NON-FINAL REJECTION, FIRST DETAILED ACTION
Status of Prosecution
The present application, 18/511,659 filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
The application was filed on Nov. 16, 2023 in the Office
Claims 1-20 are pending and all are rejected. Claims 1, 8 and 15 are independent.
Status of the Claims
Claims 1-2, 4-5, 8-9, 12, 15 are rejected under 35 USC. § 103 as being unpatentable over non-patent literature, Bruttini et al., (“Bruttini”), “A Semantic Digital Twin Prototype for Workplace Performance Assessment,” published in 2023 in view of Barat et al. (“Barat”), United States Patent Application Publication 2023/0376877 published on Nov. 3, 2023 in view of Campbell et al. (“Campbell”), United States Patent Application Publication 2021/0234885 published on July 29, 2021.
Claims 3, 10-11 and 16-18 are rejected under 35 USC. § 103 as being unpatentable over Bruttini in view of Barat in view of Campbell and in further view of Ramanasankaran et al. (“Ramanasankaran”), United States Patent Application Publication 2023/0169223 published on June 1, 2023.
Claims 6-7 and 13-14 are rejected under 35 USC. § 103 as being unpatentable over Bruttini in view of Barat in view of Campbell and in further view of Silva et al. (“Silva”), United States Patent Application Publication 2023/0214544 published on July 6, 2023.
Claims 19-20 are rejected under 35 USC. § 103 as being unpatentable over Bruttini in view of Barat in view of Campbell in view of Ramanasankaran and in further view of Silva.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. § 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102 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.
A.
Claims 1-2, 4-5, 8-9, 12, 15 are rejected under 35 USC. § 103 as being unpatentable over non-patent literature, Bruttini et al., (“Bruttini”), “A Semantic Digital Twin Prototype for Workplace Performance Assessment,” published in 2023 in view of Barat et al. (“Barat”), United States Patent Application Publication 2023/0376877 published on Nov. 3, 2023 in view of Campbell et al. (“Campbell”), United States Patent Application Publication 2021/0234885 published on July 29, 2021.
As to Claim 1, Bruttini teaches: A computer-implemented method for assigning an activity to an optimal workplace (Bruttini: sec. 5.2, worker’s feedback is collected for different activities in a specified workspace along with productivity feedback; Sec. 5.3 all visible in a dashboard to understand trends) comprising the computer-implemented steps of:
measuring, for each workplace environment of a plurality of different workplace environments (Burttini: Fig. 3, feedback and sensor data are collected for each physical workspace);
using a digital twin of each workplace environment (Bruttini: Fig. 2, Sec. 4.3, the application layer allows the manager with digital twin-based services that can provide various use cases such as “workplace condition monitoring and visualization; building-activity-worker data correlation for workplace performance assessment, issue discovery and spatial recommendation”);
determining a set of critical success factors in order to perform the activity;
determining the optimal workplace for the activity; and
assigning the activity to the optimal workplace (Bruttini: Sec. 4.3, the manager is able to use the visual dashboard of the digital twin of the workspaces to determine what optimal conditions for the workspace for certain activities may be assigned).
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Bruttini may not explicitly teach: simulating a performance of the activity on each of the plurality of different workplace environments using a digital twin of each workplace environment based on the set of critical success factors of the activity;
determining the optimal workplace for the activity based on the simulating.
Barat teaches in general concepts related to techniques and apparatuses for ensuring business continuity by determining safe return to workplaces in the face of pandemic. (Barat: Abstract). Specifically, Barat teaches the use of digital twins of the office using different key performance indicators based on simulations for determining indication of infection of the employees (Barat: par. 0005). Several offices (i.e. workplaces) are modeled with accompanying modeling of stock and flow models of populations, infection rates, etc. (i.e. critical success factors) (Barat: Fig. 2, par. 0061, at step [204], the stock and flow model for each of the locations). Comparisons of the simulation runs allow for comparison of different strategies to select the correct strategy for the optimal workplace return based on the factors (Barat: pars. 0085-86, experimentation for different hypothetical scenarios and multiple runs to determine KPIs).
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It would have been obvious to a person having ordinary skill in the art at a time before the effective filing date of the invention to have modified the Bruttini device by including computer instructions to run simulations in the digital twin environment for each workplace based on the various factors as taught and disclosed by Barat. Such a person would have been motivated to do so with a reasonable expectation of success to decide appropriately what the various possibilities may be in an experimental way (Barat: par. 0085).
Bruttini and Barat may not explicitly teach: simulating a performance of the activity on each of the plurality of different workplace environments using a digital twin of each workplace environment based on a respective maturity level of a respective workplace environment and respective critical success factors and the set of critical success factors of the activity;
measuring, for each workplace environment of a plurality of different workplace environments, a plurality of different maturity levels, each maturity level of the plurality of different maturity levels corresponding to a critical success factor from a plurality of different critical success factors of the workplace environment;
determining a set of critical success factors and a required maturity necessary for each of the set of critical success factors in order to perform the activity;
Campbell teaches in general concepts related to identifying gaps in an organization’s cyber defenses and identifying and prioritizing remediations to eliminate those gaps, using a maturity model to score the risk (Campbell: Abstract). Specifically, Campbell teaches that a knowledge management system is used to assess the maturity of an organization (Campbell: par. 0022). The assessed maturity score is compared to a target score which is set to what comparable reasonable organizations would expect to mitigate its inherent risks (i.e. different maturity levels corresponding to a critical success factor). (Campbell: par. 0022).
It would have been obvious to a person having ordinary skill in the art at a time before the effective filing date of the invention to have modified the Bruttini-Barat device by including computer instructions to utilize the maturity framework to affect the evaluation and assessment of the workplaces as taught and disclosed by Campbell. Such a person would have been motivated to do so with a reasonable expectation of success to utilize industry norms as a standard in making such assessments (Campbell: par. 0022).
As to Claim 2, Bruttini, Barat and Campbell teach the limitations of claim 1.
Bruttini, Barat and Campbell further teaches: wherein the set of critical success factors include cyber security(Campbell: Abstract), safety (Bruttini: temperature, Barat: pandemic), recovery speed, skills, and health of machines .
As to Claim 4, Bruttini, Barat and Campbell teach the limitations of claim 1.
Campbell further teaches: wherein the measuring of the plurality of different maturity levels comprises applying, for each of the plurality of different critical success factors, a set of rules in a maturity model to measurable attributes corresponding to the critical success factor of the workplace environment to determine the respective maturity level (Campbell: pars. 0148-50, “The KMS maturity model has two components: selection maturity and implementation maturity-to manage a certain level of inherent risk, the KMS expects the organization to select certain controls or their equivalents (compensating controls) and implement them to a certain maturity level. Selection maturity in the KMS is characterized using [various fields], … Thus, the KMS establishes three goals for the maturity assessment based on the total inherent Risk Score calculated above.”).
As to Claim 5, Bruttini, Barat and Campbell teach the limitations of claim 1.
Campbell further teaches: wherein the required maturity for each critical success factor of the set of critical success factors includes an optimum maturity and a minimal required maturity (Campbell: par. 0144, there are risk scores (used to calculate the maturity level) that have minimal and significant).
As to Claim 8, it is rejected for similar reasons as claim 1. Barat further teaches processor, memory (Barat: pars. 0053-54).
As to Claim 9, it is rejected for similar reasons as claim 2.
As to Claim 12, it is rejected for similar reasons as claim 5.
As to Claim 15, it is rejected for similar reasons as claims 1 and 8.
B.
Claims 3, 10-11 and 16-18 are rejected under 35 USC. § 103 as being unpatentable over non-patent literature, Bruttini et al., (“Bruttini”), “A Semantic Digital Twin Prototype for Workplace Performance Assessment,” published in 2023 in view of Barat et al. (“Barat”), United States Patent Application Publication 2023/0376877 published on Nov. 3, 2023 in view of Campbell et al. (“Campbell”), United States Patent Application Publication 2021/0234885 published on July 29, 2021 and in further view of Ramanasankaran et al. (“Ramanasankaran”), United States Patent Application Publication 2023/0169223 published on June 1, 2023.
As to Claim 3, Bruttini, Barat and Campbell teach the limitations of claim 1.
Bruttini, Barat and Campbell may not explicitly teach: training a cognitive engine to identity critical success factors of activities in a workplace environment;
analyzing, using the cognitive engine, activities performed on the plurality of different workplace environments using historical learning over time; and
identifying, using the cognitive engine, what critical success factors are required for the activity and the required maturity for each of the critical success factors that is required for the activity.
Ramanaskaran teaches in general concepts related to having digital twins of buildings use artificial intelligence to generate a plurality of inference data point for future times related to the building’s interrelationship with the digital twin of the building (Ramananskaran: Abstract). Specifically, Ramananskaran teaches that historical data values are considered and put into an artificial intelligence model (i.e. cognitive engine) and multiple different scenarios are generated (Ramananskaran: pars. 0356-56, steps [5102-04]). An operating scenario is selected with the most favorable performance values, based on various performance values (Ramananskaran: par. 0358, “the building data platform 100 may analyze each operating scenario based on one or more performance values ( e.g., clean air score, occupancy number, reproductive number, etc.). Furthermore, the building data platform 100 analyzes each operating scenario of the building to determine an operating scenario with the most favorable performance values.”)
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It would have been obvious to a person having ordinary skill in the art at a time before the effective filing date of the invention to have modified the Bruttini-Barat-Campbell device by including computer instructions to utilize an artificial intelligence evaluator for the workplaces to select an optimum workplace based on various factors and historical data as taught and disclosed by Ramananskaran. Such a person would have been motivated to do so with a reasonable expectation of success to reduce the cognitive burden on a user to allow for machine learning models to perform the evaluation.
As to Claim 10, it is rejected for similar reasons as claim 3.
As to Claim 11, it is rejected for similar reasons as claim 4.
As to Claim 16, it is rejected for similar reasons as claims 2 and 3.
As to Claim 17, it is rejected for similar reasons as claims 4.
As to Claim 18, it is rejected for similar reasons as claims 5.
C.
Claims 6-7 and 13-14 are rejected under 35 USC. § 103 as being unpatentable over non-patent literature, Bruttini et al., (“Bruttini”), “A Semantic Digital Twin Prototype for Workplace Performance Assessment,” published in 2023 in view of Barat et al. (“Barat”), United States Patent Application Publication 2023/0376877 published on Nov. 3, 2023 in view of Campbell et al. (“Campbell”), United States Patent Application Publication 2021/0234885 published on July 29, 2021 and in further view of Silva et al. (“Silva”), United States Patent Application Publication 2023/0214544 published on July 6, 2023.
As to Claim 6, Bruttini, Barat and Campbell teach the limitations of claim 1.
Bruttini, Barat and Campbell may not explicitly teach: the determining of the optimal workplace for the activity further comprising: determining an optimal volume of activities to be processed by the optimal workplace based on the simulating; and
scheduling the activity together with a plurality of other activities at the optimal workplace over time based on the optimal volume of activities.
Silva teaches in general concepts related to allocating space in a building by using artificial intelligence algorithms to satisfy mandatory constraints and to optimize a satisfaction of preferences (Silva: Abstract). Specifically Silva teaches the using sets of data, an allocation of respective persons to responstive space withn a building and scheduling is performed to optimize the space and resources (Silva: par. 0082, Fig. 4, [S408, the AI reasoning module [302]).
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It would have been obvious to a person having ordinary skill in the art at a time before the effective filing date of the invention to have modified the Bruttini-Barat-Campbell device by including computer instructions to optimize the volume of activities and scheduling using the AI module as taught and suggested by Silva. Such a person would have been motivated to do so with a reasonable expectation of success to allow for the reduction of cognitive burden in dealing with scale and complexity of different constraints in such scheduling tasks (Silva: par. 0008).
As to Claim 7, Bruttini, Barat, Campbell and Silva teach the limitations of claim 6.
Bruttini, Barat, Campbell and Silva as combined further teaches: the determining of the optimal workplace for the activity further comprising:
determining a second optimal workplace for a second activity based on the simulating; assigning the second activity to the second optimal workplace;
determining a second optimal volume of activities to be processed by the second optimal workplace based on the simulating; and
scheduling the second activity together with a second plurality of other activities at the second optimal workplace over time based on the second optimal volume of activities, wherein the assigning of the activity and the second activity maximizes an aggregated effectiveness of the plurality of workplaces achieving the critical success factors associated over all scheduled activities (Examiner asserts that the combination as provided would allow for the additional activities and workplaces to be considered and to optimize over them).
As to Claim 13, it is rejected for similar reasons as claim 6.
As to Claim 14, it is rejected for similar reasons as claim 7.
D.
Claims 19-20 are rejected under 35 USC. § 103 as being unpatentable over non-patent literature, Bruttini et al., (“Bruttini”), “A Semantic Digital Twin Prototype for Workplace Performance Assessment,” published in 2023 in view of Barat et al. (“Barat”), United States Patent Application Publication 2023/0376877 published on Nov. 3, 2023 in view of Campbell et al. (“Campbell”), United States Patent Application Publication 2021/0234885 published on July 29, 2021 in view of Ramanasankaran et al. (“Ramanasankaran”), United States Patent Application Publication 2023/0169223 published on June 1, 2023 and in further view of Silva et al. (“Silva”), United States Patent Application Publication 2023/0214544 published on July 6, 2023.
As to Claim 19, it is rejected for similar reasons as claim 6.
As to Claim 20, it is rejected for similar reasons as claim 7.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JAMES T TSAI whose telephone number is (571)270-3916. The examiner can normally be reached M-F 8-5 Eastern.
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/JAMES T TSAI/ Primary Examiner, Art Unit 2147
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