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 .
Introduction
The following is a final Office Action in response to Applicant’s communications received on September 18, 2025. Claims 1, 3-5, 10-13, 15 and 19 have been amended.
Currently claims 1-20 are pending. Claims 1, 10 and 15 are independent.
Response to Amendments
Applicant’s amendments necessitated the new ground(s) of rejection in this Office Action.
Applicant’s amendments to the specification is acknowledged.
The 35 U.S.C. § 112(f) claim interpretation and § 112(b) rejection as set forth in the previous Office Action is withdrawn in response to Applicant’s amendments.
Applicant’s amendments to claims 1, 3-5, 10-13, 15 and 19 are NOT sufficient to overcome the 35 U.S.C. § 101 rejection as set forth in the previous Office Action. Therefore, the 35 U.S.C. § 101 rejection to claims 1-20 is maintained
Response to Arguments
Applicant’s arguments field on September 18, 2025 have been fully considered but they are not persuasive.
In the Remarks on page 12, Applicant’s arguments regarding the 35 U.S.C. § 101 rejection that 35 U.S.C. § 101 does not state that a process must be tied to a particular machine, but broadly states “whoever invents or discovers any new or useful process, machine…”. One skilled in the art would recognize that a chemical process such as the mixing of different substances within a test tube is not a process tied to a particular machine.
In response to Applicant’s arguments, the Examiner respectfully disagrees. One factor to consider when determining whether a claim recites a §101 patent eligible process is to be sure, a claim that transforms a particular article to another state or thing, or is tied to a particular machine to satisfy the machine-or-transformation test can be a “useful clue” to eligibility in the Alice/Mayo framework. See Ultramercial, Inc. v. Hulu, LLC, 772 F.3d 709, 716 (Fed. Cir. 2014)(quoting Bilski v. Kappos, 561 U.S. 593, 594 (2010)). Even though the test tube may not be consider as a “particular machine”, however, the chemical in the test tube may transform to another state or thing, which passed the M-T test.
With respect to the amended claim 15, the claim does not indicate any or what machine is performing the steps, for example, receiving, by what/who, project data, extracting, by what/who, a feature, applying, by what/who, the extracted feature to a machine learning model implemented by a machine learning based computing device, and so on.
In the Remarks on page 14, Applicant’s arguments regarding the 35 U.S.C. § 101 rejection that the claimed invention of claims 1-20 does not recite a mental process and so does not recite an abstract idea, since the human mind, even with pencil and paper, cannot practically predict a state or problem of a project from an extracted feature of the project, as can be performed by a machine learning model, as in the claimed invention.
In response to Applicant’s arguments, the Examiner respectfully disagrees. Making prediction with known information is a fundamental building block of human ingenuity. As such it is an abstract idea. Further, reciting “by a machine learning model” is merely adding the words “apply it” or using “a particular machine” with an abstract idea, or mere instructions to implement an abstract idea on a generic computer. The Supreme Court has repeatedly made clear that merely limiting the field of use of the abstract idea to a particular existing technological environment does not render the claims any less abstract. See Affinity Labs of Texas, LLC v. DirecTV, LLC, 838 F.3d 1253, 1258 (Fed. Cir. 2016). As to learning per se, such an argument overlooks the entire education system. Reciting machine learning is placing such learning in a computer context, offering no technological implementation details beyond the conceptual idea to use a machine for learning.
In the Remarks on page 16, Applicant’s arguments regarding the 35 U.S.C. § 101 rejection that claims 1-14 recite a system to analyze a predicted state and to initiate an action on the analyzed predicted state, which is a practical application of the functioning of the claimed system to predict problems with projects and to generate early alerts using artificial intelligence…; Therefore, claims 1-14 recite additional elements that integrate the judicial exception (abstract idea) into a practical application.
In response to Applicant’s arguments, the Examiner respectfully disagrees. In order for a claim to integrate the exception into a practical application, the additional claimed elements must, for example, improve the functioning of a computer or any other technology or technical field (see MPEP § 2106.05(a)), apply the judicial exception with a particular machine (see MPEP § 2106.05(b)), affect a transformation or reduction of a particular article to a different state or thing (see MPEP § 2106.05(c)), or apply or use the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment (see MPEP § 2106.05(e)). See Revised 2019 Guidance. Here, additional elements beyond the abstract idea are, for example, claim 1 recites the additional elements of “a hardware-based processor”, “a memory”, and “a plurality of computing devices” to execute the instructions provided to the hardware-based processor. When considered individually and as a combination, the memory, at best, may store the instructions and provide the instructions to the hardware-based processor, and the plurality of computing devices (including a first, a second, a third, a fourth) are recited to execute the instructions and perform the steps. Since the steps of: receive project data, extract a feature from the project data, apply extracted feature and predict a state of the project, analyze the predicted state of the project to confirm the predicted state, initiate an action (e.g., reporting the analyzed predicted state) [based] on the analyzed predicted state are directed abstract idea. None of the additional elements, when performing the steps can reflect an improvement to the functioning of a computer (i.e., hardware-based processor) itself or another technology or technical field (e.g., a network, machine learning model, or an AI). They do not improve the functioning of computers or other technology. They do not implement the abstract idea with a particular machine that is integral to the claims. They do not transform or reduce a particular article to a different state or thing. They do not apply the abstract idea in a meaningful way beyond linking its use to a particular technological environment. See Revised Guidance, 84 Fed. Reg. at 55. Therefore, the additional elements do not integrate the judicial exception into a practical application.
In the Remarks on page 17, Applicant’s arguments regarding the 35 U.S.C. § 101 rejection that claims 1-20 recite components and steps, which analyze a predicted state and initiate an action (e.g., reporting the analyzed predicted state), generate early alerts, or remediate the predicted problems, which is significantly more than the judicial exception (abstract idea)
In response to Applicant’s arguments, the Examiner respectfully disagrees. Step 2B is to determine whether the claims contain “an element or combination of elements that is ‘sufficient to ensure that the patent in practice amounts to significantly more than a patent upon the [ineligible concept] itself.’” See Alice, 573 U.S. at 217-18 (quoting Mayo, 132 S.Ct. at 1294). As described above, the additional elements are recited at a high level of generality and merely involved as tools to perform generic computer functions including receiving, storing, displaying manipulating and transmitting information over a network. However, generic computer components for performing generic computer functions have been recognized by the courts as merely well-understood, routine, and conventional functions of generic computers. See MPEP 2106.05 (d) (II) (Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); Storing and retrieving information in memory, Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F/3d 1306. 1334. 115 USPQ2d 1681, 1701 (Fed. Cir. 2015). Therefore, simply implementing the abstract idea on a generic computer for performing generic computer functions do not amount to significantly more than the abstract idea. (MPEP 2106.05(a)-(c), (e-f) & (h)).
In the Remarks on pages 17-19, Applicant argues that there is no disclosure, suggestion, hint, motivation, or indication in Cella that the system or methods of Cella are responsive to a confirmation are responsive to a confirmation of the predicted state by the artificial intelligence computing device, to initiate or perform an action on the analyzed predicted state including reporting the predicted state or remediating the predicted state of the project, respectively, as amended independent claims 1, 10 and 15. However, Applicant’s arguments are directed to the newly amended claims, and therefore, the newly amended claims will be fully addressed in this Office Action.
Claim Rejections – 35 USC § 112
The following is a quotation of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), first paragraph:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claims 1-20 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claims contain subject matters which were not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for pre-AIA the inventor(s), at the time the application was filed, had possession of the claimed invention. The subject matters which are not in the original specification is as follows:
Regarding claims 1, 10, 15 and 19, the claims recite “artificial intelligence based computing device”. The newly added limitations appear to constitute new matter. Applicant did not point out, nor was Examiner able to find, any support for these newly added limitations in the specification as originally filed. Applicant is required to cancel the new matter throughout the application in the reply to this Office Action.
Further, claims 1 and 10, the claims recite “a first computing device”, “a second computing device”, “a third computing device”. The newly added limitations appear to constitute new matter. Applicant did not point out, nor was Examiner able to find, any support for these newly added limitations in the specification as originally filed. Applicant is required to cancel the new matter throughout the application in the reply to this Office Action.
Further, claims 3-5 and 11-13, the claims recite “fourth computing device”. The newly added limitations appear to constitute new matter. Applicant did not point out, nor was Examiner able to find, any support for these newly added limitations in the specification as originally filed. Applicant is required to cancel the new matter throughout the application in the reply to this Office Action.
Further, claim 15, the claims recite “machine learning based computing device”. The newly added limitations appear to constitute new matter. Applicant did not point out, nor was Examiner able to find, any support for these newly added limitations in the specification as originally filed. Applicant is required to cancel the new matter throughout the application in the reply to this Office Action.
Claim Rejections – 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(B) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-14 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which applicant regards as the invention.
Regarding claims 1, 3, 4, 10, 11 and 12, the claims recite one or more of “a first computing device”, “a second computing device”, “a third computing device” and “a fourth computing device” render the claims indefinite because it is unclear how a system comprising a plurality computing device and each computing device performs an individual step without linking the data to each computing device. For example, how does the third computing device get the predicted state from the second computing device, and how does the second computing device get the extracted feature from the first computing device. Applicant is required to particularly point out and distinctly claim the subject matter which applicant regards as the invention. Examiner interpreted these different computing devices to “a/the computing device” for the purpose of examination.
Further, claims 5 and 13 recite “the fourth computing device” renders the claims indefinite because it is unclear whether “the fourth computing device” is referred to “a fourth computing device” in claims 3 and 11, respectively, or “the fourth computing device” is referred to “a fourth computing device”, in claims 4 and 12, respectively. Applicant is required to particularly point out and distinctly claim the subject matter which applicant regards as the invention.
The other dependent claims 2 and 6-9 are also rejected for the same reasons as each depends on the rejected claim.
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 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
As per Step 1 of the subject matter eligibility analysis, it is to determine whether the claim is directed to one of the four statutory categories of invention, i.e., process, machine, manufacture, or composition of matter.
In this case, claims 1-14 are directed to systems comprising a hardware-based processor and a memory, which fall within the statutory category of a machine. Claims 15-20 are directed to a method for predicting problems with projects without tied to a particular machine, which falls outside of the four statutory categories. However, claims 15-20 will be included in Step 2 Analysis for the purpose of compact prosecution.
With respect to claims 15-20, the claims are directed to non-statutory subject matter because the claims are directed to a method without tied to a particular machine in the body of the claims for performing the steps. One factor to consider when determining whether a claim recites a §101 patent eligible process is to determine if the claimed process (1) is tied to a particular machine or; (2) transforms a particular article to a different state or thing. See In re Bilski, 545 F.3d 943, 88 USPQ2d 1385 (Fed. Cir. 2008) (en banc) aff’d, Bilski v. Kappos, 561 U.S. ___, 130 S.Ct. 3218, 95 USPQ2d 1001 (U.S. 2010). (Machine-or-Transformation Test).
In Step 2A of the subject matter eligibility analysis, it is to “determine whether the claim at issue is directed to a judicial exception (i.e., an abstract idea, a law of nature, or a natural phenomenon). Under this step, a two-prong inquiry will be performed to determine if the claim recites a judicial exception (an abstract idea enumerated in the 2019 Guidance), then determine if the claim recites additional elements that integrate the exception into a practical application of the exception. See 2019 Revised Patent Subject Matter Eligibility Guidance (2019 Guidance), 84 Fed. Reg. 50, 54-55 (January 7, 2019).
In Prong One, it is to determine if the claim recites a judicial exception (an abstract idea enumerated in the 2019 Guidance, a law of nature, or a natural phenomenon).
Taking the method as representative, the claims recite the limitations of “receiving project data from a data source, extracting a feature from the project data, applying the extracted feature to a machine learning model, predicting a problem associated with the project using the machine learning model to generate a predicted state, analyzing the project from the predicted state using a project analysis module, preforming an action on the analyzed predicted state including reporting the predicted state or remediating the predicted state of the project, displaying a report having a visual color indication, classifies the analyzed predicted state with a color indication, and training the machine learning model using a predetermined training set”. None of the limitations recites technological implementation details for any of these steps, but instead recite only results desired by any and all possible means. The limitations, as drafted, are directed to processes, under their broadest reasonable interpretation, cover performance of the limitations in the mind but for the recitation of generic computer components. That is, other than reciting “a computer-based method”, nothing in the claim elements precludes the steps from practically being performed in the mind (including an observation, evaluation, judgment, opinion), or by a human using a pen and paper. For example, the claim encompasses a person can manually receiving project data, predicting a problem associated with the project, and analyzing the project from the predicted state, which fall within the “mental processes” grouping. Even through claim 1 recites “using a machine learning model” for predicting a problem, but this machine learning model merely provides a technological environment and/or field of use for implementing the abstract idea. “The Supreme Court has repeatedly made clear that merely limiting the field of use of the abstract idea to a particular existing technological environment does not render the claims any less abstract.” Affinity Labs of Texas, LLC v. DirecTV, LLC, 838 F.3d 1253, 1258 (Fed. Cir. 2016). As to learning per se, such an argument overlooks the entire education system. Reciting machine learning is placing such learning in a computer context, offering no technological implementation details beyond the conceptual idea to use a machine for learning. The mere nominal recitation of “a computer-based” does not take the claim out of the mental processes grouping. See Under the 2019 Guidance, 84 Fed. Reg. 52. Further, claims recite a concept similar to the claims as discussed in Electric Power Group (e.g., collecting information, analyzing it, and displaying certain result of the collection and analysis, see Electric Power Group, LLC v. Alstom, S.A., 830 F.3d 1350, 1351-52, 119 USPQ2d 1739, 1740 (Fed. Cir. 2016)). Accordingly, the claims recite an abstract idea, and the analysis is proceeding to Prong Two.
In Prong Two, it is to determine if the claim recites additional elements that integrate the exception into a practical application of the exception.
Beyond the abstract idea, claim 1 recites no additional element for performing the steps, when given the broadest reasonable interpretation, a machine is not required in the claim. Even if claim 1 recites the additional elements of “a hardware-based processor” as recited in claim 1 for performing the steps. The specification discloses these additional elements at a high level of generality and merely invoked as tools to perform the generic computer functions including receive data over a network. For example, the specification discloses “The processor 202 can be a hardware-based processor.” See ¶ 26. When given the broadest reasonable interpretation and in light of the Specification, these additional elements are no more than generic computer components. The additional elements are recited at a high level of generality and merely invoked as tools to perform generic computer functions including receiving, manipulating and transmitting data over a network. Thus, merely adding a generic computer, generic computer components, or programmed computer to perform generic computer functions does not automatically overcome an eligibility rejection. Alice Corp. Pty. Ltd. V. CLS Bank Int’l, 134 S. Ct. 2347, 2358-59, 110 USPQ2d 1976, 1983-84 (2014). Further, using a trained machine learning model is merely adding the words “apply it” or using “a particular machine” with an abstract idea, or mere instructions to implement the abstract idea on a computer. With this regard, the courts have held that a process defined simply as using a computer and memory to perform a series of mental steps that people can and regularly do perform in their heads. See CyberSource Corp. v. Retail Decisions, Inc., 654 F.3d 1366, 1373 (Fed. Cir. 2011); see also In re Grams, 888 F.2d 835, 840-41 (Fed. Cir. 1989); In re Meyer, 688 F.2d 789, 794-95 (C.C.P.A. 1982). However, simply implementing the abstract idea on a generic computer does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. Furthermore, nothing in the claims that reflects an improvement to the functioning of a computer itself or another technology, effects a transformation or reduction of a particular article to a different state or thing, or applies or uses the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than a drafting effect designed to monopolize the exception. Therefore, the additional elements do not integrate the judicial exception into a practical application. The claims are directed to an abstract idea, the analysis is proceeding to Step 2B.
In Step 2B of Alice, it is "a search for an ‘inventive concept’—i.e., an element or combination of elements that is ‘sufficient to ensure that the patent in practice amounts to significantly more than a patent upon the [ineligible concept’ itself.’” Id. (alternation in original) (quoting Mayo Collaborative Servs. v. Prometheus Labs., Inc., 132 S. Ct. 1289, 1294 (2012)).
The claims as described in Prong Two above, nothing in the claims that integrates the abstract idea into a practical application. The same analysis applies here in Step 2B.
Beyond the abstract idea, claim 1 recites no additional element for performing the steps, when given the broadest reasonable interpretation, a machine is not required in the claim. Even if claim 1 recites the additional elements of “a hardware-based processor” as recited in claim 1 for performing the steps. The specification discloses these additional elements at a high level of generality and merely invoked as tools to perform the generic computer functions including receive data over a network. For example, the specification discloses “The processor 202 can be a hardware-based processor.” See ¶ 26. When given the broadest reasonable interpretation and in light of the Specification, these additional elements are no more than generic computer components. The additional elements are recited at a high level of generality and merely invoked as tools to perform generic computer functions including receiving, manipulating and transmitting data over a network. Taking the claim elements separately and as an ordered combination, the additional elements, at best, may perform the generic computer functions including receiving, storing, displaying, and transmitting information over a network. However, generic computer for performing generic computer functions have been recognized by the courts as merely well-understood, routine, and conventional functions of generic computers. See MPEP 2106.05 (d) (II) (Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network); Storing and retrieving information in memory, Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F/3d 1306. 1334. 115 USPQ2d 1681, 1701 (Fed. Cir. 2015); Collecting information, analyzing it, and displaying certain results of the collection and analysis, Electric Power Group, LLC v. Alstom, S.A., 830 F.3d 1350, 1351-52, 119 USPQ2d 1739, 1740 (Fed. Cir. 2016); RecogniCorp, LLC v. Nintendo Co., 855 F.3d 1322, 1326-27, 122 USPQ2d 1377, 1379-80 (Fed. Cir. 2017) (claim reciting multiple abstract ideas, i.e., the manipulation of information through a series of mental steps and a mathematical calculation, was held directed to an abstract idea)). Thus, simply implementing the abstract idea on a generic computer for performing generic computer functions do not amount to significantly more than the abstract idea. (MPEP 2106.05(a)-(c), (e-f) & (h)).
For the foregoing reasons, claims 15-20 cover subject matter that is judicially-excepted from patent eligibility under § 101 as discussed above, the other claims 1-14 parallel claims 15-20—similarly cover claimed subject matter that is judicially excepted from patent eligibility under § 101.
Therefore, the claims as a whole, viewed individually and as a combination, do not provide meaningful limitations to transform the abstract idea into a patent eligible application of the abstract idea such that the claims amount to significantly more than the abstract idea itself. The claims are not patent eligible.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis 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 of this title, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1-20 are rejected under 35 U.S.C. 103 as being unpatentable over Cella et al., (US 2023/0419277, hereinafter: Cella), and in view of Werr et al., (US 11379416 B1, hereinafter: Werr).
Regarding claim 1, Cella discloses the project management system, comprising:
a hardware-based processor (see Fig. 139, # 13938; ¶ 4, ¶ 638);
a memory configured to store instructions and configured to provide the instructions to the hardware-based processor (see ¶ 638); and
a plurality of computing devices (see Fig. 138, # 13870-13890) to execute the instructions provided to the hardware-based processor (see ¶ 702), the plurality of computing devices including:
a first computing device to extract a feature from the project data (see Fig. 147, # 14706; ¶ 401, ¶ 405, ¶ 1264, ¶ 1366, ¶ 2316, ¶ 2593, ¶ 2710);
a second computing device to implement a machine learning model (see Fig. 223, # 2213), to apply the extracted feature to the machine learning model, and to predict a state of the project from the extracted feature processed by the machine learning model (see ¶ 40, ¶ 44, ¶ 68, ¶ 76, ¶ 120, 598-599, ¶ 2233, ¶ 2240, ¶ 3172); and
a third computing device, including an artificial intelligence based computing device (see Fig. 153), to analyze the predicted state of the project, to confirm the predicted state using the artificial intelligence based computing device processing at least the predicted state, and, responsive to a confirmation of the predicted state by the artificial intelligence based computing device, to initiate an action on the analyzed predicted state (see ¶ 441, ¶ 666, ¶ 1423, ¶ 1436, ¶ 2026, ¶ 2710),
wherein the action is a reporting of the analyzed predicted state or a remediation of the analyzed predicted state (see ¶ 566, ¶ 1218, ¶ 2210 ¶ 2367, ¶ 2436-2438, ¶ 32223-3225).
Cella provides an ERP system for integrating business processes including marketing, product management, accounting, procurement, distribution, and project management within a manufacturing node (see ¶ 2663); and receiving data related to amounts of stock of products of the retail environment (see ¶ 2791).
Cella does not explicitly disclose receiving project data; however, Werr in an analogous art for information processing discloses
a communication interface configured to receive project data corresponding to a project (see Abstract; and claim 1).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Cella to include teaching of Werr in order to gain the commonly understood benefit of such adaption, such as providing the benefit of a more optimal solution, in turn of more specific type of data processing. Since the combination of each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
Regarding claim 2, Cella discloses the project management system of claim 1, wherein the machine learning model is trained using a predetermined training set of data (see ¶ 659, ¶ 679-682, ¶ 1615, ¶ 2609, ¶ 2667, ¶ 2671).
Regarding claim 3, Cella discloses the project management system of claim 1, wherein the plurality of computing devices further comprises:
a fourth computing device to perform the remediation of the analyzed predicted state including remediating the project (see ¶ 1267, ¶ 1437, ¶ 1993).
Regarding claim 4, Cella discloses the project management system of claim 1, wherein the plurality of computing devices further comprises:
a fourth computing device to perform the reporting of the analyzed predicted state including generating and outputting a report of the predicted state of the project (see ¶ 566, ¶ 1218, ¶ 2210, ¶ 2367, ¶ 2436-2438, ¶ 32223-3225).
Regarding claim 5, Cella discloses the project management system of claim 4, wherein the fourth computing device includes an output device configured to output the report (see ¶ 402, ¶ 768, ¶ 862, ¶ 887, ¶ 2452).
Regarding claim 6, Cella discloses the project management system of claim 5, wherein the output device is a display configured to display the report (see ¶ 402, ¶ 770, ¶ 893, ¶ 919, ¶ 1042, ¶ 3338, ¶ 3345).
Regarding claim 7, Cella discloses the project management system of claim 6, wherein the displayed report includes a text message classifying the analyzed predicted state of the project (see ¶ 659, ¶ 2007, ¶ 2654, ¶ 2315, ¶ 3342-3345).
Regarding claim 8, Cella discloses the project management system of claim 6, wherein the displayed report includes a visual color indication using a predetermined color scheme, wherein the visual color indication classifies the analyzed predicted state of the project (see ¶ 803, ¶ 861-863, ¶ 897, ¶ 3447).
Regarding claim 9, Cella discloses the project management system of claim 8, wherein the predetermined color scheme includes a dark green color representing no issues with the project, a medium green color representing an earliest indication of a potential issue with the project, a light green color representing a potential delay of completion of the project, a yellow color representing the project being behind between 5 % and 10 % in a progress of the project, and a red color representing the project being greater than or equal to 10 % behind in the progress of the project (see ¶ 803, ¶ 896, ¶ 952, ¶ 1045, ¶ 1995, ¶ 2184, ¶ 2586).
In addition, claim 9 merely describing the color representing the project elements is directed to nonfunctional descriptive material because they cannot exhibit any functional interrelationship with the way the steps are performed. Therefore, it has been held that nonfunctional descriptive material will not distinguish the invention from prior art in term of patentability. (In re Gulack, 217 USPQ 401 (Fed. Cir. 1983), In re Ngai, 70 USPQ2d (Fed. Cir. 2004), In re Lowry, 32 USPQ2d 1031 (Fed. Cir. 1994); MPEP 2111.05).
Regarding claim 10, Cella discloses a system, comprising:
a data source providing project data corresponding to a project (see ¶ 6, ¶ 27, ¶ 31);
a network (see ¶ 34-35, ¶ 37, ¶ 52); and
a project management sub-system (see ¶ 2663), comprising:
a hardware-based processor (see Fig. 139, # 13938; ¶ 4, ¶ 638);
a memory configured to store instructions and configured to provide the instructions to the hardware-based processor (see ¶ 638); and
a plurality of computing devices (see Fig. 138, # 13870-13890) to execute the instructions provided to the hardware-based processor (see ¶ 702), the plurality of computing devices including:
a first computing device to extract a feature from the project data (see Fig. 147, # 14706; ¶ 401, ¶ 405, ¶ 1264, ¶ 1366, ¶ 2316, ¶ 2593, ¶ 2710);
a second computing device to implement a machine learning model trained using a predetermined training set, to apply the extracted feature to the trained machine learning model, and to predict a state of the project from the extracted feature processed by the trained machine learning model (see ¶ 40, ¶ 44, ¶ 68, ¶ 76, ¶ 120, ¶ 598-599, ¶ 2233, ¶ 2240, ¶ 3172); and
a third computing device, including an artificial intelligence based computing device (see Fig. 153), to analyze the predicted state of the project, to confirm the predicted state using the artificial intelligence based computing device processing at least the predicted state, and, responsive to a confirmation of the predicted state by the artificial intelligence based computing device, to initiate an action on the analyzed predicted state (see ¶ 441, ¶ 666, ¶ 1423, ¶ 1436, ¶ 2026, ¶ 2710),
wherein the action is a reporting of the analyzed predicted state or a remediation of the analyzed predicted state (see ¶ 566, ¶ 1218, ¶ 2210 ¶ 2367, ¶ 2436-2438, ¶ 32223-3225).
Cella provides an ERP system for integrating business processes including marketing, product management, accounting, procurement, distribution, and project management within a manufacturing node (see ¶ 2663); and receiving data related to amounts of stock of products of the retail environment (see ¶ 2791).
Cella does not explicitly disclose receiving project data; however, Werr in an analogous art for information processing discloses
a communication interface operatively connected to the data source through the network and configured to receive the project data from the data source (see Abstract; and claim 1).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Cella to include teaching of Werr in order to gain the commonly understood benefit of such adaption, such as providing the benefit of a more optimal solution, in turn of more specific type of data processing. Since the combination of each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
Regarding claim 11, Cella discloses the system of claim 10, wherein the plurality of computing devices further comprises:
A fourth computing device to perform the remediation of the predicted state including remediating the project (see ¶ 1267, ¶ 1437, ¶ 1993).
Regarding claim 12, Cella discloses the system of claim 10, wherein the plurality of computer devices further comprises:
a fourth computing device to perform the reporting of the predicted state including generating and outputting a report of the predicted state of the project (see ¶ 566, ¶ 1218, ¶ 2210, ¶ 2367, ¶ 2436-2438, ¶ 32223-3225).
Regarding claim 13, Cella discloses the system of claim 12, wherein the fourth computing device includes an output device configured to output the report classifying the predicted state of the project (see ¶ 402, ¶ 768, ¶ 862, ¶ 887, ¶ 2452).
Regarding claim 14, Cella discloses the system of claim 12, wherein the report visually classifies the predicted state with a color indication using a predetermined color scheme includes a dark green color representing no issues with the project, a medium green color representing an earliest indication of a potential issue with the project, a light green color representing a potential delay of completion of the project, a yellow color representing the project being behind between 5 % and 10 % in a progress of the project, and a red color representing the project being greater than or equal to 10 % behind in the progress of the project (see ¶ 803, ¶ 896, ¶ 952, ¶ 1045, ¶ 1995, ¶ 2184, ¶ 2586).
In addition, claim 9 merely describing the color representing the project elements is directed to nonfunctional descriptive material because they cannot exhibit any functional interrelationship with the way the steps are performed. Therefore, it has been held that nonfunctional descriptive material will not distinguish the invention from prior art in term of patentability. (In re Gulack, 217 USPQ 401 (Fed. Cir. 1983), In re Ngai, 70 USPQ2d (Fed. Cir. 2004), In re Lowry, 32 USPQ2d 1031 (Fed. Cir. 1994); MPEP 2111.05).
Regarding claim 15, Cella discloses the computer-based method, comprising:
extracting a feature from the project data (see ¶ 405, ¶ 1366, ¶ 2316, ¶ 2593, ¶ 2710);
applying the extracted feature to a machine learning model implemented by a machine learning based computing device (see ¶ 40-45, ¶ 68, ¶ 76, ¶ 120, ¶ 598-599, ¶ 2233, ¶ 2240, ¶ 3172);
predicting a problem associated with the project using the machine learning model implemented by the machine learning based computing device to process the applied extracted feature to generate a predicted state of the project (see ¶ 40, ¶ 44, ¶ 68, ¶ 76, ¶ 120, ¶ 598-599, ¶ 2233, ¶ 2240, ¶ 3172);
analyzing the project by processing at least the predicted state using an artificial intelligence based computing device (see ¶ 666, ¶ 2710);
confirming, using the artificial intelligence based computing device, the predicted state (see ¶ 441, ¶ 1436, ¶ 2618); and
responsive to a confirmation of the predicted state by the artificial intelligence computing device, performing an action on the analyzed predicted state including reporting the predicted state or remediating the predicted state of the project (see ¶ 441, ¶ 566, ¶ 1218, ¶ 2210 ¶ 2367, ¶ 2436-2438, ¶ 32223-3225).
Cella provides an ERP system for integrating business processes including marketing, product management, accounting, procurement, distribution, and project management within a manufacturing node (see ¶ 2663); and receiving data related to amounts of stock of products of the retail environment (see ¶ 2791).
Cella does not explicitly disclose receiving project data; however, Werr in an analogous art for information processing discloses
receiving project data from a data source corresponding to a project (see Abstract; and claim 1).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Cella to include teaching of Werr in order to gain the commonly understood benefit of such adaption, such as providing the benefit of a more optimal solution, in turn of more specific type of data processing. Since the combination of each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
Regarding claim 16, Cella discloses the method of claim 15, wherein reporting the analyzed predicted state includes displaying a report having a text message classifying the predicted state of the project (see ¶ 659, ¶ 2007, ¶ 2654, ¶ 2315, ¶ 3342-3345).
Regarding claim 17, Cella discloses the method of claim 15, wherein reporting the analyzed predicted state includes displaying a report having a visual color indication using a predetermined color scheme, wherein the visual color indication classifies the predicted state of the project (see ¶ 803, ¶ 861-863, ¶ 897, ¶ 3447).
Regarding claim 18, Cella discloses the method of claim 17, wherein the report visually classifies the analyzed predicted state with a color indication using a predetermined color scheme includes a dark green color representing no issues with the project, a medium green color representing an earliest indication of a potential issue with the project, a light green color representing a potential delay of completion of the project, a yellow color representing the project being behind between 5 % and 10 % in a progress of the project, and a red color representing the project being greater than or equal to 10 % behind in the progress of the project (see ¶ 803, ¶ 896, ¶ 952, ¶ 1045, ¶ 1995, ¶ 2184, ¶ 2586).
In addition, claim 18 merely describing the color representing the project elements is directed to nonfunctional descriptive material because they cannot exhibit any functional interrelationship with the way the steps are performed. Therefore, it has been held that nonfunctional descriptive material will not distinguish the invention from prior art in term of patentability. (In re Gulack, 217 USPQ 401 (Fed. Cir. 1983), In re Ngai, 70 USPQ2d (Fed. Cir. 2004), In re Lowry, 32 USPQ2d 1031 (Fed. Cir. 1994); MPEP 2111.05).
Regarding claim 19, Cella discloses the method of claim 15, wherein analyzing the project includes applying artificial intelligence to the predicted state using the artificial intelligence based computing device (see ¶ 40, ¶ 404-405, ¶ 473).
Regarding claim 20, Cella discloses the method of claim 15, further comprising:
training the machine learning model using a predetermined training set (see ¶ 659, ¶ 679-682, ¶ 1615, ¶ 2609, ¶ 2667, ¶ 2671).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Srivastava et al., (US 10042636) discloses a project management platform that provides one or more tools associated with managing portions of a project utilizing an artificial intelligence lay to process data related to the project.
Zhang et al., (WO 2022197294) discloses a method for project management and milestone management by executing feature extraction on the project data and the employee data to generate features using machine learning model.
Fischbach et al., (US 2007/0156484) discloses a method for project management includes receiving guideline data for a project, determining associated data utilized for each of the sub-projects and generating updated project data to repository and project status feedback data.
Fishman (US 2008/0082388) discloses a method for managing a project with multiple tasks and milestones by defining probabilities of key project events and assessing their performance risk.
Sanchez, (WO 2022/010792) discloses a method for data management includes collecting a plurality of personal data set and a plurality of sensor data associated with one or more sensing modules, generating and continually updating an operator profile.
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.
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/PAN G CHOY/Primary Examiner, Art Unit 3624