The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.
The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.
Patent No.:
Date of Patent:
Jul. 30, 2024
Filed:
Apr. 01, 2021
Allstate Insurance Company, Northbrook, IL (US);
Deborah-Anna Reznek, Redwood City, CA (US);
Adam Sturt, Chicago, IL (US);
Jeremy Werner, Oak Park, IL (US);
Adam Austin, Wheaton, IL (US);
Amber Parsons, Bothell, WA (US);
Xiaolan Wu, Sunnyvale, CA (US);
Ryan Rosenberg, Palo Alto, CA (US);
Lizette Lemus Gonzalez, Bothell, WA (US);
Weizhou Wang, Redwood City, CA (US);
Stephanie Wong, Chicago, IL (US);
Charles Cox, Seattle, WA (US);
Jean Utke, Lisle, IL (US);
Yusuf Mansour, Bothell, WA (US);
Tia Miceli, Aurora, IL (US);
Lakshmi Prabha Nattamai Sekar, Aurora, IL (US);
Meg G. Walters, Chicago, IL (US);
Dylan Stark, Arlington Heights, IL (US);
Emily Pavey, Chicago, IL (US);
Allstate Insurance Company, Northbrook, IL (US);
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.