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 .
This office action is in response to amendments filed on September 2, 2025.
Claims 10-11, 21 are canceled. Claims 1, 7, 12-20 have been amended.
Claims 1-9, 12-20, 22 are pending.
Response to Arguments
The rejections regarding 35 U.S.C. 101 have been withdrawn as the claims have been amended.
The rejections regarding 35 U.S.C. 112 have been withdrawn as the claims have been amended.
Applicant's arguments filed September 2, 2025. have been fully considered but they are not persuasive.
On page 11 of Remarks, Applicant mainly argues that the claimed invention differs from prior art reference Asenjo as the claimed invention is directed towards data sharing whereas Asenjo regards distribution of processing tasks: “Hence, the claimed invention differs from Asenjo at least in that data and processing code are not merely distributed for distributed processing by other machines in the cloud or fog layer. Rather, it involves data sharing, in which a unit's own data can be enhanced by the data of another system. It is therefore not merely a matter of decentralized distribution of processing tasks across multiple machines as noted by Asenjo” (Remarks, Page 11, Par. 5). Examiner respectfully disagrees. Firstly, it is not clear from the limitations of the claimed invention itself what the data sharing/enhancement entails to differentiate the invention over the prior art. The Applicant’s argument is directed towards a high-level overview of the invention, but these differences are not supported by the claim language itself, nor do the Applicant’s arguments indicate specifically where these differences exist in the claims. Secondly, the Applicant characterizes Asenjo as being directed towards the “decentralized distribution of processing tasks”, but Asenjo is directed towards a system for risk assessment using big data analysis (Par. [0009]). That is, Asenjo is directed towards data collection, i.e. sharing, of devices/assets to characterize overall system behavior over time, i.e. a type of enhancement under the broadest reasonable interpretation. Lastly, the newly amended limitations of Claim 1 are further shown to be taught by Asenjo below. For these reasons, Claims 1-9, 12-20, 22 remain rejected under 35 U.S.C. 102 and 35 U.S.C. 103.
Claim Objections
Claims 1-9, 12-20, 22 are objected to because of the following informalities:
Claims 1-9, 12-20, 22 use the conjunction “and/or” frequently with multiple lists of items. For example, Claim 13 recites the limitation “wherein the central digital platform includes a data processing module providing exposure-based forecasts and/or data-driven expert opinions and/or process optimization by parameter feedback based on the captured data of the data transmission pipelines and/or the data streaming and/or the parameter values of the at least one of the standardized digital twin structures”. It is recommended by the Examiner to avoid using “and/or” and to rewrite the claims with additional formatting to clarify the scope of the claimed limitations.
Appropriate correction is required.
Claim Rejections - 35 USC § 102
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 the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claim(s) 1-2, 4-7, 9, 12-20, 22 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Asenjo et al. (U.S. Pub. No. 2014/0337086 A1), hereinafter referred to as “Asenjo”.
Regarding Claim 1:
Asenjo teaches the following limitations:
An open scalable and modular cross-data system providing a standardized secured data aggregator, comprising: a central digital platform, implemented by first processing circuitry, for interlinking sensitive risk-related data (Fig. 1, Par. [0041], Par. [0046], Fig. 3, Par. [0054], Par. [0055], Par. [0130]). Asenjo teaches a scalable cloud-based platform which collects data to assess risk.
and a plurality of units, implemented by second processing circuitry, wherein the system provides controlled data-driven or process-driven cross-data interaction between different ones of the units and the central digital platform (Fig. 1, Par. [0041], Fig. 3, Par. [0054], Par. [0055], Par. [0130]). The platform in Asenjo collects data from multiple industrial devices, and this is data/process-driven interaction under the broadest reasonable interpretation.
the units have associated heterogeneous data sources and/or data measuring or capturing devices associated with real-world objects or individuals and use one or more network-enabled devices to access the central digital platform by a secure network (Fig. 3, Par. [0041], Par. [0045], Par. [0054], Par. [0055], Par. [0072]). The industrial devices in Asenjo collect real-world asset data from sensors, and communicate with the platform over a network secured by a firewall.
each of the units has an assigned authentication, authorization, and group allocation within the system providing a controlled network access to the central digital platform and a fenced data space of a persistence storage of the central digital platform for each of the units via the secure network (Par. [0044], Par. [0054], Par. [0059], Par. [0072]). Asenjo provisions storage to individual subscribers, and controls access to these services.
the central digital platform includes a network-interface for secure bidirectional data transmission between the central digital platform and one of the units, all data transmissions and communications between the one of the units and the central digital platform are hosted in the fenced data space associated with the one of the units uploading and/or assessing data via the network-enabled devices of the one of the units and the network-interface for data pre-processing and processing by central digital platform (Par. [0044], Par. [0054], Par. [0059], Par. [0071], Par. [0072]). Asenjo teaches securing data transmission with a firewall as a network interface and pre-processing data for gathered data from the industrial devices.
and uploaded data is standardized and normalized and enriched by the central digital platform providing uniform access to each of the units to its data (Par. [0044], Par. [0054], Par. [0059], Par. [0071], Par. [0072]). The gathered data is pre-processed, i.e. standardized/normalized/enriched under the broadest reasonable interpretation, and uploaded for access.
and the central digital platform includes standardized digital twin structures available throughout an entire lifecycle of the real-world object or individual, the standardized digital twin structures providing an individual/object replica with an artificial intelligence of an individual/object physical entity in the central digital platform (Par. [0045], Par. [0057], Par. [0075], Par. [0084], Par. [0098], Par. [0104], Par. [0114]). Asenjo teaches tracking monitoring data over time which reflects a physical quantity, i.e. a digital twin under the broadest reasonable interpretation. This includes modeling the behavior of a device/asset, which can be considered a type of artificial intelligence under the broadest reasonable interpretation. the standardized digital twin structures are fed by real-time or quasi real-time data captured via the secure bidirectional data transmission (Par. [0045], Par. [0057], Par. [0075], Par. [0084], Par. [0104], Par. [0114]). This monitoring is done in real-time.
parameter evolution of at least one of the standardized digital twin structures corresponds to the physical object or individual at any given point in time (Par. [0045], Par. [0057], Par. [0075], Par. [0084], Par. [0104], Par. [0114]). Asenjo teaches this data tracking physical quantities through sensors, such as heart rate for example. and each standardized digital twin structure comprises a definable threshold value for a capture latency given by a maximum latency time value of digital twin parameter values and actual real-time parameter values of the physical object or process or individual (Par. [0057], Par. [0068]). Asenjo teaches an upload frequency which is defined by an administrator for generated data. Under the broadest reasonable interpretation, this is a maximum latency time value as this upload frequency represents the amount of time for updating data at maximum.
Regarding Claim 2:
Asenjo teaches the following limitations:
wherein each of the units includes defined unit-specific data- and process-access parameters and defined group-specific data- and process-access parameters (Par. [0071], Par. [0073], Par. [0075], Par. [0076]). Asenjo teaches the industrial devices having device data parameters for access on a hierarchical level.
and groups within the group allocation at least includes insured unit and/or broker unit and/or insurer and/or risk analysis provider data- and process-access parameters (Par. [0071], Par. [0073], Par. [0075], Par. [0076]). These parameters can be considered risk analysis provider data under the broadest reasonable interpretation as they are used for access with the risk management system.
Regarding Claim 4:
Asenjo teaches the following limitations:
wherein the uploaded data is enriched by processing or enhancing transferred data of the one of the units using by data linked to enriched or pre-processed data or data from additional sources (Par. [0044], Par. [0054], Par. [0059], Par. [0071], Par. [0072]). Under the broadest reasonable interpretation, the claim can be parsed as listing options between “the uploaded data is enriched by processing” or “the uploaded data is enriched by… enhancing transferred data of the one of the units using by data linked to enriched or pre-processed data or data from additional sources”. As argued above, the data is enriched by pre-processing, i.e. processing.
Regarding Claim 5:
Asenjo teaches the following limitation:
wherein the additional sources include anonymized data associated with fenced data spaces of others of the units (Par. [0082], Par. [0089], Par. [0092]). As this limitation corresponds to the second option of Claim 4 listed above, the previous rejection of Claim 4 additionally rejects Claim 5 as the previous rejection met the first option listed. For the sake of compact prosecution, it is additionally noted however that Asenjo further teaches anonymized data for uploaded data for collective risk analysis.
Regarding Claim 6:
Asenjo teaches the following limitation:
wherein the data transmissions and communications between the one of the units and the central digital platform hosted in the fenced data space associated with the one of the units include periodically scheduled data transmission pipelines and/or data streaming transmitting data continuously or periodically generated by different sources (Par. [0057], Par. [0068]). Asenjo teaches the data being periodically uploaded to the online platform.
Regarding Claim 7:
Asenjo teaches the following limitation:
wherein data captured by the central digital platform from the periodically scheduled data transmission pipelines and/or the data streaming are processed by the central digital platform incrementally using stream processing techniques without having access to all of data generated by various different data sources at high speed (Par. [0045], Par. [0057], Par. [0075], Par. [0084], Par. [0104], Par. [0114]). Asenjo teaches performing real-time risk assessment using a subset data. This is a type of incremental stream processing under the broadest reasonable interpretation, as it uses current partial data for risk notification/assessment.
Regarding Claim 9:
Asenjo teaches the following limitations:
wherein the open system and/or the central digital platform include an access control unit (Par. [0044], Par. [0054], Par. [0059], Par. [0071], Par. [0072]). Asenjo teaches access control through a firewall.
and access parameter values for access to the fenced data space as secure environment of the one of the units can be set by the one of the units of said fenced data space individually and hierarchically define access level to at least parts of data of the fenced data space for use by single units and/or groups of units and/or the central digital platform as anonymized data (Par. [0050], Par. [0071], Par. [0073], Par. [0075], Par. [0076]). Asenjo further teaches device parameters being used to add a device in accordance with a device management component.
Regarding Claim 12:
Asenjo teaches the following limitation:
wherein data captured in the fenced data space of the one of the units at least includes exposure linked data associated with the one of the units (Par. [0051], Par. [0060], Par. [0068], Par. [0083]). Asenjo teaches the captured data being assessed for risk factors, i.e. exposure linked data under the broadest reasonable interpretation, as this data is linked to risk/exposure at least partially.
Regarding Claim 13:
Asenjo teaches the following limitation:
wherein the central digital platform includes a data processing module providing exposure-based forecasts and/or data-driven expert opinions and/or process optimization by parameter feedback based on the captured data of the data transmission pipelines and/or the data streaming and/or the parameter values of the at least one of the standardized digital twin structures (Par. [0045], Par. [0099], Par. [0111]). Under the broadest reasonable interpretation, the claim can be parsed as listing options in which one is “providing exposure-based forecasts”. Asenjo teaches the system having predictive services based on collected risk data.
Regarding Claim 14:
Asenjo teaches the following limitation:
wherein the central digital platform includes an automated digital process for automated loss analytics and automated process optimization and/or for providing parameter-based indication of present of future loss trends and/or automated structuring or assembling of optimized risk-transfer structures based on the captured data of data transmission pipelines and/or the data streaming and/or the parameter values of the at least one of the standardized digital twin structures (Par. [0051], Par. [0086], Par. [0105], Par. [0110], Par. [0119]). Asenjo teaches the risk assessment system performing cost-benefit analysis, i.e. loss analytics, and identifying areas for optimization.
Regarding Claim 15:
Asenjo teaches the following limitation:
wherein the central digital platform provides automated property exposure management and automated visualization of property portfolio and risk exposures based on the captured data of data transmission pipelines and/or the data streaming and/or the parameter values of the at least one of the standardized digital twin structures (Par. [0060], Par. [0099], Par. [0105], Par. [0115]). Asenjo teaches visually rendering a risk management report on a screen of a client, and this report can be considered a type of property exposure management under the broadest reasonable interpretation, as this report includes the risk/costs of industrial equipment, i.e. a customer’s property.
Regarding Claim 16:
Asenjo teaches the following limitation:
wherein the central digital platform provides employee health risk-transfer structures and/or processes and/or programs facilitating automated analysis of complex impact of risks on employee health programs and/or risk-transfer structures based on the captured data of the data transmission pipelines and/or the data streaming and/or the parameter values of the at least one of the standardized digital twin structures (Par. [0111], Par. [0113], Par. [0114]). Under the broadest reasonable interpretation, this claim may be interpreted as the central digital platform providing at least one item among a list of options, in which one of the options is simply “processes”. For the sake of compact prosecution, Asenjo teaches computing risks associated with employee health, and this can be considered a risk-transfer structure under the broadest reasonable interpretation.
Regarding Claim 17:
Asenjo teaches the following limitation:
wherein the central digital platform provides automated policy and/or certificate and/or exposure and/or claims management by automated capturing and automated managing of risk-relevant data and documents via data transmission pipelines and/or the data streaming and/or the parameter values of the at least one of the standardized digital twin structures (Par. [0045], Par. [0057], Par. [0075], Par. [0076], Par. [0084]). Asenjo teaches risk, i.e. exposure, management from capturing device data, including documents, which are risk-relevant.
Regarding Claim 18:
Asenjo teaches the following limitation:
wherein the central digital platform provides automated supply chain resilience by automatically generating one or more digital twin structures of production and supplier networks to be covered and/or fenced by risk mitigation based on the captured data of data transmission pipelines and/or the data streaming and/or the parameter values of the at least one of the standardized digital twin structures (Par. [0055], Par. [0056], Par. [0057], Par. [0085]). Asenjo is directed towards risk assessment for supply chains and tracking data associated with the supply chain, i.e. creating digital twin structures.
Regarding Claim 19:
Asenjo teaches the following limitation:
wherein the central digital platform provides automated sustainability solutions and/or automated compiling of sustainability metrics and tracking based on the captured data of data transmission pipelines and/or the data streaming and/or the parameter values of the at least one of the standardized digital twin structures (Par. [0049], Par. [0103], Par. [0105], Par. [0106]). Under the broadest reasonable interpretation, the recommended risk mitigation strategies of Asenjo can be considered a type of operational sustainability solution.
Regarding Claim 20:
Asenjo teaches the following limitations:
wherein the system is based on a digital twin structure of a twinned physical object and/or process and/or individual, comprising (Par. [0045], Par. [0057], Par. [0075], Par. [0084], Par. [0104], Par. [0114]). Asenjo was previously shown to teach digital twin structures through data tracking.
one or more sensors configured to sense and/or measure measuring values of one or more designated parameters of the twinned physical object and/or process and/or individual (Fig. 3, Par. [0041], Par. [0045], Par. [0054], Par. [0055], Par. [0072]). Asenjo was previously shown to teach sensors for reporting data.
a processor-driven core engine, implemented by the first processing circuitry, configured to: receive data associated with the one or more sensors, and for at least a selected portion of the twinned physical object and/or process and/or individual, execute at least one of: (i) a monitoring process to monitor a condition of the selected portion of the twinned physical object and/or process and/or individual based at least in part on the sensed values of the one or more designated parameters and/or (ii) an assessing process to generate and propagate forward-looking measuring values and/or a time-series of forward-looking measuring values of the selected portion of the twinned physical abject and/or process and/or individual based at least in part on the sensed values of the one or more designated parameters to a definable future time-window (Par. [0036], Par. [0055], Par. [0070], Par. [0072], Par. [0114]). Asenjo teaches these industrial devices as having processors and monitoring conditions of their physical counterpart through the sensed values.
and a data transmission interface coupled to the core engine configured to transmit information associated with a result generated by the core engine (Par. [0036], Par. [0048], Par. [0049]). Asenjo further teaches an interface component for transmitting information.
and the one or more sensors are configured to sense and/or measure measuring values of the one or more designated parameters and the core engine is configured to execute at least one of the monitoring and assessing processes, when the twinned physical object and/or process and/or individual time-dependently changes or propagates (Par. [0045], Par. [0057], Par. [0075], Par. [0084], Par. [0104], Par. [0114]). This sensing/monitoring is performed in real-time, i.e. when the twinned physical counterpart changes with time.
Regarding Claim 22:
Asenjo teaches the following limitations:
wherein the central digital platform includes a data-loopback structure, and data of the units are processed automatically, generating risk analysis parameter values being feed back to the system for use by the system and/or the units and/or a data-enrichment process (Par. [0045], Par. [0057], Par. [0075], Par. [0084], Par. [0104], Par. [0114]). Asenjo teaches continuous real-time monitoring of data for risk assessment, and this can be considered a data-loopback structure under the broadest reasonable interpretation as this data is subsequently used for optimization/feedback for the industrial devices.
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, 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.
Claim 3 is rejected under 35 U.S.C. 103 as being unpatentable over Asenjo in view of Carttar et al. (U.S. Pub. No. 2007/0118291 A1) hereinafter referred to as “Carttar”.
Regarding Claim 3:
Asenjo teaches the following limitations:
wherein the uploaded data is enriched at least by replenishment of object or unit data by geographic (Par. [0056], Par. [0073], Par. [0111]). Asenjo teaches enriching data with geographic location information for risk assessment.
(taught by Carttar below)
Carttar teaches the following limitations:
latitude and/or longitude (Par. [0016], Par. [0031], Par. [0056]). Carttar teaches using latitude/longitude data for risk assessment.
and the geographic latitude and/or longitude parameter values of the object or unit is used to automatically generated exposure parameter values associated with the object or unit (Par. [0016], Par. [0031], Par. [0056]). This geographic data is used to determine risk exposure/assessment.
Asenjo teaches using geographic location for risk assessment, but does not explicitly teach latitude/longitude values. Carttar however teaches a system in which latitude/longitude values form geocodes for assessing risk, and that such a system allows for flexible modeling for risk assessment (Par. [0010], Par. [0011]). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the risk assessment system of Asenjo with the latitude/longitude values of Carttar in order to gain the benefit of additional flexibility in assessing risk. One of ordinary skill in the art would have recognized that the latitude/longitude values of Carttar are compatible with the geographic data collected with Asenjo for assessing risk, and that such values would allow for flexible determination in risk exposure.
Claim 8 is rejected under 35 U.S.C. 103 as being unpatentable over Asenjo in view of Trainor et al. (U.S. Pub. No. 2017/0091870 A1) hereinafter referred to as “Trainor”.
Regarding Claim 8:
Trainor teaches the following limitation:
wherein the central digital platform includes a monitoring unit for detecting any concept drift occurring in the data pre-processing and processing by central digital platform based on any detected changes in properties of a stream or pipeline over time (Par. [0005], Par. [0009], Par. [0064], Par. [0065]). Trainor teaches monitoring state drift for equipment failure/risk.
Asenjo teaches risk assessment, but does not teach monitoring for drift. Trainor however teaches a system in which states are monitored for drift for assessing risk, and that such a system has the advantage of improved prediction for risk assessment (Par. [0009]). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the risk assessment system of Asenjo with the drift monitoring of Trainor in order to gain the benefit of improved risk assessment. One of ordinary skill in the art would have recognized that the drift monitoring of Trainor is compatible with the system of Asenjo as both are directed towards assessing risk, and that such monitoring would allow for improved risk assessment by predicting future states from the drift analysis.
Related Art
The following prior art made of record and cited on PTO-892, but not relied upon, is considered pertinent to applicant’s disclosure:
DeLuca et al. (U.S. Patent No. 11,263,337 B2) – Includes methods regarding digital twins
Cella (U.S. Pub. No. 2021/0272394 A1) – Includes methods regarding digital twins
Chapin (U.S. Pub. No. 2020/0118053 A1) – Includes methods regarding digital twins for asset performance
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ETHAN V VO whose telephone number is (571)272-2505. The examiner can normally be reached M-F 8am-5pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Lynn Feild can be reached on (571)272-2092. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/E.V.V./Examiner, Art Unit 2431 /LYNN D FEILD/Supervisory Patent Examiner, Art Unit 2431
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