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公开(公告)号：US20250029072A1
公开(公告)日：2025-01-23
申请号：US18906389
申请日：2024-10-04
Inventor： Jody Ann Thoele , Jaime Skaggs , Scott T. Christensen , Ashish Sawhney , Neill Broadstone , Angela Glusick , Gustufus Phillip Theofanis
IPC: G06Q10/20 , G06N20/00 , G06Q30/0283 , G06Q40/08
Abstract: Systems and methods for determining a reparability of a vehicle are provided. In some embodiments, vehicle data is obtained, and a list of variables is generated from the obtained data. A machine learning algorithm may then be trained to generate a reparability metric by: (i) generating correlation metrics between the variables and costs to repair the vehicle, (ii) removing variables with correlation metrics below a threshold, and (iii) training the machine learning algorithm based upon unremoved variables.
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公开(公告)号：US12140959B2
公开(公告)日：2024-11-12
申请号：US18149488
申请日：2023-01-03
Inventor： Blake Konrardy , Scott T. Christensen , Gregory Hayward , Scott Farris
Abstract: Methods and systems for monitoring use and determining risks associated with operation of a vehicle having one or more autonomous operation features are provided. According to certain aspects, operating data may be recorded during operation of the vehicle. This may include information regarding the vehicle, the vehicle environment, use of the autonomous operation features, and/or control decisions made by the features. The control decisions may include actions the feature would have taken to control the vehicle, but which were not taken because a vehicle operator was controlling the relevant aspect of vehicle operation at the time. The operating data may be recorded in a log, which may then be used to determine risk levels associated with vehicle operation based upon risk levels associated with the autonomous operation features. The risk levels may further be used to adjust an insurance policy associated with the vehicle.
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公开(公告)号：US12125106B1
公开(公告)日：2024-10-22
申请号：US17036228
申请日：2020-09-29
Inventor： James M. Gallagher , Scott T. Christensen
IPC: G06Q40/08 , G06N20/00 , G06Q10/10 , G06Q30/0201 , G06Q30/0204 , G06Q40/03 , G06Q50/40 , G07C5/00 , G07C5/08
CPC classification number: G06Q40/08 , G06N20/00 , G06Q10/10 , G06Q30/0201 , G06Q30/0205 , G06Q30/0206 , G06Q40/03 , G06Q50/40 , G07C5/008 , G07C5/0841
Abstract: Cloud-based vehicular telematics systems and methods are described for automatically generating rideshare-based risk profiles of rideshare drivers of a transport network company (TNC) platform. The systems and methods comprise receiving telematics data originating from sensor(s) traveling with a rideshare vehicle during an operating segment of the rideshare vehicle; and rideshare data originating from a rideshare app configured to execute on a telematics device during one or more portions of the operating segment. The rideshare data indicates a rideshare app mode for each portion of the operating segment. The systems and methods include determining, based on the telematics data, operating state(s) of the rideshare vehicle during the operating segment of the rideshare vehicle, and generating, based on the telematics data and the rideshare data, a rideshare-based risk profile and driver score of a driver.
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公开(公告)号：US20240331047A1
公开(公告)日：2024-10-03
申请号：US18216449
申请日：2023-06-29
Inventor： Aaron Williams , Joseph Harr , Scott T. Christensen , Ryan M. Gross
IPC: G06Q40/08 , G06N3/045 , G06Q30/0601
CPC classification number: G06Q40/08 , G06N3/045 , G06Q30/0617 , H04L51/02
Abstract: A computer system for flood monitoring and insurance provider notification, the computer system may include one or more processors configured to: detect a flood event in a structure, transmit information associated with the structure and a prompt for flood reimbursement services to a machine learning (ML) chatbot to cause the ML chatbot to file a flood reimbursement claim with an insurance provider having an insurance policy associated with the structure via telephone by converting a text output into a voice output.
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公开(公告)号：US20240331043A1
公开(公告)日：2024-10-03
申请号：US18216346
申请日：2023-06-29
Inventor： Aaron Williams , Joseph Harr , Scott T. Christensen , Ryan M. Gross
IPC: G06Q40/06
CPC classification number: G06Q40/06
Abstract: A computer system for automated investment advising may include one or more processors configured to: receive from an investor an investment strategy, send the investment strategy and a prompt for investment instructions to an ML chatbot (or voice bot) to cause an ML model to generate the investment instructions, and receive the investment instructions from the ML chatbot (or voice bot).
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Patent Agency Ranking
公开(公告)号：US20240328410A1
公开(公告)日：2024-10-03
申请号：US18216374
申请日：2023-06-29
Inventor： Aaron Williams , Joseph Harr , Scott T. Christensen , Ryan M. Gross
CPC classification number: F04B51/00 , G06Q10/20 , G08B21/187 , F04B2207/70
Abstract: A computer system for sump pump monitoring and repair service provider notification may include one or more processors configured to: detect that a sump pump is faulty, transmit a prompt for service quotes to a machine learning (ML) chatbot to cause the ML chatbot to: request sump pump replacement or repair services from one or more service providers, receive cost estimates from the one or more repair service providers, receive schedule availability from the one or more repair service providers, receive, from the ML chatbot, the cost estimates and the schedule availability, and communicate the cost estimates and/or the schedule availability to a user associated with the sump pump.
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公开(公告)号：US12005910B2
公开(公告)日：2024-06-11
申请号：US18130736
申请日：2023-04-04
Inventor： Scott T. Christensen , Brian Mark Fields , Stephen R. Prevatt , Steve Roberson
IPC: B60W50/00
CPC classification number: B60W50/0098 , B60W2900/00
Abstract: Systems and methods are provided for dynamically protecting transportable articles in vehicles. A system for dynamically protecting a transportable article in a vehicle may include one or more processors and non-volatile memory storing instructions. The instructions, when executed by the one or more processors, cause the system to determine at least one of a characteristic or a trait of the transportable article; detect, based on sensed data, an emergency condition; select one or more article protection components based on (i) the at least one of the characteristic or the trait of the transportable article, and (ii) the detected emergency condition; and in response to detecting the emergency condition, deploy the selected one or more article protection components to protect the transportable article.
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公开(公告)号：US20240183673A1
公开(公告)日：2024-06-06
申请号：US18417786
申请日：2024-01-19
Inventor： Blake Konrardy , Scott T. Christensen , Gregory Hayward , Scott Farris
IPC: G01C21/34 , B60L53/36 , B60L58/12 , B60P3/12 , B60R16/023 , B60R21/00 , B60R21/01 , B60R21/0136 , B60R21/34 , B60R25/04 , B60R25/10 , B60R25/102 , B60R25/104 , B60R25/25 , B60R25/30 , B60R25/31 , B60W10/04 , B60W10/18 , B60W10/20 , B60W30/095 , B60W30/12 , B60W30/16 , B60W30/18 , B60W40/04 , B60W60/00 , G01B21/00 , G01C21/36 , G01S19/13 , G01S19/42 , G05B15/02 , G05B23/02 , G05D1/223 , G05D1/227 , G05D1/228 , G05D1/247 , G05D1/249 , G05D1/617 , G05D1/646 , G05D1/69 , G05D1/692 , G05D1/693 , G05D1/695 , G05D1/697 , G06F11/36 , G06F16/2455 , G06F16/903 , G06F17/00 , G06F21/32 , G06F21/55 , G06F30/15 , G06F30/20 , G06N20/00 , G06Q10/1093 , G06Q10/20 , G06Q30/0283 , G06Q30/0645 , G06Q40/08 , G06Q50/163 , G06Q50/26 , G06Q50/40 , G07C5/00 , G07C5/08 , G07C9/00 , G08B21/00 , G08B21/02 , G08B21/18 , G08B25/00 , G08B25/01 , G08G1/00 , G08G1/017 , G08G1/0965 , G08G1/0967 , G08G1/14 , G08G1/16 , G16Y10/80 , G16Y30/00 , H04L12/28 , H04L67/12 , H04L67/306 , H04N7/18
CPC classification number: G01C21/3461 , B60L53/36 , B60L58/12 , B60P3/12 , B60R16/0234 , B60R21/0136 , B60R21/34 , B60R25/04 , B60R25/10 , B60R25/1001 , B60R25/102 , B60R25/104 , B60R25/252 , B60R25/255 , B60R25/305 , B60R25/31 , B60W10/04 , B60W10/18 , B60W10/20 , B60W30/0956 , B60W30/12 , B60W30/16 , B60W30/18163 , B60W40/04 , B60W60/0023 , B60W60/0053 , B60W60/0059 , G01B21/00 , G01C21/34 , G01C21/3415 , G01C21/343 , G01C21/3438 , G01C21/3453 , G01C21/3469 , G01C21/3617 , G01C21/362 , G01C21/3697 , G01S19/13 , G05B15/02 , G05B23/0245 , G05D1/223 , G05D1/227 , G05D1/228 , G05D1/247 , G05D1/249 , G05D1/617 , G05D1/646 , G05D1/69 , G05D1/692 , G05D1/693 , G05D1/695 , G05D1/697 , G06F11/3688 , G06F11/3692 , G06F16/2455 , G06F16/90335 , G06F17/00 , G06F21/32 , G06F21/55 , G06F30/15 , G06F30/20 , G06Q10/1095 , G06Q10/20 , G06Q30/0284 , G06Q30/0645 , G06Q40/08 , G06Q50/163 , G06Q50/265 , G06Q50/40 , G07C5/006 , G07C5/008 , G07C5/0808 , G07C5/0816 , G07C5/0841 , G07C9/00563 , G08B21/00 , G08B21/02 , G08B21/18 , G08B25/00 , G08B25/014 , G08G1/017 , G08G1/0965 , G08G1/096725 , G08G1/146 , G08G1/148 , G08G1/161 , G08G1/165 , G08G1/166 , G08G1/167 , G08G1/20 , G16Y10/80 , G16Y30/00 , H04L12/2803 , H04L12/2816 , H04L12/2825 , H04L67/306 , H04N7/183 , B60R2021/0027 , B60R2021/01013 , B60R2025/1013 , B60W2420/403 , B60W2420/408 , B60W2530/209 , B60W2540/229 , B60W2552/05 , B60W2552/35 , B60W2554/4026 , B60W2554/4029 , B60W2554/4041 , B60W2554/406 , B60W2556/10 , G01S19/42 , G06F2221/034 , G06N20/00 , H04L67/12
Abstract: Methods and systems for assessing, detecting, and responding to malfunctions involving components of autonomous vehicles and/or smart homes are described herein. Autonomous operation features and related components can be assessed using direct or indirect data regarding operation. Such assessment may be performed to determine the robustness of autonomous systems, including the use of virtual assessment of software components within a simulated environment. To this end, a server may retrieve one or more routines associated with autonomous operation. The server may also generate a set of test data associated with test conditions. The server may also execute an emulator that virtually simulates autonomous environment. The test data may be presented to the routines executing in the emulator to generate output data. The server may then analyze the output data to determine a quality metric.
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公开(公告)号：US12002104B2
公开(公告)日：2024-06-04
申请号：US17701829
申请日：2022-03-23
Inventor： Scott T. Christensen , Gregory Hayward , Christopher E. Gay , Steven Cielocha , Todd Binion
IPC: G06Q40/08 , B60C1/00 , B60Q1/00 , B60R25/20 , G06Q10/0635 , G06Q30/0207 , G06Q30/0208 , G06Q40/00 , G07C5/00 , G08G1/0968 , H04W4/40
CPC classification number: G06Q40/08 , B60C1/00 , B60Q1/00 , B60R25/20 , G06Q10/0635 , G06Q30/0207 , G06Q30/0208 , G06Q40/00 , G07C5/00 , G07C5/008 , G08G1/096838 , H04W4/40
Abstract: Computer-implemented methods, servers, and tangible, non-transitory computer-readable media storing instructions for creating one or more new insurance policy quotes for a customer associated with a customer vehicle may be may be described. The computer-implemented methods, servers, and instructions may include receiving a coverage type for the customer vehicle, causing usage data corresponding to the coverage type to be tracked, receiving the usage data, generating the new insurance policy quotes corresponding to the coverage type based upon at least the usage data, and causing the new insurance policy quotes to be displayed.
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公开(公告)号：US11898862B2
公开(公告)日：2024-02-13
申请号：US18117642
申请日：2023-03-06
Inventor： Blake Konrardy , Scott T. Christensen , Gregory Hayward , Scott Farris
IPC: G08G1/00 , B60W30/095 , B60W40/04 , B60R21/00 , B60R21/01 , H04L67/12 , G01S19/42 , G06N20/00 , G01C21/34 , B60W10/04 , B60W10/18 , B60W10/20 , B60W30/18 , G08G1/16 , G01S19/13 , G05D1/02 , G08G1/14 , B60L53/36 , G05B15/02 , G08B25/01 , H04L12/28 , G06F16/2455 , B60R25/04 , B60R25/10 , B60R25/102 , B60R25/25 , G06F21/32 , B60R21/0136 , B60R21/34 , G05D1/00 , G01C21/36 , G08G1/017 , B60P3/12 , G05B23/02 , G01B21/00 , G06F17/00 , G08B21/00 , G08B21/18 , G06Q10/1093 , G06Q10/20 , B60L58/12 , B60R25/104 , B60R25/30 , B60R25/31 , G06Q30/0283 , G06Q30/0645 , G06Q50/30 , G07C9/00 , G08B21/02 , G08B25/00 , H04L67/306 , G06F30/20 , G06F30/15 , G07C5/08 , G06F21/55 , G06Q50/16 , G08G1/0967 , G06F16/903 , G06Q50/26 , H04N7/18 , G16Y10/80 , G16Y30/00 , G06F11/36 , B60W60/00 , G06Q40/08 , B60R16/023 , G07C5/00 , G08G1/0965
CPC classification number: G01C21/3461 , B60L53/36 , B60L58/12 , B60P3/12 , B60R16/0234 , B60R21/0136 , B60R21/34 , B60R25/04 , B60R25/10 , B60R25/1001 , B60R25/102 , B60R25/104 , B60R25/252 , B60R25/255 , B60R25/305 , B60R25/31 , B60W10/04 , B60W10/18 , B60W10/20 , B60W30/0956 , B60W30/18163 , B60W40/04 , B60W60/0023 , B60W60/0053 , B60W60/0059 , G01B21/00 , G01C21/34 , G01C21/343 , G01C21/3415 , G01C21/3438 , G01C21/3453 , G01C21/3469 , G01C21/362 , G01C21/3617 , G01C21/3697 , G01S19/13 , G05B15/02 , G05B23/0245 , G05D1/0011 , G05D1/0055 , G05D1/0212 , G05D1/0231 , G05D1/0246 , G05D1/0255 , G05D1/0285 , G05D1/0287 , G05D1/0289 , G05D1/0293 , G05D1/0295 , G06F11/3688 , G06F11/3692 , G06F16/2455 , G06F16/90335 , G06F17/00 , G06F21/32 , G06F21/55 , G06F30/15 , G06F30/20 , G06Q10/1095 , G06Q10/20 , G06Q30/0284 , G06Q30/0645 , G06Q40/08 , G06Q50/163 , G06Q50/265 , G06Q50/30 , G07C5/006 , G07C5/008 , G07C5/0808 , G07C5/0816 , G07C5/0841 , G07C9/00563 , G08B21/00 , G08B21/02 , G08B21/18 , G08B25/00 , G08B25/014 , G08G1/017 , G08G1/0965 , G08G1/096725 , G08G1/146 , G08G1/148 , G08G1/161 , G08G1/165 , G08G1/166 , G08G1/167 , G08G1/20 , G16Y10/80 , G16Y30/00 , H04L12/2803 , H04L12/2816 , H04L12/2825 , H04L67/306 , H04N7/183 , B60R2021/0027 , B60R2021/01013 , B60R2025/1013 , B60W2420/403 , B60W2420/52 , B60W2530/209 , B60W2540/229 , B60W2552/05 , B60W2552/35 , B60W2554/406 , B60W2554/4026 , B60W2554/4029 , B60W2554/4041 , B60W2556/10 , G01S19/42 , G05D2201/0212 , G05D2201/0213 , G06F2221/034 , G06N20/00 , H04L67/12
Abstract: Methods and systems for assessing, detecting, and responding to malfunctions involving components of autonomous vehicles and/or smart homes are described herein. Autonomous operation features and related components can be assessed using direct or indirect data regarding operation. Such assessment may be performed to determine the robustness of autonomous systems, including the use of virtual assessment of software components within a simulated environment. To this end, a server may retrieve one or more routines associated with autonomous operation. The server may also generate a set of test data associated with test conditions. The server may also execute an emulator that virtually simulates autonomous environment. The test data may be presented to the routines executing in the emulator to generate output data. The server may then analyze the output data to determine a quality metric.
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