A hybrid sensing apparatus for collecting data inside a well, the apparatus including an optical cable that acquires a first set of data; and an array of discrete probes connected to each other with an electrical cable. The discrete probes are configured to acquire a second set of data. The apparatus further includes an attachment system attached to the discrete probes and configured to hold the optical cable. The attachment system is configured to expose the optical cable to directly contact the well.

A mine safety apparatus, and related method, that records movement data of a scene, visual images of the scene and correlates the movement data with the visual images. The apparatus comprises: a slope monitoring device that records location data in the scene and tracks the location data over time to identify movement and produce visual movement overlays; an image capture device that records a plurality of visual images of the scene from a location; and a processor that stitches the visual images into a panoramic image of the entire scene and for selected Points of Interest in the scene accurately determines a coordinate so that the visual movement overlays are correctly correlated with the Points of Interest.

A mine safety apparatus, and related method, that records movement data of a scene, visual images of the scene and correlates the movement data with the visual images. The apparatus comprises: a slope monitoring device that records location data in the scene and tracks the location data over time to identify movement and produce visual movement overlays; an image capture device that records a plurality of visual images of the scene from a location; and a processor that stitches the visual images into a panoramic image of the entire scene and for selected Points of Interest in the scene accurately determines a coordinate so that the visual movement overlays are correctly correlated with the Points of Interest.

An object detection apparatus includes a sensor module including a sensor, and a controller that controls the sensor and generates output information, based on a signal that the sensor outputs; and a detector that determines presence or absence of the object, based on the output information. The detector executes a reference object detection process of detecting a reference object existing at a predetermined position within the detection range, by comparing the output information and predetermined reference information, and, when the reference object is detected, executes a correction process of correcting at least one of the output information or a parameter for the sensor, based on the reference information and reference object information that is information indicative of the reference object in the output information.

A permittivity sensor, for determining an image of a distribution of permittivity of a material of an object in a scene, comprising an input interface, a hardware processor, and an output interface is provided. The input interface is configured to accept phaseless measurements of propagation of a known incident field through the scene and scattered by the material of the object in the scene. The hardware processor is configured to solve a multi-variable minimization problem over unknown phases of the phaseless measurements and unknown image of the permittivity of the material of the object by minimizing a difference of a nonlinear function of the known incident field and the unknown image with a product of known magnitudes of the phaseless measurements and the unknown phases. Further, the output interface is configured to render the permittivity of the material of the object provided by the solution of the multi-variable minimization problem.

A permittivity sensor, for determining an image of a distribution of permittivity of a material of an object in a scene, comprising an input interface, a hardware processor, and an output interface is provided. The input interface is configured to accept phaseless measurements of propagation of a known incident field through the scene and scattered by the material of the object in the scene. The hardware processor is configured to solve a multi-variable minimization problem over unknown phases of the phaseless measurements and unknown image of the permittivity of the material of the object by minimizing a difference of a nonlinear function of the known incident field and the unknown image with a product of known magnitudes of the phaseless measurements and the unknown phases. Further, the output interface is configured to render the permittivity of the material of the object provided by the solution of the multi-variable minimization problem.

A pet watering system. The pet watering system includes a housing and a waterspout. The waterspout is connected to a water source and is configured to allow water to stream from the water source to the exterior of the housing. The pet watering system also includes a trough, where the trough is configured to receive water that has streamed from the waterspout. The pet watering system further includes a proximity sensor, where the proximity sensor is configured to allow a pet to control the flow of water from the reservoir to the waterspout.

A measuring device for a tube is disclosed. The measuring device includes a drift tool configured to verify roundness of the tube, a first electromagnetic (EM) emitter disposed on the drift tool and configured to emit EM waves while the drift tool drifts inside the tube, and an EM receiver disposed on the drift tool and configured to receive the EM waves reflected from an internal surface of the tube, wherein parameters of the emitted and received EM waves are analyzed to compute an internal diameter of the tube.

The subject disclosure provides for a method of optical sensor calibration implemented with neural networks through machine learning to make real-time optical fluid answer product prediction adapt to optical signal variation of synthetic and actual sensor inputs integrated from multiple sources. Downhole real-time fluid analysis can be performed by monitoring the quality of the prediction with each type of input and determining which type of input generalizes better. The processor can bypass the less robust routine and deploy the more robust routine for remainder of the data prediction. Operational sensor data can be incorporated from a particular optical tool over multiple field jobs into an updated calibration when target fluid sample compositions and properties become available. Reconstructed fluid models adapted to prior field job data, in the same geological or geographical area, can maximize the likelihood of quality prediction on future jobs and optimize regional formation sampling and testing applications.

An apparatus includes a cassette configured to hold optical fiber comprising one or more optical sensors. The cassette comprises a spool configured to one or more of extract and retract the optical fiber from the cassette. A fiber monitor is coupled to the cassette. The fiber monitor is configured to monitor at least one parameter of the optical fiber as the optical fiber is extracted from the cassette.