DETAILED ACTION
This Non-Final Office Action is in response to the originally filed specification and claim amendments [November 20, 2024].
Claims 1-16 are currently pending and have been considered below.
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 .
Priority
Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55. Examiner notes that additional PCT documentation was provided and received for PCT/EP2024/074491 [September 29, 2023]. It is unclear if this documentation was provided to establish further priority to the PCT application. The current receipt and acknowledged priority is for PCT/EP2023/062299 [May 30, 2022].
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:
a data store that stores a digital model of the equipment at each step of a stepwise installation process in claim 1.
a logic unit that executes a comparator to compare a representation of the equipment indicating a configuration of the equipment with the digital model of the equipment at a current step in the stepwise installation process to generate a degree of conformity of the equipment at the current step in claim 1.
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 § 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 1-16 are rejected under 35 U.S.C. 101 because the claimed invention is directed towards non-eligible subject matter.
In terms of step 1, claims 1-16 are directed towards one of the four categories of statutory subject matter.
In terms of step 2(a)(1), independent claims 1, 7, 8, and 16 are directed towards (as represented by claim 8), “A method to automatically verify a correctness of each of a sequence of installation steps for the installation of an item of equipment, the method comprising: accessing a digital model of the equipment at each step of a stepwise installation process; receiving a representation of the equipment indicating a configuration of the equipment; comparing the received representation with the model to determine a degree of conformity of the equipment with the model of the equipment at a current step in the stepwise installation process; and communicating the degree of conformity to an operative”. The claims are describing a set of rules based on digital models of equipment to provide conformity for installation. This is providing rules/instructions for installing equipment correctly that falls into the abstract idea grouping of certain method of organizing human activity.
The claims further recite aspects of collecting, analyzing, and displaying information that can be practically performed in the human mind. Installation guides through an instruction manual can provide instruction in terms of installation conformity that a person could opine and judge. The claims are merely providing these aspects in a technical environment through a digital model, but a person could read instructions to repair/install and follow the instructions to determine conformity with respect to the installation guide. As such, the claims also fall into the abstract idea grouping of mental process.
Step 2(a)(II) considers the additional elements of the claims in terms of being transformative into a practical application. The additional elements of the independent claims are, “the system comprising: a data store; a logic unit; and a communications interface {claim 1}; at least one sensor generating data including a representation of the equipment indicating a configuration of the equipment at a current step in a stepwise installation process {claim 7}; A computer program element comprising computer program code to, when loaded into a computer system and executed thereon, cause the computer to perform the steps of a method as claimed in claim 8 {claim 16}; accessing a digital model”. The additional elements are described in the originally filed specification pgs. 11, 17-19, and figures 4 and 7. The additional elements are merely described in terms of generic technology to implement the abstract idea. The additional elements are not technical improvements and are merely tools to implement the identified abstract idea. As such, the additional elements are not transformative into a practical application. Refer to MPEP 2106.05(f).
Step 2(b) considers the additional elements of the claims in terms of being significantly more than the identified abstract idea(s). The additional elements of the independent claims are, “the system comprising: a data store; a logic unit; and a communications interface {claim 1}; A computer program element comprising computer program code to, when loaded into a computer system and executed thereon, cause the computer to perform the steps of a method as claimed in claim 8 {claim 16}; accessing a digital model”. The additional elements are described in the originally filed specification pgs. 11, 17-19, and figures 4 and 7. The additional elements are merely described in terms of generic technology to implement the abstract idea. The additional elements are not technical improvements and are merely tools to implement the identified abstract idea. As such, the additional elements are not significantly more than the identified abstract idea(s). Refer to MPEP 2106.05(f).
Dependent claims 2, 3, 5, and 6 further describe the identified abstract idea(s) and are not directed towards additional elements beyond those identified above. The claims are directed towards, “wherein the comparator further determines the current step of the stepwise installation process for the equipment”, “wherein the comparator compares the representation of the equipment with the digital model at the current step by segmenting the representation of the equipment into a plurality of partial representations, each partial representation corresponding to a part of the equipment, and comparing each partial representation with a corresponding part of the model to identify one or more parts of the equipment for which a degree of conformity of the part is below a threshold degree of conformity”, “wherein the communications interface further communicates an indication of a correct configuration of the equipment at the current step based on the model”, and “wherein the communications interface further communicates an indication of one or more parts of the equipment for which a degree of conformity is below a threshold degree”. The claims are further describing aspects of both the mental process and certain method of organizing human activity abstract ideas. The mental process is with respect to further describing the comparison using a threshold analysis (a high level of analysis), displaying the results of the analysis (communicating an indication), and providing the current step of the instruction. In terms of the certain method of organizing human activity abstract idea, the claims are describing the aspects in terms of comparison to a rule/analysis of conformity, providing the result of the conformity, and providing the step of the installation process. These aspects further describe the identified abstract idea without additional elements beyond those considered above. As such the claims are not transformative into a practical application or significantly more than the identified abstract idea.
Dependent claim 4 is further describing additional elements beyond those considered above. Claim 4 is directed towards, “wherein the model is a machine learning model trained to determine a degree of conformity of a representation of the equipment”. The claim is describing the additional element of a machine learning model to determine conformity. The machine learning model is described in the originally filed specification pgs. 6-7 and 11. The machine learning is merely describing generic technology to implement the abstract idea. This is further supported by the specification describing a mere list of techniques, “a decision tree classifier; a naïve Bayes classifier; a K-nearest neighbour classifier; a support vector machine; and an artificial neural network” (pgs. 6-7). Providing a list of techniques is utilizing generic technology to implement the abstract idea. The machine learning is not directed towards a technical improvement, but rather as a tool to implement the abstract idea. The claim is not directed towards additional elements that are transformative into a practical application or significantly more than the identified abstract idea. Refer to MPEP 2106.05(f).
Dependent claims 9, 10, 12, 13 are further describing the abstract idea and is not directed towards additional elements beyond those identified above. The claims are directed towards, “wherein comparing the received representation with the model further includes determining the current step of the stepwise installation process for the equipment”, “segmenting the received representation into a plurality of partial representations, each partial representation corresponding to a part of the equipment; and comparing each partial representation with a corresponding part of the model to identify one or more parts of the equipment for which a degree of conformity of the part is below a threshold degree of conformity”, “responsive to a determination that the degree of conformity of the equipment is below a threshold degree of conformity, generating an indication of a correct configuration of the equipment at the current step; and communicating the correct configuration of the equipment at the current step to the operative”, and “responsive to a determination that the degree of conformity of one or more parts of the equipment is below a threshold degree of conformity, generating an indication of a correct configuration of the one or more parts of the equipment at the current step; and communicating the correct configuration of the equipment at the current step to the operative”. The claims are further describing the aspects of collecting, analyzing, and displaying the conformity information for the equipment installation. The claims provide high level analysis in terms of threshold analysis and providing an indication based on the threshold analysis to the user. This falls within the mental process abstract idea as a person, based on observation and judgement, could determine a level of conformity to correctly install the equipment. In terms of the certain method of organizing human activity, the claims are describing the rules and interaction in terms of determining the conformity based on a threshold analysis and providing an indication. The claims further describe comparison aspects based on the representation for the installation process that further falls into the certain method of organizing human activity grouping. The claims are further describing the identified abstract idea(s). The claims are not directed towards additional elements beyond those identified above.
Dependent claim 11 is further describing additional elements beyond those considered above. Claim 11 is directed towards, “where the model is a machine learning model trained to determine a degree of conformity of a representation of the equipment”. The claim is describing the additional element of a machine learning model to determine conformity. The machine learning model is described in the originally filed specification pgs. 6-7 and 11. The machine learning is merely describing generic technology to implement the abstract idea. This is further supported by the specification describing a mere list of techniques, “a decision tree classifier; a naïve Bayes classifier; a K-nearest neighbour classifier; a support vector machine; and an artificial neural network” (pgs. 6-7). Providing a list of techniques is utilizing generic technology to implement the abstract idea. The machine learning is not directed towards a technical improvement, but rather as a tool to implement the abstract idea. The claim is not directed towards additional elements that are transformative into a practical application or significantly more than the identified abstract idea. Refer to MPEP 2106.05(f).
Dependent claims 14 and 15 are further directed towards additional elements beyond those identified above. The claims are directed towards, “wherein the representation of the equipment is received from one or more sensors” and “wherein the one or more sensors includes one or more of: an optical sensor; and a sound sensor”. The additional elements are the sensor information (specific towards optical and sound sensor) to receive the representation of the equipment. The sensors are described in the originally filed specification pgs. 10-11. The specification describes the additional elements as tools to implement the abstract idea. The sensors are merely tools listed to receive information for the identified abstract idea. The claims are not directed towards additional elements that are significantly more or transformative into a practical application. Refer to MPEP 2106.05(f).
The claimed invention is describing an abstract idea without additional elements that are significantly more or transformative into a practical application. Therefore, claims 1-16 are rejected under 35 USC 101 for being directed towards non-eligible subject matter.
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.
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.
Claim(s) 1-16 are rejected under 35 U.S.C. 103 as being unpatentable over Tyson, II [11,132,479], hereafter Tyson, in view of Rajagopal et al [2023/0350704], hereafter Rajagopal.
Regarding claim 1, Tyson discloses an automated equipment installation verification system to automatically verify correctness of each of a sequence of installation steps for the installation of an item of equipment, the system comprising: a data store that stores a digital model of the equipment at each step of a stepwise installation process (Fig 2, 6, and C13:6 to C14:8; Tyson discloses a CAD/RVAT file and assembly component that provides a digital representation of the operation/item. The data store is interpreted through the component library and storage aspect that provides the monitoring and identification.);
a logic unit that executes a comparator to compare a representation of the equipment indicating a configuration of the equipment with the digital model of the equipment to generate a degree of conformity of the equipment at the current step (Figs 2, 6, and C14:30 to C15:53; Tyson discloses comparing the installation and position for adjusted locations to provide proper installation and orientation in real-time for assembly.);
and a communications interface that communicates the degree of conformity to an operative (C16:32-63; Tyson discloses providing guidance and other presentation elements for the assembly components. This is further shown within an AR display system discussed in C20:12-59.).
Tyson discloses the above-enclosed limitations, however, Tyson does not specifically state stepwise instruction.
Rajagopal teaches at a current step in the stepwise installation process (Paragraphs [18-19 56-60] Rajagopal teaches a similar image analysis system for installation conformity that specifically provides stepwise instruction based on the image analysis and metadata including the digital representation of the equipment being installed. Within the combination, Tyson provides elements of instruction steps for equipment installation and Rajagopal teaches the specific stepwise instructions for similar equipment installation using image analysis.).
Tyson discloses equipment installation guidance using image analysis, however, Tyson does not specifically teach stepwise (sequential) elements of the installation guidance.
Rajagopal teaches a similar installation system that specifically provides sequence steps for the equipment installation. Rajagopal shows that the use of stepwise installation guidance was known in the prior art at the time of the invention.
Since each individual element and its function are shown in the prior art, albeit it shown in separate references, the difference between the claimed subject matter and the prior art rests not on any individual element or function but in the very combination itself—that is in the substitution for installation guidance of Tyson for the specific sequence step installation guidance of Rajagopal. Therefore, the simple substitution of one known element for another producing a predictable result renders the claim obvious.
Regarding claim 2, the combination teaches the above-enclosed limitations of the system of claim 1;
Rajagopal further teaches wherein the comparator further determines the current step of the stepwise installation process for the equipment (Paragraphs [56-62]; Rajagopal teaches that the image analysis includes step elements to perform error detection at each step based on image analysis in the process and further provides guidance for next steps based on the current step being completed correctly.).
Tyson discloses equipment installation guidance using image analysis, however, Tyson does not specifically teach stepwise (sequential) elements of the installation guidance.
Rajagopal teaches a similar installation system that specifically provides sequence steps for the equipment installation. Rajagopal shows that the use of stepwise installation guidance was known in the prior art at the time of the invention.
Since each individual element and its function are shown in the prior art, albeit it shown in separate references, the difference between the claimed subject matter and the prior art rests not on any individual element or function but in the very combination itself—that is in the substitution for installation guidance of Tyson for the specific sequence step installation guidance of Rajagopal. Therefore, the simple substitution of one known element for another producing a predictable result renders the claim obvious.
Regarding claim 3, the combination teaches the above-enclosed limitations of the system of claim 1
Tyson discloses wherein the comparator compares the representation of the equipment with the digital model at the current step by segmenting the representation of the equipment into a plurality of partial representations, each partial representation corresponding to a part of the equipment, and comparing each partial representation with a corresponding part of the model to identify one or more parts of the equipment for which a degree of conformity of the part is below a threshold degree of conformity (Fig 3, 4, and C15:9-54; Tyson discloses that the system provides partial representation in terms of each element of the installation is digitally represented for the specific installation and the partial component is provided guidance for correct installation.).
Regarding claim 4, the combination teaches the above-enclosed limitations of the system of claim 1
Rajagopal further teaches wherein the model is a machine learning model trained to determine a degree of conformity of a representation of the equipment (Paragraphs [56-62]; Rajagopal teaches that the image analysis includes machine learning/AI techniques to provide image analysis for the correctness of the installation.).
The combination teaches equipment installation guidance using image analysis, however, the combination does not specifically teach machine learning determinations.
Rajagopal teaches a similar installation system that specifically provides machine learning for image analysis installation guidance. Rajagopal shows that the use of machine learning with respect to installation guidance was known in the prior art at the time of the invention.
Since each individual element and its function are shown in the prior art, albeit it shown in separate references, the difference between the claimed subject matter and the prior art rests not on any individual element or function but in the very combination itself—that is in the substitution for installation guidance conformity and correctness of the combination for the specific machine learning installation guidance of Rajagopal. Therefore, the simple substitution of one known element for another producing a predictable result renders the claim obvious.
Regarding claim 5, the combination teaches the above-enclosed limitations of the system of claim 1
Tyson further discloses wherein the communications interface further communicates an indication of a correct configuration of the equipment at the current step based on the model (Fig 3, 4, and C8-54; Tyson discloses that the display provides guidance for real-time installation adjustments for the specific component being installed.).
Regarding claim 6, the combination teaches the above-enclosed limitations of the system of claim 3;
Tyson further discloses wherein the communications interface further communicates an indication of one or more parts of the equipment for which a degree of conformity is below a threshold degree (Fig 3, 4, 5, and C8-54; Tyson discloses that the display provides guidance for real-time installation adjustments for the specific component being installed. Further, Tyson provides degrees of tolerance [C4:8-18 and C8:25-41] that falls within threshold analysis. Within the combination, Rajagopal teaches [61-63] error detection and providing modifications and notifications based on the analyzed image analysis for the installed equipment.).
Regarding claim 7, Tyson discloses an automated equipment installation verification system to automatically verify correctness of each of a sequence of installation steps for the installation of an item of equipment, the system comprising: at least one sensor generating data including a representation of the equipment indicating a configuration of the equipment at a current step in a stepwise installation process (Fig 2, 6, and C13:6 to C14:8; Tyson discloses a CAD/RVAT file and assembly component that provides a digital representation of the operation/item. The sensor is interpreted through the camera provided to capture images of the work area to configure component imaging.);
a communications interface that communicates the representation of the equipment at the current step and receives a degree of conformity of the equipment at the current step based on a comparison of the representation of the equipment indicating a configuration of the equipment with a digital model of the equipment at a current step (Figs 2, 6, and C14:30 to C15:53; Tyson discloses comparing the installation and position for adjusted locations to provide proper installation and orientation in real-time for assembly. Further, Tyson provides degrees of tolerance [C4:8-18 and C8:25-41] that falls within degrees of conformity.);
an output device that outputs information to an operative indicating the degree of conformity (C16:32-63; Tyson discloses providing guidance and other presentation elements for the assembly components. This is further shown within an AR display system discussed in C20:12-59. Further, Tyson provides degrees of tolerance [C4:8-18 and C8:25-41] that falls within degrees of conformity output to the user.).
Tyson discloses the above-enclosed limitations, however, Tyson does not specifically state stepwise instruction.
Rajagopal teaches at a current step in a stepwise installation process (Paragraphs [18-19 56-60] Rajagopal teaches a similar image analysis system for installation conformity that specifically provides stepwise instruction based on the image analysis and metadata including the digital representation of the equipment being installed. Within the combination, Tyson provides elements of instruction steps for equipment installation and Rajagopal teaches the specific stepwise instructions for similar equipment installation using image analysis.).
Tyson discloses equipment installation guidance using image analysis, however, Tyson does not specifically teach stepwise (sequential) elements of the installation guidance.
Rajagopal teaches a similar installation system that specifically provides sequence steps for the equipment installation. Rajagopal shows that the use of stepwise installation guidance was known in the prior art at the time of the invention.
Since each individual element and its function are shown in the prior art, albeit it shown in separate references, the difference between the claimed subject matter and the prior art rests not on any individual element or function but in the very combination itself—that is in the substitution for installation guidance of Tyson for the specific sequence step installation guidance of Rajagopal. Therefore, the simple substitution of one known element for another producing a predictable result renders the claim obvious.
Regarding claim 8, Tyson discloses a method to automatically verify a correctness of each of a sequence of installation steps for the installation of an item of equipment, the method comprising: accessing a digital model of the equipment at each step of a stepwise installation process; receiving a representation of the equipment indicating a configuration of the equipment (Fig 2, 6, and C13:6 to C14:8; Tyson discloses a CAD/RVAT file and assembly component that provides a digital representation of the operation/item.);
comparing the received representation with the model to determine a degree of conformity of the equipment with the model of the equipment at a current step in the stepwise installation process (Figs 2, 6, and C14:30 to C15:53; Tyson discloses comparing the installation and position for adjusted locations to provide proper installation and orientation in real-time for assembly. Further, Tyson provides degrees of tolerance [C4:8-18 and C8:25-41] that falls within degrees of conformity.); and
communicating the degree of conformity to an operative (C16:32-63; Tyson discloses providing guidance and other presentation elements for the assembly components. This is further shown within an AR display system discussed in C20:12-59.).
Tyson discloses the above-enclosed limitations, however, Tyson does not specifically state stepwise instruction.
Rajagopal teaches at a current step in the stepwise installation process (Paragraphs [18-19 56-60] Rajagopal teaches a similar image analysis system for installation conformity that specifically provides stepwise instruction based on the image analysis and metadata including the digital representation of the equipment being installed. Within the combination, Tyson provides elements of instruction steps for equipment installation and Rajagopal teaches the specific stepwise instructions for similar equipment installation using image analysis.).
Tyson discloses equipment installation guidance using image analysis, however, Tyson does not specifically teach stepwise (sequential) elements of the installation guidance.
Rajagopal teaches a similar installation system that specifically provides sequence steps for the equipment installation. Rajagopal shows that the use of stepwise installation guidance was known in the prior art at the time of the invention.
Since each individual element and its function are shown in the prior art, albeit it shown in separate references, the difference between the claimed subject matter and the prior art rests not on any individual element or function but in the very combination itself—that is in the substitution for installation guidance of Tyson for the specific sequence step installation guidance of Rajagopal. Therefore, the simple substitution of one known element for another producing a predictable result renders the claim obvious.
Regarding claim 9, the combination teaches the above-enclosed limitations of the method of claim 8
Rajagopal further teaches wherein comparing the received representation with the model further includes determining the current step of the stepwise installation process for the equipment (Paragraphs [56-62]; Rajagopal teaches that the image analysis includes step elements to perform error detection at each step based on image analysis in the process and further provides guidance for next steps based on the current step being completed correctly.).
Tyson discloses equipment installation guidance using image analysis, however, Tyson does not specifically teach stepwise (sequential) elements of the installation guidance.
Rajagopal teaches a similar installation system that specifically provides sequence steps for the equipment installation. Rajagopal shows that the use of stepwise installation guidance was known in the prior art at the time of the invention.
Since each individual element and its function are shown in the prior art, albeit it shown in separate references, the difference between the claimed subject matter and the prior art rests not on any individual element or function but in the very combination itself—that is in the substitution for installation guidance of Tyson for the specific sequence step installation guidance of Rajagopal. Therefore, the simple substitution of one known element for another producing a predictable result renders the claim obvious.
Regarding claim 10, the combination teaches the above-enclosed limitations of the method of claim 8
Tyson further discloses further comprising: segmenting the received representation into a plurality of partial representations, each partial representation corresponding to a part of the equipment; and comparing each partial representation with a corresponding part of the model to identify one or more parts of the equipment for which a degree of conformity of the part is below a threshold degree of conformity (Fig 3, 4, and C15:9-54; Tyson discloses that the system provides partial representation in terms of each element of the installation is digitally represented for the specific installation and the partial component is provided guidance for correct installation. Further, Tyson provides degrees of tolerance [C4:8-18 and C8:25-41] that falls within threshold analysis.).
Regarding claim 11, the combination teaches the above-enclosed limitations of the method of claim 8
Rajagopal teaches where the model is a machine learning model trained to determine a degree of conformity of a representation of the equipment (Paragraphs [56-62]; Rajagopal teaches that the image analysis includes machine learning/AI techniques to provide image analysis for the correctness of the installation.).
The combination teaches equipment installation guidance using image analysis, however, the combination does not specifically teach machine learning determinations.
Rajagopal teaches a similar installation system that specifically provides machine learning for image analysis installation guidance. Rajagopal shows that the use of machine learning with respect to installation guidance was known in the prior art at the time of the invention.
Since each individual element and its function are shown in the prior art, albeit it shown in separate references, the difference between the claimed subject matter and the prior art rests not on any individual element or function but in the very combination itself—that is in the substitution for installation guidance conformity and correctness of the combination for the specific machine learning installation guidance of Rajagopal. Therefore, the simple substitution of one known element for another producing a predictable result renders the claim obvious.
Regarding claim 12, the combination teaches the above-enclosed limitations of the method of claim 8
Tyson discloses further comprising: responsive to a determination that the degree of conformity of the equipment is below a threshold degree of conformity, generating an indication of a correct configuration of the equipment at the current step; and communicating the correct configuration of the equipment at the current step to the operative (Fig 3, 4, 5, and C8-54; Tyson discloses that the display provides guidance for real-time installation adjustments for the specific component being installed. Further, Tyson provides degrees of tolerance [C4:8-18 and C8:25-41] that falls within threshold analysis. Within the combination, Rajagopal teaches [61-63] error detection and providing modifications and notifications based on the analyzed image analysis for the installed equipment.).
Regarding claim 13, the combination teaches the above-enclosed limitations of the method of claim 10
Tyson further discloses further comprising: responsive to a determination that the degree of conformity of one or more parts of the equipment is below a threshold degree of conformity, generating an indication of a correct configuration of the one or more parts of the equipment at the current step; and communicating the correct configuration of the equipment at the current step to the operative (Fig 3, 4, 5, and C8-54; Tyson discloses that the display provides guidance for real-time installation adjustments for the specific component being installed. Further, Tyson provides degrees of tolerance [C4:8-18 and C8:25-41] that falls within threshold analysis. Within the combination, Rajagopal teaches [61-63] error detection and providing modifications and notifications based on the analyzed image analysis for the installed equipment.).
Regarding claim 14, the combination teaches the above-enclosed limitations of the method of claim 8
Tyson further discloses wherein the representation of the equipment is received from one or more sensors (Fig 2, 6, and C13:6 to C14:8; Tyson discloses a CAD/RVAT file and assembly component that provides a digital representation of the operation/item. The sensor is interpreted through the camera provided to capture images of the work area to configure component imaging.).
Regarding claim 15, the combination teaches the above-enclosed limitations of the method of claim 14
Tyson further discloses wherein the one or more sensors includes one or more of: an optical sensor; and a sound sensor (Fig 2, 6, and C13:6 to C14:8; Tyson discloses a CAD/RVAT file and assembly component that provides a digital representation of the operation/item. The sensor is interpreted through the camera provided to capture images of the work area to configure component imaging.).
Regarding claim 16, the combination teaches the above-enclosed limitations;
Tyson further discloses a computer program element comprising computer program code to, when loaded into a computer system and executed thereon, cause the computer to perform the steps of a method as claimed in claim 8 (C13:6-50; Tyson discloses the structural elements including processor, computer, and other aspects to provide the installation guidance system.).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Knipfer et al [2010/0125354] (part installation guidance including sequential ordering);
Priest et al [2018/0249343] (AR maintenance and installation guidance);
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/ANDREW CHASE LAKHANI/Primary Examiner, Art Unit 3629