Patent Issued for Apparatus and method for remote determination of architectural feature elevation and orientation (USPTO 11480683): Assurant Inc.

2022 NOV 11 (NewsRx) -- By a News Reporter-Staff News Editor at Insurance Daily News -- Assurant Inc. (New York, New York, United States) has been issued patent number 11480683, according to news reporting originating out of Alexandria, Virginia, by NewsRx editors.

The patent’s inventors are Brusky, Ron (Miami, FL, US), Kambhatla, Prasanth (Atlanta, GA, US), Matta, Rajiv (Atlanta, GA, US), Schmitt, Mathew (Atlanta, GA, US).

This patent was filed on May 3, 2019 and was published online on October 25, 2022.

From the background information supplied by the inventors, news correspondents obtained the following quote: “Effectively preparing for the damage to land, buildings, and other structures caused by floods has challenged individuals and communities for centuries. As the populations of coastal regions and other areas susceptible to flood events have grown, so too has the need to effectively assess the risks to people and property posed by such flood events. The inventors of the invention disclosed herein have identified technical challenges associated with efficiently determining the elevation and orientation of architectural features of structures erected on particular parcels of land, and developed the solutions described and otherwise referenced herein.”

Supplementing the background information on this patent, NewsRx reporters also obtained the inventors’ summary information for this patent: “An apparatus, computer program product, and method are therefore provided in accordance with an example embodiment in order permit the efficient determination of an elevation position of an architectural feature of a structure. In this regard, the method, apparatus and computer program product of an example embodiment provide for the creation of a predicted feature position data set that can be stored within a renderable object and otherwise presented to a user via an interface of a client device. Moreover, the method, apparatus, and computer program product of an example embodiment provide for use of the machine learning model in connection with the determination and retrieval of a predicted feature elevation position set determined based at least in part on location context data associated with a target geographic location and location context data associated with one or more other geographic locations.

“In an example embodiment, an apparatus is provided, the apparatus comprising a processor and a memory, the memory comprising instructions that configure the apparatus to: receive a message request data object from a client device associated with a user; extract, from the message request data object, a location identification data set, wherein the location identification data set is associated with a first geographic location; receive a first location context data object, wherein the first location context data object is associated with the first geographic location; receive a second location context data object, wherein the second location context data object is associated with a second geographic location; retrieve a predicted feature elevation position data set, wherein retrieving the predicted feature elevation position data set comprises applying the location identification data set, the first location context data object, and the second location context data object to a first model; and generate a control signal causing a renderable object comprising the predicted feature position data set to be displayed on a user interface of the client device associated with the user.

“In some example implementations of such an apparatus, the message request data object comprises an authenticated indication of the identity of the user. In some such example implementations, and in other example implementations, the location identification data set comprises a geographic coordinates set for the first geographic location. In some such example implementations, the geographic coordinates set define a location of an architectural feature of a structure located at the first geographic location.

“In some example implementations of such an apparatus, the first location context data object comprises a light detection and ranging (LiDAR) data set associated with the first geographic location. In some such example implementations, and in other example implementations, the first location context data object further comprises a land use data set associated with the first geographic location. In some such example implementations, the first location context data object further comprises a property characteristic dataset, which may include information regarding the foundation type, date of construction, construction materials used, and/or other information that may be obtained from databases associated with permitting, taxation, and/or other sources, for example. In some such example implementations, the first location context data object further comprises a land coverage data set associated with the first geographic location. In some such example implementations, the first location context data object further comprises a census data set associated with the first geographic location.

“In some example implementations of such an apparatus, the second location context data object comprises an identification of an elevation position of an architectural feature of a structure located at the second geographic location. In some such example implementations, and in other example implementations, the first model is a geospatial machine learning model. In some such example implementations, and in other example implementations, retrieving a predicted feature position data set comprises: applying the location identification data set, the first location context data object, and the second location context data object to the geo spatial machine learning model; and determining, by the geospatial machine learning model, a predicted location of a finished floor of the structure located at the first geographic location.”

The claims supplied by the inventors are:

“1. A system for determining an elevation position of an architectural feature of a structure, the system comprising: a survey vehicle comprising at least one sensor configured to transmit ranging signals towards one or more structures, receive returns from a reflection of the ranging signals, and generate ranging data objects based on the returns; a client device associated with a user configured to generate a message request data object and display a renderable object on a user interface; at least one elevation prediction apparatus comprising at least one processor and at least one memory comprising computer program code, the at least one memory and the computer program code configured to, with the at least one processor, cause the at least one elevation prediction apparatus to: receive the message request data object from the client device; extract, from the message request data object, a location identification data set, wherein the location identification data set is associated with a first geographic location; receive a first location context data object, wherein the first location context data object is associated with the first geographic location and based at least in part on the ranging data object; receive a second location context data object, wherein the second location context data object is associated with a second geographic location; retrieve a predicted feature elevation position data set, wherein retrieving the predicted feature elevation position data set comprises applying the location identification data set, the first location context data object, and the second location context data object to a first model; and generate a control signal causing the renderable object comprising the predicted feature elevation position data set to be displayed on the user interface of the client device associated with the user.

“2. The system of claim 1, wherein the message request data object comprises an authenticated indication of the identity of the user.

“3. The system of claim 1, wherein the location identification data set comprises a geographic coordinates set for the first geographic location.

“4. The system of claim 1, wherein the first location context data object comprises a light detection and ranging (LiDAR) data set associated with the first geographic location.

“5. The system of claim 1, wherein at least one of the first location context data object and the second location context data object includes one or more calculated elevation values based on the ranging data objects.

“6. The system of claim 5, wherein the system is configured to calculate the one or more calculated elevation values based upon the ranging data objects in an instance in which the one or more calculated elevation values are missing from an initial data object.

“7. The system of claim 6, wherein the at least one sensor comprises a LiDAR sensor and wherein the one or more calculated elevation values are based on LiDAR data returns.

“8. The system of claim 7, wherein the one or more calculated elevation values comprise at least one of highest adjacent grade value or a lowest adjacent grade value.

“9. The system of claim 1, wherein the second location context data object comprises an identification of an elevation position of an architectural feature of a second structure located at the second geographic location.

“10. The system of claim 1, wherein the predicted feature elevation position data set comprises a predicted elevation position of the architectural feature of the structure located at the first geographic location.

“11. The system of claim 1, wherein the first model is a geospatial machine learning model.

“12. The system of claim 11, wherein retrieving the predicted feature elevation position data set comprises: applying the location identification data set, the first location context data object, and the second location context data object to the geospatial machine learning model; and determining, by the geospatial machine learning model, a predicted finished floor elevation position of the structure located at the first geographic location.

“13. An apparatus for determining an elevation position of an architectural feature of a structure, the apparatus comprising at least one processor and at least one memory comprising computer program code, the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus to: receive a message request data object from a client device associated with a user; extract, from the message request data object, a location identification data set, wherein the location identification data set is associated with a first geographic location; receive a first location context data object, wherein the first location context data object is associated with the first geographic location; receive a second location context data object, wherein the second location context data object is associated with a second geographic location; retrieve a predicted feature elevation position data set, wherein retrieving the predicted feature elevation position data set comprises applying the location identification data set, the first location context data object, and the second location context data object to a first model; and generate a control signal causing a renderable object comprising the predicted feature elevation position data set to be displayed on a user interface of the client device associated with the user.

“14. The apparatus of claim 13, wherein the message request data object comprises an authenticated indication of the identity of the user.

“15. The apparatus of claim 13, wherein the location identification data set comprises a geographic coordinates set for the first geographic location.

“16. The apparatus of claim 15, wherein the geographic coordinates set defines a geographic location of the architectural feature of the structure located at the first geographic location.

“17. The apparatus of claim 13, wherein the first location context data object comprises a light detection and ranging (LiDAR) data set associated with the first geographic location.

“18. The apparatus of claim 17, wherein the first location context data object further comprises a land use data set associated with the first geographic location.

“19. The apparatus of claim 18, wherein the first location context data object further comprises a land coverage data set associated with the first geographic location.

“20. The apparatus of claim 19, wherein the first location context data object further comprises a census data set associated with the first geographic location.

“21. The apparatus of claim 13, wherein the second location context data object comprises an identification of an elevation position of an architectural feature of a second structure located at the second geographic location.

“22. The apparatus of claim 13, wherein the predicted feature elevation position data set comprises a predicted elevation position of the architectural feature of the structure located at the first geographic location.

“23. The apparatus of claim 13, wherein the first model is a geospatial machine learning model.

“24. The apparatus of claim 23, wherein retrieving the predicted feature elevation position data set comprises: applying the location identification data set, the first location context data object, and the second location context data object to the geospatial machine learning model; and determining, by the geospatial machine learning model, a predicted finished floor elevation position of the structure located at the first geographic location.

“25. A method for predicting an elevation of an architectural feature of a structure at a geographic location, the method comprising: receiving a message request data object from a client device associated with a user; extracting, from the message request data object, a location identification data set, wherein the location identification data set is associated with a first geographic location; receiving a first location context data object, wherein the first location context data object is associated with the first geographic location; receiving a second location context data object, wherein the second location context data object is associated with a second geographic location; retrieving a predicted feature elevation position data set, wherein retrieving the predicted feature elevation position data set comprises applying the location identification data set, the first location context data object, and the second location context data object to a first model; and generating a control signal causing a renderable object comprising the predicted feature position data set to be displayed on a user interface of the client device associated with the user.

“26. The method of claim 25, wherein the first location context data object does not include an elevation certificate data object.”

For the URL and additional information on this patent, see: Brusky, Ron. Apparatus and method for remote determination of architectural feature elevation and orientation. U.S. Patent Number 11480683, filed May 3, 2019, and published online on October 25, 2022. Patent URL: http://patft.uspto.gov/netacgi/nph-Parser?Sect1=PTO1&Sect2=HITOFF&d=PALL&p=1&u=%2Fnetahtml%2FPTO%2Fsrchnum.htm&r=1&f=G&l=50&s1=11480683.PN.&OS=PN/11480683RS=PN/11480683

(Our reports deliver fact-based news of research and discoveries from around the world.)