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 .
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, 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 set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1, 3, 6-13, 15, and 18-23 are rejected under 35 U.S.C. 103 as being unpatentable over Siebel et al. (US 2017/0006135) in view of O’Toole et al. (US 2021/0216928).
Regarding Claims 1, 13, and 20, Siebel discloses a system, comprising:
one or more processors ([0086],” processors and storage devices,” Siebel);
a memory ([0255], memory, Siebel); and
one or more programs stored in the memory, the one or more programs comprising instructions configured to (Fig. 2, Siebel):
receive a request to1 generate a dashboard visualization associated with a portfolio of assets, the request comprising:
an asset descriptor, the asset descriptor describing one or more assets in the portfolio of assets ([0578], “a user is interested in calculating the average annual electricity use for hundreds of thousands of meters, the enterprise Internet-of-Things application development platform 3002 is capable of rapidly responding by distributing the request across multiple servers,” wherein the “annual electricity use for hundreds of thousands of meters” is an example of the asset descriptor claimed; Siebel); and
in response to the request:
obtain, based on the asset descriptor, aggregated data associated with the portfolio of assets ([0579], wherein the “sophisticated analyses on real-time and near-real-time streams of data” corresponds to aggregated data claimed; Siebel);
determine asset relationship data for the one or more related assets ([0494], “Unusual flow patterns are correlated with equipment diagnostic and operational data, based on a library of analytics that codify business rules for loss detection,” Siebel);
determine contextual data for the portfolio of assets based on attributes for the aggregated data ([0580], wherein “data about the unexpected load change” corresponds to contextual data claimed; Siebel) and the asset relationship data, wherein the contextual data comprises one or more events associated with the one or more related assets ([0498], “analyze real and near real-time data from connected home devices, home characteristic data, and dynamic weather data to identify high-risk home assets,” wherein real and near real-time data are examples of events as claimed; Siebel);
determine, based on the contextual data, one or more relationships between a first portion of the aggregated data associated with an asset of the one or more asset, wherein the first portion of the aggregated data comprises of a first fault-priority data associated with a first asset from the portfolio of assets and a second portion of the aggregated data associated with the asset ([0498], “home maintenance providers will be able to manage residential HVAC maintenance across multiple customers, and use the prioritized ranking of highest-risk HVAC assets across homes to more efficiently allocate their customer maintenance budgets,” wherein highest-risk HVAC assets across homes are examples of a first fault-priority data associated with a first asset and a second fault-priority data associated with a second asset as claimed; wherein the prioritized ranking is an example of determining one or more relationships as claimed; [0591], “with respect to revenue protection, the results of analytics processing on batch data and stream data can be provided to the a machine learning model of the machine learning and predictions module 3217 to score where revenue theft might be occurring. The machine learning and predictions module 3217 can rank various cases of potential revenue theft for a user of the enterprise Internet-of-Things application development platform 3002, such as a utility, to investigate,” wherein ranking implies that there is a relationship determination of at least a first portion and a second portion of data; [0596], “with respect to the energy industry and the utilities sector in particular, the enterprise Internet-of-Things application development platform 3002 allows a utility administrator to group energy intensity, energy consumption, and energy demand together on a page for easier viewing. The UI services module 3224 may provide role-based access controls. Administrators can determine which parts of the application will be visible to certain types of users,” wherein grouping is a form of determining relationships as claimed; [0461], [0579], and [0587], Siebel), wherein the second portion of the aggregated data comprises of a second fault-priority data associated with a second asset from the portfolio of assets ([0498], “home maintenance providers will be able to manage residential HVAC maintenance across multiple customers, and use the prioritized ranking of highest-risk HVAC assets across homes to more efficiently allocate their customer maintenance budgets,” wherein highest-risk HVAC assets across homes are examples of a first fault-priority data associated with a first asset and a second fault-priority data associated with a second asset as claimed; Siebel);
indicate whether the one or more related assets are associated with a fault based on the relationship between the first fault-priority data and the second fault-priority data ([0498], “identify homes that have a high risk of pipes freezing, and use these insights to proactively engage customers to encourage them to take action, reducing insurance claim reimbursement costs. Similarly, home maintenance providers will be able to manage residential HVAC maintenance;” wherein identifying homes with a high risk of pipes freezing and managing residential HVAC maintenance are examples of indicating whether related assets are associated with fault based as claimed; Siebel);
identify, based at least on the one or more relationships, one or more metrics corresponding to the one or more assets at each of one or more asset hierarchy levels ([0422], “assign a non-technical loss (NTL) score to each sensor. This score may be calculated using a NTL classifier. The NTL classifier can be thought of as a routine that performs a set of mathematical operations on the data signals corresponding to a meter at a given time. The classifier computes analytic features that describe different characteristics of these signals, and then processes them in aggregate to calculate a numerical NTL score. The NTL score is a number between 0 and 1 that provides an estimate of the probability that the meter is experiencing NTL at the point in time being investigated,” [0430], “assign a probability score that describes the extent to which the meter is exhibiting signs of NTL at this point,” probability score, [0478], “estimates the risk score for any equipment or system as a combination of its probability of failure as well as the consequence of failure,” [0478], “update the health index score for assets in real time. Operators are able to seamlessly prioritize operational issues across millions of different, distributed assets and make more informed maintenance decisions by assessing risk at different levels of equipment, systems, geospatial, or organizational hierarchy,” wherein a score is an example of one metric as claimed; Baur);
determine prioritized actions for the portfolio of assets based on the one or more metrics and the one or more relationships between the first portion of the aggregated data and the second portion of the aggregated data ([0592], “With respect to ranking, resulting opportunities may be prioritized based on the preferences and business operations of the enterprise 3006,” Siebel teaches prioritizing based on ranking; [0581], Siebel); and
provide the dashboard visualization to an electronic interface of a computing device, the dashboard visualization configured to provide remote control of at least one asset from the portfolio of asserts based on the prioritized actions for the portfolio of assets, wherein the remote control of the at least one asset includes modification of one or more settings of the at least one asset via the electronic interface ([0487], “System operators and engineers may use the sensor and network health application to: prioritize operational issues across millions of different, distributed assets and make more informed maintenance decisions; remotely reconcile deployment issues and effectively manage third-party installation vendors; recognize patterns and trends of asset failure to support effective management of maintenance resources; remotely update asset configuration at the individual asset level or for a cluster of assets using the bulk action functionality; visualize sensor and network asset health in an interactive, geospatial view that intuitively supports prioritization of issues at the system level; create a single, continuously updated, and prioritized work queue of installation and maintenance work orders, increasing field team efficiency and effectiveness” and [0503], “Revenue-generating and cost-saving opportunities for appliance manufacturers include offering stronger warranty and maintenance offerings by remotely monitoring appliance (e.g., refrigerators) performance and proactively identifying and mitigating impending failures before they impact the customer,” Siebel).
Siebel discloses all the limitations discussed above including determine one or more alerts for the one or more assets based on the prioritized actions for the portfolio assets ([0494], “The loss detection application may provide investigation management and feedback that automatically tracks identified loss cases, work orders, resolution confirmations, and investigation results. The loss detection application may provide revenue reporting and monitoring that delivers pre-built reports and dashboards, provides ad hoc reporting tools for opportunity reporting and monitoring, analysis of revenue recovery performance against targets (historical and forecasted), revenue tracking, and investigation results,” [0561], and [0592], Siebel).
However, Siebel does not expressly disclose: group the one or more alerts based on a location of the one or more assets. O’Toole discloses: group the one or more alerts based on a location of the one or more assets ([0024], O’Toole). It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify the system of Siebel by incorporating the step of grouping the one or more alerts based on a location of the one or more assets, as disclosed by O’Toole, in order to be able to save time and resources by efficiently combining and resolving multiple related issues located at a common location. See: KSR International Co. v. Teleflex Inc., 82 USPQ 1385, 1396 (US 2007); MPEP § 2143.
Regarding Claims 3 and 15, Siebel/O’Toole discloses a system of claim 1, the portfolio of assets being a portfolio of supervisory control and data acquisition (SCADA) systems, and the one or more programs further comprising instructions configured to:
obtain the aggregated data based on a SCADA system descriptor describing one or more SCADA systems in the portfolio of SCADA systems ([0478], Siebel).
Regarding Claims 6 and 18, Siebel/O’Toole discloses a system of claim 1, the one or more programs further comprising instructions configured to:
determine one or more relationships between a first portion of the aggregated data associated with a first asset from the portfolio of assets and a second portion of the aggregated data associated with a second asset from the portfolio of assets ([0579] and [0587], Siebel); and
determine the prioritized actions for the portfolio of assets based on the one or more relationships ([0579] and [0587], Siebel).
Regarding Claims 7 and 19, Siebel/O’Toole discloses a system of claim 1, the one or more programs further comprising instructions configured to:
group the prioritized actions for the portfolio of assets based the contextual data ([0485], “identify anomalies at the both the individual sensor level as well as for clusters of sensors,” Siebel); and
configuring the dashboard visualization with the prioritized actions based on the grouping of the prioritized actions for the portfolio of assets ([0485], “are able to prioritize a comprehensive list of all sensor and network assets based on their individual health index and determine the appropriate course of remedial action,” Siebel).
Regarding Claim 8, Siebel/O’Toole discloses a system of claim 1, the one or more programs further comprising instructions configured to:
rank, based on impact of respective prioritized actions with respect to the portfolio of assets, the prioritized actions to2 generate a list of the prioritized actions ([0485], “are able to prioritize a comprehensive list of all sensor and network assets based on their individual health index and determine the appropriate course of remedial action,” [0487], Siebel); and
provide the list of the prioritized actions to the electronic interface via the dashboard visualization ([0485], “are able to prioritize a comprehensive list of all sensor and network assets based on their individual health index and determine the appropriate course of remedial action,” [0487], Siebel).
Regarding Claim 9, Siebel/O’Toole discloses a system of claim 1, the one or more programs further comprising instructions configured to:
determine a list of the prioritized actions for the portfolio of assets based the contextual data ([0488] and [0493]-[0494], Siebel); and
provide the list of the prioritized actions to the electronic interface via the dashboard visualization ([0488] and [0493]-[0494], Siebel).
Regarding Claim 10, Siebel/O’Toole discloses a system of claim 1, the request further comprising a user identifier, the user identifier describing a user role for a user associated with access of the dashboard visualization via the electronic interface, and the one or more programs further comprising instructions configured to:
obtain the aggregated data comprising obtaining the aggregated data based on the user identifier ([0445] and [0449], roles); and
configure the dashboard visualization based on the user identifier ([0445] and [0449], roles).
Regarding Claims 11, Siebel/O’Toole discloses a system of claim 1, the one or more programs further comprising instructions configured to:
determine the contextual data for different hierarchy level of assets ([0461], Siebel); and
provide the contextual data for the different hierarchy level of assets ([0461], Siebel).
Regarding Claim 12, Siebel/O’Toole discloses a system of claim 1, the one or more programs further comprising instructions configured to:
determine an alerts list associated with one or more recommendations for the portfolio of assets based on the prioritized actions for the portfolio of assets ([0462] and [0580], Siebel); and
provide the alerts list to the electronic interface via the dashboard visualization ([0462] and [0580], Siebel).
Regarding Claims 21, Siebel/O’Toole discloses a system of claim 1, the one or more programs further comprising instructions configured to determine an ordering for the prioritized actions related to the portfolio of assets ([0592], Siebel).
Regarding Claims 22, Siebel/O’Toole discloses a system of claim 1, wherein the remote control of the at least one asset from the portfolio of assets includes modification of one or more thresholds for the at least one asset from the portfolio of assets ([0487], “System operators and engineers may use the sensor and network health application to: prioritize operational issues across millions of different, distributed assets and make more informed maintenance decisions; remotely reconcile deployment issues and effectively manage third-party installation vendors; recognize patterns and trends of asset failure to support effective management of maintenance resources; remotely update asset configuration at the individual asset level or for a cluster of assets using the bulk action functionality; visualize sensor and network asset health in an interactive, geospatial view that intuitively supports prioritization of issues at the system level; create a single, continuously updated, and prioritized work queue of installation and maintenance work orders, increasing field team efficiency and effectiveness” and [0503], “Revenue-generating and cost-saving opportunities for appliance manufacturers include offering stronger warranty and maintenance offerings by remotely monitoring appliance (e.g., refrigerators) performance and proactively identifying and mitigating impending failures before they impact the customer,” Siebel).
Regarding Claims 23, Siebel/O’Toole discloses a system of claim 1, wherein the remote control of the at least one asset from the portfolio of assets includes at least one of modification of one or more parameters of the at least one asset, modification of one or more faults of the at least one asset, transmission of one or more command signals to the at least one asset, transmission of one or more control signals to the at least one asset, transmission of one or more protocol commands to the at least one asset, and transmission of one or more firmware updates to the at least one asset ([0487], “System operators and engineers may use the sensor and network health application to: prioritize operational issues across millions of different, distributed assets and make more informed maintenance decisions; remotely reconcile deployment issues and effectively manage third-party installation vendors; recognize patterns and trends of asset failure to support effective management of maintenance resources; remotely update asset configuration at the individual asset level or for a cluster of assets using the bulk action functionality; visualize sensor and network asset health in an interactive, geospatial view that intuitively supports prioritization of issues at the system level; create a single, continuously updated, and prioritized work queue of installation and maintenance work orders, increasing field team efficiency and effectiveness” and [0503], “Revenue-generating and cost-saving opportunities for appliance manufacturers include offering stronger warranty and maintenance offerings by remotely monitoring appliance (e.g., refrigerators) performance and proactively identifying and mitigating impending failures before they impact the customer,” Siebel).
Response to Arguments
Applicant argues that the applied art fails to disclose; “determine asset relationship data for the one or more related assets; determine contextual data for the portfolio of assets based on attributes for the aggregated data and the asset relationship data, wherein the contextual data comprises one or more events associated with the one or more related assets; determine, based on the contextual data, one or more relationships between a first portion of the aggregated data associated with an asset of the one or more assets, wherein the first portion of the aggregated data comprises of a first fault-priority data associated with a first asset from the portfolio of assets and a second portion of the aggregated data associated with the asset, wherein the second portion of aggregated data comprises of a second fault-priority data associated with a second asset from the portfolio of assets; indicate whether the one or more related assets are associated with a fault based on the relationship between the first fault-priority data and the second fault-priority data.”
The Examiner respectfully disagrees. The applied art does disclose: determine asset relationship data for the one or more related assets ([0494], “Unusual flow patterns are correlated with equipment diagnostic and operational data, based on a library of analytics that codify business rules for loss detection,” Siebel); determine contextual data for the portfolio of assets based on attributes for the aggregated data ([0580], wherein “data about the unexpected load change” corresponds to contextual data claimed; Siebel) and the asset relationship data, wherein the contextual data comprises one or more events associated with the one or more related assets ([0498], “analyze real and near real-time data from connected home devices, home characteristic data, and dynamic weather data to identify high-risk home assets,” wherein real and near real-time data are examples of events as claimed; Siebel); determine, based on the contextual data, one or more relationships between a first portion of the aggregated data associated with an asset of the one or more asset, wherein the first portion of the aggregated data comprises of a first fault-priority data associated with a first asset from the portfolio of assets and a second portion of the aggregated data associated with the asset ([0498], “home maintenance providers will be able to manage residential HVAC maintenance across multiple customers, and use the prioritized ranking of highest-risk HVAC assets across homes to more efficiently allocate their customer maintenance budgets,” wherein highest-risk HVAC assets across homes are examples of a first fault-priority data associated with a first asset and a second fault-priority data associated with a second asset as claimed; wherein the prioritized ranking is an example of determining one or more relationships as claimed; [0591], “with respect to revenue protection, the results of analytics processing on batch data and stream data can be provided to the a machine learning model of the machine learning and predictions module 3217 to score where revenue theft might be occurring. The machine learning and predictions module 3217 can rank various cases of potential revenue theft for a user of the enterprise Internet-of-Things application development platform 3002, such as a utility, to investigate,” wherein ranking implies that there is a relationship determination of at least a first portion and a second portion of data; [0596], “with respect to the energy industry and the utilities sector in particular, the enterprise Internet-of-Things application development platform 3002 allows a utility administrator to group energy intensity, energy consumption, and energy demand together on a page for easier viewing. The UI services module 3224 may provide role-based access controls. Administrators can determine which parts of the application will be visible to certain types of users,” wherein grouping is a form of determining relationships as claimed; [0461], [0579], and [0587], Siebel), wherein the second portion of the aggregated data comprises of a second fault-priority data associated with a second asset from the portfolio of assets ([0498], “home maintenance providers will be able to manage residential HVAC maintenance across multiple customers, and use the prioritized ranking of highest-risk HVAC assets across homes to more efficiently allocate their customer maintenance budgets,” wherein highest-risk HVAC assets across homes are examples of a first fault-priority data associated with a first asset and a second fault-priority data associated with a second asset as claimed; Siebel); indicate whether the one or more related assets are associated with a fault based on the relationship between the first fault-priority data and the second fault-priority data ([0498], “identify homes that have a high risk of pipes freezing, and use these insights to proactively engage customers to encourage them to take action, reducing insurance claim reimbursement costs. Similarly, home maintenance providers will be able to manage residential HVAC maintenance;” wherein identifying homes with a high risk of pipes freezing and managing residential HVAC maintenance are examples of indicating whether related assets are associated with fault based as claimed; Siebel);
Conclusion
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to GIOVANNA B COLAN whose telephone number is (571)272-2752. The examiner can normally be reached on Mon - Fri 8:30-5:00.
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/GIOVANNA B COLAN/Primary Examiner, Art Unit 2165
January 7, 2026
1 The limitation “to generate a dashboard visualization associated with a portfolio of assets, the request comprising” has not been given patentable weight since it is a statement of intended use which does not limit the scope of the claim. See MPEP 2103 C. and 2111.04(I)
2 The limitation “to generate a list of the prioritized actions” has not been given patentable weight since it is a statement of intended use which does not limit the scope of the claim. See MPEP 2103 C. and 2111.04(I)