure has occurred by comparing the integrated vibration strengths at different times.

Abstract: A traffic monitoring apparatus includes a distributed acoustic sensor (DAS) for acquiring waterfall data, wherein the waterfall data includes a generation position of a vibration on a roadway adjacent to the DAS, a generation time of the vibration and an amplitude of the vibration. The traffic monitoring apparatus further includes a processor connected to the DAS. The processor is configured to receive the waterfall data from the DAS. The processor is further configured to preprocess the waterfall data. The processor is further configured to separate the preprocessed waterfall data into a plurality of patches, wherein a size of each patch of the plurality of patches is determined based on a parameter of the roadway. The processor is further configured to process each of the plurality of patches to estimate at least one traffic flow property of the roadway.

Abstract: A purpose of the present disclosure is to provide a source separation method, a non-transitory computer readable medium, and a source separation apparatus. The source separation apparatus includes an input means for inputting mixture data obtained by mixing a plurality of data; and a matrix decomposition means for separating the input mixture data by estimating a mixing/unmixing matrix, a basis matrix for each source, an activations matrix for each source and a reliability vector for each source, and a means for unmixing of input mixture data using the estimated matrices from the matrix decomposition means to estimate the sources.

Abstract: A traffic monitoring apparatus includes a distributed acoustic sensor (DAS) for acquiring waterfall data, wherein the waterfall data includes a generation position of a vibration on a roadway adjacent to the DAS, a generation time of the vibration and an amplitude of the vibration. The traffic monitoring apparatus further includes a processor connected to the DAS. The processor is configured to receive the waterfall data from the DAS. The processor is further configured to preprocess the waterfall data. The processor is further configured to separate the preprocessed waterfall data into a plurality of patches, wherein a size of each patch of the plurality of patches is determined based on a parameter of the roadway. The processor is further configured to process each of the plurality of patches to estimate at least one traffic flow property of the roadway.