Systems, methods and apparatus for data collection in an industrial environment are described. Signals from a plurality of analog sensors may be routed via an analog crosspoint switch which includes at least one high current output drive circuit suitable for routing an analog signal. The switch may be configured with data routing information from a data collection template where the routing includes switching a portion of the analog signals to a portion of the plurality of analog signal paths.

Method of back-calculation for determining candidate sources of data collection for data that contributes to a condition of an industrial machine are disclosed. Methods may include determining a condition of interest, following routes of data collection determined from a configuration and operational template, determining a data collection template configured for collecting and processing data from the contributing data, and updating the operational template of the data collection system in response to the determined data collection template.

A computing device divides a training image into a plurality of training blocks, and the training image includes a training object. The computing device calculates, for each of the training blocks, a correct confidence score of the training object covering the training block according to an image-marking data and a confidence-score-translating function, and the image-marking data includes a piece of location information of the training object in the training image. Then, the computing device trains a deep-learning model with the training image, the correct confidence scores and the image-marking data to generate the object-detecting model.

An automated method and system for validating (cross-validating) data fields in an electronic document, such as a document that has been passed through an optical character recognition (“OCR”) or Intelligent Document Recognition (“IDR”) system or software, to improve accuracy of the electronic document.

A method for acquiring privacy-enhancing encodings in an optical domain before image capture is presented. The method includes feeding a differentiable sensing model with a plurality of images to obtain encoded images, the differentiable sensing model including parameters for sensor optics, integrating the differentiable sensing model into an adversarial learning framework where parameters of attack networks, parameters of utility networks, and the parameters of the sensor optics are concurrently updated, and, once adversarial training is complete, validating efficacy of a learned sensor design by fixing the parameters of the sensor optics and training the attack networks and the utility networks to learn to estimate private and public attributes, respectively, from a set of the encoded images.

Methods and systems for data collection for a chemical or pharmaceutical production process is disclosed. The system according to one disclosed non-limiting embodiment of the present disclosure can include a plurality of data collectors including a swarm of self-organized data collector members, wherein the swarm of self-organized data collector members organize to enhance data collection based on at least one of capabilities and conditions of the data collector members of the swarm, and wherein the plurality of data collectors is coupled to a plurality of input channels for acquiring collected data relating to the chemical or pharmaceutical production process, and a data acquisition and analysis circuit for receiving the collected data via the plurality of input channels and structured to analyze the received collected data using a neural network to monitor a plurality of conditions relating to the chemical or pharmaceutical production process.

Methods and systems for detection in an industrial Internet of Things (IoT) data collection environment with intelligent data collection and equipment package adjustment for oil and gas equipment are disclosed. An example monitoring system for data collection in an oil and gas production environment can include a data collector communicatively coupled to a plurality of input channels connected to data collection points operatively coupled to at least one piece of equipment of an equipment package of the oil and gas production environment. The system further includes a data acquisition circuit to interpret detection values from the plurality of input channels and a data analysis circuit to utilize an expert system diagnostic tool to identify an off-nominal process state based on the detection values. The system may further include a response circuit to adjust an equipment package parameter in response to the off-nominal process state.

Methods and systems for noise detection and removal in a motor are disclosed. An example system for monitoring a plurality of components of a motor in an industrial environment may include a data acquisition circuit to interpret a plurality of detection values, each detection value corresponding to a plurality of input sensors operationally coupled to the motor; a data processing circuit to utilize at least one of the detection values to perform at least one noise processing operation on at least a portion of the detection values; a signal evaluation circuit to determine a motor performance parameter in response to the noise processed portion of the of detection values; and a response circuit structured to perform at least one operation in response to the motor performance parameter.

Methods and systems for data collection in an industrial environment with haptic feedback and data communication and bandwidth control are disclosed. A system can include a data collector to collect data based on a selected data collection routine, a data storage to store a plurality of collector routes and data, a data acquisition circuit to interpret the data and determine an occurrence of an anomalous condition, a data analysis circuit to evaluate a data communication constraint and adjust a volume of data communicated between the input channels and the data storage, wherein the data analysis circuit determines an aggregate rate of data being collected, and, if the aggregate rate exceeds a current bandwidth allocation rate, request an increase to the current bandwidth allocation rate, and a haptic user device for generating a haptic stimulation in response an occurrence of a specified anomalous condition.

Methods and systems for detection in an industrial internet of things data collection environment with intelligent data collection and equipment package adjustment for a production line are disclosed. An example system includes a data collector communicatively coupled to a plurality of input channels connected to data collection points operatively coupled to at least one piece of equipment of an equipment package of the production environment and a data acquisition circuit structured to interpret a plurality of detection values from the plurality of input channels. A data analysis circuit utilizes an expert system diagnostic tool to identify an off-nominal process state in response to the plurality of detection values and a response circuit adjusts an equipment package parameter in response to the off-nominal process state.