DETAILED ACTION
Notice of Pre-AIA or AIA Status
01. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Drawings
02. The drawings were received on 04/25/2025. These drawings are accepted.
Claim Rejections - 35 USC § 101
03. 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.
04. Claims 1 – 20 are rejected under 35 U.S.C. 101 because the claims are directed to an abstract idea without significantly more. The claims are directed to inferring information from images, which amounts to an abstract idea, as explained in detail below. The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional computer elements, which are recited at a high level of generality, provide conventional computer functions that do not add meaningful limits to practicing the abstract idea.
Step 1: The claim (claim 1) recites a system comprising a combination of devices for requesting and receiving information about images. Thus, the claim is directed to a machine, which is one of the statutory categories of invention.
Step 2A, prong one: The claim recites the limitation of “infer…the demographic information for the identified geographic location based on one or more images…”. Although the claim recites some generic computing hardware, nothing in the claim elements precludes the step from practically being performed in the human mind. For example, the “infer” step in the claim encompasses an observation, evaluation, judgment, or opinion, in that a person can determine information from an image. A person can easily determine some sort of demographic information, for example the age, gender, or race, of people in a group that are seen in an image.
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claims recites an abstract idea.
Step 2A, prong two: The judicial exception is not integrated into a practical application. In particular, the claim includes the additional element of “receive…a user request for demographic information for an identified geographic location”. This limitation represents the environment in which the judicial exception is used, in that BLANK. This element is thus a mere indication of the field of use or technological environment in which the judicial exception is performed. This element is also insignificant extra-solution activity because it merely gathers data for use in calculating BLANK. This limitation therefore represents a field of use or mere data gathering that is necessary for use of the recited judicial exception.
The claim recites the additional element of “send a response to the user request”. This represents mere data gathering that is necessary for use of the recited judicial exception and is recited at a high level of generality. Limitation (a) in the claim is thus insignificant extra-solution activity.
Even when viewed in combination, the additional elements in this claim do no more than automate the mental processes that a person performs (e.g. determine the characteristic of users in images), using the computer components as a tool. While this type of automation improves the daily life of human (by performing an analysis of people), there is no change to the computers and other technology that are recited in the claim as automating the abstract ideas, and thus this claim cannot improve computer functionality or other technology.
Step 2B: As discussed previously with respect to Step 2A prong two, the controller in the claim amounts to no more than mere instructions to apply the exception using a generic computer component. The same analysis applies here in 2B, i.e., mere instructions to apply an exception using a generic computer component cannot integrate a judicial exception into a practical application at Step 2A or provide an inventive concept in Step 2B. The claims do not include additional elements that are sufficient to amount to significantly more than the abstract idea, but are instead limited to appending well-understood, routine, and conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception (abstract idea).
In this instance, the claim includes that the request is for demographic information and that the response has inferred demographic information for a geographic area. However, most search engines include some type of criteria for the request, as well as return results that are in line with what the request was for. Returning results for the supplied criteria is merely extra-solution activity and does not meaningfully limit the claims. Therefore this claim limitation is understood to be well-understood, routine, and conventional activity, which can be performed by generic computing components.
The same analysis is applied to dependent claims 2 – 10 and 12 – 19, (as well as independent claims 11 and 20) because the limitations recite additional mental processes and/or mathematical calculations and do not integrate into a practical application. Further, they do not include additional elements that amount to significantly more.
Claims 2 and 12 recite the additional element of storing latitude and longitude information. However, this is understood to be data gathering. Specifying what type of data is obtained or compared, which in this case is coordinate information, does not render idea of inferring image characteristics any less abstract. Furthermore, this limitation is insignificant extra-solution activity, which is well-understood, routine, and conventional activity, which can be performed by generic computing components.
Claims 3, 4, and 13 only recite performing the steps of searching and returning results another time, and they do not add any additional elements.
Claims 5 and 14 recite the additional element of obtaining the images from a remote source. However, this is understood to be data gathering. Specifying where the data comes from, which in this case is from another source, does not render idea of inferring image characteristics any less abstract. Furthermore, this limitation is insignificant extra-solution activity, which is well-understood, routine, and conventional activity, which can be performed by generic computing components.
Claims 6 and 15 recite the additional element of pre-processing the images. However, this is understood to be data gathering. Performing a processing step on the images merely provides additional data for the images, and does not render the abstract idea any less abstract.
Claims 7 and 16 recite the additional element of feature extraction on the images. However, this is understood to be data gathering. Performing a step extracting features on the images merely provides additional data for the images, and does not render the abstract idea any less abstract.
Claims 8 and 17 recite the additional element of using artificial intelligence or machine learning. However, this is merely indicating the technological environment in which the judicial exception is applied to, and does not amount to significantly more than the abstract idea.
Claims 9 and 18 recite the additional element of the model being trained. Much like claims 8 and 17, this is merely indicating the technological environment in which the judicial exception is applied to, and does not amount to significantly more than the abstract idea.
Claims 10 and 19 recite the additional element of integrating geographic information system data into the profile. However, this is understood to be data gathering. Specifying what type of data is obtained or compared, which in this case is GIS information, does not render idea of inferring image characteristics any less abstract. Furthermore, this limitation is insignificant extra-solution activity, which is well-understood, routine, and conventional activity, which can be performed by generic computing components.
Claim Rejections - 35 USC § 103
05. 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.
06. 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 of this title, 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.
07. Claims 1 – 7, 11 – 16, and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Terrazas et al. (US PGPub 2014/0270355), hereinafter “Terrazas”, in view of Heimendinger (US PGPub 2012/0084276).
Consider claim 1, Terrazas discloses a demographic inference computer system, comprising:
a communication interface; memory; and one or more processors coupled to the memory and the communication interface, wherein the one or more processors are configured to execute information stored in the memory to cause the demographic inference computer system to (paragraphs [0137], [0171], [0191], computer hardware is used for a system, which includes a memory, processor, and interface):
receive, via the communication interface of a demographic inference system, a [user request] for demographic information for an identified geographic location (paragraphs [0017] – [0021], [0025], a request is received, that is used to determine the demography of a particular requested geographic area);
infer, based on the identified geographic location in the user request, the demographic information for the identified geographic location based on one or more mages of the identified geographic location (paragraphs [0017], [0024], [0033] – [0035], after the geographic area is identified, the demography of that area is estimated, which is done so by obtaining one or more images of the geographic area, so that the demography of that geographic area can be estimated);
send a response to the [user request], via the communication interface, with inferred demographic information for the identified geographic location (paragraphs [0025], [0026], [0055], a response is determined for the request, which includes the estimated demography for the geographic area).
Although Terrazas discloses requests for demography for geographic areas (paragraphs [0025], [0026]), the requests are generally performed by the system, and Terrazas does not explicitly describe a user performing the searches.
In the same field of endeavor, Heimendinger discloses a system comprising:
a user request (paragraphs [0028], [0033], [0056], a user performs a search in order to locate information, such as demographic data for a geographic location).
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the user searching for demographic data taught by Heimendinger into the inferring of demographic data at geographic locations taught by Terrazas for the purpose of allowing a user to be able to use the system for searching, so that a user can be provided with up to date demographic data at geographic locations, which allows for more specific and detailed data to be returned to the user.
Consider claim 2, and as applied to claim 1 above, Terrazas discloses a system comprising:
store, in a central database, the inferred demographic information with latitude and longitude information for the identified geographic location (paragraphs [0024] [0025], the system stores coordinate information, which is indicative of latitude and longitude data).
Consider claim 3, and as applied to claim 2 above, Heimendinger discloses a system comprising:
receive, at the communication interface of the demographic inference system, an additional user request for the demographic information for the identified geographic location; and determine whether the demographic information for the identified geographic location has been previously inferred (paragraphs [0032], [0049], [0054], [0056], [0062], multiple searches can be performed by the user, such as by a user requesting different data or for data at a different location, whereby the system stores the information retrieved).
Consider claim 4, and as applied to claim 3 above, Terrazas discloses a system comprising:
obtain the inferred demographic information stored for the identified geographic location at the central database, in response to determining that the demographic information was previously inferred (paragraphs [0024], [0034], [0040], the obtained demographic data is stored in a database so that it can later be retrieved);
send an additional response to the additional user request, with the inferred demographic information for the identified geographic location (paragraphs [0033], [0034], additional searches can be performed in order to return the demographic data for the geographical area).
Consider claim 5, and as applied to claim 1 above, Terrazas discloses a system comprising:
obtain the one or more images from a remote source, wherein the one or more images comprise at least one of a satellite image or a street view image for the identified geographic location (paragraph [0023], the images can be obtained from satellites).
Consider claim 6, and as applied to claim 1 above, Terrazas discloses a system comprising:
pre-process the one or more images including one or more of image normalization, noise reduction, or geometric correction on the one or more images prior to analysis for a demographic inference (paragraph [0026], a specific analysis is performed on the images in order to determine the objects that are detected within).
Consider claim 7, and as applied to claim 6 above, Terrazas discloses a system comprising:
perform feature extraction from the one or more images, after pre-processing, to extract features that affect the demographic inference (paragraph [0018], features are extracted from the images as part of the demographic determination).
08. Claims 8 – 10 and 17 – 19 are rejected under 35 U.S.C. 103 as being unpatentable over Terrazas et al. (US PGPub 2014/0270355), hereinafter “Terrazas”, in view of Heimendinger (US PGPub 2012/0084276), in further view of McLean (US PGPub 2021/0334831), hereinafter “McLean”.
Consider claim 8, and as applied to claim 7 above, Terrazas and Heimendinger disclose the claimed invention except that artificial intelligence is used for the processing.
In the same field of endeavor, McLean discloses a system comprising:
inference of the demographic information includes analysis of features extracted from the one or more images using an artificial intelligence or machine learning (AI/ML) model to infer the demographic information from the one or more images (paragraphs [0040], [0044], machine learning and/or artificial intelligence is used in order to perform extraction of features from images in order to determine information such as demographics that are present in the images).
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the artificial intelligence taught by McLean into the determining of demographic data at geographic locations taught by Terrazas and Heimendinger for the purpose of allowing more advanced techniques to be used to extract information from images, which would lead to better and/or faster feature extraction and demographic determining.
Consider claim 9, and as applied to claim 8 above, McLean discloses a system comprising:
the AI/ML model is trained for the demographic inference from geoencoded images (paragraph [0044], the artificial intelligence model is trained).
Consider claim 10, and as applied to claim 8 above, Terrazas discloses a system comprising:
integrate the inferred demographic information with geographic information system (GIS) data to generate a location-based demographic profile (paragraph [0043], geographic information is incorporated into the demographic data that is stored in the database).
Claims 11 – 20 recite the same embodiments found in claims 1 – 10, except that either a system, method, or media is recited. Since the same claim limitations are otherwise recited, claims 11 – 20 are rejected under the same rationale provided above with respect to claims 1 – 10.
Relevant Prior Art Directed to State of Art
09. The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Sharma et al. (US PGPub 2016/0300105) discloses a method of geo-demographic classification of a geographical region that utilizes satellite imagery in order to determine geo-demographic clustering.
Conclusion
10. Any inquiry concerning this communication or earlier communications from the Examiner should be directed to Christopher Raab whose telephone number is (571) 270-1090. The Examiner can normally be reached on Monday-Friday from 9:00am to 5:00pm.
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, Ajay Bhatia can be reached on (571) 272-3906. The fax phone number for the organization where this application or proceeding is assigned is (571) 273-8300.
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/CHRISTOPHER J RAAB/Primary Examiner, Art Unit 2156
February 07, 2026