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公开(公告)号：US20220318980A1
公开(公告)日：2022-10-06
申请号：US17220161
申请日：2021-04-01
Applicant: Allstate Insurance Company
Inventor： Deborah-Anna Reznek , Adam Sturt , Jeremy Werner , Adam Austin , Amber Parsons , Xiaolan Wu , Ryan Rosenberg , Lizette Lemus Gonzalez , Weizhou Wang , Stephanie Wong , Charles Cox , Jean Utke , Yusuf Mansour , Tia Miceli , Lakshmi Prabha Nattamai Sekar , Meg G. Walters , Dylan Stark , Emily Pavey
Abstract: Aspects of the disclosure relate to using computer vision methods for asset evaluation. A computing platform may receive historical images of a plurality of properties and corresponding historical inspection results. Using the historical images and historical inspection results, the computing platform may train a roof waiver model (which may be a computer vision model) to output inspection prediction information directly from an image. The computing platform may receive a new image corresponding to a particular residential property. Using the roof waiver model, the computing platform may analyze the new image to output of a likelihood of passing inspection. The computing platform may send, to a user device and based on the likelihood of passing inspection, inspection information indicating whether or not a physical inspection should be performed and directing the user device to display the inspection information, which may cause the user device to display the inspection information.
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公开(公告)号：US20230296804A1
公开(公告)日：2023-09-21
申请号：US17696421
申请日：2022-03-16
Applicant: Allstate Insurance Company
Inventor： Mark Slusar , Nilesh Malpekar , Anna Reifman , Gabriel Federico Carballo Nunez , Meg G. Walters
CPC classification number: G01W1/10 , G01S19/14 , G06F30/27 , G06N3/08 , G01W2203/00
Abstract: Systems and methods for deployment of a protective component, generation of a customized design for the protective component, or combinations thereof are associated with a structure comprising a portion, a neural network model, processor(s), and memory storing machine readable instructions. When executed for deployment, the neural network model predicts the likelihood of the occurrence of the natural event in the geographic area within the time frame as high as defined by when the likelihood is above a threshold, and deploys the protective component for protecting the portion of the structure when the likelihood is high. For customized design, the neural network model is used to access dimension and weather data associated with a structure and weather data to generate the customized design of the protective component for the structure.
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公开(公告)号：US11068985B1
公开(公告)日：2021-07-20
申请号：US16513162
申请日：2019-07-16
Applicant: Allstate Insurance Company
Inventor： Christine L. Bischoff , Dana Ferguson , Eric Huls , Grady Irey , William Polisson , Caryl M. Styrsky , Ralph Adam Benjamin Tyner , Meg G. Walters
Abstract: Methods, computer-readable media, systems and apparatuses for determining and implementing dynamic usage-based insurance policies are presented. A cost per day and a cost per mile associated with the dynamic usage-based insurance policy may be determined. The cost per mile may be computed independently for each of a plurality of road segments comprising a trip based on a time of day that the vehicle traveled each road segment, a road type associated with each road segment. The cost per mile of each road segment of the driving trip may further include whether or not hard braking or hard cornering events were encountered during a specified cumulative driving distance that may include, at least a portion, of a plurality of driving trips. The cost per mile for each of the plurality of driving trips may be adjusted once a threshold distance has been traveled by the vehicle based on the number of hard braking events and hard cornering events occurred during that distance.
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公开(公告)号：US11521268B1
公开(公告)日：2022-12-06
申请号：US17361564
申请日：2021-06-29
Applicant: Allstate Insurance Company
Inventor： Christine L. Bischoff , Dana Ferguson , Eric Huls , Grady Irey , William Polisson , Caryl M. Styrsky , Ralph Adam Benjamin Tyner , Meg G. Walters
Abstract: Methods, computer-readable media, systems and apparatuses for determining and implementing dynamic usage-based insurance policies are presented. A cost per day and a cost per mile associated with the dynamic usage-based insurance policy may be determined. The cost per mile may be computed independently for each of a plurality of road segments comprising a trip based on a time of day that the vehicle traveled each road segment, a road type associated with each road segment. The cost per mile of each road segment of the driving trip may further include whether or not hard braking or hard cornering events were encountered during a specified cumulative driving distance that may include, at least a portion, of a plurality of driving trips. The cost per mile for each of the plurality of driving trips may be adjusted once a threshold distance has been traveled by the vehicle based on the number of hard braking events and hard cornering events occurred during that distance.
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公开(公告)号：US10430883B1
公开(公告)日：2019-10-01
申请号：US15430963
申请日：2017-02-13
Applicant: Allstate Insurance Company
Inventor： Christine L. Bischoff , Dana Ferguson , Eric D. Huls , Grady Irey , William Polisson , Caryl M. Styrsky , Ralph Adam Benjamin Tyner , Meg G. Walters
Abstract: Methods, computer-readable media, systems and apparatuses for determining and implementing dynamic usage-based insurance policies are presented. A cost per day and a cost per mile associated with the dynamic usage-based insurance policy may be determined. The cost per mile may be computed independently for each of a plurality of road segments comprising a trip based on a time of day that the vehicle traveled each road segment, a road type associated with each road segment. The cost per mile of each road segment of the driving trip may further include whether or not hard braking or hard cornering events were encountered during a specified cumulative driving distance that may include, at least a portion, of a plurality of driving trips. The cost per mile for each of the plurality of driving trips may be adjusted once a threshold distance has been traveled by the vehicle based on the number of hard braking events and hard cornering events occurred during that distance.
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Patent Agency Ranking
公开(公告)号：US12169787B1
公开(公告)日：2024-12-17
申请号：US16868780
申请日：2020-05-07
Applicant: Allstate Insurance Company
Inventor： Meg G. Walters , Mark S. Richards
Abstract: Methods, computer-readable media, software, and apparatuses may assist in assessing proportional fault in an automobile accident involving an automobile having one or more autonomous features. An expected behavior of an autonomous feature is compared to an observed outcome of an accident and a fault proportion between a human driver and the autonomous feature may be determined, based on the comparison.
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公开(公告)号：US20230186388A1
公开(公告)日：2023-06-15
申请号：US17969993
申请日：2022-10-20
Applicant: Allstate Insurance Company
Inventor： Christine L. Bischoff , Dana Ferguson , Eric D. Huls , Grady Irey , William Polisson , Caryl M. Styrsky , Ralph Adam Benjamin Tyner , Meg G. Walters
Abstract: Methods, computer-readable media, systems and apparatuses for determining and implementing dynamic usage-based insurance policies are presented. A cost per day and a cost per mile associated with the dynamic usage-based insurance policy may be determined. The cost per mile may be computed independently for each of a plurality of road segments comprising a trip based on a time of day that the vehicle traveled each road segment, a road type associated with each road segment. The cost per mile of each road segment of the driving trip may further include whether or not hard braking or hard cornering events were encountered during a specified cumulative driving distance that may include, at least a portion, of a plurality of driving trips. The cost per mile for each of the plurality of driving trips may be adjusted once a threshold distance has been traveled by the vehicle based on the number of hard braking events and hard cornering events occurred during that distance.
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公开(公告)号：US12153190B2
公开(公告)日：2024-11-26
申请号：US17696421
申请日：2022-03-16
Applicant: Allstate Insurance Company
Inventor： Mark Slusar , Nilesh Malpekar , Anna Reifman , Gabriel Federico Carballo Nunez , Meg G. Walters
Abstract: Systems and methods for deployment of a protective component, generation of a customized design for the protective component, or combinations thereof are associated with a structure comprising a portion, a neural network model, processor(s), and memory storing machine readable instructions. When executed for deployment, the neural network model predicts the likelihood of the occurrence of the natural event in the geographic area within the time frame as high as defined by when the likelihood is above a threshold, and deploys the protective component for protecting the portion of the structure when the likelihood is high. For customized design, the neural network model is used to access dimension and weather data associated with a structure and weather data to generate the customized design of the protective component for the structure.
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公开(公告)号：US12106462B2
公开(公告)日：2024-10-01
申请号：US17220161
申请日：2021-04-01
Applicant: Allstate Insurance Company
Inventor： Deborah-Anna Reznek , Adam Sturt , Jeremy Werner , Adam Austin , Amber Parsons , Xiaolan Wu , Ryan Rosenberg , Lizette Lemus Gonzalez , Weizhou Wang , Stephanie Wong , Charles Cox , Jean Utke , Yusuf Mansour , Tia Miceli , Lakshmi Prabha Nattamai Sekar , Meg G. Walters , Dylan Stark , Emily Pavey
IPC: G06T7/00 , G06N5/04 , G06N20/00 , G06Q30/0283 , G06V20/10
CPC classification number: G06T7/0004 , G06N5/04 , G06N20/00 , G06Q30/0283 , G06V20/176 , G06V20/188 , G06T2200/24 , G06T2207/10032 , G06T2207/30161
Abstract: Aspects of the disclosure relate to using computer vision methods for asset evaluation. A computing platform may receive historical images of a plurality of properties and corresponding historical inspection results. Using the historical images and historical inspection results, the computing platform may train a roof waiver model (which may be a computer vision model) to output inspection prediction information directly from an image. The computing platform may receive a new image corresponding to a particular residential property. Using the roof waiver model, the computing platform may analyze the new image to output of a likelihood of passing inspection. The computing platform may send, to a user device and based on the likelihood of passing inspection, inspection information indicating whether or not a physical inspection should be performed and directing the user device to display the inspection information, which may cause the user device to display the inspection information.
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公开(公告)号：US12051114B2
公开(公告)日：2024-07-30
申请号：US17220091
申请日：2021-04-01
Applicant: Allstate Insurance Company
Inventor： Deborah-Anna Reznek , Adam Sturt , Jeremy Werner , Adam Austin , Amber Parsons , Xiaolan Wu , Ryan Rosenberg , Lizette Lemus Gonzalez , Weizhou Wang , Stephanie Wong , Charles Cox , Jean Utke , Yusuf Mansour , Tia Miceli , Lakshmi Prabha Nattamai Sekar , Meg G. Walters , Dylan Stark , Emily Pavey
IPC: G06Q40/00 , G06F18/214 , G06Q10/10 , G06Q30/0283 , G06Q40/08 , G06V20/17
CPC classification number: G06Q40/08 , G06F18/214 , G06Q10/10 , G06Q30/0283 , G06V20/17
Abstract: Aspects of the disclosure relate to using computer vision methods to forecast damage. A computing platform may receive historical images comprising aerial images of residential properties and historical loss data corresponding to the residential properties. Using the historical images and the historical loss data, the computing platform may train a computer vision model, which may configure the computer vision model to output loss prediction information directly from an image. The computing platform may receive a new image corresponding to a particular residential property, and may analyze the new image, using the computer vision model, which may directly result in a likelihood of damage score. Based on the likelihood of damage score, the computing platform may send likelihood of damage information and one or more commands directing a user device to display the likelihood of damage information, which may cause the user device to display the likelihood of damage information.
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