Patents Assigned to Insight, Inc.
  • Patent number: 10798598
    Abstract: A large-scale radio frequency signal information processing and analysis system that provides advanced signal analysis for telecommunication applications, including band capacity and geographical density determinations and detection, classification, identification, and geolocation of signals across a wide range of frequencies and across broad geographical areas. The system may utilize a range of novel algorithms for bin-wise processing, Rayleigh distribution analysis, telecommunication signal classification, receiver anomaly detection, transmitter density estimation, transmitter detection and location, geolocation analysis, telecommunication activity estimation, telecommunication utilization estimation, frequency utilization estimation, and data interpolation.
    Type: Grant
    Filed: March 3, 2020
    Date of Patent: October 6, 2020
    Assignee: AURORA INSIGHT INC.
    Inventors: Jennifer Alvarez, Benjamin Kempke, Wyatt Tyree, Michael Skaug
  • Publication number: 20200304376
    Abstract: A method, system, and computer program product to manage a network comprising a plurality of interconnected components are described. The method includes obtaining a set of all the components that are part of the network over time, and identifying one or more repeating patterns of components among the set of all the components as corresponding lower-level definitions to generate a hierarchical set of all the components. The method also includes obtaining time-varying information regarding topology and operational values within the network, and creating a representation of the network at a set of times based on the hierarchical set of all the components and the time-varying information.
    Type: Application
    Filed: February 25, 2020
    Publication date: September 24, 2020
    Applicant: Utopus Insights, Inc.
    Inventors: Ulrich A. Finkler, Fook-Luen Heng, Steven N. Hirsch, Mark A. Lavin, Jun Mei Qu, Amith Singhee, Wei Wu
  • Publication number: 20200289839
    Abstract: Magnetic particle actuating systems may include a magnet system configured to generate a magnetic field that includes a field-free region. A corresponding control system can be configured to control the magnet system to create a field-free region at least partially matching a target region. An excitation system can be configured to generate an excitation field to cause actuation of magnetic nanoparticles in an actuation region.
    Type: Application
    Filed: March 13, 2020
    Publication date: September 17, 2020
    Applicant: Magnetic Insight, Inc.
    Inventors: Daniel Westbrook Hensley, Matthias Weber, Elaine Yuiyi Yu, Robert Blayne Kettlewell, Kyle David Fields, Patrick William Goodwill
  • Patent number: 10779179
    Abstract: A large-scale radio frequency signal collection and processing system comprising a plurality of sensor systems mounted on a plurality of collection platforms that integrates a plurality of overlapping datasets with differing characteristics (e.g., different resolutions, different view angles, different heights, different time periods, unrelated types of data) to generate an enriched dataset or datasets using a variety of processing techniques (e.g., statistical analysis, signal processing, image processing) that allows for more comprehensive analysis of the radio frequency signal landscape than would be possible using any of the datasets individually, or in combination but without such integration.
    Type: Grant
    Filed: March 18, 2020
    Date of Patent: September 15, 2020
    Assignee: AURORA INSIGHT INC.
    Inventors: Brian Thomas Mengwasser, Jennifer L. Alvarez, Augustus S. Moore
  • Patent number: 10775452
    Abstract: A Magnetic Particle Imaging (MPI) system with a magnet configured to generate a magnetic field having a field free line, the system including at least one shim magnet configured to modify the magnetic field in a manner to maintain desired magnetic flux distributions during imaging.
    Type: Grant
    Filed: July 12, 2017
    Date of Patent: September 15, 2020
    Assignees: MAGNETIC INSIGHT, INC., UNIVERSITY OF CALIFORNIA AT BERKELEY
    Inventor: Patrick W. Goodwill
  • Patent number: 10778529
    Abstract: A system and method of managing a network that includes assets are described. The method includes modeling the network as a directed graph with each of the assets represented as a node and determining alternative paths to each node from each available corresponding source of the node. The method also includes computing upstream robustness of each node, computing upstream robustness of the network, and computing downstream criticality of each node. Managing the network and each asset of the network is based on the upstream robustness and the downstream criticality of each node.
    Type: Grant
    Filed: June 5, 2018
    Date of Patent: September 15, 2020
    Assignee: Utopus Insights, Inc.
    Inventors: Aanchal Aggarwal, Harsh Chaudhary, Yakup KoƧ, Younghun Kim, Tarun Kumar, Abhishek Raman
  • Patent number: 10751008
    Abstract: A medical imaging system for detecting ionizing radiation. The system includes one or more pixilated imagers positioned to acquire patient image data and one or more position sensors positioned to acquire patient position data. Once the patient image data and patient position data are acquired, one or more processors operably connected to each of the one or more pixilated imagers and one or more position sensors calculate a three-dimensional mass distribution based on patient image data and patient position data.
    Type: Grant
    Filed: May 6, 2019
    Date of Patent: August 25, 2020
    Assignee: IMAGE INSIGHT, INC.
    Inventors: Eric P. Rubenstein, Peter R. Solomon, Gordon A. Drukier, Marek A. Wojtowicz, Joseph E. Cosgrove, Michael A. Serio, James R. Markham, Kenneth W. Wang, William M. Pramenko
  • Patent number: 10732228
    Abstract: An apparatus for estimating a condition of a battery includes a mode identifying unit configured to identify a usage mode of the battery during a period of time and its corresponding attenuation curve, according to recorded data on battery usage, stored usage modes of the battery and attenuation curves corresponding to the various usage modes, the attenuation curve representing a change of a fully charged capacity of the battery with battery usage; and a condition estimating unit configured to calculate battery degradation according to the recorded data, the identified usage mode and its corresponding attenuation curve, the degradation representing a quantity of the fully charged capacity of the battery that is reduced over the battery usage. The condition of the battery is estimated so as to rationally judge the residual value of the battery in operation.
    Type: Grant
    Filed: January 30, 2014
    Date of Patent: August 4, 2020
    Assignee: Utopus Insights, Inc.
    Inventors: Jin Dong, Carlton Gammons, Jin Yan Shao, Qi Ming Tian, Ming Xie, Wen Jun Yin, Hong Guang Yu, Li Li Zhao
  • Publication number: 20200219116
    Abstract: A method for generating a preferred assortment of products that are intended to be offered for sale in a future time period.
    Type: Application
    Filed: January 3, 2020
    Publication date: July 9, 2020
    Applicant: First Insight, Inc.
    Inventors: Mangalprasad ANANDAN, Nicholas PETRO
  • Publication number: 20200209841
    Abstract: An example method comprises receiving historical sensor data of a renewable energy asset for a first time period, identifying historical log data in one or more log sources, retrieving dates of the identified historical log data, retrieving sequences of historical sensor data using the dates, training hidden Markov models using the sequences of historical sensor data to identify probability of shifting states of one or more components of the renewable energy asset, receiving current sensor data of a second time period, identifying current log data in the one or more log sources, retrieving dates of the identified current log data, retrieving sequences of current sensor data using the dates, applying the hidden Markov models to the sequences of the current sensor data to assess likelihood of the one or more faults, creating a prediction of a future fault, and generating a report including the prediction of the future fault.
    Type: Application
    Filed: December 27, 2018
    Publication date: July 2, 2020
    Applicant: Utopus Insights, Inc.
    Inventors: Guruprasad Srinivasan, Younghun Kim
  • Publication number: 20200210854
    Abstract: An example method comprises receiving historical sensor data of a first time period, the historical data including sensor data of a renewable energy asset, extracting features, performing a unsupervised anomaly detection technique on the historical sensor data to generate first labels associated with the historical sensor data, performing at least one dimensionality reduction technique to generate second labels, combining the first labels and the second labels to generate combined labels, generating one or more models based on supervised machine learning and the combined labels, receiving current sensor data of a second time period, the current sensor data including sensor data of the renewable energy asset, extracting features, applying the one or more models to the extracted features of the current sensor data to create a prediction of a future fault in the renewable energy asset, and generating a report including the prediction of the future fault in the energy asset.
    Type: Application
    Filed: December 27, 2018
    Publication date: July 2, 2020
    Applicant: Utopus Insights, Inc.
    Inventors: Guruprasad Srinivasan, Younghun Kim, Tarun Kumar
  • Publication number: 20200210537
    Abstract: An example method comprises receiving historical sensor data from sensors of components of wind turbines, training a set of models to predict faults for each component using the historical sensor data, each model of a set having different observation time windows and lead time windows, evaluating each model of a set using standardized metrics, comparing evaluations of each model of a set to select a model with preferred lead time and accuracy, receive current sensor data from the sensors of the components, apply the selected model(s) to the current sensor data to generate a component failure prediction, compare the component failure prediction to a threshold, and generate an alert and report based on the comparison to the threshold.
    Type: Application
    Filed: December 27, 2018
    Publication date: July 2, 2020
    Applicant: Utopus Insights, Inc.
    Inventors: Yajuan Wang, Gabor Solymosi, Younghun Kim
  • Publication number: 20200209430
    Abstract: An example method comprises receiving first historical meso-scale numerical weather predictions (NWP) and power flow information for a geographic distribution area, correcting for overfitting of the historical NWP predictions, reducing parameters in the first historical NWP predictions, training first power flow models using the first reduced, corrected historical NWP predictions and the historical power flow information for all or parts of the first geographic distribution area, receiving current NWP predictions for the first geographic distribution area, applying any number of first power flow models to the current NWP predictions to generate any number of power flow predictions, comparing one or more of the any number of power flow predictions to one or more first thresholds to determine significance of reverse power flows, and generating a first report including at least one prediction of the reverse power flow and identifying the first geographic distribution area.
    Type: Application
    Filed: December 28, 2018
    Publication date: July 2, 2020
    Applicant: Utopus Insights, Inc.
    Inventors: Srivats Shukla, Younghun Kim, Aijun Deng
  • Publication number: 20200210824
    Abstract: An example method utilizing different pipelines of a prediction system, comprises receiving failure data, and asset data from SCADA system(s), receiving and dividing historical sensor data from sensors of components of wind turbines into different classes of different lead times, training a set of models to predict faults for each component using the historical sensor data and lead times with a deep neural network, evaluating each model of a set using standardized metrics, comparing evaluations of each model of a set to select a model with preferred lead time and accuracy, receive current sensor data from the sensors of the components, apply the selected model(s) to the current sensor data to generate a component failure prediction, compare the component failure prediction to a threshold, and generate an alert and report based on the comparison to the threshold.
    Type: Application
    Filed: December 28, 2018
    Publication date: July 2, 2020
    Applicant: Utopus Insights, Inc.
    Inventors: Zahra Mahmoodzadeh Poornaki, Yajuan Wang, Younghun Kim
  • Publication number: 20200210538
    Abstract: An example method utilizing different pipelines of a prediction system, comprises receiving event and alarm data from event logs, failure data, and asset data from SCADA system(s), retrieve patterns of events, receiving historical sensor data from sensors of components of wind turbines, training a set of models to predict faults for each component using the patterns of events and historical sensor data, each model of a set having different observation time windows and lead time windows, evaluating each model of a set using standardized metrics, comparing evaluations of each model of a set to select a model with preferred lead time and accuracy, receive current sensor data from the sensors of the components, apply the selected model(s) to the current sensor data to generate a component failure prediction, compare the component failure prediction to a threshold, and generate an alert and report based on the comparison to the threshold.
    Type: Application
    Filed: December 27, 2018
    Publication date: July 2, 2020
    Applicant: Utopus Insights, Inc.
    Inventors: Yajuan Wang, Gabor Solymosi, Ede Szarka, Younghun Kim
  • Patent number: 10699280
    Abstract: An ingredient data system that ingests text and graphics of product labels associated with consumer products generally includes a memory having instructions stored thereon; and at least one processor to execute the instructions to transmit via a network a representation of a label view to a user interface on a client computing device that displays one or more of the master attributes associated with the first request, at least a portion of each of the images of one or more of the product labels of the consumer products having the one or more master attributes associated with the first request and at least a portion of the sales history, and at least a portion of each of the images of one or more of the product labels associated with the related consumer products and at least a portion of a sales history.
    Type: Grant
    Filed: June 29, 2018
    Date of Patent: June 30, 2020
    Assignee: Label Insight, Inc.
    Inventors: Ronak Sheth, Anton Xavier, Dagan Xavier, Dheeraj Patri, Tyler Trollinger, Harrison Nguyen, John Castaldo, Jeffrey Williams, Abbie Bys, Paul Hutchinson, James Shedlick, Jack Mallers
  • Patent number: 10699284
    Abstract: An ingredient data system that ingests text and graphics of product labels associated with consumer products generally includes a memory having instructions stored thereon; and at least one processor to execute the instructions to transmit via a network a representation of a label view to a user interface on a client computing device that displays one or more of the master attributes associated with the first request, at least a portion of each of the images of one or more of the product labels of the consumer products having one or more of the master attributes associated with the first request, and at least a portion of each of the images of one or more of the product labels associated with the related consumer products having the at least one master attribute different from one or more of the master attributes associated with the first request.
    Type: Grant
    Filed: June 29, 2018
    Date of Patent: June 30, 2020
    Assignee: Label Insight, Inc.
    Inventors: Ronak Sheth, Anton Xavier, Dagan Xavier, Dheeraj Patri, Tyler Trollinger, Harrison Nguyen, John Castaldo, Jeffrey Williams, Abbie Bys, Paul Hutchinson, James Shedlick, Jack Mallers
  • Publication number: 20200201950
    Abstract: An example method comprises receiving event and alarm data from event logs, failure data, and asset data from SCADA system(s), retrieve patterns of events from the SCADA data, receiving historical sensor data from sensors of components of wind turbines, training a set of models to predict faults for each component using the patterns of events and historical sensor data, each model of a set having different observation time windows and lead time windows, evaluating each model of a set using standardized metrics, comparing evaluations of each model of a set to select a model with preferred lead time and accuracy, receive current sensor data from the sensors of the components, apply the selected model(s) to the current sensor data to generate a component failure prediction, compare the component failure prediction to a threshold, and generate an alert and report based on the comparison to the threshold.
    Type: Application
    Filed: December 21, 2018
    Publication date: June 25, 2020
    Applicant: Utopus Insights, Inc.
    Inventors: Yajuan Wang, Younghun Kim
  • Patent number: 10684347
    Abstract: Energy, data and information is obtained about the state of the electromagnetic spectrum and the nature of terrestrial transmissions through the use of a remote spectrum sensing system. The disclosure comprises at least one satellite in orbit around Earth capable of sensing frequencies in use by terrestrial transmitters such as those used for radiocommunication or radiodetermination services. In addition, various processing functions are applied to the collected energy, data and information before and/or after they are relayed to at least one ground station in order to reveal a greater understanding of the state of the spectrum and nature of transmissions. The disclosure relates to the described system in multiple embodiments and the method for obtaining energy, data and information about terrestrially used spectrum with such a system.
    Type: Grant
    Filed: May 2, 2017
    Date of Patent: June 16, 2020
    Assignee: AURORA INSIGHT INC.
    Inventor: Brian Thomas Mengwasser
  • Patent number: 10653995
    Abstract: Disclosed embodiments provide a system and method for producing hydrocarbons from biomass. Certain embodiments of the method are particularly useful for producing substitute natural gas from forestry residues. Certain disclosed embodiments of the method convert a biomass feedstock into a product hydrocarbon by hydropyrolysis. Catalytic conversion of the resulting pyrolysis gas to the product hydrocarbon and carbon dioxide occurs in the presence of hydrogen and steam over a CO2 sorbent with simultaneous generation of the required hydrogen by reaction with steam. A gas separator purifies product methane, while forcing recycle of internally generated hydrogen to obtain high conversion of the biomass feedstock to the desired hydrocarbon product. While methane is a preferred hydrocarbon product, liquid hydrocarbon products also can be delivered.
    Type: Grant
    Filed: September 14, 2017
    Date of Patent: May 19, 2020
    Assignee: G4 Insights Inc.
    Inventors: Bowie G. Keefer, Matthew L. Babicki, Brian G. Sellars, Edson Ng