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 .
Claims 1-20 are pending in this office correspondence.
Drawings
The Drawings filed on 9/18/2023, have been acknowledged.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 11/22/2023 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
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 abstract idea without significantly more.
Step 1:
The claims are directed to a process and a system, wherein the claimed process may calculate or update task or job execution schedules for a plurality of resources and perform automated actions based on the calculated or updated schedules. This process/system may be used for forecasting or reforecasting task properties for relevant time intervals, where the properties may describe future tasks to be handled by a plurality of resources; calculating an allocation matrix for the time intervals based on the predicted properties; and calculating or updating a schedule based on the calculated allocation matrix.
Step 2A – Prong One – The claims recite an abstract idea
Independent claims 1, 9 and 17 are directed to an abstract idea without significantly more.
The claim(s) recites the following limitation: “for one or more time intervals, predicting, by the processor, a plurality of task properties, each of the task properties describing one or more future tasks to be handled by one or more resources”, which is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind, but for the recitation of generic computer components. That is, other than reciting: “computer processor”, “system” and/or “memory”, nothing in the claim element precludes the steps from practically being performed in a human mind. For example, and given some information at hand, a person is mentally capable, or with the aid of pen and paper, of analyzing information at hand (for example past predictions) and be able to predict/forecast a particular action/task to be performed by a resource/person based on this information analysis, which is a mental process.
The aforementioned claim continues to recite the following – “calculating, by the processor, an allocation matrix for the one or more time intervals based on the predicted task properties, the allocation matrix describing a capacity of the resources to handle the future tasks.” At this step, the cited language of: “calculating, …, an allocation matrix for the one or more time intervals based on the predicted task properties …”, which include includes a series of steps that recite a mathematical calculation/formula for analyzing information and calculating an output based on mathematical steps, which is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind, but for the recitation of generic computer components. That is, other than reciting “computer processor”, “system” and/or “memory”, nothing in the claim element precludes the steps from practically being performed by a person, or with the aid of pen and paper, to analyze information and perform a calculation as explained above, which are steps grouped under abstract idea of mathematical calculation to compute an output.
As explained above, a process of “predicting, …, a plurality of task properties, …” and “calculating, …, an allocation matrix …” are nothing more than an abstract idea. Consequently, if a claim limitation, under its broadest reasonable interpretation, covers an abstract idea that includes a series of steps that recite mental steps, but for the recitation of generic computer components, then it falls within the “Mental Processes and/or Mathematical Calculation” grouping of “Abstract Ideas”. Accordingly, the aforementioned claim(s) recite abstract ideas.
Step 2A – Prong Two - The abstract idea is not integrated into a practical application
This judicial exception is not integrated into a practical application. In particular, the aforementioned claim(s) recites the additional limitation – “updating, by the processor, a schedule based on the calculated allocation matrix, the updating of the schedule comprising automatically extending a break for one or more of the resources, wherein the resources are not to handle tasks during the break.” This recited language of “updating, …, a schedule based on the calculated allocation matrix, …” is considered to be extra-solution activities of mere data transmission activity. In this context, “updating” is an activity that is considered data manipulation activity for simply enabling a person to deal with information/data, and analyze the content of this information, which is considered to be an insignificant extra-solution activity to the judicial exception, for which an extra-solution activity includes both pre-solution and post-solution activity. In this example, the aforementioned claim limitations amount to mere data-updating/transmission step, and is considered an insignificant extra-solution activity because it is a mere nominal or tangential addition to the claim, a mere generic process of transmission of collected and analyzed data, see MPEP 2106.05(g).
The additional elements recited in the aforementioned claim(s) are: “computer processor”, “system” and/or “memory”. The additional elements of using a computer, storage device(s) and processor(s) to obtain information, analyze information, and manipulate information amounts to no more than mere instructions to apply the exception using a generic computer components. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception. See MPEP 2106.05(f).
Step 2B:
The claim(s) do not include additional elements that are sufficient to amount to significantly more than the judicial exception. The insignificant extra-solution activities identified above, which include the data-transmission activities: “updating, …, a schedule based on the calculated allocation matrix, …”, are also considered mere instruction activities, which are recognized by the courts as well-understood, routine, and conventional activities when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity (See MPEP 2106.05(d)(II)(i) Receiving or transmitting data over a network, e.g., using the Internet to gather data, buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network); (v) Presenting offers and gathering statistics, OIP Techs., 788 F.3d at 1362-63, 115 USPQ2d at 1092-93).
Additionally, the “computer processor”, “system” and/or “memory” are recited at a high-level of generality such that it amounts no more than mere instructions to apply the exception using a generic computer component that are well-know and conventional and cannot provide an inventive concept.
Thus, there are no additional elements that amount to significantly more than the above-identified judicial exception (the abstract idea). Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually. There is no indication that any combination of elements improves the functioning of a computer or improves any other technology.
The claim(s) is not patent eligible.
Claim 2 is dependent on claim 1 and includes all the limitations of claim 1. Further, the aforementioned claim recites the additional limitations of “wherein the calculating of an allocation matrix comprises removing one or more of the resources from the allocation matrix, wherein the removing of resources is performed for one or more positive matrix entries, the positive entries representing an excess allocation for one or more of time intervals.” The recited language of “removing one or more of the resources from the allocation matrix …”, recites an insignificant extra-solution activity of data transmission, which does not amount to significantly more than the abstract idea.
Claim 3 is dependent on claim 1 and includes all the limitations of claim 1. The aforementioned claim recites the additional limitations of “wherein the task properties comprise: a volume of tasks, and an average handling time per task”, which recites a mere mental step of information evaluation, which does not amount to significantly more than the abstract idea.
Claim 4 is dependent on claim 1 and includes all the limitations of claim 1. The aforementioned claim recites the additional limitations of “wherein the predicting of the task properties comprises weighting one or more past predictions for the one or more time intervals, the weighting based on comparing the past predictions to a plurality of past task data, the past task data comprising start and end times of a plurality of tasks handled.” The claimed language of “…, the weighting based on comparing the past predictions to a plurality of past task data, …”, and given the broadest reasonable interpretation, recite mere mental steps to compare information at hand against another set of information to produce an outcome, which does not amount to significantly more than the abstract idea.
Claim 5 is dependent on claim 4 and includes all the limitations of claim 4. The aforementioned claim recites the additional limitations of “wherein the calculating of an allocation matrix comprises running a simulation based on: one or more of the task properties, a set of available resources, and the plurality of past task data.” At this step, the claim recites - “… running a simulation based on: one or more of the task properties …”, which include a series of mathematical calculation steps to be performed by a generic computer that apply mere instruction activities, which are recognized by the courts as well-understood, routine, and conventional activities when they are claimed in a merely generic manner, which does not amount to significantly more than the abstract idea.
Claim 6 is dependent on claim 5 and includes all the limitations of claim 5. The aforementioned claim recites the additional limitations of “wherein the simulation is executed during the one or more time intervals, and wherein the past task data describes the one or more time intervals prior to running the simulation.” Again, at this step, the claim recites – “the simulation is executed during the one or more time intervals …”, which disclose steps to be performed by a generic computer that apply mere instruction activities, which are recognized by the courts as well-understood, routine, and conventional activities when they are claimed in a merely generic manner, which does not amount to significantly more than the abstract idea.
Claim 7 is dependent on claim 1 and includes all the limitations of claim 1. The aforementioned claim recites the additional limitations of “wherein the extending of a break is performed for one or more randomly selected resources among the one or more resources”, which recites a mere mental step of information evaluation to be applied by a processor to apply mere instruction steps, which does not amount to significantly more than the abstract idea.
Claim 8 is dependent on claim 1 and includes all the limitations of claim 1. The aforementioned claim recites the additional limitations of “transmitting, by the processor, a task execution command to a remote computer over a communication network, the remote computer to automatically cancel an execution of at least one computer task based updated schedule.” At this step, the claimed language of – “transmitting, by the processor, a task execution command …” recites an insignificant extra-solution activity of data transmission, which does not amount to significantly more than the abstract idea.
Independent claims 9 and 17 recite similar limitations to claim 1 and therefore rejected for the same reasons as explained above.
Dependent claims 10-16 and 18-20, recite similar limitations to dependent claims 2-8, and therefore rejected for the same reasons as explained above.
The aforementioned claims are not patent eligible.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1-4, 7, 9-12, 15 and 17-20 are rejected under 35 U.S.C. 103 as being unpatentable over US Patent Application Publication (US 20240220883 A1) issued to Maciej et al. (hereinafter as “MACIEJ”), and in view of US Patent (US 9740529 B1) issued to Shei et al. (hereinafter as “SHEI”).
Regarding claim 1, MACIEJ teaches a method of resource scheduling, the method comprising, using a computer processor:
for one or more time intervals, predicting, by the processor, a plurality of task properties, each of the task properties describing one or more future tasks to be handled by one or more resources (MACIEJ Para. [0006]: “The disclosed technology further provides the predictive engagement data and scores for evaluating the agent. A schedule generator uses the predictive engagement data to generate a schedule for tasks to be performed by the agent. The schedule reflects the predictive engagement data of the agent by accommodating positive values of the predictive engagement data based on adjusting time, duration, and other aspects of tasks.”; and
Fig.1, Para. [0038]: “The predictive engagement data generator 124 generates predictive engagement data 142 associated with one or more agents. In aspects, the predictive engagement data 142 is based on the historical engagement data 140 and trends of the one or more agents seen in the historical engagement data. In examples, the predictive engagement data generator 124 may generate predictive engagement data 142 associated with future engagements in tasks by the one more agents by extrapolating the historical engagement data.”,
the examiner notes that the reference discloses predictive engagement data based on adjusting time, duration, and other aspects of tasks to that of predicting a plurality of task properties);
calculating, by the processor, an allocation matrix for the one or more time intervals based on the predicted task properties, the allocation matrix describing a capacity of the resources to handle the future tasks (MACIEJ Fig. 1, Para. [0027]: “The agent engagement server 116 includes historical engagement data generator 120, historical engagement score generator 122, predictive engagement data generator 124, predictive engagement score generator 126, and engagement data publisher 128. The agent engagement server 116 may further include historical engagement data 140, predictive engagement data 142, and predictive engagement model 144.”; and
Fig.1, Para. [0038]: “The predictive engagement data generator 124 generates predictive engagement data 142 associated with one or more agents. In aspects, the predictive engagement data 142 is based on the historical engagement data 140 and trends of the one or more agents seen in the historical engagement data. In examples, the predictive engagement data generator 124 may generate predictive engagement data 142 associated with future engagements in tasks by the one more agents by extrapolating the historical engagement data.”,
the examiner notes that the reference discloses a predictive engagement model of future agent engagement of tasks to that of an allocation matrix. Further, the reference discloses an engagement data that include metrics of agent engagement data to that of an allocation matrix describing a capacity of the resources to handle the future tasks.)
However, MACIEJ does not explicitly teach updating, by the processor, a schedule based on the calculated allocation matrix, the updating of the schedule comprising automatically extending a break for one or more of the resources, wherein the resources are not to handle tasks during the break.
But SHEI teaches updating, by the processor, a schedule based on the calculated allocation matrix, the updating of the schedule comprising automatically extending a break for one or more of the resources, wherein the resources are not to handle tasks during the break (SHEI Col. 2, line (26): “A scheduler then uses a scheduling algorithm to produce an initial assignment of available resources to the nodes within each component at defined times. The schedule is then evaluated for possible optimization by first identifying any resource-constrained components, such that the resource is allocated to two different nodes in the graph at two different respective time slots. For each resource used by such a constrained component, the resource having the longest span between an initial busy time slot and a latest busy time slot is then identified. This “longest busy span” may then be used to determine a cycle time for the component. The schedule may then be modified to specify that other resources within the component, which might not otherwise have as long a busy time, are extended or retimed within the schedule to also match the cycle time for the component. These resources may be assigned to idle states during their extended time slots, such that they produce no effect at their outputs, even if their respective applied inputs change.”,
the examiner notes that the reference discloses the process of resource schedule optimization (i.e. updating) by identifying any resource-constrained components for resource allocation to that of a schedule update based on an allocation criterion. Then, the reference discloses and the resources idle state (i.e. break) are extended or retimed within the schedule such that they produce no effect at their outputs to that of “extending a break for one or more of the resources, wherein the resources are not to handle tasks during the break.”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the teachings of MACIEJ (disclosing methods agent/resource engagement analyzer) to include the teachings of SHEI (disclosing methods for resource-constrained scheduling) and arrive at a method to manage resource scheduling and removal based on needs. One of ordinary skill in the art would have been motivated to make this combination because by enabling a resource scheduler to use an algorithm to produce an efficient assignment of available resources thereby making better use of resource-constrained environment, as recognized by (SHEI Abstract, Col. 1-Col. 2). In addition, the references of MACIEJ and SHEI teach features that are directed to analogous art and they are directed to the same field of endeavor of task scheduling and management.
Regarding claims (9 and 17), the aforementioned claims recite similar limitations to claim 1, and therefore rejected for similar reasons as discussed above.
Regarding claim 2, the combination of MACIEJ and SHEI teach the limitations of claim 1. Further, SHEI teaches wherein the calculating of an allocation matrix comprises removing one or more of the resources from the allocation matrix, wherein the removing of resources is performed for one or more positive matrix entries, the positive entries representing an excess allocation for one or more of time intervals (SHEI Col. 2, line (26): “A scheduler then uses a scheduling algorithm to produce an initial assignment of available resources to the nodes within each component at defined times. The schedule is then evaluated for possible optimization by first identifying any resource-constrained components, such that the resource is allocated to two different nodes in the graph at two different respective time slots. For each resource used by such a constrained component, the resource having the longest span between an initial busy time slot and a latest busy time slot is then identified. This “longest busy span” may then be used to determine a cycle time for the component. The schedule may then be modified to specify that other resources within the component, which might not otherwise have as long a busy time, are extended or retimed within the schedule to also match the cycle time for the component. These resources may be assigned to idle states during their extended time slots, such that they produce no effect at their outputs, even if their respective applied inputs change.”).
Regarding claims (10 and 18), the aforementioned claims recite similar limitations to claim 2, and therefore rejected for similar reasons as discussed above.
Regarding claim 3, the combination of MACIEJ and SHEI teach the limitations of claim 1. Further, MACIEJ teaches wherein the task properties comprise: a volume of tasks, and an average handling time per task (MACIEJ Fig. 1, Para. [0028]: “The activity data may include but not limited to agent turnover/retention, customer retention, resolution rate, abandon rate, reliability, time to effective/mastery, proficiency metrics (average handle time, first level resolution, and quality scores), average time to answer, and the like. In aspects, average handle time (AHT) indicates a time it takes for an agent to engage with a contact. AHT includes time spent both on contact and after contact associated with the contact. Quality scores may be determined manually or by machines based on various parameters associated with quality of an agent engaging with contacts.”).
Regarding claims (11 and 19), the aforementioned claims recite similar limitations to claim 3, and therefore rejected for similar reasons as discussed above.
Regarding claim 4, the combination of MACIEJ and SHEI teach the limitations of claim 1. Further, MACIEJ teaches wherein the predicting of the task properties comprises weighting one or more past predictions for the one or more time intervals, the weighting based on comparing the past predictions to a plurality of past task data, the past task data comprising start and end times of a plurality of tasks handled (MACIEJ Para. [0095]: “The plurality of categories of the historical engagement data comprises the historical reliability and historical contact handling, the historical reliability further comprises at least one of: after call work, adherence, conformance associated with a first time the agent spent working compared to a second time the agent was scheduled to work, or voluntary time off; and wherein the historical contact handling includes at least one of: contact difficulty, quality, average handline time associated with a contact, hold time, sentiment, speech analytics, or desktop analytics.”).
Regarding claims (12 and 20), the aforementioned claims recite similar limitations to claim 4, and therefore rejected for similar reasons as discussed above.
Regarding claim 7, the combination of MACIEJ and SHEI teach the limitations of claim 1. Further, SHEI teaches wherein the extending of a break is performed for one or more randomly selected resources among the one or more resources (SHEI Col. 2, line (26): “A scheduler then uses a scheduling algorithm to produce an initial assignment of available resources to the nodes within each component at defined times. The schedule is then evaluated for possible optimization by first identifying any resource-constrained components, such that the resource is allocated to two different nodes in the graph at two different respective time slots. For each resource used by such a constrained component, the resource having the longest span between an initial busy time slot and a latest busy time slot is then identified. This “longest busy span” may then be used to determine a cycle time for the component. The schedule may then be modified to specify that other resources within the component, which might not otherwise have as long a busy time, are extended or retimed within the schedule to also match the cycle time for the component. These resources may be assigned to idle states during their extended time slots, such that they produce no effect at their outputs, even if their respective applied inputs change.”,
the examiner notes that the resource discloses that the work schedule may then be modified to specify that other resources within the component, which might not otherwise have as long a busy time, are extended or retimed within the schedule to that of one or more randomly selected resources among the one or more resources).
Regarding claims (15), the aforementioned claims recite similar limitations to claim 7, and therefore rejected for similar reasons as discussed above.
Claims 5-6 and 13-14 are rejected under 35 U.S.C. 103 as being unpatentable over US Patent Application Publication (US 20240220883 A1) issued to Maciej et al. (hereinafter as “MACIEJ”), in view of US Patent (US 9740529 B1) issued to Shei et al. (hereinafter as “SHEI”), and in view of US Patent Application Publication (US 20090083020 A1) issued to Benayon et al. (hereinafter as “BENAYON”).
Regarding claim 5, the combination of MACIEJ and SHEI teach the limitations of claim 4.
However, the combination of MACIEJ and SHEI does not explicitly teach wherein the calculating of an allocation matrix comprises running a simulation based on: one or more of the task properties, a set of available resources, and the plurality of past task data.
But BENAYON teaches wherein the calculating of an allocation matrix comprises running a simulation based on: one or more of the task properties, a set of available resources, and the plurality of past task data (BENAYON Abstract: “…, loading simulation variables for a simulated task in a model can include loading a level of expertise for a role assigned to the task, loading a time of day for executing the task, or loading a time of year for executing the task.”; and
Para. [0007]: “The method can include loading simulation variables for a simulated attribute such as a simulated task in a model, computing a duration of time for the simulated attribute based upon the simulation variables, and simulating execution of the simulated attribute for the computed duration of time. For example, loading simulation variables for a simulated task in a model can include loading a level of expertise for a role assigned to the task, loading a time of day for executing the task, or loading a time of year for executing the task.”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the combinations teachings of MACIEJ (disclosing methods agent/resource engagement analyzer) and the teachings of SHEI (disclosing methods for resource-constrained scheduling), to include the teachings of BENAYON (disclosing methods for task processing and time modeling) and arrive at a method to incorporate task simulation based of time-driven scheduling model. One of ordinary skill in the art would have been motivated to make this combination because by efficiently utilizing schedule resources and perform a capacity utilization simulation, thereby providing a clear compute resource capacity plan for system users for deployment, as recognized by (BENAYON Abstract, Para. [0001]-[0010]). In addition, the references of MACIEJ, SHEI and BENAYON teach features that are directed to analogous art and they are directed to the same field of endeavor of task scheduling and management.
Regarding claim (13), the aforementioned claims recite similar limitations to claim 5, and therefore rejected for similar reasons as discussed above.
Regarding claim 6, the combination of MACIEJ, SHEI and BENAYON teach the limitations of claim 5. Further, BENAYON teaches wherein the simulation is executed during the one or more time intervals, and wherein the past task data describes the one or more time intervals prior to running the simulation (BENAYON Para. [0009]: “The system further can include a variable task duration processor coupled to the simulation engine. In this regard, the processor can include program code enabled to compute and assign variable durations of execution to different tasks in a model under simulation in the simulation engine according to observed simulation variables for the model. Optionally, a mapping of variable expressions to corresponding durations of execution can be provided where the expressions each are dependent upon at least one of the simulation variables.”).
Regarding claim (14), the aforementioned claims recite similar limitations to claim 6, and therefore rejected for similar reasons as discussed above.
Claims 8 and 16 are rejected under 35 U.S.C. 103 as being unpatentable over US Patent Application Publication (US 20240220883 A1) issued to Maciej et al. (hereinafter as “MACIEJ”), in view of US Patent (US 9740529 B1) issued to Shei et al. (hereinafter as “SHEI”), and in view of US Patent Application Publication (US 2005/0114858 A1) issued to Miller et al. (hereinafter as “MILLER”).
Regarding claim 8, the combination of MACIEJ and SHEI teach the limitations of claim 1.
However, the combination of MACIEJ and SHEI does not explicitly teach transmitting, by the processor, a task execution command to a remote computer over a communication network, the remote computer to automatically cancel an execution of at least one computer task based updated schedule.
But MILLER teaches transmitting, by the processor, a task execution command to a remote computer over a communication network, the remote computer to automatically cancel an execution of at least one computer task based updated schedule (MILLER Abstract: “A method and a task scheduler for canceling a task in a computer system, wherein the task scheduler manages a plurality of tasks using at least one task queue. The task scheduler is arranged to free resources assigned to a cancelled task of the plurality of tasks when the cancelled task reaches the top of any of the at least one task queue. The method comprises steps of identifying a task from the plurality of tasks as a cancelled task, actively prioritizing the identified task to the top of its corresponding task queue and allowing the task scheduler to free resources assigned to the identified task.”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the combinations teachings of MACIEJ (disclosing methods agent/resource engagement analyzer) and the teachings of SHEI (disclosing methods for resource-constrained scheduling), to include the teachings of MILLER (disclosing methods for cancelled task management in a computer system) and arrive at a method to incorporate task control in a distributed system. One of ordinary skill in the art would have been motivated to make this combination because by cancelling task based of an intelligent task scheduler, thereby providing an efficient system performance, as recognized by (MILLER Abstract, Para. [0004]-[0007]). In addition, the references of MACIEJ, SHEI and MILLER teach features that are directed to analogous art and they are directed to the same field of endeavor of task scheduling and management.
Regarding claims (16), the aforementioned claims recite similar limitations to claim 8, and therefore rejected for similar reasons as discussed above.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Gopalan et al.; (US 20200104189 A1); “Methods workload placement with forecast, wherein tasks, such as applications or virtual machines, can be allocated across a fleet of physical machines in a cluster of host machines by a resource scheduler. The resource scheduler can allocate and balance workloads across host machines that are aggregated into logical resource pools.”
Silverman et al.; (US 20220180276 A1); “Methods for forecasting using events, wherein receiving an indicator of a future time interval by the computing device and then determining event data for the future time interval by the computing device and estimating demand for the future time interval using the first forecasting model and the determined event data for the future time interval by the computing device.
Piazza et al.; (US 20110161964 A1); “Methods for optimized scheduling of time-sensitive tasks in a resource-constrained environment.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Zuheir A Mheir whose telephone number is (571)272-4151. The examiner can normally be reached on Monday - Friday 9:00 - 5:00.
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12/13/2025
/ZUHEIR A MHEIR/Patent Examiner, Art Unit 2156
/PIERRE VITAL/Supervisory Patent Examiner, Art Unit 2198