Patents by Inventor Nicholas U. Christopulos
Nicholas U. Christopulos has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
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Patent number: 11922511Abstract: A method for identifying a primary vehicle associated with a user of a mobile device includes receiving an indication of a vehicle entry event from a mobile device and retrieving sensor data from the mobile device. The method further includes receiving an indication of a vehicle exit event from the mobile device, generating a trip log including portions of the sensor data, and storing the trip log in a trip database. A server, or other suitable computing device, then analyzes the trip log and a plurality of previously stored trip logs in the trip database to determine a primary vehicle corresponding to the user of the mobile device. The method may allow a computing device to assign gathered mobile device data to a specific household vehicle.Type: GrantFiled: October 18, 2021Date of Patent: March 5, 2024Assignee: STATE FARM MUTUAL AUTOMOBILE INSURANCE COMPANYInventors: Nicholas U. Christopulos, Nicholas R. Baker, Eric Bellas, Benjamin F. Bowne
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Patent number: 11783422Abstract: Techniques for implementing machine learning to improve claim handling are disclosed. In some scenarios, the machine-learning, analytics model may be trained in accordance with data that is relevant to insurance products, such as life and health insurance. A set of labeled historical claims each corresponding to a settlement amount may be analyzed to train an artificial neural network. A claim may be received from a user mobile device, and may be analyzed using the trained artificial neural network to predict a claim settlement, which may be used to generate a settlement offer. The settlement offer may be transmitted to the user's mobile device, and if a manifestation of acceptance is received from the user, then the claim may be automatically paid.Type: GrantFiled: September 20, 2018Date of Patent: October 10, 2023Assignee: State Farm Mutual Automobile Insurance CompanyInventors: Gregory L Hayward, Meghan Sims Goldfarb, Nicholas U. Christopulos, Erik Donahue
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Publication number: 20230290066Abstract: In a computer-implemented method and system for capturing the condition of a structure, the structure is scanned with an unmanned aerial vehicle (UAV). Data collected by the UAV corresponding to points on a surface of a structure is received and a 3D point cloud is generated for the structure, where the 3D point cloud is generated based at least in part on the received UAV data. A 3D model of the surface of the structure is reconstructed using the 3D point cloud.Type: ApplicationFiled: May 17, 2023Publication date: September 14, 2023Inventors: James M. Freeman, Roger D. Schmidgall, Patrick H. Boyer, Nicholas U. Christopulos, Jonathan D. Maurer, Nathan L. Tofte, Jackie O. Jordan, II
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Publication number: 20230260048Abstract: Techniques for implementing machine learning to improve claim handling are disclosed. In some scenarios, the machine-learning, analytics model may be trained in accordance with data that is relevant to insurance products, such as life and health insurance. A set of labeled historical claims each corresponding to a settlement amount may be analyzed to train an artificial neural network, A claim may be received from a user mobile device, and may be analyzed using the trained artificial neural network to predict a claim settlement, which may be used to generate a settlement offer. The settlement offer may be transmitted to the user's mobile device, and if a manifestation of acceptance is received from the user, then the claim may be automatically paid.Type: ApplicationFiled: April 25, 2023Publication date: August 17, 2023Applicant: STATE FARM MUTUAL AUTOMOBILE INSURANCE COMPANYInventors: Gregory L. Hayward, Meghan Sims Goldfarb, Nicholas U. Christopulos, Erik Donahue
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Patent number: 11694404Abstract: In a computer-implemented method and system for capturing the condition of a structure, the structure is scanned with an unmanned aerial vehicle (UAV). Data collected by the UAV corresponding to points on a surface of a structure is received and a 3D point cloud is generated for the structure, where the 3D point cloud is generated based at least in part on the received UAV data. A 3D model of the surface of the structure is reconstructed using the 3D point cloud.Type: GrantFiled: March 7, 2022Date of Patent: July 4, 2023Assignee: STATE FARM MUTUAL AUTOMOBILE INSURANCE COMPANYInventors: James M. Freeman, Roger D. Schmidgall, Patrick H. Boyer, Nicholas U. Christopulos, Jonathan D. Maurer, Nathan L. Tofte, Jackie O. Jordan, II
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Publication number: 20220284517Abstract: A method of determining damage to property includes inputting historical data into a machine learning model to identify an insured type, features, and/or characteristics. The method may include identifying a peril, repair and/or replacement cost of the vehicle by analyzing a digital image from a device of an insured, the digital image depicting damage to the vehicle, The method may include inputting the digital image into the trained machine learning model to identify a type, feature, and/or characteristic of the vehicle, and may include identifying a peril, repair, and/or replacement cost associated with the vehicle. A method may include receiving and/or retrieving free-form text associated with an insurance claim and/or a vehicle, identifying at least one key word composing the free-form text, and determining based on the at least one key word a cause of loss and/or peril that caused damage to the vehicle.Type: ApplicationFiled: May 24, 2022Publication date: September 8, 2022Applicant: STATE FARM MUTUAL AUTOMOBILE INSURANCE COMPANYInventors: Gregory L. Hayward, Meghan Sims Goldfarb, Nicholas U. Christopulos, Erik Donahue
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Patent number: 11373249Abstract: A method of determining damage to property includes inputting historical data into a machine learning model to identify an insured type, features, and/or characteristics. The method may include identifying a peril, repair and/or replacement cost of the vehicle by analyzing a digital image from a device of an insured, the digital image depicting damage to the vehicle. The method may include inputting the digital image into the trained machine learning model to identify a type, feature, and/or characteristic of the vehicle, and may include identifying a peril, repair, and/or replacement cost associated with the vehicle. A method may include receiving and/or retrieving free-form text associated with an insurance claim and/or a vehicle, identifying at least one key word composing the free-form text, and determining based on the at least one key word a cause of loss and/or peril that caused damage to the vehicle.Type: GrantFiled: September 20, 2018Date of Patent: June 28, 2022Assignee: State Farm Mutual Automobile Insurance CompanyInventors: Gregory L Hayward, Meghan Sims Goldfarb, Nicholas U. Christopulos, Erik Donahue
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Publication number: 20220189117Abstract: In a computer-implemented method and system for capturing the condition of a structure, the structure is scanned with an unmanned aerial vehicle (UAV). Data collected by the UAV corresponding to points on a surface of a structure is received and a 3D point cloud is generated for the structure, where the 3D point cloud is generated based at least in part on the received UAV data. A 3D model of the surface of the structure is reconstructed using the 3D point cloud.Type: ApplicationFiled: March 7, 2022Publication date: June 16, 2022Inventors: James M. Freeman, Roger D. Schmidgall, Patrick H. Boyer, Nicholas U. Christopulos, Jonathan D. Maurer, Nathan L. Tofte, Jackie O. Jordan, II
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Patent number: 11295523Abstract: In a computer-implemented method and system for capturing the condition of a structure, the structure is scanned with an unmanned aerial vehicle (UAV). Data collected by the UAV corresponding to points on a surface of a structure is received and a 3D point cloud is generated for the structure, where the 3D point cloud is generated based at least in part on the received UAV data. A 3D model of the surface of the structure is reconstructed using the 3D point cloud.Type: GrantFiled: March 26, 2020Date of Patent: April 5, 2022Assignee: STATE FARM MUTUAL AUTOMOBILE INSURANCE COMPANYInventors: James M. Freeman, Roger D. Schmidgall, Patrick H. Boyer, Nicholas U. Christopulos, Jonathan D. Maurer, Nathan L. Tofte, Jackie O. Jordan, II
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Patent number: 11270504Abstract: In a computer-implemented method and system for capturing the condition of a structure, the structure is scanned with an unmanned aerial vehicle (UAV). The UAV receives an instruction to collect information on at least one aspect of a property, and identifies one or more onboard sensors of the UAV to collect the information on the at least one aspect of the property, where the UAV is configured to identify a first set of one or more onboard sensors to collect a first type of data and to identify a second set of one or more onboard sensors to collect a second type of data. The UAV also collects the information on the at least one aspect of the property using the one or more onboard sensors, and identifies, based on the collected information, a type of damage incurred on the at least one aspect of the property.Type: GrantFiled: March 26, 2020Date of Patent: March 8, 2022Assignee: STATE FARM MUTUAL AUTOMOBILE INSURANCE COMPANYInventors: James M. Freeman, Roger D. Schmidgall, Patrick H. Boyer, Nicholas U. Christopulos, Jonathan D. Maurer, Nathan L. Tofte, Jackie O. Jordan, II
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Publication number: 20220036476Abstract: A method for identifying a primary vehicle associated with a user of a mobile device includes receiving an indication of a vehicle entry event from a mobile device and retrieving sensor data from the mobile device. The method further includes receiving an indication of a vehicle exit event from the mobile device, generating a trip log including portions of the sensor data, and storing the trip log in a trip database. A server, or other suitable computing device, then analyzes the trip log and a plurality of previously stored trip logs in the trip database to determine a primary vehicle corresponding to the user of the mobile device. The method may allow a computing device to assign gathered mobile device data to a specific household vehicle.Type: ApplicationFiled: October 18, 2021Publication date: February 3, 2022Inventors: Nicholas U. Christopulos, Nicholas R. Baker, Eric Bellas, Benjamin F. Bowne
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Publication number: 20210398227Abstract: Machine learning techniques for determining a risk level of a target building or other type of real property include receiving data indicative of various historical characteristics of and/or associated with real property, and/or receiving data included in historical, electronic claims pertaining to buildings/real properties, and utilizing the received data to train a machine learning or other model that identifies or discovers risk factors associated with buildings/real properties. The machine learning or other model may be applied to characteristic data associated with the target building/real property to generate risk factors and/or risk indicators of the target building/real property. The techniques may include analyzing the generated risk factors and/or risk indicators to determine a risk level of the target building/real property. The risk factors, risk indicators, and/or risk level may be used for many purposes, such as pricing, quoting, underwriting, or re-underwriting of insurance policies.Type: ApplicationFiled: September 3, 2021Publication date: December 23, 2021Applicant: STATE FARM MUTUAL AUTOMOBILE INSURANCE COMPANYInventors: Gregory L. Hayward, Meghan Sims Goldfarb, Nicholas U. Christopulos, Erik Donahue
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Publication number: 20210390624Abstract: Machine learning techniques for determining a risk level of a target building or other type of real property include receiving data indicative of various historical characteristics of and/or associated with real property, and/or receiving data included in historical, electronic claims pertaining to buildings/real properties, and utilizing the received data to train a machine learning or other model that identifies or discovers risk factors associated with buildings/real properties. The machine learning or other model may be applied to characteristic data associated with the target building/real property to generate risk factors and/or risk indicators of the target building/real property. The techniques may include analyzing the generated risk factors and/or risk indicators to determine a risk level of the target building/real property. The risk factors, risk indicators, and/or risk level may be used for many purposes, such as pricing, quoting, underwriting, or re-underwriting of insurance policies.Type: ApplicationFiled: September 20, 2018Publication date: December 16, 2021Applicant: State Farm Mutual Automobile Insurance CompanyInventors: Gregory L. Hayward, Meghan Sims Goldfarb, Nicholas U. Christopulos, Erik Donahue
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Patent number: 11182859Abstract: A method for identifying a primary vehicle associated with a user of a mobile device includes receiving an indication of a vehicle entry event from a mobile device and retrieving sensor data from the mobile device. The method further includes receiving an indication of a vehicle exit event from the mobile device, generating a trip log including portions of the sensor data, and storing the trip log in a trip database. A server, or other suitable computing device, then analyzes the trip log and a plurality of previously stored trip logs in the trip database to determine a primary vehicle corresponding to the user of the mobile device. The method may allow a computing device to assign gathered mobile device data to a specific household vehicle.Type: GrantFiled: December 4, 2013Date of Patent: November 23, 2021Assignee: STATE FARM MUTUAL AUTOMOBILE INSURANCE COMPANYInventors: Nicholas U. Christopulos, Nicholas R. Baker, Eric Bellas, Benjamin F. Bowne
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Patent number: 11170491Abstract: Systems and methods for assessing a physical structure are provided. Information indicative of an infrared image that includes a portion of the physical structure is received, and one or more indicators within the infrared image exceeding a heat threshold are determined. A plurality of characteristics of the one or more indicators are determined. One or more edges of the portion of the physical structure are detected, and an area associated with an intended use of one or more fasteners associated with the physical structure is determined according to the detected edges. An amount of the one or more indicators corresponding to the area is determined, and the one or more indicators are classified as fasteners according to the determined amount. Based on the classification of the one or more indicators, a condition of the physical structure is determined.Type: GrantFiled: November 18, 2019Date of Patent: November 9, 2021Assignee: STATE FARM MUTUAL AUTOMOBILE INSURANCE COMPANYInventors: James M. Freeman, Patrick H. Boyer, Nicholas U. Christopulos, Jonathan D. Maurer, Nathan L. Tofte, Jackie O. Jordan, II
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Publication number: 20210312567Abstract: A method of determining loss reserves and/or providing automatic financial reporting related thereto via one or more processors includes (1) receiving a plurality of historical electronic claim documents, each respectively labeled with a claim loss amount; (2) normalizing each respective claim loss amount and training an artificial intelligence or machine learning algorithm, module, or model, such as an artificial neural network, by applying the plurality of electronic claim documents to the artificial intelligence or machine learning algorithm, module, or model. The method may include receiving a user claim and predicting a loss reserve amount by applying the user claim to the trained artificial intelligence or machine learning algorithm, module, or model, and may include unreported claims.Type: ApplicationFiled: June 21, 2021Publication date: October 7, 2021Applicant: STATE FARM MUTUAL AUTOMOBILE INSURANCE COMPANYInventors: Gregory L. Hayward, Meghan Sims Goldfarb, Nicholas U. Christopulos, Erik Donahue
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Publication number: 20210287297Abstract: A method of determining loss reserves and/or providing automatic financial reporting related thereto via one or more processors includes (1) receiving a plurality of historical electronic claim documents, each respectively labeled with a claim loss amount; (2) normalizing each respective claim loss amount and training an artificial intelligence or machine learning algorithm, module, or model, such as an artificial neural network, by applying the plurality of electronic claim documents to the artificial intelligence or machine learning algorithm, module, or model. The method may include receiving a user claim and predicting a loss reserve amount by applying the user claim to the trained artificial intelligence or machine learning algorithm, module, or model, and may include unreported claims.Type: ApplicationFiled: September 20, 2018Publication date: September 16, 2021Applicant: State Farm Mutual Automobile Insurance CompanyInventors: Gregory L Hayward, Meghan Sims Goldfarb, Nicholas U. Christopulos, Erik Donahue
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Publication number: 20210256615Abstract: Techniques for implementing machine learning for insurance loss mitigation or prevention, and claims handling are disclosed. In some scenarios, the insurance loss mitigation and claims handling may be associated with a disability, worker's compensation, life or health insurance policy, and the machine-learning analytics model may be trained in accordance with data that is relevant to identifying appropriate predictions in accordance with these particular types of insurance products. For instance, the machine-learning analytics model may utilize information within a dynamic data set as training data, which may include electronically accessible information. The machine-learning analytics model may additionally be implemented to identify various predictions that are indicative of a risk of insuring an individual as well as one or more actions that, when performed, may reduce the initial calculation of risk.Type: ApplicationFiled: September 20, 2018Publication date: August 19, 2021Inventors: Gregory L. Hayward, Meghan Sims Goldfarb, Nicholas U. Christopulos, Erik Donahue
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Publication number: 20210256616Abstract: A method of determining an automobile-based risk level via one or more processors includes training a machine learning program, such as a neural network, to identify risk factors within electronic claim features, receiving information corresponding to one or both of (i) an automobile, such as an autonomous or semi-autonomous vehicle, and (ii) an automobile operator, analyzing the information using the trained machine learning program to generate one or more risk indicators, determining, by analyzing the risk indicators, a risk level corresponding to the automobile, and/or displaying, to a user, a quotation based upon analyzing the risk indicators. The risk factors, risk indicators, and/or risk level may be used for many purposes, such as pricing, quoting, and/or underwriting of insurance policies.Type: ApplicationFiled: September 20, 2018Publication date: August 19, 2021Applicant: State Farm Mutual Automobile Insurance CompanyInventors: Gregory L. Hayward, Meghan Sims Goldfarb, Nicholas U. Christopulos, Erik Donahue
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Patent number: 10997668Abstract: A shading system creates a shaded region on a structure, enabling 3D scanning techniques that rely on light detection to generate a 3D model. The shading system includes a vehicle or device that moves the shading system into place. A light, such as a laser dot or line, can be projected onto the shaded region of the structure and detected by a 3D scanner.Type: GrantFiled: December 4, 2018Date of Patent: May 4, 2021Assignee: STATE FARM MUTUAL AUTOMOBILE INSURANCE COMPANYInventors: James M. Freeman, Patrick H. Boyer, Nicholas U. Christopulos, Jonathan D. Maurer, Nathan L. Tofte, Jackie O. Jordan, II