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 .
Status of Claims
Claims 1, 4-7, 10-12, 15 and 17-22 are pending. Claims 2-3, 8-9, 13-14, and 16 have been cancelled. Claims 21 and 22 are newly added.
Response to Arguments
Applicant's arguments filed October 31, 2025, with respect to the 35 USC 103 rejections have been fully considered but they are not persuasive.
Applicant argues that the Konrardy reference does not teach “comparing the change to an expected change predicted by a trained machine learning algorithm” because Konrardy only teaches determining risk levels and does not teach machine learning prediction for comparing the change to an expected change. Examiner respectfully disagrees. Konrardy teaches determining a salvage potential of a component based on a comparison between a received and expected response (see Konrardy, Col. 49, lines 5-28). The expected responses may be indicative of ordinary or usual responses of one or more components and may include a plurality of ranges based upon whether the components are functioning properly or malfunctioning (i.e., expected change of the component) (see Konrardy, Col. 48 lines 31-58). Konrardy further teaches that risk levels, damage evaluation, predicting repairs and etc. may be performed by trained machine learning models (see Konrardy, Col. 79, lines 40-67). Examiner asserts that Konrardy is sufficient to teach this limitation because Konrardy determines if a change is unacceptable (i.e., if the component is salvageable) by comparing a received response (i.e., the change) to an expected response (i.e., the expected change) and that this process can be performed using a trained machine learning model. Therefore, the 35 USC 103 rejection of the independent claims is upheld.
Applicant further argues that the combination of Terczynski, Skinner, Winn, DeLizio, Yoshigahara and Konrardy is not appropriate because of the large number of references that are only combined ed on hindsight reasoning. Examiner respectfully disagrees.
In response to applicant's argument that the examiner's conclusion of obviousness is based upon improper hindsight reasoning, it must be recognized that any judgment on obviousness is in a sense necessarily a reconstruction based upon hindsight reasoning. But so long as it takes into account only knowledge which was within the level of ordinary skill at the time the claimed invention was made, and does not include knowledge gleaned only from the applicant's disclosure, such a reconstruction is proper. See In re McLaughlin, 443 F.2d 1392, 170 USPQ 209 (CCPA 1971).
In response the applicant’s arguments regarding the large number of references, Examiner reasons that relying on a large number of references does not, without more, weight against the obviousness of the claimed invention (see MPEP 2145(V)).
Applicant further argues that the DeLizio and Winn references are not in the same field of endeavor as the claimed invention and are not reasonably pertinent to the particular problem faced by the inventor. It has been held that a prior art reference must either be in the field of the inventor’s endeavor or, if not, then be reasonably pertinent to the particular problem with which the inventor was concerned, in order to be relied upon as a basis for rejection of the claimed invention. See In re Oetiker, 977 F.2d 1443, 24 USPQ2d 1443 (Fed. Cir. 1992). In this case, the field of this invention is classified into the CPC subgroups: G06V20/70, G06Q30/0645, and G06V10/17. Each proposed reference is also classified into one or more of these subgroups, and are thus in the same field of endeavor as the invention herein. Additionally, the 35 USC 103 rejection below describe how modifying the Terczynski primary reference with the teachings of the Skinner, Winn, DeLizio and Yoshigahara references would result in the invention as claimed, and therefore the prior art would function together. Specifically, although Winn does involve UAVs, Examiner asserts that the invention as disclosed could be applied to a UAV and the determining if damage to the UAV is covered by an effective physical damage policy could be combined with the other prior art references to teach the limitations of determining that the change (i.e., damage) of an item (i.e., UAV) is unacceptable by comparing it to a policy (i.e., if the item is covered by an effective physical damage policy). Additionally, DeLizio may involve an autonomous car, however the DeLizio reference is used to teach the limitation “wherein the list of the descriptions is written to a block chain”. Both the current invention and DeLizio reference use the block chain as a way of efficient data storage to maintain data coherency, and therefore the DeLizio reference is in an analogous field of endeavor to the current invention. Thus, the 35 USC 103 rejections are upheld, and consequently, THIS ACTION IS FINAL.
Claim Rejections - 35 USC § 103
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1, 4-7, 10-12, 15 and 17-22 are rejected under 35 U.S.C. 103 as being unpatentable over Terczynski et al. (US 2023/0334812 A1, filed April 26, 2022) in view of Skinner et al. (US 2015/0039466 A1) further in view of Winn et al. (US 2017/0083979 A1), Andrew DeLizio (US 2018/0202822 A1), Yoshigahara (US 10311333 B2) and Konrardy et al. (US 10086782 B1).
Regarding claim 1, Terczynski teaches a method for image-assisted identification of property changes, comprising:
receiving, at a computer program executed by mobile electronic device, a first image of a property captured by an image capture device at a first time (Terczynski, Para. [0056], Terczynski teaches the mobile device captures image frames of a physical environment that may be a room within a property such as a home or a commercial property);
tagging, by the computer program, a space of the property (Terczynski, Para. [0039], the object report software may determine whether a set of one or more predefined objects of interest are not detected in the physical environment, which may be different depending on the type of physical environment. For instance, the object report software may determine whether a fire extinguisher has been identified as being in the physical environment. As another example, the object report software may determine whether a first aid kit has been identified as being in the physical environment);
identifying, by the computer program, a plurality of first items in the first image (Terczynski, Para. [0057], Terczynski teaches the images are ran through an image recognition library to identify object(s) of interest) and a location of each of the plurality of first items in the space (Terczynski, Para. [0032], the current location of the mobile device may be transmitted to the server for use in generating the object report (i.e., the location of the items, as the mobile device is in the same space as the object));
tagging, by the computer program, each of the plurality of first items with a first description by comparing each of the plurality of first items in the first image with a database of items and descriptions (Terczynski, Para. [0060], Terczynski teaches the server accesses a database and determines information to include on the object report, which may include a description of the object for each object);
generating, by the computer program, a list of the descriptions for the property (Terczynski, Para. [0060], Terczynski teaches a report including, for each identified object, a description of the object, a maintenance plan, identified condition of the object, etc.).
receiving, by the computer program, a first condition for each of the plurality of first items on the list (Terczynski, Para. [0060], Terczynski teaches the report may include, for each object, an identified condition of the object (e.g., excellent, good, fair, poor, replacement));
communicating, by the computer program, the list to a backend computer program (Terczynski, Para. [0043], Terczynski teaches multiple communications between the mobile device and the serve for generating and/or displaying the report data); and
saving, by the backend computer program, the list and descriptions (Terczynski, Para. [0045], Terczynski teaches the object report software may serialize the object(s) of interest and transmit them to the server with the other information. The server prepares the report data and may transmit it back to the mobile device and/or store it so the user can later access the report);
identifying, by the computer program, the plurality of first items in the second image (Terczynski, Para. [0057], Terczynski teaches the images are ran through an image recognition library to identify object(s) of interest);
tagging, by the computer program, each of the plurality of second items with a first description by comparing each of the plurality of second items in the second image with the database of items and descriptions (Terczynski, Para. [0060], Terczynski teaches a report including, for each identified object, a description of the object, a maintenance plan, identified condition of the object, etc.);
communicating, by the computer program, the updated list to the backend computer program (Terczynski, Para. [0043], Terczynski teaches multiple communications between the mobile device and the serve for generating and/or displaying the report data. Para. [0045], Terczynski teaches the object report software may serialize the object(s) of interest and transmit them to the server with the other information. The server prepares the report data and may transmit it back to the mobile device and/or store it so the user can later access the report).
Although Terczynski teaches identifying objects and conditions of objects in images (Terczynski, Paras. [0057] and [0060]), Terczynski does not explicitly teach “wherein the first condition is based on wear of the plurality of first items on the list”, “receiving, at the computer program, a second image of the property captured by an image capture device at a second time”, “receiving, by the computer program, a second condition for each of the plurality of first items, wherein the second condition is based on wear of the plurality of first items on the list”, “identifying, by the backend computer program, a change in condition for one of the plurality of first items based on a comparison of the first condition to the second condition, the change in condition being based on wear or a missing element”, “determining, by the backend computer program, a cost associated with the change in condition”, and ” determining, by the backend computer program, a cost associated with the one second item”. However, in an analogous field of endeavor, Skinner teaches a first condition of the property may be documented and may be an ex-ante condition, or a “before condition” of the property before or at the time that possession of the property is transferred to the first party. The documented first condition of the property may be employed to ensure accountability and/or liability for any damage, destruction, alteration, or modification to the property occurring after possession of the property has been transferred (i.e., change in condition is based on wear or a missing element) (Skinner, Para. [0043]). Skinner teaches capturing image data to determine a second condition of the property after a renter has been in possession of the property for an amount of time or after the rental period has expired (Skinner, Paras. [0053]-[0056]), determining a variance between the first condition of the property and the second condition of the property (Skinner, Para. [0057]), and determine a fee to charge the renter based on the determined variance between the first and second condition (Skinner, Para. [0061]).
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the method of Terczynski with the teachings of Skinner by including determining a first condition of the property based on wear of the item, capturing a second image at a second time to determine a second condition of the property based on wear of the item, determine a variance between the first and second condition of the property (i.e., change in property based on wear or missing element), and determine a fee to charge based on the variance in condition. One having ordinary skill in the art would have been motivated to combine these references because doing so would assure accountability for damages that occur during a rental period and reduce disputes, as recognized by Skinner.
Although Terczynski in view of Skinner teaches determining a fee to charge based on the variance in condition (Skinner, Para. [0061]), they do not explicitly teach “determining, by the backend computer program, that one of the plurality of second items is unacceptable by comparing the one second item to a policy”. However, in an analogous field of endeavor, Winn teaches determining if a damage to a structure is covered by an effective liability policy and/or if damage to a vehicle due to collision is covered by an effective physical damage policy held for the vehicle (Winn, Para. [0070]).
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the method of Terczynski in view of Skinner with the teachings of Winn by including determining if a damage is covered by a liability or physical damage policy for the vehicle. One having ordinary skill in the art would have been motivated to combine these references, because doing so would allow for determination of acceptable damages that will be covered by a policy, as recognized by Winn.
Although Terczynski in view of Skinner further in view of Winn teaches storing a report with descriptions and conditions of each object (Terczynski, Para. [0060]), they do not explicitly teach “wherein the list of the descriptions is written to a blockchain”. However, in an analogous field of endeavor, DeLizio teaches storing lists of information about vehicles in an open distributed immutable ledger, a.k.a. a blockchain (DeLizio, Para. [0149]).
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the method of Terczynski in view of Skinner further in view of Winn with the teachings of DeLizio by storing the object record by writing it to a blockchain. One having ordinary skill in the art would have been motivated to combine these references because doing so would allow for efficient data storage by allowing the lists to be periodically shared to maintain data coherency, as recognized by DeLizio. Thus, the claimed invention would have been obvious to one having ordinary skill in the art before the effective filing date.
Although Terczynski in view of Skinner further in view of Winn and DeLizio teaches creating a report with descriptions and conditions for each item (Terczynski, Para. [0060]), they do not explicitly teach “identifying, by the computer program, a plurality of second items in the second image that are not in the first image” and “updating, by the computer program, the list with the plurality of second items”. However, in an analogous field of endeavor, Yoshigahara teaches an identification unit identifies an object in the input image and determines if a new object is different from the objects identified in the previously received images. Yoshigahara teaches a subset of a feature dictionary is acquired or a new feature dictionary is generated and additive information corresponding to the identified object is transmitted (Yoshigahara, Col. 18, lines 24-49). Yoshigahara further teaches the feature dictionary is a list of the detected objects extracted from the object images that includes a feature quantity for each object (Yoshigahara, Fig. 7; Col. 11, Lines 10-32).
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the method of Terczynski in view of Skinner further in view of Winn and DeLizio with the teachings of Yoshigahara by including identifying objects in an image different from objects identified in previous images and including the new objects in a feature dictionary. One having ordinary skill in the art would have been motivated to combine these references because doing so would allow for higher object identification performance in a device with a small amount of processing resources, as recognized by Yoshigahara.
Although Terczynski in view of Skinner further in view of Winn, DeLizio and Yoshigahara teaches determining whether the change is unacceptable by determining if a damage to a structure is covered by an effective liability policy and/or if damage to a vehicle due to collision is covered by an effective physical damage policy held for the vehicle (Winn, Para. [0070]), they do not explicitly teach “determining, by the backend computer program, that the change is unacceptable by comparing the change to an expected change predicted by a trained machine learning algorithm”. However, in an analogous field of endeavor, Konrardy teaches a salvage assessment may be performed to determine a salvage potential indicative of whether each of the one or more components is salvageable based on comparison between received and expected response. The salvage potential of a component may be associated with an estimate of damage, which may include an estimate of a level, type, or extent of damage (Konrardy, Col. 49, lines 5-28). Konrardy further teaches embodiments described may include trained machine learning models to determine risk levels, evaluate damage to a vehicle, predict repairs to a vehicle, etc., and that although methods may not directly mention machine learning techniques, such methods may be read to include such machine learning (Konrardy, Col. 79, lines 40-67).
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the method of Terczynski in view of Skinner further in view of Winn, Delizio and Yoshigahara with the teachings of Konrardy by including capturing environmental conditions of the property. One having ordinary skill in the art would have been motivated to combine these references because doing so would allow for assessing, detecting, and responding to malfunctions or damages in vehicles and/or homes, as recognized by Konrardy. Thus, the claimed invention would have been obvious to one having ordinary skill in the art before the effective filing date.
Regarding claim 4, Terczynski in view of Skinner further in view of Winn, Delizio, Yoshigahara and Konrardy teaches the method of claim 1, and further teaches wherein the property comprises a living area (Terczynski, Para. [0056], Terczynski teaches the mobile device captures image frames of a physical environment that may be a room within a property such as a home or a commercial property).
Regarding claim 5, Terczynski in view of Skinner further in view of Winn, Delizio, Yoshigahara and Konrardy teaches the method of claim 1, and further teaches wherein the property comprises a vehicle (Skinner, Para. [0069], Skinner teaches a property, such as a rental vehicle).
The proposed combination as well as the motivation for combining the Terczynski, Skinner, Winn, Delizio, Yoshigahara and Konrardy references presented in the rejection of Claim 1, apply to Claim 5 and are incorporated herein by reference. Thus, the method recited in Claim 5 is met by Terczynski in view of Skinner further in view of Winn, Delizio, Yoshigahara and Konrardy.
Regarding claim 6, Terczynski in view of Skinner further in view of Winn, Delizio, Yoshigahara and Konrardy teaches the method of claim 1, and further teaches capturing, by the computer program, environmental conditions for the property at the first time (Konrardy, Col. 23, lines 18-37, collecting autonomous operation feature data including determinations regarding environmental conditions in which the vehicle and/or home operates (e.g., traffic conditions, construction, potholes, worn lane markings, obstructed views, weather conditions, etc.)).
The proposed combination as well as the motivation for combining the Terczynski, Skinner, Winn, Delizio, Yoshigahara and Konrardy references presented in the rejection of Claim 1, apply to Claim 6 and are incorporated herein by reference. Thus, the method recited in Claim 6 is met by Terczynski in view of Skinner further in view of Winn, Delizio, Yoshigahara and Konrardy.
Regarding claim 7, Terczynski in view of Skinner further in view of Winn, Delizio, Yoshigahara and Konrardy teaches the method of claim 1, and further teaches wherein the first time is at a beginning of a lease term, and the second time is at an end of the lease term (Skinner, Para. [0046], Skinner teaches the transfer of possession of the property to the first party occurs after the first condition of the property is documented. Para. [0056], Skinner teaches the second condition is documented by the user after the rental period has expired).
The proposed combination as well as the motivation for combining the Terczynski, Skinner, and Winn, Delizio, Yoshigahara and Konrardy references presented in the rejection of Claim 1, apply to Claim 7 and are incorporated herein by reference. Thus, the method recited in Claim 7 is met by Terczynski in view of Skinner further in view of Winn, Delizio, Yoshigahara and Konrardy.
Regarding claim 10, Terczynski in view of Skinner further in view of Winn, DeLizio, Yoshigahara and Konrardy teaches the method of claim 1 and further teaches wherein the backend computer program determines, for each item, whether the change in condition is acceptable by comparing the change to thresholds specific to item type and/or time of usage (Konrardy, Col. 48, lines 31-40, the salvage assessment device may obtain one or more expected responses for the one or more components. Such expected responses may be indicative of ordinary or usual responses of the one or more components to the one or more test signals, and the expected responses may be obtained from a program memory or a database. The expected responses may include ranges of response signals associated with proper operation of components, such as ranges of sensor data generated by a sensor when functioning properly (i.e., thresholds specific to item type)).
The proposed combination as well as the motivation for combining the Terczynski, Skinner, Winn, Delizio, Yoshigahara and Konrardy references presented in the rejection of Claim 1, apply to Claim 10 and are incorporated herein by reference. Thus, the method recited in Claim 10 is met by Terczynski in view of Skinner further in view of Winn, Delizio, Yoshigahara and Konrardy.
Regarding claim 11, Terczynski in view of Skinner further in view of Winn, Delizio, Yoshigahara and Konrardy teaches the method of claim 1, and further teaches wherein the trained machine learning algorithm is trained using historical data from similar properties over a similar period of time (Konrardy, Col. 80, lines 1-16, Konrardy teaches training machine learning may involve identifying and recognizing patterns in existing data).
The proposed combination as well as the motivation for combining the Terczynski, Skinner, Winn, Yoshigahara and Konrardy references presented in the rejection of Claim 1, apply to Claim 11 and are incorporated herein by reference. Thus, the method recited in Claim 11 is met by Terczynski in view of Skinner further in view of Winn, Delizio, Yoshigahara and Konrardy.
Claims 12, 17 and 18 recite systems with elements corresponding to the steps recited in Claims 1, 10 and 11, respectively. Therefore, the recited elements of these claims are mapped to the proposed combination in the same manner as the corresponding steps in their corresponding method claims. Additionally, the rationale and motivation to combine the Terczynski, Skinner, Winn, Delizio, Yoshigahara and Konrardy references, presented in rejection of Claim 1, apply to these claims. Additionally, the Terczynski, Skinner, Winn, Delizio, Yoshigahara and Konrardy references discloses a backend electronic device (Para. [0013], Terczynski teaches a remote device such as a server), a mobile electronic device comprising an image capture device (Para. [0025], Terczynski teaches a mobile device capable of taking images), and a database (Para. [0041], Terczynski teaches object report database).
Claim 15 recites a system with elements corresponding to the steps recited in a combination of Claims 4 and 5. Therefore, the recited elements of this claim are mapped to the proposed combination in the same manner as the corresponding steps in the corresponding method claims. Additionally, the rationale and motivation to combine the Terczynski, Skinner, Winn, Delizio, Yoshigahara and Konrardy references, presented in rejection of Claim 1, apply to this claim. Finally, the combination of the Terczynski, Skinner, Winn, Delizio, Yoshigahara and Konrardy references discloses a backend electronic device (Para. [0013], Terczynski teaches a remote device such as a server), a mobile electronic device comprising an image capture device (Para. [0025], Terczynski teaches a mobile device capable of taking images), and a database (Para. [0041], Terczynski teaches object report database).
Claims 19, 20, and 21 recite computer-readable storage mediums storing programs with instructions corresponding to the steps recited in Claim 1, 11 and 10, respectively. Therefore, the recited programming instructions of these claims are mapped to the proposed combination in the same manner as the corresponding steps in their corresponding method claims. Additionally, the rationale and motivation to combine the Terczynski, Skinner, Winn, Delizio, Yoshigahara and Konrardy references, presented in rejection of Claim 1, apply to this claim. Finally, the combination of the Terczynski, Skinner, Winn, Delizio, Yoshigahara and Konrardy references discloses a computer readable storage medium (Terczynski, Para. [0067], Terczynski teaches a non-transitory computer-readable storage media).
Regarding claim 22, Terczynski in view of Skinner further in view of Winn, DeLizio, Yoshigahara and Konrardy teaches the non-transitory computer readable storage medium of claim 19 as described above, and further teaches wherein the backend computer program identifies, in the second image, new items and/or missing items not present in the first image (Skinner, Para. [0023], a variance between the first condition and the second condition may be determined. In some embodiments, the variance may be a difference between the first condition and the second condition, such as damage to the property in the second condition that does not appear in the first condition. In at least one of the various embodiments, determining the damage, destruction, alterations and/or modifications that occurred during the time period that the first party had possession of the property may be determined based on at least the determined variance (i.e., new items and/or missing items not present in the first image). Para. [0053], the second condition of the property may be documented by capturing at least image data separate from the image data captured during the documenting the first condition).
The proposed combination as well as the motivation for combining the Terczynski, Skinner, Winn, Delizio, Yoshigahara and Konrardy references presented in the rejection of Claim 1, apply to Claim 22 and are incorporated herein by reference. Thus, the method recited in Claim 22 is met by Terczynski in view of Skinner further in view of Winn, Delizio, Yoshigahara and Konrardy.
Conclusion
THIS ACTION IS MADE FINAL. 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.
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/Emma Rose Goebel/Examiner, Art Unit 2662
/AMANDEEP SAINI/Supervisory Patent Examiner, Art Unit 2662
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