Patent Application 17695202 - USER EXPERIENCE RENDERING FOR INTELLIGENT WORKFLOW - Rejection
Patent Application 17695202 - USER EXPERIENCE RENDERING FOR INTELLIGENT WORKFLOW
Title: USER EXPERIENCE RENDERING FOR INTELLIGENT WORKFLOW
Application Information
- Invention Title: USER EXPERIENCE RENDERING FOR INTELLIGENT WORKFLOW
- Application Number: 17695202
- Submission Date: 2025-05-15T00:00:00.000Z
- Effective Filing Date: 2022-03-15T00:00:00.000Z
- Filing Date: 2022-03-15T00:00:00.000Z
- National Class: 705
- National Sub-Class: 007270
- Examiner Employee Number: 87699
- Art Unit: 3625
- Tech Center: 3600
Rejection Summary
- 102 Rejections: 1
- 103 Rejections: 1
Cited Patents
The following patents were cited in the rejection:
Office Action Text
DETAILED ACTION
This office action is in response to communication filed on 15 March 2022.
Claims 1 – 20 are presented for examination.
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 § 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 the judicial exception of abstract ideas without significantly more. The claims recite receiving data regarding a workflow of a user completing a task, assessing the data to identify attributes of the workflow that is expressed in a series of steps, analyzing the steps of the workflow to identify areas of improvement, generating augmentations from a plurality of technology fitments matched to the areas for improvement in the steps of the workflow, generating a user experience template, wherein content of the template is selected based upon at least an archetype for which the generating the augmentation from the plurality of technology fitments was performed, and sending the augmentations formatted in the user experience template to a user for communicating to the user. This judicial exception is not integrated into a practical application. The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. The eligibility analysis in support of these findings is provided below, in accordance section 2106 of the MPEP (hereinafter, MPEP 2106).
With respect to Step 1 of the eligibility inquiry (as explained in MPEP 2106), it is noted that the method, the system, and the computer program product are directed to an eligible categories of subject matter. Step 1 is satisfied.
With respect to Step 2A prong 1 of MPEP 2106, it is next noted that the claims recite an abstract idea by reciting concepts of determining steps and changing steps of a workflow, which falls into the “certain methods of organizing human activity” group within the enumerated groupings of abstract ideas set forth in the MPEP 2106 through the subset of following rules or instructions. The limitations reciting the abstract idea in independent claims are receiving data regarding a workflow of a user completing a task, assessing the data to identify attributes of the workflow that is expressed in a series of steps, analyzing the steps of the workflow to identify areas of improvement, generating augmentations from a plurality of technology fitments matched to the areas for improvement in the steps of the workflow, generating a user experience template, wherein content of the template is selected based upon at least an archetype for which the generating the augmentation from the plurality of technology fitments was performed, and sending the augmentations formatted in the user experience template to a user for communicating to the user.
With respect to Step 2A Prong Two of the MPEP 2106, the judicial exception is not integrated into a practical application. The additional elements are directed to computer implementation, user device, desktop type device, mobile device, wearable device, voice interface device, virtual device, neural network, blockchain memory, cloud computing, Internet of Things, artificial intelligence, edge computing, 5G mobile communications, artificial intelligence model, hardware processor, memory, computer program product, and computer readable storage medium, to implement the abstract idea. However, these elements fail to integrate the abstract idea into a practical application because they fail to provide an improvement to the functioning of a computer or to any other technology or technical field, fail to apply the exception with a particular machine, fail to effect a transformation of a particular article to a different state or thing, and fail to apply/use the abstract idea in a meaningful way beyond generally linking the use of the judicial exception to a particular technological environment. Furthermore, these elements have been fully considered, however they are directed to the use of generic computing elements to perform the abstract idea, which is not sufficient to amount to a practical application (as noted in the MPEP 2106) and is tantamount to simply saying “apply it” using a general purpose computer, which merely serves to tie the abstract idea to a particular technological environment by using the computer as a tool to perform the abstract idea, which is not sufficient to amount to particular application.
Accordingly, because the Step 2A Prong One and Prong Two analysis resulted in the conclusion that the claims are directed to an abstract idea, additional analysis under Step 2B of the eligibility inquiry must be conducted in order to determine whether any claim element or combination of elements amount to significantly more than the judicial exception.
With respect to Step 2B of the eligibility inquiry, it has been determined that the claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. The additional limitations are directed to: computer implementation, user device, desktop type device, mobile device, wearable device, voice interface device, virtual device, neural network, blockchain memory, cloud computing, Internet of Things, artificial intelligence, edge computing, 5G mobile communications, artificial intelligence model, hardware processor, memory, computer program product, and computer readable storage medium. These elements have been considered, but merely serve to tie the invention to a particular operating environment, though at a very high level of generality and without imposing meaningful limitation on the scope of the claim. This does not amount to significantly more than the abstract idea, and it is not enough to transform an abstract idea into eligible subject matter. Such generic, high-level, and nominal involvement of a computer or computer-based elements for carrying out the invention merely serves to tie the abstract idea to a particular technological environment, which is not enough to render the claims patent-eligible, as noted at pg. 74624 of Federal Register/Vol. 79, No. 241, citing Alice, which in turn cites Mayo.
In addition, when taken as an ordered combination, the ordered combination adds nothing that is not already present as when the elements are taken individually. There is no indication that the combination of elements integrates the abstract idea into a practical application. Their collective functions merely provide conventional computer implementation. Therefore, when viewed as a whole, these additional claim elements do not provide meaningful limitations to transform the abstract idea into a practical application of the abstract idea or that the ordered combination amounts to significantly more than the abstract idea itself.
The dependent claims have been fully considered as well, however, similar to the finding for claims above, these claims are similarly directed to the abstract idea of concepts of selecting technology fitments by business sector by way of example, without integrating it into a practical application and with, at most, a general purpose computer that serves to tie the idea to a particular technological environment, which does not add significantly more to the claims. The ordered combination of elements in the dependent claims (including the limitations inherited from the parent claim(s)) add nothing that is not already present as when the elements are taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Their collective functions merely provide conventional computer implementation. Accordingly, the subject matter encompassed by the dependent claims fails to amount to significantly more than the abstract idea.
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 (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 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.
Claims 1 – 7 and 9 – 20 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by U.S. P.G. Pub. 2014/0236663 (hereinafter, Smith).
Regarding claim 1, Smith teaches a computer-implemented method assess a user's workflow on a task comprising:
receiving data regarding a workflow of a user completing a task (¶ 35, “The present invention enables the definition of one or more unified sales management workflows that enable users to engage in their work, via one or more computers, supported by multiple system resources (whether cloud based resources, enterprise computer or application resources, client computers or application, or mobile devices or mobile applications).”);
assessing the data to identify attributes of the workflow that is expressed in a series of steps (¶ 41, “In one aspect of the invention, the workflow management system (2) includes a user workflow designer (6) and an automated data flow manager (8). The user workflow designer (6) may be implemented as a series of functions of a web application (10). For example, a business or government entity (the "entity") may define a series of user workflow objectives, related for example to a business process used regularly by the personnel of the entity or for example a selected group of the personnel. The workflow designer (6) provides a series of tools that enable one or more administrative users to design a new workflow (11), for example by modifying an existing workflow template stored to the database (12).”);
analyzing the steps of the workflow to identify areas of improvement (¶ 138, “it should be understood that the workflow management system (2) may be used, relying on the analytics engine (30) for example to identify possible improvements to workflows, for example by comparing existing workflows to a set of best practices stored to the database (11), whether these best practices are based on the client organization or derived from similar organizations or similar businesses recognized as being leaders in the same domain. The workflow management system (2) of the present invention enables the "tuning" of workflows in part based on output from the analytics engine, which may be generated automatically or based on one or more analysis routines or queries selected by the administrative user by operation of an appropriate user interface.”) (¶ 139, “For example, based on the type of business, and sales related attributes or objectives, the contractor may begin with a set up template which is modified based on for example discussion with key sales personnel and executives of the customer organization. For example, the contractor may establish the specific parameters of "ADDING AN OPPORTUNITY", including information required from business systems (4), information to be provided to business systems (4) automatically, associated business rules and so on.”);
generating augmentations from a plurality of technology fitments matched to the areas for improvement in the steps of the workflow (¶ 84, “In one aspect of the implementation of the invention, the API (16) and associated database (12) may be implemented in the cloud. Users may be associated with any manner of client device (20) that may access the API (16) via the Internet including for example smart phones, desktop computers accessing the system via a standard web browser, mobile tablets, televisions, laptops and desktops, etc. All client devices are operable to communicate with the API (16) via standard web protocols (http, https) by means of the cloud.”) (¶ 112, “In addition to data connectors (20), the present invention also contemplates the use of one or more data capture applications (23) which may be implemented as custom applications, configured to connect to existing business systems (4) to download and synchronize data. These data capture applications (23) may reside in the cloud infrastructure so that they can scale on an as-needed basis to meet client demand. Much like the data connectors (20), these data capture applications (23) will be individually responsible for downloading and queueing data, and sending relevant data to the API (16) layer to be entered into the database (12).”) (Examiner note: scaling is improvement) (¶ 362, “A cloud-based computing resource is thought to execute or reside somewhere on the "cloud", which may be an internal corporate network or the public Internet. From the perspective of an application developer or information technology administrator, cloud computing enables the development and deployment of applications that exhibit scalability (e.g., increase or decrease resource utilization as needed), performance (e.g., execute efficiently and fast), and reliability (e.g., never, or at least rarely, fail), all without any regard for the nature or location of the underlying infrastructure.”); and
generating a user experience template, wherein content of the user experience template is selected based upon at least an archetype for which the generating the augmentation from the plurality of technology fitments was performed (¶ 139, “the customer set up utility of the present invention, which is part of the overall workflow designer (6), may implement one or more workflows related to setting up customers on the system of the present invention. For example, based on the type of business, and sales related attributes or objectives, the contractor may begin with a set up template which is modified based on for example discussion with key sales personnel and executives of the customer organization. For example, the contractor may establish the specific parameters of "ADDING AN OPPORTUNITY", including information required from business systems (4), information to be provided to business systems (4) automatically, associated business rules and so on.”) (¶ 41, “The workflow designer (6) provides a series of tools that enable one or more administrative users to design a new workflow (11), for example by modifying an existing workflow template stored to the database (12). Workflow (11) may include a plurality of steps or processes, and each step or process may rely on one or more business systems (4). The workflow designer (6) may also enable the administrative user(s) to define the interface to be presented in connection with the steps, so as to enable the compilation of a custom interface for an underlying application, or in fact the workflow designer (6) may incorporate or be linked to an application development platform such that selection of specific steps or attributes associated with steps, may define parameters for one or more local applications (14) for implementing the workflow (11), for example based on the features accessed using the application development platform.”); and
sending the augmentations formatted in the user experience template to a user device for communicating to the user (¶ 132, “The system of the present invention may also include an analytics engine (30) that is operable analyze data related to sales activities and apply analytics for example to define trends, suggest best practices, identify insights or trends, identify in real time tops sales persons, determine sales strategies that work best for certain products or certain types of customers. Once these patterns are identified, these can be integrated in sales activity monitoring enabled by the present invention, for example a salesperson may be sent one or more notifications designed to alert the salesperson if they are diverging from a pattern that has been established as being optimal in certain circumstances. One example of a workflow feature object that constitutes a pop-up screen that informs a salesperson that "when you send an email at time x, leads have 30% less chance of closing. If you send file X at this stage, leads have a 20% higher chance".”) (¶ 148, “The workflow designer (6) may be implemented as a menu builder, in which one or more drop down menus are provided for identifying workflow parameters, selecting related actions, and provided required data such as tags for fields or instructions to sales personnel.”) (¶ 123, “an administrative user may define certain documents that sales personnel will for example use in client visits. These files may be accessed automatically using the "FILES" icon of the mobile application (24). For example, the automated data flow manager (8) is operable, when the mobile device (26) is in an area where optimal wireless connectivity is available, to push one or more files or updates to files to the mobile device (26). The files in question thereafter are made available locally on the mobile device (26). Alternatively, the "FILES" icon may be operable to provide a mechanism to download selected documents in real time from database (12) for example, on an as needed basis. This allows mobile sales personnel to have documents for presentation to customers, when they need them.”).
Regarding claim 2, Smith teaches the computer implemented method of claim 1 further comprising:
receiving confirmation of fitment to business practices of the archetype (¶ 185, “It should be understood that the use cases identified above enable the implementation of various processes and access to information at various points, for example from a mobile device, that based on existing systems would not have been possible or available without significant integration. The processes and information required may evolve. Also, administrators may review sales success stories and obtain insights suggesting changes to workflows. Again, these may be integrated easily, in fact changes may be "tested" on the system for effectiveness. Various other scenarios are possible using the present system that simply are not practical using prior art approaches. For example, sales personnel may be monitored more closely to identify sales personnel who do not return information within target timelines to potential customers, and further training may be provided or personnel may be reprimanded. Compliance processes may be linked more directly to compensation. Workflows may be adjusted to the personality of the sales targets and/or the sales personnel, and so on.”) and
adjusting augmentation responsive to confirmation of fitment to provide an optimized workflow (¶ 69, “Automatically analyzing target specific data sources, or data sources relevant to a group of individuals sharing common attributes, so as to optimize one or more workflows based on automatically extracting behavioural information for selected targets. For example, the platform may be operable to identify the best time of day, or day of week, for sending an email to, or to phone, a particular sales prospect, for example because a sales prospect may be more likely to be online or available by phone at certain periods of time.”) (¶ 132, “Once these patterns are identified, these can be integrated in sales activity monitoring enabled by the present invention, for example a salesperson may be sent one or more notifications designed to alert the salesperson if they are diverging from a pattern that has been established as being optimal in certain circumstances. One example of a workflow feature object that constitutes a pop-up screen that informs a salesperson that "when you send an email at time x, leads have 30% less chance of closing. If you send file X at this stage, leads have a 20% higher chance".”) (¶ , “”).
Regarding claim 3, Smith teaches the computer implemented method of claim 1, wherein the content of the user experience template is further selected based upon the plurality of technology fitments (¶ 74, “ For example, the computer system may link to one or more social media platforms in order to extract information concerning users who have "LIKED" particular products, content, or services, but also the content associated with the social media interactions of a target, to provide deeper analysis of the preferences or interests of a target.”) (¶ 76, “The analytics engine (30) may also apply one or more operations for generating insights based on extracted information. These may include semantic operations (for example analysis of an article that a target has read), weighting of content, fuzzy logic operations, artificial intelligence, and so on. Also, the platform may enable: site behavior profiling (e.g. click path analysis, purchase patterns analysis); collaborative filtering ("people who have behaved like you were more likely to perform some specified activity"); and keyword search of content.”).
Regarding claim 4, Smith teaches the computer implemented method of claim 1, wherein the content of the user experience template is further selected based upon modality of the user device (¶ 84, “In one aspect of the implementation of the invention, the API (16) and associated database (12) may be implemented in the cloud. Users may be associated with any manner of client device (20) that may access the API (16) via the Internet including for example smart phones, desktop computers accessing the system via a standard web browser, mobile tablets, televisions, laptops and desktops, etc. All client devices are operable to communicate with the API (16) via standard web protocols (http, https) by means of the cloud.”).
Regarding claim 5, Smith teaches the computer implemented method of claim 4, wherein the modality is selected from the group consisting of a desktop type device, a mobile device, a wearable device, a voice interface device, a virtual device and combinations thereof (¶ 84, “In one aspect of the implementation of the invention, the API (16) and associated database (12) may be implemented in the cloud. Users may be associated with any manner of client device (20) that may access the API (16) via the Internet including for example smart phones, desktop computers accessing the system via a standard web browser, mobile tablets, televisions, laptops and desktops, etc. All client devices are operable to communicate with the API (16) via standard web protocols (http, https) by means of the cloud.”).
Regarding claim 6, Smith teaches the computer implemented method of claim 1, wherein the content of the of the user experience template is further selected based upon environment of the workflow (¶ 56 , “Also, the business or technology environment that produces the need for adoption of new workflows or updates to existing workflows can be very fluid. For example, in a sales environment new insights are developed all the time regarding workflows that are effective in driving sales. Similarly, the sales environment is fluid and therefore the desired best practices for sales personnel are subject to change. Also, sales techniques need to reflect that what works for one sales person may not work for another. The changing composition of sales staff and because of this the evolving cultural, demographic, social, and personality traits of the sales staff as a whole, also requires adjustment of sales strategies and how these are applied in specific instances. All of these factors are examples of what contributes to a changing environment. To develop and update workflows that keep up with these changes is often impractical. The present invention solves this significant problem.”).
Regarding claim 7, Smith teaches the computer implemented method of claim 1, wherein the generating the user experience template comprises a user experience template matching etching comprising a neural network that is trained to match historical templates that are tagged by at least one of technology, modality, archetype, environment, and combinations thereof to the archetype for which the generating the augmentation from the plurality of technology fitments was performed (¶ 126, “The system of the present invention in compiling relevant information may apply one or more techniques for summarizing or digesting relevant information, including document summarization for summarizing relevant documents for quick perusal prior to a meeting, or generation of an interest cloud which consists of analysis of relevant information (for example relevant emails, removal of repetitive wording, to extract selected themes that appear to have significance. The system of the present invention may also include a semantic analysis engine (27) which may assist in the processing of information for example to generate one or more tag clouds reflecting for example an efficient summary of client concerns, extracted from client communications, client websites or social sites.”) (¶¶ 288-291, “Facts can include all the knowledge gained about the sales process in all the stages the process has been through before, as well as knowledge gained on the process in the current stage. This set of data for each process in the given stage is called the "training data". Based on this training data, a set of classifiers can be trained for each sale stage, using supervised learning techniques. Supervised learning techniques consist of algorithms that learn to classify data into categories (for us, the categories may be "sale will close"/"sale will not close") based on existing training data that has already been classified. Each classifier can be trained on a random subset of the training data (for example 80% of the training data), so that each classifier learns slightly different knowledge. A possible embodiment of the invention is to use decision trees. Bayesian network or rule induction systems are other possible embodiments. Each classifier can learn rules on what makes an opportunity ultimately successful or not. For example: if an opportunity has an expected closing date less than 1 month in the future, and the contract length is less than a year, it is 78% likely to close.”).
Regarding claim 9, Smith teaches the computer-implemented method of claim 1, wherein the analyzing of the steps of the workflow to identify areas of improvement comprises using a learning corpus of existing workflows to train a classifier of an artificial intelligence model that can match the data to the existing workflows for determining the plurality of technology fitments (¶¶ 288-291, “Facts can include all the knowledge gained about the sales process in all the stages the process has been through before, as well as knowledge gained on the process in the current stage. This set of data for each process in the given stage is called the "training data". Based on this training data, a set of classifiers can be trained for each sale stage, using supervised learning techniques. Supervised learning techniques consist of algorithms that learn to classify data into categories (for us, the categories may be "sale will close"/"sale will not close") based on existing training data that has already been classified. Each classifier can be trained on a random subset of the training data (for example 80% of the training data), so that each classifier learns slightly different knowledge. A possible embodiment of the invention is to use decision trees. Bayesian network or rule induction systems are other possible embodiments. Each classifier can learn rules on what makes an opportunity ultimately successful or not. For example: if an opportunity has an expected closing date less than 1 month in the future, and the contract length is less than a year, it is 78% likely to close.”).
Regarding claim 10, Smith teaches the computer-implemented method of claim 1, wherein the generating augmentations from the plurality of technology fitments matched to the areas for improvement includes selecting the plurality of technology fitments by business sector (¶ 230, “For example, the insight engine may collect and compare thousands of interaction patterns from a variety of data sources, and calculate a sales reliability index that can be applied to sales forecasts, in order to "normalize" sales forecasts based on a realistic prediction of performance. Sales reliability indices may be defined for an individual, a group, a company or an industry, in part using trend discovery techniques across relevant information domains.”) (¶ 276, “Symbolic (string) data (e.g. the industry for an opportunity) is marked as such, and left alone so the technology can analyze that, for example, industry "A" produces more closings than industry "B" in certain conditions.”).
Regarding claim 11, Smith teaches the computer-implemented method of claim 4, wherein following the adjusting of the augmentation responsive to confirmation of fitment, the learning corpus is updated with the optimized workflow (¶¶ 293-297, “1) to help the sales manager calculate the probability of each sale closing: Each time an opportunity reaches a new stage, the known facts for that opportunity are calculated, in the same manner as before with the calculated facts from past opportunities used in the training set. The known facts are then run through each classifier in the set trained for the latest stage of that opportunity. Each classifier will vote whether the opportunity will close or not (not all the classifiers in the set will have the same vote, because each has been trained on a slightly different data set). To calculate the probability of the sale closing, a calculation may be performed to calculate the percentage of classifiers that have classified the new opportunity as "will close"; more agreement between classifiers implies more certainty that the sale will close. Each time an opportunity goes through a new stage, the sales dashboard is updated as described in the following section to reflect the new probability of closing for that sale. Sales closing probabilities can be combined with deal size expectations (often entered in the CRM too) for each sale to provide a better picture of expected revenue.”).
Regarding claims 12 and 18, the claims recite substantially similar limitations to claim 1. Therefore, claims 12 and 18 are similarly rejected for the reasons set forth above with respect to claim 1.
Regarding claims 13 and 19, the claims recite substantially similar limitations to claim 2. Therefore, claims 13 and 19 are similarly rejected for the reasons set forth above with respect to claim 2.
Regarding claims 14 and 20, the claims recite substantially similar limitations to claim 3. Therefore, claims 14 and 20 are similarly rejected for the reasons set forth above with respect to claim 3.
Regarding claim 15, the claim recites substantially similar limitations to claim 4. Therefore, claim 15 is similarly rejected for the reasons set forth above with respect to claim 4.
Regarding claim 16, the claim recites substantially similar limitations to claim 6. Therefore, claim 16 is similarly rejected for the reasons set forth above with respect to claim 6.
Regarding claim 17, the claim recites substantially similar limitations to claim 7. Therefore, claim 17 is similarly rejected for the reasons set forth above with respect to claim 7.
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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claim 8 is rejected under 35 U.S.C. 103 as being unpatentable over Smither in view of U.S. P.G. Pub. 2020/0349049 (hereinafter, Krebs).
Regarding claim 8, Smith teaches the computer-implemented method of claim 1, but does not teach a full group consisting of blockchain, cloud computing, IoT, AI, edge computing and 5G computing. However, in the analogous art of workflow optimization, Krebs teaches wherein the plurality of technology fitments is selected from the group consisting of blockchain memory, cloud computing, Internet of Things (IoT) applications, applications for artificial intelligence (AI), applications for edge computing, applications for 5G mobile communications and combinations thereof (¶ 33, “In some examples, the computing environment 100 further comprises a plurality of monitored systems 140 including at least one monitored system 141 which generates event logs 145. A monitored system 141 of the plurality of monitored systems 140 may comprise, for example, a computing device configured to sense an event and generate an event log describing the event. As an illustrative example, the computing device may be closely coupled with an electronic sensor or an array of sensors for sensing events. The monitored systems 140 may comprise components of an industrial automation or control system, Internet of Things hardware, industrial Internet of Things hardware, cloud computation hardware, computer hardware, and so on, as illustrative examples. Each monitored system 141 of the plurality of monitored systems 140 may thus monitor or sense one or more events relating to a process in a system. Further, the plurality of monitored systems 140 may be communicatively coupled to the server 101 via the network 120, which may comprise a radio network, a radio link, WiFi, LPWAN, LPWA, LPN, mobile telephony (e.g., 3G, 4G, 5G telephony), a computer mesh network, a blockchain, an optical transmission network, Bluetooth, a laser communication network, an Ethernet computer network, an optical communication network, a deep space communication network, a vehicular relay station (e.g., a satellite, drone, and/or balloon) network, and/or similar communication technology.”) (¶ 36, “The event log analysis system 200 comprises one or more of an event log intake module 205, an event log analysis module 210, an artificial intelligence (AI) process improvement advisor module 250, and an output module 260.”).
It would have been obvious to one of ordinary skill in the art prior to the effective filing date to combine the workflow of Smith with the particular technology elements of Krebs. One of ordinary skill in the art would have been motivated to combine these teachings for the benefit of real time improvement or optimization of workflows (Krebs, ¶ 58).
Conclusion
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/AMANDA GURSKI/Primary Examiner, Art Unit 3625