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 .
Response to Arguments
Applicant's arguments filed on 1/12/2026, with respect to rejection of independent claims 1 and 53 (and their respective dependent claims) have been fully considered but they are not persuasive. Regarding claim 1, Applicant argues that “Applying the logic of the Kim Memo and its analysis of Example 39 to the claims of the present application, the Office must conclude that amended claim 1 does not recite a judicial exception, because processing geo-spatial data to derive spatial object representations and collecting further geo-spatial data if a quality condition of the spatial object representations is not fulfilled, wherein the quality condition comprises a confidence value representing a probability with which the spatial object representations correspond to represented objects, and wherein the confidence value is derived by comparing spatial object representations derived with a plurality of techniques or based on different geo-spatial data is not something that can practically be performed in the human mind. The Kim Memo points out that the test is not whether is possible to perform the claim elements at issue in the human mind but whether the claim elements can practically be performed in the human mind. Here, Applicant disagrees with the Office's assertion that it is even possible to perform the elements of claim 1 in the human mind, and the Office has cited no evidence to support its assertion, but certainly the elements of claim 1 cannot practically be performed in the human mind. Moreover, the Kim Memo states that claim limitations that "involve a broad array of techniques and/or activities that may involve or rely upon mathematical concepts, [when] the limitation[s] do[] not set forth or describe any mathematical relationships, calculations, formulas, or equations using words or mathematical symbols"(Kim Memo at 3) do no not recite a judicial exception, such that the claim passes muster under Step 2A, Prong One. Here, claim 1 does not set forth or describe any mathematical relationships, calculations, formulas, or equations using words or mathematical symbols, and therefore it is eligible for patent protection under Step 2A, Prong One. Therefore, for the above reasons, claim 1 and its dependent claims are eligible under the rejection under Section 101 should be withdrawn.
Examiner respectfully disagrees, as currently amended claim 1, recites “a method for analyzing geo-spatial data comprising: a. processing at least parts of the geo-spatial data to derive spatial object representations; and b. collecting further geo-spatial data if a quality condition of the spatial object representations is not fulfilled, wherein the quality condition comprises a confidence value representing a probability with which the spatial object representations correspond to represented objects, and wherein the confidence value is derived by comparing spatial object representations derived with a plurality of techniques or based on different geo-spatial data”. First of all, as can be seen from the claim language and claim as a whole recites analyzing and processing geo-spatial data i.e., nothing in the claim element precludes the steps from practically being performed in the mind and/or using pen and paper as a person can derive spatial object presentation by utilizing geo-spatial data on a paper and if the obtained/derived spatial object representation quality condition not satisfied (i.e., how close a person can draw a spatial object presentation on a paper (confidence value)) person can obtain further geo-spatial data and person can obtain/draw/derive spatial object representation utilizing multiple different techniques or based on different geo-spatial data. Hence, as can be seen from above that nowhere claims requires any step which cannot be practically performed in human mind and/or using pen and paper. Secondly, Applicant pointed to Kim Memo Example 39 to the claims of the present application, however Example 39 is not applicable to the pending claims, since nowhere pending claims requires any AI component. Therefore, rejection of claims 1-7, 10-25, and 53-55, is being maintained.
Applicant’s arguments, with respect to the rejection of claims 26-32, and 35-52, under 35 U.S.C 101, have been fully considered and are persuasive. Further, Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof. The rejection of said claims has been withdrawn.
Applicant's arguments with respect to the rejection of claims 1, 26 and 53 (and their respective dependent claims) have been fully considered but they are not persuasive. Regarding independent claims Applicant argues that “Claim 1 has been amended to include the subject matter of claims 8 and 9. Bauer et al. relates to a rooftop inspection system in which the quality of an image is assessed (see paragraph
[0034] of Bauer), for example, by a frequency domain analysis of the image. If high frequencies are found to be missing from the image, this can provide an indication that there is a lack of focus. Paragraph [0034] of Bauer states, "Additionally, a Laplacian kernel can be convolved with the image (e.g., in the spatial domain) and the result can be used to determine blurriness of the image (e.g., intensity values of pixels within a threshold distance can be compared, and a blurry image can have a lack of comparisons greater than a threshold." Additional quality information can include sufficient overlap with neighboring images, brightness measurements, exposure measurements, contrast measurements, and so on. This is very different from the approach laid out in amended claim 1. The subject matter of the claim 1 relates to analyzing geo-spatial data with respect to spatial object representations, not to the quality of the image. This is explicitly stated in claim 1, and it is evident from the embodiments described in the application, for example, in connection with Fig. 2 to 5. The analysis method is not concerned with the image as a whole - which Bauer et al. obviously is- but it is concerned with spatial object representations derived from geo-spatial data.” (please see Remarks, page 7).
Examiner respectfully disagrees, as previously cited reference of Kim discloses processing geo-spatial data to derive spatial object representations however does not explicitly discloses quality condition of the derived spatial object representation, for this missing teachings Examiner relied on Bauer teachings. As Bauer discloses in paragraphs 34 and 37, that “Additionally, a laplacian kernel can be convolved with the image (e.g., in the spatial domain) and the result can be used to determine blurriness of the image (e.g., intensity values of pixels within a threshold distance can be compared, and a blurry image can have a lack of comparisons greater than a threshold). Additional quality information can include sufficient overlap with neighboring images, brightness measurements, exposure measurements, contrast measurements, and so on. The user device may automatically transmit instructions to the UAV to retake an image at a given waypoint if the image fails to meet an image quality threshold. Optionally, the UAV may have onboard GPU processing capabilities. The UAV may after taking an image, move into a holding position, and the UAV onboard processing system may analyze the image. If the onboard processing system determines that an image does not meet a threshold quality, the UAV then retakes another picture. The UAV processing system reruns the image quality review process, and then continues with the flight plan if the image passes the quality threshold” and further from the disclosure of the Bauer specifically paragraphs 21 and 31, it is known that the image corresponds to image of rooftop (i.e., spatial object representations). Hence as can be seen from above passage that the Bauer discloses when the image (i.e., rooftop image) does not pass the quality threshold (i.e., confidence value) then another image is captured. Further Bauer also discloses confidence value is derived by comparing spatial object representations derived based on different geo-spatial data, as can be seen from above passage that Bauer discloses that if the image does not pass the quality condition then another image is taken hence each time UAV takes another image there will be different geo-spatial data. Since Applicant utilizes alternative language “or” in the claim hence only one condition needs to be met. Therefore Kim in view of Bauer references reads on the argued limitations as presented by Applicant. Examiner suggests Applicant to further elaborate on techniques and/or geo-spatial data if different from the cited references in order to overcome the cited references.
With respect to claim 1, Applicant further argues that “The features of amended claim 1 further specify this by introducing a quality condition related to the spatial object representations. This a first difference from the teaching of Bauer. Furthermore, the combination of features in claim 1 recites a confidence value representing the probabilities that the spatial object representations correspond to represented objects. Here, the claimed method effectively compares two objects with another, whereas Bauer sets a threshold on frequencies to assess a lack of focus. The comparison of two objects through their representations is technically different from the comparison of one value against a threshold. This leads to a further technical difference of the claimed invention over the teaching of Bauer. The claimed method uses the confidence value that is derived by comparing spatial object representations using a plurality of techniques or using different geo-spatial data. Hence, the one confidence value for the object representation is derived based on different data, either derived by using different techniques or by using different data itself. Bauer, however, performs something very different. Bauer uses different methods for assessing different qualities of the overall image. For example, the use of a frequency analysis for the assessment of a lack focus and a Laplacian kernel method for assessing the blurriness are two different methods for two different purposes. Given this, a person of skill in the art is pointed in a completely different direction by Bauer et al., as different methods are used for different overall image qualities. In contrast, the subject matter of claim 1 uses different methods or different data for assessing the similarity of the representations. This is nowhere suggested by the prior art. Therefore, the subject matter of amended claim 1 and its dependent claims is non- obvious in view of the combination of Kim and Bauer, and the rejection should be withdrawn. Claims 26 and 53, although different in scope, recite subject matter similar to that of claim 1, and therefore claims 26 and 53, and their dependent claims, are allowable at least for the same reasons that claim 1 is allowable.” (please see Remarks, page 8).
Examiner respectfully disagrees, In response to applicant's argument that the references fail to show certain features of the invention, it is noted that the features upon which applicant relies (i.e., “compare two objects with another” and “similarity of the representations”) are not recited in the rejected claim(s). Although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. See In re Van Geuns, 988 F.2d 1181, 26 USPQ2d 1057 (Fed. Cir. 1993). Further, as can be seen from the claim language nowhere in the claims Applicant define plurality of techniques and/or geo-spatial data. Hence, as explained above Bauer reference discloses different methods are used to assess image quality. Therefore, Kim in view of Bauer references reads on the argued limitations as presented by Applicant. Examiner suggests Applicant to further elaborate on techniques if different from the Bauer reference in order to overcome the Bauer reference.
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claim 53, rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention.
Amended claim 53, recites “A computer program product”, however, the specification does not describes “product”. The specification’s paragraphs 5-6 and 54-55, only describes “computer program” nowhere specification describes A computer program product. Therefore claim 53 raises the issue of new matter and the specification of the pending application does not have support for the amended portion of the claim. Examiner suggests Applicant to rewrite the claim as follows in order to overcome the said rejection “A non-transitory computer-readable storage means of a computer storing a computer program and comprising machine code instructions executable by a processor of the computer, the machine code instructions being executable by the processor to cause the computer to:”.
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 1- 7, 10-25, and 53-55, are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter.
Regarding claim 1:
Claim 1 is directed to idea of itself (abstract idea) without significantly more for the following reason(s):
Step 1: Claim 1 recites series of steps for a method for analyzing geo-spatial data comprising: a. processing at least parts of the geo-spatial data to derive spatial object representations; and b. collecting further geo-spatial data if a quality condition of the spatial object representations is not fulfilled, wherein the quality condition comprises a confidence value representing a probability with which the spatial object representations correspond to represented objects, and wherein the confidence value is derived by comparing spatial object representations derived with a plurality of techniques or based on different geo-spatial data. Thus, the claim is directed to a method, which is one of the statutory categories of the invention.
Step 2A prong 1, the claimed processing at least parts of the geo-spatial data to derive spatial object representations; and collecting further geo-spatial data if a quality condition of the spatial object representations is not fulfilled and deriving a confidence value by comparing spatial object representations derived with a plurality of techniques or based on different geo-spatial data are directed to abstract idea for the reason that these steps are processes found by the courts to be abstract ideas in that related to “mental processes grouping” more specifically, “collecting information, analyzing it, and displaying certain results of the collection and analysis,” where the data analysis steps are recited at a high level of generality such that they could practically be performed in the human mind, Electric Power Group v. Alstom, S.A., 830 F.3d 1350, 1353-54, 119 USPQ2d 1739, 1741-42 (Fed. Cir. 2016);. That is, nothing in the claim element precludes the steps from practically being performed in the mind and/or using pen and paper. The claim recites the step of processing geo-spatial data, collecting data if quality condition not fulfilled, and deriving confidence value which is an act of evaluating information that can be practically performed in the human mind and/or using pen and paper. Thus, this step is an abstract idea in the “mental process” grouping. Accordingly, the claim recites an abstract idea.
Step 2A prong 2, The Judicial exception is not integrated into a practical application. Treating claim 1 as a whole, the claim limitations do not show inventive concept in applying the judicial exception. From the claim scope, the claim fail to address any improvement because merely processing data, collecting additional data based on data quality and deriving confidence value is not enough to tie the claim towards the technical improvement. Thus, claim 1 as a whole is not significantly more than the abstract idea itself and is ineligible.
Step 2B, The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. The claim recites processing geo-spatial data, collecting data if quality condition not fulfilled, and deriving confidence value. The claim recites the step of processing and collecting data, which is an act of evaluating information that can be practically performed in the human mind. Thus, this step is an abstract idea in the “mental process” grouping. Courts have held computer‐implemented processes not to be significantly more than an abstract idea (and thus ineligible) where the claim as a whole amounts to nothing more than generic computer functions merely used to implement an abstract idea, such as an idea that could be done by a human analog (i.e., by hand or by merely thinking) component cannot provide an inventive concept. The claim is not patent eligible.
Regarding claims 2-5, 7-20, 24-25 and 54-55.
Claims 2-5, 7-20, 24-25, and 54-55 are rejected under 35 U.S.C 101 because the claimed invention is directed to idea of itself (abstract idea) without significantly more, nothing in the claims element precludes the steps from practically being performed in the mind and/or with a pen and paper. The claims does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
Regarding claim 6.
Claim 6, is rejected under 35 U.S.C 101 because the claimed invention is directed to idea of itself (abstract idea) without significantly more. The claim recites “artificial intelligence technique uses an artificial neural network”.
The claim include additional elements “artificial neural network” simply appending well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception, e.g., a claim to an abstract idea requiring no more than a generic computer to perform generic computer functions that are well-understood, routine and conventional activities previously known to the industry, as discussed in Alice Corp., 573 U.S. at 225, 110 USPQ2d at 1984 (see MPEP § 2106.05(d)). Hence, the additional elements do not integrate the exception into a practical application and do not amount to claiming significantly more than the recited judicial exception. Therefore, the claim is not patent eligible.
Regarding claim 21.
Claim 21, rejected under 35 U.S.C 101 because the claimed invention is directed to idea of itself (abstract idea) without significantly more. The claim 21 recites “collecting of geo-spatial data includes an automated initiating whereby geo-spatial data collection means configured to collect geospatial data and/or the further geo-spatial data are initiated to collect the further geo-spatial data in response to the fact that the quality condition is not fulfilled”.
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception, specifically, claimed “collecting of geo-spatial data includes an automated initiating” is well-understood, routine activities, a claim reciting a generic computer component performing a generic computer function is necessarily ineligible. The claim simply stated a judicial exception (e.g., law of nature or abstract idea) while effectively adding words that “apply it” in a computer. Therefore, the claim is not patent eligible.
Regarding claim 22.
Claim 22, is rejected under 35 U.S.C 101 because the claimed invention is directed to idea of itself (abstract idea) without significantly more. The claim recites “the geo-spatial data and/or the further geo-spatial data represent gravimetric or electromagnetic measurements, in particular, LIDAR, optical, RADAR, multispectral, or hyperspectral measurements”.
The claim include additional elements “LIDAR” which is well-understood, routine activities, a claim reciting a generic computer component performing a generic computer function is necessarily ineligible. The claim simply stated a judicial exception (e.g., law of nature or abstract idea) while effectively adding words that “apply it” in a computer. Therefore, the claim is not patent eligible.
Regarding claim 23.
Claim 23, is rejected under 35 U.S.C 101 because the claimed invention is directed to idea of itself (abstract idea) without significantly more. The claim recites “geo-spatial data and/or the further geo-spatial data are collected by an unmanned aerial vehicle, a satellite, a plane, a helicopter, a balloon, or a high-altitude pseudo satellite”.
The claim include additional elements “an unmanned aerial vehicle, a satellite” which is well-understood, routine activities, a claim reciting a generic computer component performing a generic computer function is necessarily ineligible. The claim simply stated a judicial exception (e.g., law of nature or abstract idea) while effectively adding words that “apply it” in a computer. Therefore, the claim is 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 (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.
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.
Claim(s) 1-7, 10-32, and 35-55, is/are rejected under 35 U.S.C. 103 as being unpatentable over Kim (NPL Document “3D reconstruction from very high resolution satellite stereo and its application to object identification” provided by the Applicant in the IDS, hereinafter Kim) and further in view of Bauer (US PGPUB 2017/0193829 A1).
As per claim 1, Kim discloses a method for analyzing geo-spatial data (Kim, Abstract) comprising:
a. processing at least parts of the geo-spatial data to derive spatial object representations (Kim, Section 1, Introduction, second paragraph discloses “We have assessed stereo IKONOS DEM quality from commercially available software for this purpose, such as SocetSet, as well as our own in-house stereo- matching system (Kim & Muller, 1999) but the output DSM quality appears to be insufficient for the automated delineation of individual buildings in urban areas apart from very large structures so that such focusing strategies don’t work": where the DSM is output from stereo IKONOS DEM (i.e. geo-spatial data) and where the Digital Surface Model or the delineation of buildings is considered to represent the spatial object representations); and
Although Kim does not explicitly disclose b. collecting further geo-spatial data if a quality condition of the spatial object representations is not fulfilled, wherein the quality condition comprises a confidence value representing a probability with which the spatial object representations correspond to represented objects, wherein the confidence value is derived by comparing spatial object representations derived with a plurality of techniques or based on different geo-spatial data, however Kim, abstract: discloses "However, the detailed structure of buildings and trees is still ambiguous (i.e. a quality condition of the spatial object representation (11') is not fulfilled) for the application of existing machine vision algorithms, mainly due to the resolution limit, currently about 1 metre, the existence of strong shadows due to the large oblique angles and the local time of overpass"; section 1. Introduction: 2nd par.: "[...] but the output DSM quality appears to be insufficient [...]"i.e. quality condition of the spatial object representation is not fulfilled; "Two possible solutions are here tested. The first is to exploit secondary information such as Lidar": where the Lidar data is considered to represent the further geo-spatial data. Hence said limitation would have been obvious in view of Kim teachings further said limitation is well known in the art for instance Bauer discloses collecting further geo-spatial data if a quality condition of the spatial object representations is not fulfilled (Bauer, paragraph 34, discloses If the onboard processing system determines that an image does not meet a threshold quality, the UAV then retakes another picture. The UAV processing system reruns the image quality review process, and then continues with the flight plan if the image passes the quality threshold), wherein the quality condition comprises a confidence value representing a probability with which the spatial object representations correspond to represented objects (Bauer, paragraph 34, and 37), wherein the confidence value is derived by comparing spatial object representations derived with a plurality of techniques or based on different geo-spatial data (Bauer, paragraph 34, discloses a laplacian kernel can be convolved with the image (e.g., in the spatial domain) and the result can be used to determine blurriness of the image (e.g., intensity values of pixels within a threshold distance can be compared, and a blurry image can have a lack of comparisons greater than a threshold). Additional quality information can include sufficient overlap with neighboring images, brightness measurements, exposure measurements, contrast measurements, and so on….)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Kim teachings by implementing image quality determination to the system, as taught by Bauer.
The motivation would be to provide an imaging sensor with maximum image contrast and minimum shadow (paragraph 22), as taught by Bauer.
As per claim 2, Kim in view of Bauer further discloses the method of claim 1, wherein the geospatial data and/or the further geo-spatial data are image data of at least one object whereby the image data show a part of the Earth's surface (Kim, Section 1, Introduction, second paragraph discloses “automated delineation of individual buildings in urban areas”).
As per claim 3, Kim in view of Bauer further discloses the method of claim 1, wherein the object representations are spatially distributed but not necessarily connected (Kim, Section 1, Introduction, second paragraph discloses “automated delineation of individual buildings in urban areas”).
As per claim 4, Kim in view of Bauer further discloses the method of claim 1, wherein the object representations represent, at least in part, stationary and/or moving objects, such as pipelines, powerlines, railways, roads, buildings, mining sites, dams, construction sites, industrial facilities, or vegetation (Kim, Abstract, discloses trees and buildings).
As per claim 5, Kim in view of Bauer further discloses the method of claim 1, wherein the processing of the geo-spatial data and/or the further geo-spatial data uses an artificial intelligence technique (Bauer, paragraph 85).
As per claim 6, Kim in view of Bauer further discloses the method of claim 5, wherein the artificial intelligence technique uses an artificial neural network (Bauer, paragraph 85).
As per claim 7, Kim in view of Bauer further discloses the method of claim 1, wherein the quality condition comprises metadata of the geo-spatial data and/or the further geo-spatial data that said spatial object representations are derived from (Bauer, paragraphs 25, 120-121, and 129 discloses metadata of geo-spatial data).
As per claim 10, Kim in view of Bauer further discloses the method of claim 1, wherein the quality condition comprises a resolution of the spatial object representations (Bauer, paragraphs 32, 41 and 57).
As per claim 11, Kim in view of Bauer further discloses the method of claim 1, wherein the quality condition comprises a date of recording the geo-spatial data and/or the further geo-spatial data from which said spatial object representations are derived (Bauer, paragraphs 25, 78 and 85).
As per claim 12, Kim in view of Bauer further discloses the method of claim 1, wherein the quality condition comprises an extension of a grid the spatial object representations are distributed on (Bauer, paragraph 34, discloses quality information can include sufficient overlap with neighboring images, brightness measurements, exposure measurements, contrast measurements, and so on).
As per claim 13, Kim in view of Bauer further discloses the method of claim 1, wherein the quality condition is fulfilled if a predetermined set of at least one constraint regarding said quality condition is verified (Bauer, paragraph 34).
As per claim 14, Kim in view of Bauer further discloses the method of claim 13, further comprising checking a plurality of constraints, whereby at least two constraints are directed to different spatial object representations (Bauer, paragraphs 34, 37 and 60).
As per claim 15, Kim in view of Bauer further discloses the method of claim 13, wherein the at least one constraint links the quality condition with at least one threshold (Bauer, paragraph 34).
As per claim 16, Kim in view of Bauer further discloses the method of claim 15, wherein the at least one threshold is changeable, in particular, adaptable (Bauer, paragraphs 34 and 65).
As per claim 17, Kim in view of Bauer further discloses the method of claim 1, further comprising determining geo-spatial data to be replaced if at least a part of the spatial object representations do not fulfill the quality condition (Bauer, paragraphs 34, 37 and 129), whereby said part of the spatial object representations not fulfilling the quality condition is derived from said geo-spatial data to be replaced (Bauer, paragraphs 34 and 129).
As per claim 18, Kim in view of Bauer further discloses the method of claim 1, further comprising estimating a set of quality parameters of the geo-spatial data such that spatial object representations derived from geo-spatial data exhibiting said quality parameters fulfill the quality condition (Bauer, paragraphs 34, 60, and 95).
As per claim 19, Kim in view of Bauer further discloses the method of claim 18, wherein the collecting of geo-spatial data comprises complementing current geo-spatial data of the geo-spatial data with the further geo-spatial data corresponding to the set of quality parameters (Bauer, paragraphs 60 and 95), whereby in response to collecting said further geo-spatial data the current geo-spatial data are complemented (Bauer, paragraphs 34 and 60).
As per claim 20, Kim in view of Bauer further discloses the method of claim 17 further comprising estimating of a set of quality parameters of the geo-spatial data such that spatial object representations derived from geo-spatial data exhibiting said quality parameters fulfill the quality condition (Bauer, paragraphs 34 and 60, discloses quality parameters), wherein the collecting of current geo-spatial data comprises replacing of the geospatial data to be replaced with the further geo-spatial data corresponding to the set of quality parameters, whereby in response to collecting the further geo-spatial data the current geo-spatial data are replaced (Bauer, paragraphs 34 and 60, discloses retake image).
As per claim 21, Kim in view of Bauer further discloses the method of claim 1, wherein the collecting of geo-spatial data includes an automated initiating whereby geo-spatial data collection means configured to collect geospatial data and/or the further geo-spatial data are initiated to collect the further geo-spatial data in response to the fact that the quality condition is not fulfilled (Bauer, paragraphs 28 and 34, discloses automated flight plan to perform rooftop damage inspection of a property 20).
As per claim 22, Kim further discloses the method of claim 1, wherein the geo-spatial data and/or the further geo-spatial data represent gravimetric or electromagnetic measurements, in particular, LIDAR, optical, RADAR, multispectral, or hyperspectral measurements (Kim, Abstract discloses LIDAR).
As per claim 23, Kim further discloses the method of claim 1, wherein the geo-spatial data and/or the further geo-spatial data are collected by an unmanned aerial vehicle, a satellite, a plane, a helicopter, a balloon, or a high-altitude pseudo satellite. (Kim, Abstract discloses satellite)
As per claim 24, Kim further discloses the method of claim 1, further comprising training a processing means using a training data set comprising geo-spatial data and/or the further geospatial data with associated spatial object representations (Bauer, paragraphs 71, 136, and 139).
As per claim 25, Kim further discloses the method of claim 24, wherein the training data set is provided via a validation of at least parts of said spatial object representations by a user (Bauer, paragraphs 136 and 139).
As per claim 26, please see the analysis of claim 1.
As per claim 27, please see the analysis of claim 2.
As per claim 28, please see the analysis of claim 3.
As per claim 29, please see the analysis of claim 4.
As per claim 30, please see the analysis of claim 5.
As per claim 31, please see the analysis of claim 6.
As per claim 32, Kim in view of Bauer further discloses the system of claim 26, wherein the analyzing means is configured to test metadata of the geospatial data and/or the further geo-spatial data that said spatial object representations are derived from (Bauer, paragraphs 25, 120-121, and 129 discloses metadata of geo-spatial data).
As per claim 35, please see the analysis of claim 10.
As per claim 36, please see the analysis of claim 11.
As per claim 37, please see the analysis of claim 12.
As per claim 38, please see the analysis of claim 13.
As per claim 39, please see the analysis of claim 14.
As per claim 40, please see the analysis of claim 15.
As per claim 41, please see the analysis of claim 16
.
As per claim 42, please see the analysis of claim 17.
As per claim 43, please see the analysis of claim 18.
As per claim 44, Kim in view of Bauer further discloses the system of claim 43, wherein the geospatial data collection means is configured to complement the geo-spatial data and/or further geo-spatial data or replace the geo-spatial data to be replaced with the further geo-spatial data corresponding to the set of quality parameters (Bauer, paragraphs 34, 60 and 95).
As per claim 45, Kim in view of Bauer further discloses the system of claim 26, wherein the geo-spatial data collection means is configured to be automatically initiated if said quality condition is not fulfilled (Bauer, paragraphs 28 and 34, discloses automated flight plan to perform rooftop damage inspection of a property 20).
As per claim 46, please see the analysis of claim 22.
As per claim 47, please see the analysis of claim 23.
As per claim 48, please see the analysis of claim 24.
As per claim 49, please see the analysis of claim 25.
As per claim 50, Kim in view of Bauer further discloses the system of claim 26, wherein the processing means comprises at least one interface and is further configured to receive geo-spatial data and/or the further geo-spatial data and output said spatial object representations (Bauer, paragraphs 26 and 37).
As per claim 51, Kim in view of Bauer further discloses the system of claim 26, wherein the analyzing means comprises at least one interface and is further configured to receive the spatial object representations, and output an initializing signal if said quality condition is not fulfilled (Bauer, paragraphs 34, 37, and 52).
As per claim 52, Kim in view of Bauer further discloses the system of claim 26, wherein the geo-spatial data collection means comprises at least one interface and is further configured to receive said initializing signal and output the geospatial data (Bauer, paragraphs 23-24, and 34).
As per claim 53, Kim in view of Bauer discloses all the claim limitations as being addressed with respect to claim 1. Furthermore, Bauer also discloses a computer program for analyzing geo-spatial data, the computer program stored on a storage means of a computer and comprising machine code instructions executable by a processor of the computer (Bauer, paragraph 158), the machine code instructions being executable by the processor to cause the computer to (Bauer, paragraphs 158 and 168):
Conclusion
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 nonprovisional extension fee (37 CFR 1.17(a)) 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 mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to SYED Z HAIDER whose telephone number is (571)270-5169. The examiner can normally be reached MONDAY-FRIDAY 9-5:30 EST.
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, SAM K Ahn can be reached at 571-272-3044. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/SYED HAIDER/ Primary Examiner, Art Unit 2633