DETAILED ACTION
Notice of Pre-AIA or AIA Status
1. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Information Disclosure Statement
2. The information disclosure statements (IDS) submitted on 09/08/2025, 09/17/2025, 10/07/2025, and 10/10/2025. The submissions are in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statements are being considered by the examiner.
Claim Rejections - 35 USC §101
3. 35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
4. Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
5. In the instant case, independent claims 1, 8, 14, and 20 are directed to a “method, systems, and non-transitory computer-readable medium for evaluating properties”.
6. Claim 1 recites “generating a property model for an evaluation report”. Specifically, claim 1 recites [abstract ideas emphasized in bold] “transmitting, by a processor to an imaging vehicle and via an Application Programming Interface (API), a command to capture an image of a property, the command indicating a location of the property;
capturing, by the processor via the imaging vehicle and based at least in part on the command, the image;
receiving, by the processor from the imaging vehicle via the API, the image;
generating, by the processor, an evaluation report comprising a risk attribute associated with a characteristic of the property;
generating, by the processor and using the image, a virtual environment comprising a model of the property;
integrating, by the processor, the evaluation report into the model;
generating, by the processor, a visual overlay associated with the model and comprising a representation of the evaluation report; and
displaying, by the processor, the model and the visual overlay in the virtual environment”. Subject matter grouped under “Certain methods of organizing human activity” (e.g., fundamental economic principles or practices), and an abstract idea in prong one of step 2A (MPEP 2106.04(a)).
7. This judicial exception is not integrated into a practical application because, when analyzed under prong two of step 2A (MPEP 2106.04 II), the additional elements of claim 1 such as “a processor”, “an image vehicle”, “an Application Programming Interface (API)”, “a virtual environment”, “a visual overlay”, and “displaying, by the processor, the model and the visual overlay in the virtual environment” represent the use of a computer as a tool to perform an abstract idea and/or does no more than generally link the abstract idea to a particular field of use. With respect to “transmitting, by a processor to an imaging vehicle and via an Application Programming Interface (API), a command to capture an image of a property, the command indicating a location of the property” and “receiving, by the processor from the imaging vehicle via the API, the image” is simply transmitting data, “[use] of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) (e.g., a fundamental economic practice) does not integrate a judicial exception into a practical application or provide significantly more, (MPEP 2106.05(f)(2)).
8. When analyzed under step 2B (MPEP 2106.04 II), as the additional elements do no more than represent the use of a computer, or computer technology, as a tool to perform generating a property model for an evaluation report and/or generally link the abstract idea to a particular technological environment or field of use, they do not improve computer functionality or provide an improvement to another technology or technological field.
9. Hence, claim 1 is not patent eligible.
10. Claims 8, 14, and 20 also recite “generating a property model for an evaluation report”. Subject matter grouped under “Certain methods of organizing human activity” (e.g., fundamental economic principles or practices), and an abstract idea in prong one of step 2A (MPEP 2106.04(a)).
11. As in the case of claim 1, the judicial exception is not integrated into a practical application because when analyzed under prong two of step 2A (MPEP 2106.04 II), the additional elements of claims 8, 14, and 20 such as “a processor”, “a non-transitory memory”, “an image vehicle”, “an Application Programming Interface (API)”, “a virtual environment”, “a visual overlay”, “displaying the model and the visual overlay in the virtual environment”, “a non-transitory computer-readable medium”, “means for transmitting”, “means for capturing”, “means for receiving”, “means for generating”, “means for generating”, “means for integrating”, “means for generating”, and “means for displaying” represent the use of a computer as a tool to perform an abstract idea and/or does no more than generally link the abstract idea to a particular field of use. With respect to “transmitting, to an imaging vehicle and via an Application Programming Interface (API), a command to capture an image of a property, the command indicating a location of the property” and “receiving, from the imaging vehicle via the API, the image” is simply transmitting data, “[use] of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) (e.g., a fundamental economic practice) does not integrate a judicial exception into a practical application or provide significantly more, (MPEP 2106.05(f)(2)).
12. When analyzed under step 2B (MPEP 2106.04 II), as the additional elements do no more than represent the use of a computer, or computer technology, as a tool to perform generating a property model for an evaluation report and/or generally link the abstract idea to a particular technological environment or field of use, they do not improve computer functionality or provide an improvement to another technology or technological field.
13. Hence, claims 8, 14, and 20 are not patent eligible.
14. The following dependent claims recent additional elements not addressed above:
claims 6, 11, and 15 recite “a user device”;
claims 7 and 19 recite “Global Positioning System (GPS) coordinates”;
claim 9 recites “an aquatic vehicle” and “a ground vehicle”;
claim 10 recites “a satellite link”; and
claim 18 recites “a user device” and “displaying the additional visual overlay in the virtual environment”.
When considered individually, and as a whole, each of these additional elements amount to merely "apply it", as they are merely applying the abstract idea to the technical environment of the user device, the Global Positioning System (GPS) coordinates, the aquatic vehicle, the ground vehicle, the satellite link, and displaying the additional visual overlay in the virtual environment.
15. Dependent claims 2-7, 9-13, and 15-19 merely expand upon the abstract ideas of the independent claims and are therefore rejected under the same rationale as claims 1, 8, and 14 respectively.
Conclusion of 35 USC §101
16. The claims as a whole do not amount to significantly more than the abstract idea itself. This is because the claims do not effect an improvement to another technology or technical field; the claims do not amount to an improvement to the functioning of a computer system itself; and the claims do not move beyond a general link of the use of an abstract idea to a particular technological environment.
17. Accordingly, there are no meaningful limitations in the claims that transform the judicial exception into a patent eligible application such that the claims amount to significantly more than the judicial exception itself.
Claim Rejections - 35 USC § 103
18. In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
19. The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
20. The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
21. Claims 1-4, 6-7, 14-16, and 18-20 are rejected under 35 U.S.C. 103 as being unpatentable over US20170206648A1 to Marra et al. in view of US20200234379A1 to Geylani.
22. As per claim 1:
Marra et al. discloses the following limitations:
transmitting, by a processor to an imaging vehicle and via an Application Programming Interface (API), a command to capture an image of a property, the command indicating a location of the property ([0023] “…The mobile computing device issues commands to the UAV's flight and camera controller via the UAV system's API to traverse a series of geographic waypoints and capture photos in specific orientations, and record camera position and orientation.”, [0061] “In an embodiment, upon user approval, the mobile computing device 101 executes the flight plan 150 using the UAV control data 144 by issuing commands to the UAV's flight and camera controller via the UAV system's API to traverse a series of geographic waypoints, and capture photos in specific orientations, and record camera position and orientation…”, [claim 7] “…wherein the flight plan is executed by issuing commands to the unmanned aerial vehicle's flight and camera controller at least in part via the unmanned aerial vehicle's application program interface, to traverse a series of geographic waypoints, capture images in orientations ensuring substantially complete coverage of the structure area of interest, and record camera position and orientation…”, [0052] “The third party data 142 could include the geographic boundary from a public or commercially available database, based on the property mailing address or geolocation, location information from the UAV 102, or information from other sources, for example, Google Maps, and may be based on GPS location, among others.”, [0056] “The mobile computing device 101 may then transmit the UAV control data 144 to a UAV 102 via a communication link 111…”)
capturing, by the processor via the imaging vehicle and based at least in part on the command, the image ([0044] “Device 101 may have an application that maintains connectivity via a local wireless network protocol 111 or other connection to a UAV or drone 102 in order to acquire geotagged images of the structure 103 while flying above common obstacles or obstructions 104, such as utility wires or trees, but within a given property boundary 200 of the building owner or manager 114.”, [0066] “…The images are captured at camera exposure stations 208 along the trajectory 202 such that successive camera positions are angularly separated by less than an angle θ 207 with respect to the AOI centroid 205…”, [0062] “…The images captured and other data constitute UAV output data 146, which is transferred from the UAV 102 to the mobile computing device 101.”)
receiving, by the processor from the imaging vehicle via the API, the image ([0024] “After the image and data capturing process has been completed, the mobile computing device may then receive the data and images in the form of UAV output data…”, [0046] “…At the end of or during the flight, images and data comprising UAV output data 146 can be transferred from the UAV's on board storage via Wi-Fi 111, SD card, or other method, to the mobile computing device 101 so that the application running on device 101 can compress, manipulate and securely upload images and data via a wide area network 105 or other connection to computer servers 106 running web services…”, [claim 1] “…receive unmanned aerial vehicle output data from the unmanned aerial vehicle; and transmit the unmanned aerial vehicle output data to a server via a wireless or wired communication link…”)
generating, by the processor, an evaluation report comprising a risk attribute associated with a characteristic of the property ([0027] “…providing a structural report enumerating surface type, area, condition, slope, and dimensions that can be quickly compiled from the three-dimensional wireframe or regularized vector model, photo textured polygonal mesh, and image inspection results, which is suitable for accurate repair or enhancement cost estimation…”, [0026] “…In one embodiment, the server can generate a condensed report for inspection and construction estimation, and other analysis and reports.”, [0048] “Once three-dimensional reconstruction and image inspection is completed, use case specific report generation is performed by a Structure Report Engine 110 where reports 520 are published into a Structure data base 107 for review by the enterprise or other user 112 and property owners 114.”, [0078] “…an example image on the user interface of a mobile computing device inspection application 302 that is intended for use by field users 100 for inspecting the structure AOI 201 in varying respects such as automated damage detection, assessing condition and composition of the structure 103, identifying structural features requiring maintenance, repair or replacement, assessing hazards of the site from an occupant or construction perspective, planning staging and work areas…”, [0006] “The construction and insurance industries expend substantial time and effort in performing both inspection and measurement of structures…”)
integrating, by the processor, the evaluation report into the model ([claim 19] “…wherein the structure model generator creates a report with data suitable to estimate a needed task by the structure report engine, wherein the structure report engine uses the regularized vector model as input, and annotates the regularized vector model with descriptive information, wherein the descriptive information comprises dimensions and selected inspection annotations stored in the structure database, to form a report design plan diagram…”, [0100] “…This process, may be performed by the Structure report engine 110, and uses the regularized vector model 510 as input and annotates it with descriptive information such as dimensions and selected inspection annotations 308 stored in the structure database 107 to form a report design plan diagram 522.”, [0092] “…The report design plan diagram 522 or component list 524 may also include attributed annotations 308 that were optionally specified by users with the example image inspection interface 302 shown in FIG. 3…”, “…Components of this list 524 can be attributed automatically from the vector model 510 geometric topology…”)
generating, by the processor, a visual overlay associated with the model and comprising a representation of the evaluation report ([0080] “The application 302 provides the field user 100 a means of adding annotations 308 to the image that can be categorized and added to the structure database 107 via image inspection service 113… The annotation can be recorded according to its precise image coordinates or projected to an approximate geographic position based on image orientation parameters stored in the Image Database 108, the image coordinates of the annotation, and the geographic elevation plane specified by the sum of the home point 203 elevation and the structure height 211.”, [0100] “…uses the regularized vector model 510 as input and annotates it with descriptive information such as dimensions and selected inspection annotations 308 stored in the structure database 107 to form a report design plan diagram 522.”, [0084] “FIG. 4a 402 provides a convenient image underlay when editing or validating three-dimensional vector models in a variety of Computer Aided Design (CAD) products such as AutoCAD or SketchUp…”)
displaying, by the processor, the model and the visual overlay in the virtual environment ([0099] “…Embodiments using interactive editing for this process 610 can display the polygonal mesh 402 for the operator to use as a visual reference in order to verify the model portrays needed features seen in the imagery…”, [0039] “FIG. 5b illustrates an example of a three-dimensional building model viewed from overhead as a wireframe generated from the three-dimensional polygonal facets (from FIG. 6a ) and photo textured mesh (from FIG. 5a ).”, [0047] “The images and their geotags may be stored in an Image Database 108 and are generally immediately made available to enterprise and other users 112 via an Image Inspection Service 113…”)
Marra et al. does not disclose, however, Geylani, as shown, teaches the following limitations:
generating, by the processor and using the image, a virtual environment comprising a model of the property ([0021] “…The system, by using devices such as 3D scanner, visual media capture equipment, can create a 3D modelling of the insured asset or interest in virtual and augmented reality platform in a structured way…”, [0054] “…With remote material detection system and image processing, the SANCAR creates a 3D model of the insured. The model can include the dimension, material types of structural assets and their distances to one another.”, [0056] “After the data capture, end users of the system shown in FIG. 7B can walk through the digital 3D model of the insured asset in virtual reality environment provided by the API database 4050 application…”, [0059] “Based on the above detailed structural asset automatic detection and automatic estimation methodology, insured assets/interests are scheduled and modelled in a digital environment that is saved in SANCAR central database…”)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate a system for allowing continuous risk monitoring and dynamic underwriting pricing that can use visual media capture equipment to create a 3D modelling of the insured asset or interest in virtual and augmented reality platform of Geylani (‘379, [0011]) with the teaching of Marra et al. for allowing a field user to operate a UAV via a mobile computing device to capture images of a structure area of interest (‘648, [0021]) for generating a three-dimensional model of the property from the captured visual data and placing inside a virtual reality environment (‘379, [0021],[0054], [0056).
Claims 8, 14, and 20 are rejected using the same rationale that was used for the rejection of claim 1.
As per claims 8 Marra et al. additionally discloses the following limitations:
A system comprising: a processor; and a non-transitory memory storing computer-executable instructions that, when executed by the processor, cause the processor to perform operations comprising: ([claim 20] “A non-volatile computer readable medium with instructions stored thereon which, if executed by a processor, causes the processor to:”, [0105] “In FIG. 7, computing system 710 includes processing system 716, storage system 714, software 712, communication interface 718, and user interface 720…”, [0108] “…Storage system 714 can comprise any storage media readable by processing system 716, and capable of storing software 712…”, [0109] “…In some implementations, the storage media can be a non-transitory storage media…”)
As per claim 14 Marra et al. additionally discloses the following limitations:
A non-transitory computer-readable medium comprising instructions that, when executed by a processor, cause the processor to perform operations comprising: ([claim 20] “A non-volatile computer readable medium with instructions stored thereon which, if executed by a processor, causes the processor to:”, [0105] “In FIG. 7, computing system 710 includes processing system 716, storage system 714, software 712, communication interface 718, and user interface 720…”, [0108] “…Storage system 714 can comprise any storage media readable by processing system 716, and capable of storing software 712…”, [0109] “…In some implementations, the storage media can be a non-transitory storage media…”)
As per claim 20 Marra et al. additionally discloses the following limitations:
A system for evaluating properties, the system comprising: ([claim 1] “An image and information capturing and processing system, comprising:”, [0002] “The present disclosure relates to a system and method for capturing and processing images and more particularly to an automated system and method for structural inspection and construction estimation using images from an unmanned aerial vehicle (UAV).”, [0005] “For a variety of purposes, the condition of building exteriors regularly needs to be assessed to evaluate and to permit cost effective maintenance and repair…”)
23. As per claim 2:
Marra et al. discloses the following limitations:
determining, by the processor, that a first resolution of the image is below an image resolution threshold ([0047] “…a three-dimensional reconstruction processing of the image data set may be performed by a Structure Model Generator 109, which performs initial quality checks on the data to verify the acquired data is usable and can issue a notification to the field user 100 if data needs to be reacquired.”, [claim 15] “…further comprising a structure model generator, on the server, configured to perform initial quality checks on the modified unmanned aerial vehicle data to verify the modified unmanned aerial vehicle data is usable, and wherein the structure model generator issues a notification if the modified unmanned aerial vehicle data needs to be reacquired.”, [0064] “…If this is unsuccessful the problem can be characterized within minutes of upload and the field user 100 can be notified through the mobile computing device 101 that a problem occurred during acquisition 134…”, [0009] “…Various features of a property critical for accurate construction or repair estimates are often not visible in aerial imagery archives because of limited coverage, inadequate resolution, occlusions from trees or roof overhangs, and out dated content…”)
based at least in part on determining that the first resolution is below the image resolution threshold, transmitting, by the processor to the imaging vehicle via the API, an additional command to capture an additional image of the property having a second resolution greater than the first resolution ([0058] “…Images can also be captured in multiple acquisition trajectories 202 with varying ranges to support a variety of use cases that demand higher resolution imagery. A pyramid of higher resolution imagery covering all or parts of the structure 103 can be collected for inspection purposes so that even very detailed images covering very small portions of the structure 103 can be automatically matched allowing rapid indexing of the image collection and preventing fraudulent exchange of imagery from another property…”, [0056] “…While the acquisition trajectory 202 is paused or after it has been completed, the field user 100 can manually control the UAV 102 with or without the aid of onboard obstacle avoidance systems to for instance, capture supplemental images of interest such as close up photos of defective features before resuming the flight plan 150.”, [claim 7] “…wherein the flight plan, when paused, allows the field user to manually control the unmanned aerial vehicle to capture supplemental images of interest before resuming the flight plan.”, [0023] “…The mobile computing device issues commands to the UAV's flight and camera controller via the UAV system's API to traverse a series of geographic waypoints and capture photos in specific orientations, and record camera position and orientation.”)
receiving, by the processor from the imaging vehicle, the additional image ([0062] “Based on whether the field user 100 requires ground level images 129, the mobile computing device 101 will enter a mode with the propeller motors disengaged to capture images while the field user 100 is holding the UAV 102 with the camera pointed towards the structure AOI 201 and traversing the flight path 130 generally. The images captured and other data constitute UAV output data 146, which is transferred from the UAV 102 to the mobile computing device 101.”, [0024] “After the image and data capturing process has been completed, the mobile computing device may then receive the data and images in the form of UAV output data…”)
24. As per claim 3:
Marra et al. discloses the following limitations:
receiving an input associated with the virtual environment ([0099] “Embodiments using interactive editing for this process 610 can display the polygonal mesh 402 for the operator to use as a visual reference in order to verify the model portrays needed features seen in the imagery…”, [0096] “…Some segmentation of the point cloud 404 may be applied with standard interactive point cloud edit tools prior to generating the vector model 502 in order to reduce processing time and minimize extraneous geometry in the scene that is not part of the structure such as from ground or vegetation surfaces.”, [0056] “…The mobile computing device 101 allows the field user 100 to start, pause, resume, or abort the flight plan 150 and track the UAV 102 position as well as display imagery from the camera in real-time…”, [claim 19] “…wherein the report design plan diagram is published into a structure database and is capable of being retrieved by an enterprise user or other users along with other three dimensional data products available for self annotation, interactive measurement, and report modification.”)
determining, by the processor based at least in part on the input, that the first resolution of the image is below the image resolution threshold ([0099] “Embodiments using interactive editing for this process 610 can display the polygonal mesh 402 for the operator to use as a visual reference in order to verify the model portrays needed features seen in the imagery. The small roof protrusions 514 are examples of features that can be corrupted or omitted during the reconstruction 606 or model fit processes 608 but that can be restored with manual editing during creation of the regularized vector model 610 using standard solid geometry operations with a CAD package such as Autodesk Revit, Bentley MicroStation, or Trimble SketchUp…”, [0056] “…While the acquisition trajectory 202 is paused or after it has been completed, the field user 100 can manually control the UAV 102 with or without the aid of onboard obstacle avoidance systems to for instance, capture supplemental images of interest such as close up photos of defective features before resuming the flight plan 150.”)
25. As per claim 4:
Marra et al. discloses the following limitations:
wherein generating the virtual environment comprises removing one or more flaws from the model ([0088] “…However, there are extraneous facets or artifacts 504 of this model that in some embodiments may be undesirable for a succinct design model.”, [0089] “…This regularized vector model 510 lacks the extraneous facets 504 apparent in the previous figure (FIG. 5a ) as well as the gaps, small jagged edge segments, and irregular edge angles…”, [0098] “A vector cleaning step 610 can be applied next where the facets of the initial structural vector model 502 are regularized with algorithms such as Ramer-Douglas-Peucker algorithm (RDP), Sleeve, Minimum Description Length (MDL), or the like…Extraneous facets 504 can be eliminated algorithmically based on area, perimeter, and surface normal thresholds or through interactive editing.”, [claim 17] “…wherein the structure model generator performs vector cleaning, wherein facets of the initial structural vector model are regularized with algorithms to create a regularized watertight vector model with edges labeled according to their topology and construction conventions.”, [0102] “Robust methods can then be used to eliminate the systematic tilts of the three dimensional models (402, 404, and 510) based on building construction conventions that maintain level structures to within a fraction of a degree by calculating the average or median tilt angles of various labeled edges in the vector model 510 and subtracting those tilt vectors from the models (402, 404, and 510).”)
26. As per claim 5:
Marra et al. discloses the following limitations:
determining a feature of the property associated with the characteristic, wherein the feature is associated with an additional risk attribute distinct from the risk attribute ([0099] “…In some embodiments, machine learning techniques such as Convolutional Neural Networks can be combined with segmentation techniques such as Conditional Random Fields in order to detect and segment features that need to be either included or removed from vector models such as roof vents, chimneys, windows, trees, or power lines.”, [0082] “In some embodiments, this same geographic positioning technique can be used in reverse in order to project a subset of the polygonal mesh 402 that falls outside the property boundary line 200 into image coordinates of the inspection image(s) 304 thus creating image masks corresponding to pixels within the inspection images 304 that fall outside the property owner's 114 possession or legal right to view. This process permits the system to reduce the effective image resolution of the inspection images 304 by blurring convolution in areas outside of the property 200 being surveyed and in doing so maintain compliance with privacy regulations of some governments as well as to minimize the potential risk of privacy related law suits.”, [0078] “…assessing hazards of the site from an occupant or construction perspective…”)
excluding the feature of the property from the model of the property ([claim 12] “…wherein the unmanned aerial vehicle output data is limited to the structure area of interest and eliminates or degrades imagery of objects or people outside the property bounds based on an image mask derived from the three-dimensional reconstruction polygon mesh and the property boundary.”, [0099] “…In some embodiments, machine learning techniques such as Convolutional Neural Networks can be combined with segmentation techniques such as Conditional Random Fields in order to detect and segment features that need to be either included or removed from vector models such as roof vents, chimneys, windows, trees, or power lines.”, [0096] “…Some segmentation of the point cloud 404 may be applied with standard interactive point cloud edit tools prior to generating the vector model 502 in order to reduce processing time and minimize extraneous geometry in the scene that is not part of the structure such as from ground or vegetation surfaces.”, [0098] “…Extraneous facets 504 can be eliminated algorithmically based on area, perimeter, and surface normal thresholds or through interactive editing.”)
27. As per claim 6:
Marra et al. discloses the following limitations:
receiving, by the processor from a user device, an input associated with the virtual environment, the input indicating an assessment of an additional characteristic of the property represented in the model of the property ([0080] “The application 302 provides the field user 100 a means of adding annotations 308 to the image that can be categorized and added to the structure database 107 via image inspection service 113… The annotation can be recorded according to its precise image coordinates or projected to an approximate geographic position based on image orientation parameters stored in the Image Database 108, the image coordinates of the annotation, and the geographic elevation plane specified by the sum of the home point 203 elevation and the structure height 211.”, [0078] “…an example image on the user interface of a mobile computing device inspection application 302 that is intended for use by field users 100 for inspecting the structure AOI 201 in varying respects such as automated damage detection, assessing condition and composition of the structure 103, identifying structural features requiring maintenance, repair or replacement, assessing hazards of the site from an occupant or construction perspective, planning staging and work areas…”, [claim 19] “…wherein the report design plan diagram is published into a structure database and is capable of being retrieved by an enterprise user or other users along with other three dimensional data products available for self annotation, interactive measurement, and report modification.”)
determining, by the processor based at least in part on the assessment and the evaluation report, an updated evaluation report comprising an updated risk attribute associated with the additional characteristic of the property ([0093] “…Portions of the report 520 can be automatically updated if, for example, the enterprise user 112, field user 100, or internal algorithm provides additional information via the image inspection service 113 to be added to the report 520 at a later time…”, [0100] “…This process, may be performed by the Structure report engine 110, and uses the regularized vector model 510 as input and annotates it with descriptive information such as dimensions and selected inspection annotations 308 stored in the structure database 107 to form a report design plan diagram 522.”, [0092] “…The report design plan diagram 522 or component list 524 may also include attributed annotations 308 that were optionally specified by users with the example image inspection interface 302 shown in FIG. 3…”)
28. As per claim 7:
Marra et al. discloses the following limitations:
wherein the command comprises Global Positioning System (GPS) coordinates corresponding to the location of the property ([0023] “…The mobile computing device issues commands to the UAV's flight and camera controller via the UAV system's API to traverse a series of geographic waypoints and capture photos in specific orientations, and record camera position and orientation.”, [0045] “The mobile computing device 101 may be capable of running an operating system, such as the Android or Apple operating system, that can sufficiently control a UAV 102 such as a DJI Phantom, three-dimensional Robotics Solo, Yuneec Typhoon, or Microdrone MD4 series or other UAV 102 via Wi-Fi or other connection, such that GPS geotagged imagery can be captured at desired geospatial locations and orientations…”, [0051] “…This polygon 200 can be designated by (a) sketching with the mobile computing device 102 interface over the apparent property lines 200 in the application's map image display, (b) tracking the mobile computing device's GNSS (global navigation satellite system) or GPS (global positioning system) position as the field user 100 walks around the property perimeter 200, or (c) retrieving third party data 142.”, [claim 4] “…wherein the home location comprises the global positioning system location of where the unmanned aerial vehicle is initialized, will launch from, and will land near.”)
29. As per claim 9:
Marra et al. does not disclose, however, Geylani, as shown, teaches the following limitations:
wherein the imaging vehicle comprises one or more of an aquatic vehicle or a ground vehicle ([0043] “…There is a ground mobile data capture/collector unit (GMDCU) 10. This unit can include, but is not limited to, a field engineer, loss adjuster, drone, any mobile ground unit that is capable of capturing the required/defined data…”, [0070] “FIG. 4 shows details of the ground mobile data collection unit 10 (GDMCU). This unit can be a human, a robot or a drone that is capable to move in confined spaces and collect data based on a set of defined, selected processes… These devices and equipment can include, for example, virtual reality (VR)/360 cameras 1030, structural sensor/3D scanning devices 1010, smart phones/tablets/devices 1040…”, [0050] “… With this instrument, GDMCU scans the insured risk location 50 along with all assets within the premise.”)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate a system for allowing continuous risk monitoring and dynamic underwriting pricing that can use visual media capture equipment to create a 3D modelling of the insured asset or interest in virtual and augmented reality platform of Geylani (‘379, [0011]) with the teaching of Marra et al. for allowing a field user to operate a UAV via a mobile computing device to capture images of a structure area of interest (‘648, [0021]) for having an imaging unit that travels on the ground (e.g., a mobile ground unit), which may be a robot or a drone moving through confined spaces with ability to capture images of the property of interest (‘379, [0021],[0054], [0056).
30. As per claim 10:
Marra et al. discloses the following limitations:
wherein receiving, from the imaging vehicle via the API, the image comprises receiving the image via a satellite link ([0107] “Additionally, computing system 710 includes communication interface 718 that can be further configured to transmit the collected data to computing system 750 using communication network 705. Communication network 705 could include the Internet, cellular network, satellite network, RF communication, blue-tooth type communication, near field, or any other form of communication network capable of facilitating communication between computing systems 710 and 750…”, [0046] “…In some embodiments, the UAV output data 146 can be transferred from the UAV 102 directly to a server 160, via, for example, long-term evolution (LTE) or other wired or wireless communication.”)
31. As per claim 11:
Marra et al. discloses the following limitations:
receiving, from a user device, an input associated with the virtual environment ([0099] “Embodiments using interactive editing for this process 610 can display the polygonal mesh 402 for the operator to use as a visual reference in order to verify the model portrays needed features seen in the imagery…”, [0056] “…The mobile computing device 101 allows the field user 100 to start, pause, resume, or abort the flight plan 150 and track the UAV 102 position as well as display imagery from the camera in real-time…”, [claim 19] “…wherein the report design plan diagram is published into a structure database and is capable of being retrieved by an enterprise user or other users along with other three dimensional data products available for self annotation, interactive measurement, and report modification.”)
based at least in part on the input, transmitting, to the imaging vehicle via the API, an additional command to capture an additional image of a feature of the property ([0056] “…While the acquisition trajectory 202 is paused or after it has been completed, the field user 100 can manually control the UAV 102 with or without the aid of onboard obstacle avoidance systems to for instance, capture supplemental images of interest such as close up photos of defective features before resuming the flight plan 150.”, [claim 7] “…wherein the flight plan, when paused, allows the field user to manually control the unmanned aerial vehicle to capture supplemental images of interest before resuming the flight plan.”, [0023] “…The mobile computing device issues commands to the UAV's flight and camera controller via the UAV system's API to traverse a series of geographic waypoints and capture photos in specific orientations, and record camera position and orientation.”, [0058] “…Images can also be captured in multiple acquisition trajectories 202 with varying ranges to support a variety of use cases that demand higher resolution imagery…”)
receiving, by the processor from the imaging vehicle, the additional image ([0062] “Based on whether the field user 100 requires ground level images 129, the mobile computing device 101 will enter a mode with the propeller motors disengaged to capture images while the field user 100 is holding the UAV 102 with the camera pointed towards the structure AOI 201 and traversing the flight path 130 generally. The images captured and other data constitute UAV output data 146, which is transferred from the UAV 102 to the mobile computing device 101.”, [0024] “After the image and data capturing process has been completed, the mobile computing device may then receive the data and images in the form of UAV output data…”)
32. As per claim 12:
Marra et al. discloses the following limitations:
wherein the input comprises an annotation indicating the feature ([0080] “The application 302 provides the field user 100 a means of adding annotations 308 to the image that can be categorized and added to the structure database 107 via image inspection service 113…”, [0078] “…an example image on the user interface of a mobile computing device inspection application 302 that is intended for use by field users 100 for inspecting the structure AOI 201 in varying respects such as automated damage detection, assessing condition and composition of the structure 103, identifying structural features requiring maintenance, repair or replacement, assessing hazards of the site from an occupant or construction perspective, planning staging and work areas…”, [0056] “…capture supplemental images of interest such as close up photos of defective features…”)
33. As per claim 13:
Marra et al. discloses the following limitations:
the input comprises an image resolution ([0022] “…The UAV control data is then used by the mobile computing device to create a flight plan based at least in part on the UAV control data that assures that images and data capturing are taken at optimal distances and intervals for three-dimensional reconstruction with required resolution…”, [0058] “…Images can also be captured in multiple acquisition trajectories 202 with varying ranges to support a variety of use cases that demand higher resolution imagery…”, [0050] “…The mobile computing device 101 receives user input data 140 at least in part via the user interface of device 101, from the field user 100 which includes the property bounds 200, the structure area of interest (AOI) 201, the structure AOI's height 211, and the obstacle clearance height 210, if any.”)
the additional command comprises instructions to capture the additional image at the image resolution ([0022] “…The UAV control data is then used by the mobile computing device to create a flight plan based at least in part on the UAV control data that assures that images and data capturing are taken at optimal distances and intervals for three-dimensional reconstruction with required resolution…”, [0058] “…Images can also be captured in multiple acquisition trajectories 202 with varying ranges to support a variety of use cases that demand higher resolution imagery. A pyramid of higher resolution imagery covering all or parts of the structure 103 can be collected for inspection purposes so that even very detailed images covering very small portions of the structure 103 can be automatically matched allowing rapid indexing of the image collection and preventing fraudulent exchange of imagery from another property…”, [0061] “In an embodiment, upon user approval, the mobile computing device 101 executes the flight plan 150 using the UAV control data 144 by issuing commands to the UAV's flight and camera controller via the UAV system's API to traverse a series of geographic waypoints, and capture photos in specific orientations, and record camera position and orientation…”)
34. As per claim 15:
Marra et al. discloses the following limitations:
receiving, from a user device, an input associated with the virtual environment ([0099] “Embodiments using interactive editing for this process 610 can display the polygonal mesh 402 for the operator to use as a visual reference in order to verify the model portrays needed features seen in the imagery…”, [0056] “…The mobile computing device 101 allows the field user 100 to start, pause, resume, or abort the flight plan 150 and track the UAV 102 position as well as display imagery from the camera in real-time…”, [claim 19] “…wherein the report design plan diagram is published into a structure database and is capable of being retrieved by an enterprise user or other users along with other three dimensional data products available for self annotation, interactive measurement, and report modification.”)
based at least in part on the input, transmitting, to the imaging vehicle via the API, an additional command to capture an additional image of a feature of the property ([0056] “…While the acquisition trajectory 202 is paused or after it has been completed, the field user 100 can manually control the UAV 102 with or without the aid of onboard obstacle avoidance systems to for instance, capture supplemental images of interest such as close up photos of defective features before resuming the flight plan 150.”, [claim 7] “…wherein the flight plan, when paused, allows the field user to manually control the unmanned aerial vehicle to capture supplemental images of interest before resuming the flight plan.”, [0023] “…The mobile computing device issues commands to the UAV's flight and camera controller via the UAV system's API to traverse a series of geographic waypoints and capture photos in specific orientations, and record camera position and orientation.”, [0058] “…Images can also be captured in multiple acquisition trajectories 202 with varying ranges to support a variety of use cases that demand higher resolution imagery…”)
receiving, by the processor from the imaging vehicle, the additional image ([0062] “Based on whether the field user 100 requires ground level images 129, the mobile computing device 101 will enter a mode with the propeller motors disengaged to capture images while the field user 100 is holding the UAV 102 with the camera pointed towards the structure AOI 201 and traversing the flight path 130 generally. The images captured and other data constitute UAV output data 146, which is transferred from the UAV 102 to the mobile computing device 101.”, [0024] “After the image and data capturing process has been completed, the mobile computing device may then receive the data and images in the form of UAV output data…”)
35. As per claim 16:
Marra et al. discloses the following limitations:
wherein the input comprises virtual coordinates indicating the feature ([0080] “The application 302 provides the field user 100 a means of adding annotations 308 to the image that can be categorized and added to the structure database 107 via image inspection service 113…The annotation can be recorded according to its precise image coordinates or projected to an approximate geographic position based on image orientation parameters stored in the Image Database 108, the image coordinates of the annotation, and the geographic elevation plane specified by the sum of the home point 203 elevation and the structure height 211.”, [0082] “In some embodiments, this same geographic positioning technique can be used in reverse in order to project a subset of the polygonal mesh 402 that falls outside the property boundary line 200 into image coordinates of the inspection image(s) 304…”)
36. As per claim 17:
Marra et al. discloses the following limitations:
wherein generating the virtual environment comprises removing one or more features of the property from the model ([0099] “…In some embodiments, machine learning techniques such as Convolutional Neural Networks can be combined with segmentation techniques such as Conditional Random Fields in order to detect and segment features that need to be either included or removed from vector models such as roof vents, chimneys, windows, trees, or power lines.”, [0096] “…Some segmentation of the point cloud 404 may be applied with standard interactive point cloud edit tools prior to generating the vector model 502 in order to reduce processing time and minimize extraneous geometry in the scene that is not part of the structure such as from ground or vegetation surfaces.”, [0098] “…Extraneous facets 504 can be eliminated algorithmically based on area, perimeter, and surface normal thresholds or through interactive editing.”, [claim 12] “…wherein the unmanned aerial vehicle output data is limited to the structure area of interest and eliminates or degrades imagery of objects or people outside the property bounds based on an image mask derived from the three-dimensional reconstruction polygon mesh and the property boundary.”)
37. As per claim 18:
Marra et al. discloses the following limitations:
receiving, from a user device, an input associated with the virtual environment ([0099] “Embodiments using interactive editing for this process 610 can display the polygonal mesh 402 for the operator to use as a visual reference in order to verify the model portrays needed features seen in the imagery…”, [0056] “…The mobile computing device 101 allows the field user 100 to start, pause, resume, or abort the flight plan 150 and track the UAV 102 position as well as display imagery from the camera in real-time…”, [claim 19] “…wherein the report design plan diagram is published into a structure database and is capable of being retrieved by an enterprise user or other users along with other three dimensional data products available for self annotation, interactive measurement, and report modification.”)
based at least in part on the input, generating an additional visual overlay associated with a feature of the property ([0080] “The application 302 provides the field user 100 a means of adding annotations 308 to the image that can be categorized and added to the structure database 107 via image inspection service 113…The annotation can be recorded according to its precise image coordinates or projected to an approximate geographic position based on image orientation parameters stored in the Image Database 108…”, [0092] “…The report design plan diagram 522 or component list 524 may also include attributed annotations 308 that were optionally specified by users with the example image inspection interface 302 shown in FIG. 3…”, [0091] “Additional manually added features 514 are also present in this model 510 that were not evident or completely portrayed in the previous version 502…”)
displaying the additional visual overlay in the virtual environment ([0099] “Embodiments using interactive editing for this process 610 can display the polygonal mesh 402 for the operator to use as a visual reference in order to verify the model portrays needed features seen in the imagery…”, [claim 19] “…wherein the report design plan diagram is published into a structure database and is capable of being retrieved by an enterprise user or other users along with other three dimensional data products available for self annotation, interactive measurement, and report modification.”, [0047] “The images and their geotags may be stored in an Image Database 108 and are generally immediately made available to enterprise and other users 112 via an Image Inspection Service 113…”)
38. As per claim 19:
Marra et al. discloses the following limitations:
receiving an address of the property ([0052] “The third party data 142 could include the geographic boundary from a public or commercially available database, based on the property mailing address or geolocation, location information from the UAV 102, or information from other sources, for example, Google Maps, and may be based on GPS location, among others.”, [claim 5] “…wherein the third party data comprises geographic or property information from public or commercially available databases based at least in part on the property mailing address or geolocation.”, [0021] “…The mobile computing device receives user and third party data which includes the property bounds, the structure area of interest (AOI), the structure AOI's height, and height of any obstacle(s).”)
generating Global Positioning System (GPS) coordinates based at least in part on the address ([0052] “The third party data 142 could include the geographic boundary from a public or commercially available database, based on the property mailing address or geolocation, location information from the UAV 102, or information from other sources, for example, Google Maps, and may be based on GPS location, among others.”, [0051] “…This polygon 200 can be designated by (a) sketching with the mobile computing device 102 interface over the apparent property lines 200 in the application's map image display, (b) tracking the mobile computing device's GNSS (global navigation satellite system) or GPS (global positioning system) position as the field user 100 walks around the property perimeter 200, or (c) retrieving third party data 142.”)
generating the command comprising the GPS coordinates indicating the location of the property ([0023] “…The mobile computing device issues commands to the UAV's flight and camera controller via the UAV system's API to traverse a series of geographic waypoints and capture photos in specific orientations, and record camera position and orientation.”, [0045] “The mobile computing device 101 may be capable of running an operating system, such as the Android or Apple operating system, that can sufficiently control a UAV 102 such as a DJI Phantom, three-dimensional Robotics Solo, Yuneec Typhoon, or Microdrone MD4 series or other UAV 102 via Wi-Fi or other connection, such that GPS geotagged imagery can be captured at desired geospatial locations and orientations…”, [0054] “…The UAV control data 144 is then used to create a flight plan 150 based at least in part on the UAV control data 144, which may include the property bounds 200, if specified, the structure AOI 201, the structure AOI's height 211, and the obstacle clearance height 210, if any, and other information.”)
Conclusion
39. The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
US10275834B1 – Tofte et al. – Discloses unmanned aerial vehicles (UAVs) may facilitate insurance-related tasks, wherein UAVs may actively be dispatched to an insured asset and the area surrounding an insured asset, such as with the policyholder or insured's permission and collect data related to the insured asset, such as images, video, audio, weather conditions, thermal signatures, wood and soil samples, etc., and transmit this data to a computing device.
US20160314545A1 – Jessen – Discloses a system for collecting, storing, and/or analyzing data received from one or more inputs comprising a property information database, a profile preference database, and one or more modules for accessing the databases. The system may receive data from a multiple listing service, internet source, and/or drone.
US20160048934A1 – Gross – Discloses a home rating and assessment system that includes logic configured to identify, analyze and rate features of properties in accordance with customizable filters, and by accounting for specific structural aspects of properties, including key structural features, their workmanship, condition, etc. more precise estimates can be calculated for rating/ranking homes relative to each other for particular industries.
40. Any inquiry concerning this communication or earlier communications from the examiner should be directed to AMANULLA ABDULLAEV whose telephone number is (571)272-4367. The examiner can normally be reached Monday-Friday 9:30AM -4:30PM ET.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Ryan D Donlon can be reached at 571-270-3602. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/AMANULLA ABDULLAEV/Examiner, Art Unit 3692
/RYAN D DONLON/Supervisory Patent Examiner, Art Unit 3692 September 6, 2026
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