Response to Arguments
Applicant’s arguments with respect to claim(s) 1, 3-14, and 16-28 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 3/11/2026 was filed after the mailing date of the Non-Final Rejection on 12/3/2025. The submission is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are: terminal device and sensing device in claims 1-26.
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.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
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.
Claims 1, 3-4, 10, 12-14, 16-17, and 23-26 are rejected under 35 U.S.C. 103 as being unpatentable over Hirai (US Patent Pub. # 2021/0037084) in view of Kobayashi (US Patent Pub. # 2018/0268307).
As to claim 1, Hirai teaches an information processing system (management system 100) including a terminal device (edge environments 102) that includes a sensing device (sensor 123) and performs analysis processing on data from the sensing device, and a server (management device 101) that performs data transmission (network 103) with the terminal device (123) via wireless communication( (regardless of wire/wireless), such as the Internet, a LAN (Local Area Network), a WAN (Wide Area Network), or the like), the information processing system (100) comprising:
a hardware processor (management device 101, the first communication unit 112, the calculation unit 113, and the blending unit 114) that controls an analysis operation (convolutional neural network (CNN) as an example of the DNN) setting that is a setting of the terminal device (102) for performing the analysis processing (convolutional neural network (CNN) as an example of the DNN) on the data from the sensing device (Para 37, 38, and 41),
wherein the hardware processor (101, 112, 113, and 114) controls the analysis operation setting (convolutional neural network (CNN) as an example of the DNN) in such a manner as to enable performing optimum analysis (relevant information which is determined based on the relevancy between existing environmental information E1 to En (see FIG. 2) of the respective edge terminals T1 to Tn−1 and the environmental information En of the edge terminal Tn) (Para 37 and 41).
Hirai does not teach the analysis processing by the terminal device is processing by a machine learning model of artificial intelligence, the control of the analysis operation setting by the hardware processor includes a change of the machine learning model, and the control of the analysis operation setting by the hardware processor further includes a change of a setting of the sensing device such the processing by the machine learning model of artificial intelligence performs optimum analysis. Kobayashi teaches the analysis processing (analysis-side control unit 210 and 710) by the terminal device (analysis device 200 and 700) is processing by a machine learning model (learning device 600) of artificial intelligence, the control of the analysis operation setting (hyperparameter set) by the hardware processor (200 and 700) includes a change of the machine learning model (600), and the control of the analysis operation setting (hyperparameter set) by the hardware processor (200 and 700) further includes a change of a setting of the sensing device (camera) such the processing by the machine learning model (600) of artificial intelligence performs optimum analysis (optimum parameter of a component of the analysis target) (Para 160, 160, 288, and 300). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have provided an analysis device and learning device as taught by Kobayashi to the management system of Hirai, to provide an analysis device includes: (i) an acquisition unit that acquires an evaluation value for evaluating an action taken by a user who has viewed an electronic page containing summary information of content, and (ii) a determiner that determines an improvement parameter preferable as a summary parameter to be used when the content is converted into the summary information, based on a summary parameter used in the conversion and the evaluation value acquired by the acquisition unit, by optimization of an unknown function (Para 4 of Kobayashi).
As to claim 3, Hirai teaches wherein the hardware processor (101, 112, 113, and 114) changes the analysis operation setting (122) according to an analysis result by the analysis processing (inference result) (Para 41).
As to claim 4, Hirai teaches wherein the terminal device is movable (robot, or a vehicle) (Para 32).
As to claim 10, Hirai teaches further comprising: a plurality (plurality) of the terminal devices(102) , wherein the hardware processor (101, 112, 113, and 114) controls the analysis operation setting (convolutional neural network (CNN) as an example of the DNN) for each of the terminal devices (102) (Para 30).
As to claim 12, Hirai teaches wherein the hardware processor (101, 112, 113, and 114) selects the terminal device (102) to be caused to execute the analysis processing (convolutional neural network (CNN) as an example of the DNN) from among the plurality of terminal devices (102) on a basis of the analysis result by the analysis processing (convolutional neural network (CNN) as an example of the DNN) (Para 30).
As to claim 13, Hirai teaches wherein the hardware processor (101, 112, 113, and 114) selects the terminal device (102) to be caused to execute the analysis processing (convolutional neural network (CNN) as an example of the DNN) according to a position (arrangement position) of each of the plurality of the terminal devices (102) (Para 35).
As to claim 14, this claim differs from claim 1 only in that the claim 1 is an information processing system claim whereas claim 14 is a non-transitory recording medium claim. Thus claim 14 is analyzed as previously discussed with respect to claim 1 above.
As to claims 16-17 and 23, 25, and 26, these claims differ from claims 3-4 and 10-13 only in that the claims 3-4 and 10-13 depend on claim 1 whereas claims 16-17 and 23, 25, and 26 depend on claim 14. Thus claims 16-17 and 23, 25, and 26 are analyzed as previously discussed with respect to claims 3-4 and 10-13 above.
As to claim 24, Hirai teaches wherein each of the plurality of the terminal devices (102) transmits data of the sensing device and/or an analysis result by the analysis processing to the server (103), the server (101) includes a storage that stores the data of the sensing device and/or the analysis result (model DB 110 and the environmental information DB 111 are realized, for example, by the storage device 802) by the analysis processing setting (convolutional neural network (CNN) as an example of the DNN) in association with the terminal device (102) that has transmitted the data and/or the analysis result, and the hardware processor (101, 112, 113, and 114) controls the analysis operation setting (convolutional neural network (CNN) as an example of the DNN) of each of the terminal devices (102) on a basis of the data of the sensing device (123) and/or the analysis result by the analysis processing stored in the storage (802) (Para 34, 35, and 57).
Claims 5-8 and 18-21 are rejected under 35 U.S.C. 103 as being unpatentable over Hirai (US Patent Pub. # 2021/0037084) in view of Kobayashi (US Patent Pub. # 2018/0268307) and further in view of Etou (US Patent Pub. # 2021/0120185).
As to claim 5, note the discussion above in regards to claims 1 and 4. Hirai in view of Kobayashi do not specifically teach wherein the hardware processor designates a destination of the terminal device according to an analysis result by the analysis processing. Etou teaches wherein the hardware processor (controller 100) designates a destination (delivery destination) of the terminal device (mobile robot 10) according to an analysis result by the analysis processing (image analysis) (Para 51, 68, and 69). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have provided a controller as taught by Etou to the management system of Hirai in view of Kobayashi, to achieve a mechanism for acquiring accurate information on an area to be monitored (Para 5 of Etou).
As to claim 6, Etou teaches wherein the hardware processor (100) changes the analysis operation setting (current state of the monitoring target or predict a future state of the monitoring target) according to a position of the terminal device (10) (Para 68 and 69).
As to claim 7, Etou teaches wherein the hardware processor (100) changes the analysis operation setting according to a distance from the terminal device (10) to a sensing target by the sensing device (global positioning system (GPS) receiver 104) (Para 53).
As to claim 8, Etou teaches wherein the sensing device (first camera 50a, a second camera 50b) is a camera (camera) that captures a moving image (video), and the hardware processor (100) changes the analysis operation setting (current state of the monitoring target or predict a future state of the monitoring target) according to a moving distance between frames of a target object shown in the moving image (current state of the monitoring target or predict a future state of the monitoring targe) (Para 29, 54, and 69).
As to claims 18-21, these claims differ from claims 5-8 only in that the claims 5-8 depend on claim 1 whereas claims 18-21 depend on claim 14. Thus claims 18-21 are analyzed as previously discussed with respect to claims 5-8 above.
Claims 9, 11, and 22 are rejected under 35 U.S.C. 103 as being unpatentable over Hirai (US Patent Pub. # (2021/0037084) in view of Kobayashi (US Patent Pub. # 2018/0268307) and further in view of Sarin (US Patent Pub. # 2017/0316418).
As to claim 9, note the discussion above in regards to claim 1. Hirai in view of Kobayashi do not specifically teach wherein, in the hardware processor, the control of the analysis operation setting by the hardware processor includes switching between operation and non-operation of the sensing device. Sarin teaches wherein, in the hardware processor (one or more processors 512), the control of the analysis operation setting (determine that communication device 110 is failing, will become inoperable, or is in danger of failing or becoming inoperable) by the hardware processor (512) includes switching between operation and non-operation (in-operable, or is susceptible to failure or non-operation) of the sensing device (communication device 110) (Para 28, 85, and 86). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have provided a processor as taught by Sarin to the management system of Hirai in view of Kobayashi, to provide the user a convenient and recoverable method from potentially losing valuable data (Para 2 of Sarin).
As to claim 11, Hirai teaches wherein each of the plurality of the terminal devices (102) transmits data of the sensing device and/or an analysis result by the analysis processing to the server (103), the server (101) includes a storage that stores the data of the sensing device and/or the analysis result (model DB 110 and the environmental information DB 111 are realized, for example, by the storage device 802) by the analysis processing setting (convolutional neural network (CNN) as an example of the DNN) in association with the terminal device (102) that has transmitted the data and/or the analysis result, and the hardware processor (101, 112, 113, and 114) controls the analysis operation setting (convolutional neural network (CNN) as an example of the DNN) of each of the terminal devices (102) on a basis of the data of the sensing device (123) and/or the analysis result by the analysis processing stored in the storage (802) (Para 34, 35, and 57).
As to claim 22, this claim differs from claim 9 only in that the claim 9 is an information processing system claim whereas claim 22 is a non-transitory recording medium claim. Thus claim 22 is analyzed as previously discussed with respect to claim 9 above.
Claims 27 and 28 are rejected under 35 U.S.C. 103 as being unpatentable over Hirai (US Patent Pub. # 2021/0037084) in view of Kobayashi (US Patent Pub. # 2018/0268307) and further in view of Hurwitz (US Patent Pub. # 2022/0053195).
As to claim 27, Hirai teaches wherein the sensing device (123) is a camera (camera) (Para 35). Kobayashi teaches captures a moving image (video data) or a still image (image data) (Para 79). Hirai in view of Kobayashi do not teach the setting of the sensing device (camera 208 and camera application 152) includes at least one of a resolution (resolution settings) of an image, a frame rate or a magnification of a zoom lens. Hurwitz teaches the setting of the sensing device (50) includes at least one of a resolution (resolution) of an image, a frame rate (different frame rates, e.g., 25 frames per second (fps), 30 fps, 50 fps, 60 fps, etc.) or a magnification (zoom in to the scene or zoom out) of a zoom lens (Para 30). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have provided a camera as taught by Hurwitz to the management system of Hirai in view of Kobayashi, to provide the user-specific machine-learning model a rating for the input image and mapping the rating to the compression setting, wherein the mapping is based on the baseline compression setting (Para 10 of Hurwitz).
As to claim 28, this claim differs from claim 27 only in that the claim 27 depends on claim 1 whereas claim 28 depends on claim 14. Thus claim 28 is analyzed as previously discussed with respect to claim 27 above.
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 CHRISTOPHER K PETERSON whose telephone number is (571)270-1704. The examiner can normally be reached Monday-Friday 7AM-4PM.
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/CHRISTOPHER K PETERSON/Primary Examiner, Art Unit 2637 11/28/2025
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