DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Applicant filed a response dated June 25, 2026 in which claims 2, 3, 6, 9, 10, 13, 16, 17, and 20 have been amended. Therefore, claims 2-21 are currently pending in the application.
Priority
Application 19/036,168 was filed on 01/24/2025 and is a CON of 16/702,414 12/03/2019 PAT 12,236,487 which is a CON of 14/331,065 07/14/2014 PAT 10,529,026 which claims benefit of 61/847,055 07/16/2013.
Examiner Request
The Applicant is requested to indicate where in the specification there is support for amendments to claims should Applicant amend. The purpose of this is to reduce potential 35 U.S.C. § 112(a) or § 112 1st paragraph issues that can arise when claims are amended without support in the specification. The Examiner thanks the Applicant in advance.
Double Patenting
The terminal disclaimer filed on June 25, 2026 disclaiming the terminal portion of any patent granted on this application which would extend beyond the expiration date has been reviewed and is accepted. The terminal disclaimer has been recorded.
Claim Rejections - 35 USC § 101
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.
Claims 2-21 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. (MPEP 2106). The claims are directed to a method, system, and apparatus which is one of the statutory categories of invention (Step 1: YES). The recitation of the claimed invention is analyzed as follows, in which the abstract elements are boldfaced.
Claim 2 recites the limitations of:
A system for performing a property inspection, the system including: at least one processor; and a machine-readable medium storing instructions, which when executed by the at least one processor, causes the system to perform operations comprising: identify a property using a location identifier;
receive image data associated with the property based on the location identifier, the image data including one or more images of the property comprising spectral imagery and thermal imagery;
generate chemical composition data associated with the property by executing a spectral imaging algorithm applied to the spectral imagery associated with the property;
generate energy leakage data associated with the property by executing an image recognition algorithm applied to the thermal imagery associated with the property;
generate wear data associated with the property by comparing the chemical composition data and the energy leakage data to one or more indexes;
generate output data using the wear data, the output data including a condition of the property; and
transmit the output data to a computing device to cause the computing device to indicate the condition of the property based on the output data.
Claim 16 recites the limitations of:
A non-transitory computer-readable medium including computer program code, which when executed by at least one processor, causes operations comprising: receiving image data associated with a property, the image data including one or more images of the property comprising spectral imagery and thermal imagery;
generating chemical composition data associated with the property by executing a spectral imaging algorithm applied to the spectral imagery associated with the property;
generating energy leakage data associated with the property by executing an image recognition algorithm applied to the thermal imagery associated with the property;
generating wear data associated with the property by comparing the chemical composition data and the energy leakage data to one or more known indexes; and
generating output data using the wear data, the output data including a condition of the property;
transmitting the output data to a computing device, the computing device indicates the condition of the property based on the output data.
The claim as a whole recites a method that, under its broadest reasonable interpretation, covers collecting, analyzing, and transmitting data to facilitate performance of a property inspection to be utilized in determining insurance eligibility and insurance coverage. This is a fundamental economic practice of a financial transaction; a commercial interaction, such as for business relations; and managing personal behavior or relationships or interactions between people, which are certain methods of organizing human activity.
Furthermore, the claims cover the use of a computer system to provide for collecting, analyzing, and transmitting data to facilitate performance of a property inspection to be utilized in determining insurance eligibility and insurance coverage. As the steps could be performed by a human without a computer, the claim limitations fall within the mental processes grouping, and the claim recites an abstract idea.
Thus, the claims recite an abstract idea. (Step 2A, prong 1: YES).
Moreover, the judicial exception is not integrated into a practical application. Other than reciting a “A system for performing a property inspection, the system including: at least one processor; and a machine-readable medium storing instructions, which when executed by the at least one processor, causes the system to perform operations comprising:”, “a computing device”, and “A non-transitory computer-readable medium including computer program code, which when executed by at least one processor, causes operations comprising:”, to perform the steps of “identifying” and “generating”, nothing in the claim elements preclude the steps from practically being a certain method for organizing human activity or mental process. The claim as a whole does not integrate the judicial exception into a practical application. The claim merely describes how to generally “apply” the concept of collecting, analyzing, and transmitting data to facilitate performance of a property inspection to be utilized in determining insurance eligibility and insurance coverage in a computer environment. The additional computer elements recited in the claim limitations are recited at a high-level of generality such that it amounts to no more than mere instructions to apply the exception utilizing generic computer components.
For example, the Specification discloses “[0024] In some example implementations, electronic devices 102, 104, 106 can be computing devices such as laptop or desktop computers, smartphones, PDAs, portable media players, tablet computers, or other appropriate computing devices. In some examples, electronic devices 102, 104, 106 have an image capturing capability. In the example of FIG. 1, electronic device 102 is depicted as a smartphone, electronic device 104 is depicted as a desktop computer and electronic device 106 is depicted as a Personal Digital Assistant (PDA).” “[0044] FIG. 4 conceptually illustrates an electronic system with which some implementations of the subject technology are implemented. Electronic system 400 can be a server, computer, phone, PDA, laptop, tablet computer, television with one or more processors embedded therein or coupled thereto, or any other sort of electronic device. Such an electronic system includes various types of computer readable media and interfaces for various other types of computer readable media. Electronic system 400 includes a bus 408, processing unit(s) 412, a system memory 404, a read-only memory (ROM) 410, a permanent storage device 402, an input device interface 414, an output device interface 406, and a network interface 416.”
Thus, the specification supports that general purpose computers or computer components are utilized to implement the steps of the abstract idea.
Merely implementing the abstract idea on a generic computer is not a practical application of the abstract idea. The claim as a whole, in viewing the additional elements both individually and in combination, does not integrate the judicial exception into a practical application. Accordingly, these additional elements do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea. (Step 2A prong two: No)
The claim does not include additional elements, when considered both individually and as an ordered combination, that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements of using “A system for performing a property inspection, the system including: at least one processor; and a machine-readable medium storing instructions, which when executed by the at least one processor, causes the system to perform operations comprising:”, “a computing device”, and “A non-transitory computer-readable medium including computer program code, which when executed by at least one processor, causes operations comprising:”, to perform the steps of “identifying” and “generating”, amounts to no more than mere instructions to apply the exception using generic computer component. The claim merely describes how to generally “apply” the concept of collecting, analyzing, and transmitting data to facilitate performance of a property inspection to be utilized in determining insurance eligibility and insurance coverage in a computer environment. Thus, even when viewed as a whole, nothing in the claim adds significantly more (i.e. an inventive concept) to the abstract idea. Such additional elements are determined to not contain an inventive concept according to MPEP 2106.05(f). It should be noted that (1) the “recitation of claim limitations that attempt to cover any solution to an identified problem with no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result, does not provide significantly more because this type of recitation is equivalent to the words “apply it”, and (2) “Use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice, commercial interaction, or managing personal behavior or relationships or interactions between people, mental process, or mathematical calculation) does not integrate a judicial exception into a practical application or provide significantly more”.
Claim 9 is substantially similar to claim 2, thus, it is rejected on similar grounds.
Furthermore, claims 4, 11, and 18 recite the additional elements of “an image capturing apparatus”.
For similar reasons as explained above with regard to claim 2, under Step 2A, prong two, these additional elements are merely applying generic computer components to implement the abstract idea. Under Step 2B, when viewing the additional elements individually and in combination, the additional elements do not amount to an inventive concept amounting to significantly more than the judicial exception itself as the claimed computer-related technologies are mere tools for implementing the abstract idea as explained with regard to claim 2.
Dependent claims 3-8, 10-15, and 17-21 merely limit the abstract idea and do not recite any further additional elements beyond the cited abstract idea and the elements addressed above, thus, they do not amount to significantly more. The dependent claims are abstract for the reasons presented above because there are no additional elements that integrate the abstract idea into a practical application or are sufficient to amount to significantly more than the judicial exception when considered both individually and as an ordered combination. Thus, the dependent claims are directed to an abstract idea. (Step 2B: No)
Therefore, claims 2-21 are not patent-eligible.
Claim Rejections - 35 USC § 103
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 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.
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.
Claims 2-21 are rejected under 35 U.S.C. 103 as being unpatentable over Phan, U.S. Patent Application Publication Number 2016/0148363; in view of Swanson, U.S. Patent Application Publication Number 2014/0019166.
As per claim 2,
Phan explicitly teaches:
A system for performing a property inspection, the system including: at least one processor; and a machine-readable medium storing instructions, which when executed by the at least one processor, causes the system to perform operations comprising: identify a property using a location identifier;
(Phan US20160148363 at paras. 4-10, 36-40, 103-110) ("Example 1 [0103] FIGS. 5 and 6 show screenshots of an app (top), which displays homes adjacent to one another. A user of the app has selected a home from the app. Upon selection, the app displays a thermal image of the home (bottom) to the user. Each app provides an address of the building and indicates that there are 24 vertical images associated with a given building. Example 2 [0104] FIGS. 7-16 show example reports that can be generated by a system programmed to obtain sets of images from a house and analyze the sets of images. The system can be the server 401 of FIG. 4. The reports can be generated for a user, such as an owner of the house. The reports can be presented by way of an overall assessment of the house of the user.")
receive image data associated with the property based on the location identifier, the image data including one or more images of the property comprising spectral imagery and thermal imagery;
(Phan US20160148363 at paras. 4-10, 35-37, 103-110) ("[0007] An aspect of the present disclosure provides a method for analyzing a structure. A first set of images of a structure is captured in a first range of wavelengths (for example, 350 nm to 1.2 μm) with a vehicle mounted image capture device while the vehicle is moving. A second set of images of the structure in a second range of wavelengths (for example, 8 μm to 12 μm) is similarly captured. A single vehicle mounted capture device may capture images in both the wavelength ranges, or multiple image capture devices may be used. A single set of images may comprise at least one image. One or more properties of the structure are determined based on the captured first and second set of images. The one or more properties of the structure may comprise structural, heating, and energy information. And, the one or more properties may be determined by comparing the captured first and second set of images with a separate set of data to infer the structural, heating, and energy information. This separate set of data may comprise one or more of public geographic information service (GIS) data, private GIS data, demographic data, self-reported homeowner information, and manual energy audit information. One or more fixes and improvements may be suggested based on the determined properties." "Example 1 [0103] FIGS. 5 and 6 show screenshots of an app (top), which displays homes adjacent to one another. A user of the app has selected a home from the app. Upon selection, the app displays a thermal image of the home (bottom) to the user. Each app provides an address of the building and indicates that there are 24 vertical images associated with a given building. Example 2 [0104] FIGS. 7-16 show example reports that can be generated by a system programmed to obtain sets of images from a house and analyze the sets of images. The system can be the server 401 of FIG. 4. The reports can be generated for a user, such as an owner of the house. The reports can be presented by way of an overall assessment of the house of the user.")
generate energy leakage data associated with the property by executing an image recognition algorithm applied to the thermal imagery associated with the property;
(Phan US20160148363 at paras. 85-89) ("[0085] The server 401 can be programmed or otherwise configured with machine learning algorithms, which may be used to identify structural defects and structural inefficiencies. In some situations, the server 401 can be trained to recognized structures without defects, and use those structures as baselines to identify structures with defects." "[0088] With the aid of a server (e.g., server 401 of FIG. 4) of the system, the processed images together with the other data can be used to estimate one or more properties about the structure. In some cases, the material used to form the structure can be estimated by correlating a shape of the structure and loss information (e.g., as may be gleaned from the collected images) associated with the structure with that of known structures having known materials. For example, the server can determine whether the structure has a vapor barrier or determine the type of insulation of the structure. This can enable the server to recommend remedial measures to the user, such as the installation of a vapor barrier or a given type of insulation to decrease heat loss. [0089] In some situations, the server can estimate physical, tangible qualities about the structure. Next, the server can estimate a fitness of items (e.g., whether a vapor barrier been installed correctly, whether insulation been installed correctly). Based on these features, the server can estimate an R-value of the total envelope of the structure (e.g., whether the structure is adequately insulated) and consumption and utility cost.")
the energy leakage data to one or more indexes;
(Phan US20160148363 at paras. 7-10, 38-39, 103-110) ("[0008] Various structural properties may be determined based on the above steps. The structural, heating, and energy information determined may include one or more of a presence of insulation, a type and effectiveness of the insulation, a presence of vapor barriers, a presence of baseboard heaters, wear and tear of structural features, weathering of structural features, a presence of cracks, structural integrity, a presence of gas leaks, a presence of water leaks, a presence of heat leaks, a presence of roof degradation, a presence of water damage, structural degradation, sagging insulation, improperly installed insulation, defective insulation, thermal emissivity, a presence or fitness of windows, a presence or fitness of roofing material, a presence or fitness of cladding (e.g., siding, brick), R-value, and wetness (e.g., the degree of wetness). The one or more properties of the structure may comprise energy flux per leak, which may be computed based on the inferred structural, heating, and energy information. The one or more properties of the structure may also comprise an energy consumption rate of the structure. The energy consumption rate may be compared with a second energy consumption rate of the structure from an energy audit, utility data, or database information of the structure.")
transmit the output data to a computing device to cause the computing device to indicate the condition of the property based on the output data.
(Phan US20160148363 at paras. 73-75, 85-87) ("[0074] The server 401 can communicate with one or more remote computer systems through the network 430. In the illustrated example, the server 401 is in communication with a first computer system 435 and a second computer system 440 that are located remotely with respect to the server 401. The first computer system 435 and the second computer system 440 can be computer systems of a first user and second user, respectively, each of which may wish to view one or more properties of a structure. The first computer system 435 and second computer system 440 can be, for example, personal computers (e.g., portable PC), slate or tablet PC's (e.g., Apple® iPad, Samsung® Galaxy Tab), telephones, Smartphones (e.g., Apple® iPhone, Android-enabled device, Blackberry®), or personal digital assistants. The first and/or second users can access the server 401 via the network 430 to, for example, view one or more properties of the structure." "[0086] Systems of the present disclosure (e.g., the serve 401) can generate reports. Such reports can be displayed on an app on an electronic device of a user, or provided to the user on a physical medium. A report can include a summary of any structural defects and/or identify any losses associated with a structure of the user or a structure of interest to the user (e.g., a home of the user, a home of potential or planned purchase by the user). The report can also include a total cost of ownership associated with the structure (see below).")
Phan does not explicitly teach, however, Swanson does teach:
generate chemical composition data associated with the property by executing a spectral imaging algorithm applied to the spectral imagery associated with the property;
(Swanson US20140019166 at paras. 28-30, 43-47) ("[0029] Step 54 involves spectral classification of the HSI data. Step 54 uses a spectral library of roof type information 56 that has information on the changes in spectral images of various surfaces over time. Spectral analysis can use a number of common methodologies available through commercial software, such as ENVI (Environment for Visualizing Images) using Spectral Angel Mapper, Endmember Analysis or embodiments of the many algorithms published on spectral analysis, from Principle Component Analysis to other image classification algorithms. Spectral analysis can be carried out in an automated processing or batch processing methodology. A well developed and controlled spectral library is crucial for the accuracy of determining the type and condition of the roof materials. A spectral library containing the spectra of the most commonly manufactured materials in both new and weathered states must be used to classify the airborne HSI imagery. Altogether, step 54 utilizes the crucial roof spectral reference database 56 to detect roof condition from the HSI remote sensing imagery." "[0046] Roof materials beyond asphalt shingle can possess a range of spectral reflectances as shown in FIG. 7. Distinctive spectra are observed from composite shingle to wood shake, fiberglass, tile, and concrete roof materials. There are also a range of colors within the tile materials which help with classification and demonstrate clear difference in spectral reflectance with the impacts of aging and weathering.")
generate wear data associated with the property by comparing the chemical composition data and
(Swanson US20140019166 at paras. 7-9, 43-47) ("[0008] By comparing the spatially subset spectral reflection of rooftops within the scene to a reference spectra, the rooftop type and condition of wear can be accurately assessed. " "[0044] Distinct regions within the spectra contain identifying markers for each type of shingle (inflection points and slopes between wavelength bands), and the aging process changes the relative intensity from visible to infrared reflectivity. The two independent manufacturer brands in new condition are shown in FIG. 6 in the lowest part of the graph, (marked “Manufacturer 1” and “Manufacturer 2”), and show nearly identical spectra, with modest rise in reflectivity into the infrared. The two manufacturers collected represent over 90% of the market sampled for residential rooftop materials and many commercial markets across the United States. Two residences that were visited with medium amount of wear, with location #1 rated according to visual inspection as “moderately aged, but acceptable,” while the location #2 was classified by visual inspection as “acceptable”, but was being replaced for hail damage in a single quadrant. Both locations #1 and #2 show a moderate rise into the infrared, showing the gradual rise in SWIR as roofs age over 5-10 years. Aged spectra obtained at three separate residences at location #3, location #4, and location #5, all show significantly enhanced signatures into the infrared, while maintaining the unique pattern of the new standard samples. All “Aged” samples were unacceptable from an insurance liability standpoint and required replacement of roofing material." "[0046] Roof materials beyond asphalt shingle can possess a range of spectral reflectances as shown in FIG. 7. Distinctive spectra are observed from composite shingle to wood shake, fiberglass, tile, and concrete roof materials. There are also a range of colors within the tile materials which help with classification and demonstrate clear difference in spectral reflectance with the impacts of aging and weathering.")
generate output data using the wear data, the output data including a condition of the property; and
(Swanson US20140019166 at paras. 7-9, 43-45) ("[0008] By comparing the spatially subset spectral reflection of rooftops within the scene to a reference spectra, the rooftop type and condition of wear can be accurately assessed. " "[0044] Distinct regions within the spectra contain identifying markers for each type of shingle (inflection points and slopes between wavelength bands), and the aging process changes the relative intensity from visible to infrared reflectivity. The two independent manufacturer brands in new condition are shown in FIG. 6 in the lowest part of the graph, (marked “Manufacturer 1” and “Manufacturer 2”), and show nearly identical spectra, with modest rise in reflectivity into the infrared. The two manufacturers collected represent over 90% of the market sampled for residential rooftop materials and many commercial markets across the United States. Two residences that were visited with medium amount of wear, with location #1 rated according to visual inspection as “moderately aged, but acceptable,” while the location #2 was classified by visual inspection as “acceptable”, but was being replaced for hail damage in a single quadrant. Both locations #1 and #2 show a moderate rise into the infrared, showing the gradual rise in SWIR as roofs age over 5-10 years. Aged spectra obtained at three separate residences at location #3, location #4, and location #5, all show significantly enhanced signatures into the infrared, while maintaining the unique pattern of the new standard samples. All “Aged” samples were unacceptable from an insurance liability standpoint and required replacement of roofing material.")
Therefore, it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Phan and Swanson, because it allows for improved systems using remote sensing capabilities like hyperspectral imaging to identify roof characteristics for insurance purposes. (Swanson at Abstract and paras. 1-12).
As per claim 3,
Phan explicitly teaches:
wherein the machine-readable medium stores further instructions, which when executed by the at least one processor, further causes the system to perform operations comprising: receive hyperspectral imagery associated with the property; and generate the chemical composition data associated with the property by executing a hyperspectral imaging algorithm applied to the hyperspectral imagery, the output data generated using the chemical composition data.
(Phan US20160148363 at paras. 38-39, 126) ("[0038] A method for analyzing a structure comprises capturing a first set of images of the structure in a first range of wavelengths of light with an image capture device mounted on a vehicle, and capturing a second set of images of the structure in a second range of wavelengths of light with the image capture device. The first and second sets of images can be captured while the vehicle is moving. In some situations, the first and second sets of images can be captured while the vehicle is moving adjacent to the structure. With the aid of a computer processor, one or more properties of the structure can be calculated based on the captured first and second set of images. For example, the images can be digitized and analyzed to determine thermal losses and structural defects of the structure." "[0039] The one or more properties of the structure can comprise structural, heating, and energy consumption information. In some situations, the one or more properties are determined by comparing the captured first and second set of images with a separate set of data to infer the structural, heating, and energy information. The separate set of data can include one or more of public geographic information service (GIS) data, private GIS data, demographic data, self-reported homeowner information, and manual energy audit information. The structural, heating, and energy consumption information can include one or more of a presence of insulation, a type and effectiveness of the insulation, a presence of vapor barriers, a presence of baseboard heaters, wear and tear of structural features, weathering of structural features, a presence of cracks, structural integrity, a presence of gas leaks, a presence of water leaks, a presence of heat leaks, a presence of roof corrosion (or degradation), a presence of water damage, structural degradation, thermal emissivity, a presence or fitness of windows, a presence or fitness of roofing material, a presence or fitness of cladding (e.g., siding, brick), R-value, and wetness.")
As per claim 4,
Phan explicitly teaches:
wherein the machine-readable medium stores further instructions, which when executed by the at least one processor, further causes the system to perform operations comprising: generate a command to cause an image capturing apparatus to obtain the image data using the location identifier.
(Phan US20160148363 at paras. 37-41, 44-46, 126-128) ("[0045] The first and second sets of images can be captured using imaging sensors that are tuned to the respective wavelengths of light. The sensors can be tuned to, for example, the infrared (IR) portion of the electromagnetic spectrum, the ultraviolet portion of the electromagnetic spectrum, or the visible portion of the electromagnetic spectrum. As an alternative, or in addition to, the image capture device can be configured for light detection and ranging laser imaging detection and ranging (LIDAR), radio detection and ranging (RADAR), detecting x-rays, and/or detecting electrons." "[0038] A method for analyzing a structure comprises capturing a first set of images of the structure in a first range of wavelengths of light with an image capture device mounted on a vehicle, and capturing a second set of images of the structure in a second range of wavelengths of light with the image capture device. The first and second sets of images can be captured while the vehicle is moving. In some situations, the first and second sets of images can be captured while the vehicle is moving adjacent to the structure." "Geolocation (e.g., GPS) data is also imported into the system and used to geotag vertical panoramas and match vertical panoramas to buildings. Next, from a given processed image, the average surface temperature of the building is calculated and an internal temperature of the building is inferred. Next, the building surface heat flow is calculated. The energy use of the building within a given time period (e.g., annual) is then calculated. Such information is used to calculate a raw energy score that is a function of the energy use of the building with the given time period. The raw energy score is then converted to a percentile.")
As per claim 5,
Phan explicitly teaches:
wherein the one or more images include aerial image data.
(Phan US20160148363 at paras. 39-41) ("[0040] In some situations, information gleaned from images captured by the image capture device can be combined with information gleaned from aerial images. The aerial images can include images of the structure imaged, which can identify defects and losses from locations of the structure that are not capable of being imaged from the image capture device onboard the vehicle. For example, aerial images can identify structural defects on a roof and/or chimney of the structure.")
As per claim 6,
Phan explicitly teaches:
wherein the machine-readable medium stores further instructions, which when executed by the at least one processor, further causes the system to perform operations comprising: generate property characteristic data using the one or more images, the property characteristic data includes at least one of a size of at least a portion of the property, property information, a size of at least a portion of one or more structures on the property, or at least one construction component of the one or more structures.
(Phan US20160148363 at paras. 6-10) ("[0006] Systems and methods of the present disclosure can identify various structural parameters, such as, for example, poor insulation, energy efficiency, latent structural features, structural fitness (or lack thereof). In some situations, methods of the present disclosure can be employed to detect latent structural features, which can be used to assess energy efficiency. [0007] An aspect of the present disclosure provides a method for analyzing a structure. A first set of images of a structure is captured in a first range of wavelengths (for example, 350 nm to 1.2 μm) with a vehicle mounted image capture device while the vehicle is moving. A second set of images of the structure in a second range of wavelengths (for example, 8 μm to 12 μm) is similarly captured. A single vehicle mounted capture device may capture images in both the wavelength ranges, or multiple image capture devices may be used. A single set of images may comprise at least one image. One or more properties of the structure are determined based on the captured first and second set of images. The one or more properties of the structure may comprise structural, heating, and energy information. And, the one or more properties may be determined by comparing the captured first and second set of images with a separate set of data to infer the structural, heating, and energy information. This separate set of data may comprise one or more of public geographic information service (GIS) data, private GIS data, demographic data, self-reported homeowner information, and manual energy audit information. One or more fixes and improvements may be suggested based on the determined properties.")
As per claim 7,
Phan explicitly teaches:
wherein the output data includes a coverage decision.
(Phan US20160148363 at paras. 112-114) ("[0113] FIG. 15 is a report with insights on the total cost of ownership (TCO) and potential savings. The TCO takes into account the principal cost (“Principal), associated interest (“Interest”) and taxes (“Taxes”), insurance costs (“Insurance”), energy costs (“Energy”) and cost of commute (“Commute”). The TCO of the user ($44,716) is displayed against a national average ($25,227). The national average can be generated by comparing the house of the user to similar homes, in some cases in similar areas. A bottom portion of the report shows examples of approaches that the user can take to potentially reduce the TCO of the user. The approaches include minimizing interest, taxes, insurance, energy and commute. The report indicates that the user can potentially reduce the TCO by $7,625 on an annual basis.")
As per claim 8,
Phan explicitly teaches:
wherein the location identifier includes at least one of latitude and longitude information or an address.
(Phan US20160148363 at paras. 4-10, 37-40, 103-110) ("Example 1 [0103] FIGS. 5 and 6 show screenshots of an app (top), which displays homes adjacent to one another. A user of the app has selected a home from the app. Upon selection, the app displays a thermal image of the home (bottom) to the user. Each app provides an address of the building and indicates that there are 24 vertical images associated with a given building. Example 2 [0104] FIGS. 7-16 show example reports that can be generated by a system programmed to obtain sets of images from a house and analyze the sets of images. The system can be the server 401 of FIG. 4. The reports can be generated for a user, such as an owner of the house. The reports can be presented by way of an overall assessment of the house of the user.")
As per claim 16,
Phan explicitly teaches:
A non-transitory computer-readable medium including computer program code, which when executed by at least one processor, causes operations comprising: receiving image data associated with a property, the image data including one or more images of the property comprising spectral imagery and thermal imagery;
(Phan US20160148363 at paras. 4-10, 35-37, 103-110) ("[0007] An aspect of the present disclosure provides a method for analyzing a structure. A first set of images of a structure is captured in a first range of wavelengths (for example, 350 nm to 1.2 μm) with a vehicle mounted image capture device while the vehicle is moving. A second set of images of the structure in a second range of wavelengths (for example, 8 μm to 12 μm) is similarly captured. A single vehicle mounted capture device may capture images in both the wavelength ranges, or multiple image capture devices may be used. A single set of images may comprise at least one image. One or more properties of the structure are determined based on the captured first and second set of images. The one or more properties of the structure may comprise structural, heating, and energy information. And, the one or more properties may be determined by comparing the captured first and second set of images with a separate set of data to infer the structural, heating, and energy information. This separate set of data may comprise one or more of public geographic information service (GIS) data, private GIS data, demographic data, self-reported homeowner information, and manual energy audit information. One or more fixes and improvements may be suggested based on the determined properties." "Example 1 [0103] FIGS. 5 and 6 show screenshots of an app (top), which displays homes adjacent to one another. A user of the app has selected a home from the app. Upon selection, the app displays a thermal image of the home (bottom) to the user. Each app provides an address of the building and indicates that there are 24 vertical images associated with a given building. Example 2 [0104] FIGS. 7-16 show example reports that can be generated by a system programmed to obtain sets of images from a house and analyze the sets of images. The system can be the server 401 of FIG. 4. The reports can be generated for a user, such as an owner of the house. The reports can be presented by way of an overall assessment of the house of the user.")
generating energy leakage data associated with the property by executing an image recognition algorithm applied to the thermal imagery associated with the property;
(Phan US20160148363 at paras. 85-89) ("[0085] The server 401 can be programmed or otherwise configured with machine learning algorithms, which may be used to identify structural defects and structural inefficiencies. In some situations, the server 401 can be trained to recognized structures without defects, and use those structures as baselines to identify structures with defects." "[0088] With the aid of a server (e.g., server 401 of FIG. 4) of the system, the processed images together with the other data can be used to estimate one or more properties about the structure. In some cases, the material used to form the structure can be estimated by correlating a shape of the structure and loss information (e.g., as may be gleaned from the collected images) associated with the structure with that of known structures having known materials. For example, the server can determine whether the structure has a vapor barrier or determine the type of insulation of the structure. This can enable the server to recommend remedial measures to the user, such as the installation of a vapor barrier or a given type of insulation to decrease heat loss. [0089] In some situations, the server can estimate physical, tangible qualities about the structure. Next, the server can estimate a fitness of items (e.g., whether a vapor barrier been installed correctly, whether insulation been installed correctly). Based on these features, the server can estimate an R-value of the total envelope of the structure (e.g., whether the structure is adequately insulated) and consumption and utility cost.")
the energy leakage data to one or more known indexes; and
(Phan US20160148363 at paras. 7-10, 38-39, 103-110) ("[0008] Various structural properties may be determined based on the above steps. The structural, heating, and energy information determined may include one or more of a presence of insulation, a type and effectiveness of the insulation, a presence of vapor barriers, a presence of baseboard heaters, wear and tear of structural features, weathering of structural features, a presence of cracks, structural integrity, a presence of gas leaks, a presence of water leaks, a presence of heat leaks, a presence of roof degradation, a presence of water damage, structural degradation, sagging insulation, improperly installed insulation, defective insulation, thermal emissivity, a presence or fitness of windows, a presence or fitness of roofing material, a presence or fitness of cladding (e.g., siding, brick), R-value, and wetness (e.g., the degree of wetness). The one or more properties of the structure may comprise energy flux per leak, which may be computed based on the inferred structural, heating, and energy information. The one or more properties of the structure may also comprise an energy consumption rate of the structure. The energy consumption rate may be compared with a second energy consumption rate of the structure from an energy audit, utility data, or database information of the structure.")
transmitting the output data to a computing device, the computing device indicates the condition of the property based on the output data.
(Phan US20160148363 at paras. 73-75, 85-87) ("[0074] The server 401 can communicate with one or more remote computer systems through the network 430. In the illustrated example, the server 401 is in communication with a first computer system 435 and a second computer system 440 that are located remotely with respect to the server 401. The first computer system 435 and the second computer system 440 can be computer systems of a first user and second user, respectively, each of which may wish to view one or more properties of a structure. The first computer system 435 and second computer system 440 can be, for example, personal computers (e.g., portable PC), slate or tablet PC's (e.g., Apple® iPad, Samsung® Galaxy Tab), telephones, Smartphones (e.g., Apple® iPhone, Android-enabled device, Blackberry®), or personal digital assistants. The first and/or second users can access the server 401 via the network 430 to, for example, view one or more properties of the structure." "[0086] Systems of the present disclosure (e.g., the serve 401) can generate reports. Such reports can be displayed on an app on an electronic device of a user, or provided to the user on a physical medium. A report can include a summary of any structural defects and/or identify any losses associated with a structure of the user or a structure of interest to the user (e.g., a home of the user, a home of potential or planned purchase by the user). The report can also include a total cost of ownership associated with the structure (see below).")
Phan does not explicitly teach, however, Swanson does teach:
generating chemical composition data associated with the property by executing a spectral imaging algorithm applied to the spectral imagery associated with the property;
(Swanson US20140019166 at paras. 28-30, 43-47) ("[0029] Step 54 involves spectral classification of the HSI data. Step 54 uses a spectral library of roof type information 56 that has information on the changes in spectral images of various surfaces over time. Spectral analysis can use a number of common methodologies available through commercial software, such as ENVI (Environment for Visualizing Images) using Spectral Angel Mapper, Endmember Analysis or embodiments of the many algorithms published on spectral analysis, from Principle Component Analysis to other image classification algorithms. Spectral analysis can be carried out in an automated processing or batch processing methodology. A well developed and controlled spectral library is crucial for the accuracy of determining the type and condition of the roof materials. A spectral library containing the spectra of the most commonly manufactured materials in both new and weathered states must be used to classify the airborne HSI imagery. Altogether, step 54 utilizes the crucial roof spectral reference database 56 to detect roof condition from the HSI remote sensing imagery." "[0046] Roof materials beyond asphalt shingle can possess a range of spectral reflectances as shown in FIG. 7. Distinctive spectra are observed from composite shingle to wood shake, fiberglass, tile, and concrete roof materials. There are also a range of colors within the tile materials which help with classification and demonstrate clear difference in spectral reflectance with the impacts of aging and weathering.")
generating wear data associated with the property by comparing the chemical composition data and
(Swanson US20140019166 at paras. 7-9, 43-47) ("[0008] By comparing the spatially subset spectral reflection of rooftops within the scene to a reference spectra, the rooftop type and condition of wear can be accurately assessed. " "[0044] Distinct regions within the spectra contain identifying markers for each type of shingle (inflection points and slopes between wavelength bands), and the aging process changes the relative intensity from visible to infrared reflectivity. The two independent manufacturer brands in new condition are shown in FIG. 6 in the lowest part of the graph, (marked “Manufacturer 1” and “Manufacturer 2”), and show nearly identical spectra, with modest rise in reflectivity into the infrared. The two manufacturers collected represent over 90% of the market sampled for residential rooftop materials and many commercial markets across the United States. Two residences that were visited with medium amount of wear, with location #1 rated according to visual inspection as “moderately aged, but acceptable,” while the location #2 was classified by visual inspection as “acceptable”, but was being replaced for hail damage in a single quadrant. Both locations #1 and #2 show a moderate rise into the infrared, showing the gradual rise in SWIR as roofs age over 5-10 years. Aged spectra obtained at three separate residences at location #3, location #4, and location #5, all show significantly enhanced signatures into the infrared, while maintaining the unique pattern of the new standard samples. All “Aged” samples were unacceptable from an insurance liability standpoint and required replacement of roofing material." "[0046] Roof materials beyond asphalt shingle can possess a range of spectral reflectances as shown in FIG. 7. Distinctive spectra are observed from composite shingle to wood shake, fiberglass, tile, and concrete roof materials. There are also a range of colors within the tile materials which help with classification and demonstrate clear difference in spectral reflectance with the impacts of aging and weathering.")
generating output data using the wear data, the output data including a condition of the property;
(Swanson US20140019166 at paras. 7-9, 43-45) ("[0008] By comparing the spatially subset spectral reflection of rooftops within the scene to a reference spectra, the rooftop type and condition of wear can be accurately assessed. " "[0044] Distinct regions within the spectra contain identifying markers for each type of shingle (inflection points and slopes between wavelength bands), and the aging process changes the relative intensity from visible to infrared reflectivity. The two independent manufacturer brands in new condition are shown in FIG. 6 in the lowest part of the graph, (marked “Manufacturer 1” and “Manufacturer 2”), and show nearly identical spectra, with modest rise in reflectivity into the infrared. The two manufacturers collected represent over 90% of the market sampled for residential rooftop materials and many commercial markets across the United States. Two residences that were visited with medium amount of wear, with location #1 rated according to visual inspection as “moderately aged, but acceptable,” while the location #2 was classified by visual inspection as “acceptable”, but was being replaced for hail damage in a single quadrant. Both locations #1 and #2 show a moderate rise into the infrared, showing the gradual rise in SWIR as roofs age over 5-10 years. Aged spectra obtained at three separate residences at location #3, location #4, and location #5, all show significantly enhanced signatures into the infrared, while maintaining the unique pattern of the new standard samples. All “Aged” samples were unacceptable from an insurance liability standpoint and required replacement of roofing material.")
Therefore, it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Phan and Swanson, because it allows for improved systems using remote sensing capabilities like hyperspectral imaging to identify roof characteristics for insurance purposes. (Swanson at Abstract and paras. 1-12).
Claims 9-15 are substantially similar to claims 2-8, thus, they are rejected on similar grounds.
Claims 17-21 are substantially similar to claims 3-7, thus, they are rejected on similar grounds.
Response to Arguments
Applicant’s arguments filed on June 25, 2026 have been fully considered but are not persuasive for the following reasons:
With respect to Applicant’s arguments as to the § 101 rejections for now pending claims 2-21, Examiner notes the following:
Applicant argues that the claims are not directed to an abstract idea.
Examiner disagrees, however, and notes that the claim as a whole recites a method that, under its broadest reasonable interpretation, covers collecting, analyzing, and transmitting data to facilitate performance of a property inspection to be utilized in determining insurance eligibility and insurance coverage. This is a fundamental economic practice of a financial transaction; a commercial interaction, such as for business relations; and managing personal behavior or relationships or interactions between people, which are certain methods of organizing human activity.
Furthermore, the claims cover the use of a computer system to provide for collecting, analyzing, and transmitting data to facilitate performance of a property inspection to be utilized in determining insurance eligibility and insurance coverage. As the steps could be performed by a human without a computer, the claim limitations fall within the mental processes grouping, and the claim recites an abstract idea.
Thus, the claims recite an abstract idea.
Regarding the applicant's argument that the amended features would integrate the abstract idea into a practical application, the examiner respectfully disagrees.
Examiner disagrees, however, and notes that the additional elements of the computer system - “A system for performing a property inspection, the system including: at least one processor; and a machine-readable medium storing instructions, which when executed by the at least one processor, causes the system to perform operations comprising:”, “a computing device”, and “A non-transitory computer-readable medium including computer program code, which when executed by at least one processor, causes operations comprising:”, to perform the steps of “identifying” and “generating”, in all steps is recited at a high-level of generality such that it amounts to no more than mere instructions to apply the exception using a generic computer component. The claims at issue covers a system for collecting, analyzing, and transmitting data to facilitate performance of a property inspection to be utilized in determining insurance eligibility and insurance coverage. The claims invoke the “A system for performing a property inspection, the system including: at least one processor; and a machine-readable medium storing instructions, which when executed by the at least one processor, causes the system to perform operations comprising:”, “a computing device”, and “A non-transitory computer-readable medium including computer program code, which when executed by at least one processor, causes operations comprising:”, to perform the steps of “identifying” and “generating” merely as tools to execute the abstract idea. Use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a certain method of organizing human activity or mental process or mathematical calculation) does not integrate a judicial exception into a practical application. (MPEP 2106.05 (f))
Examiner notes that, the stated problems of burdensome identification and tracking of a wear level of a property is not a technical problem, and the claimed solution is not a technical solution. In the claim, the solution of performing an efficient property evaluation process is part of the abstract idea, as it is merely involves collecting, analyzing, and transmitting data to facilitate performance of a property inspection to be utilized in determining insurance eligibility and insurance coverage. Furthermore, the data manipulation and analysis could be completed mentally or manually by paper or pen.
Finally, the Applicant argues that the claims are directed to significantly more than the abstract idea.
Examiner disagrees, however, and notes that, as explained above in the instant rejection under 35 U.S.C. § 101, that the additional elements do not amount to an inventive concept. The additional elements of the computer system - “A system for performing a property inspection, the system including: at least one processor; and a machine-readable medium storing instructions, which when executed by the at least one processor, causes the system to perform operations comprising:”, “a computing device”, and “A non-transitory computer-readable medium including computer program code, which when executed by at least one processor, causes operations comprising:”, to perform the steps of “identifying” and “generating” are merely generic computer components performing their well-known basic functions of collecting, analyzing, and transmitting data to facilitate performance of a property inspection to be utilized in determining insurance eligibility and insurance coverage. Per the specification, the recited computer elements are described only at a high level of generality, (see Spec. at paras. [0024], [0044]). In view of the specification, the application of the computer elements is merely being applied to the abstract idea.
The other limitations which are simply supporting the abstract idea correspond to insignificant extra-solution activity which do not transform the abstract idea into a patent eligible subject matter. Also, the functionality here is already present in the recited hardware, which is merely routine and conventional. Collecting, analyzing, and transmitting data is routine and conventional. There is no technological problem or solution identified. This is merely a business solution to transfer data between devices. (MPEP 2106.05 (f))
With respect to Applicant’s arguments as to the § 102 rejections for now pending claims 2-21, Examiner notes that the rejection is withdrawn.
Additionally, Applicant argues that Phan fails to teach the limitation of “generate energy leakage data by executing an image recognition algorithm applied to the thermal imagery associated with the property”. Examiner notes that Phan does teach the limitation. (See Phan US20160148363 at paras. 85-89) ("[0085] The server 401 can be programmed or otherwise configured with machine learning algorithms, which may be used to identify structural defects and structural inefficiencies. In some situations, the server 401 can be trained to recognized structures without defects, and use those structures as baselines to identify structures with defects." "[0088] With the aid of a server (e.g., server 401 of FIG. 4) of the system, the processed images together with the other data can be used to estimate one or more properties about the structure. In some cases, the material used to form the structure can be estimated by correlating a shape of the structure and loss information (e.g., as may be gleaned from the collected images) associated with the structure with that of known structures having known materials. For example, the server can determine whether the structure has a vapor barrier or determine the type of insulation of the structure. This can enable the server to recommend remedial measures to the user, such as the installation of a vapor barrier or a given type of insulation to decrease heat loss. [0089] In some situations, the server can estimate physical, tangible qualities about the structure. Next, the server can estimate a fitness of items (e.g., whether a vapor barrier been installed correctly, whether insulation been installed correctly). Based on these features, the server can estimate an R-value of the total envelope of the structure (e.g., whether the structure is adequately insulated) and consumption and utility cost.")
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure and is available for review on Form PTO-892 Notice of References Cited.
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any extension fee pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MERRITT J HASBROUCK whose telephone number is (571)272-3109. The examiner can normally be reached M-F 9:00-5:00.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Christine Tran can be reached on 571-272-8103. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/MERRITT J HASBROUCK/Examiner, Art Unit 3695
/CHRISTINE M Tran/Supervisory Patent Examiner, Art Unit 3695
