DETAILED ACTION
This Office Action is in response to Applicants application filing received on March 14, 2025. Claim(s) 1-20 is/are currently pending in the instant application. The application claims priority
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 .
Drawings
The drawings are objected to because the drawings several of the drawings are not clear enough.
Fig. 3 is objected to as the provided copy and the file copy are illegible in the current state. The Examiner also suggests the Applicant change the orientation of the figure from portrait ro landscape in order to utilize more of the page.
PNG
media_image1.png
896
812
media_image1.png
Greyscale
Fig. 4A is objected to as the provided copy is unable to read the text.
PNG
media_image2.png
610
804
media_image2.png
Greyscale
Fig. 4B is objected to as the text is not easily readable and it appears that several words are underlined for their spelling and grammar.
PNG
media_image3.png
632
812
media_image3.png
Greyscale
Figures 10-12 contain text in which the provided copy are fuzzy. The file copies are slightly better (only Fig. 12 is provided for example)
PNG
media_image4.png
566
814
media_image4.png
Greyscale
Corrected drawing sheets in compliance with 37 CFR 1.121(d) are required in reply to the Office action to avoid abandonment of the application. Any amended replacement drawing sheet should include all of the figures appearing on the immediate prior version of the sheet, even if only one figure is being amended. The figure or figure number of an amended drawing should not be labeled as “amended.” If a drawing figure is to be canceled, the appropriate figure must be removed from the replacement sheet, and where necessary, the remaining figures must be renumbered and appropriate changes made to the brief description of the several views of the drawings for consistency. Additional replacement sheets may be necessary to show the renumbering of the remaining figures. Each drawing sheet submitted after the filing date of an application must be labeled in the top margin as either “Replacement Sheet” or “New Sheet” pursuant to 37 CFR 1.121(d). If the changes are not accepted by the examiner, the applicant will be notified and informed of any required corrective action in the next Office action. The objection to the drawings will not be held in abeyance.
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 a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
Claims 1-20 are directed to one of the four statutory classes of invention (e.g. process, machine, manufacture, or composition of matter). The claims include a system or “apparatus”, method or “process”, or product or “article of manufacture” and is a method and a product for forecasting for enterprises which is a process (Step 1: YES).
The Examiner has identified independent method Claim 1 as the claim that represents the claimed invention for analysis and is similar to independent product Claim 11. Claim 1 recites the limitations of (abstract ideas highlighted in italics and additional elements highlighted in bold)
collecting first data from a first data source using a first protocol;
collecting second data from a second data source using a second protocol different from the first protocol;
generating an indexed data store comprising at least a portion of the first data and at least a portion of the second data; and
forecasting a resource availability based on data in the indexed data store.
These limitations, under their broadest reasonable interpretation, cover performance of the limitation as “Mental Processes”. Collecting first and second data from different sources, storing the data in an indexed storage, and forecasting resource availability recites concepts performed in the human mind. But for the “first and second data sources”, “first and second protocols”, and “indexed data store”, the claim encompasses collecting data form two sources to be stored in an indexed source for forecasting resource availability using his/her mind. The mere nominal recitation of generic data sources and protocols with known storge methods does not take the claim limitation out of the mental processes grouping. Accordingly, the claim recites an abstract idea. The non-transitory machine-readable medium having executable instructions to cause a processor in Claim 11 appears to be just software. Claim 11 is also abstract for similar reasons. (Step 2A-Prong 1: YES. The claims are abstract)
These limitations, under their broadest reasonable interpretation, cover performance of the limitation as “Certain Methods of Organizing Human Activity”. Collecting first and second data from different sources, storing the data in an indexed storage, and forecasting resource availability recites managing personal behavior or relationships. Accordingly, the claim recites an abstract idea. The non-transitory machine-readable medium having executable instructions to cause a processor in Claim 11 appears to be just software. Claim 11 is also abstract for similar reasons. (Step 2A-Prong 1: YES. The claims are abstract)
This judicial exception is not integrated into a practical application. In particular, the claims only recite computer [preamble] (Claim 1) and/or non-transitory machine-readable medium having executable instructions and one or more processing units (Claim 11). The computer hardware is recited at a high-level of generality (i.e., as a generic processor performing a generic computer function) such that it amounts no more than mere instructions to apply the exception using a generic computer component. Accordingly, these additional elements, when considered separately and as an ordered combination, do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. Therefore claims 1 and 11 are directed to an abstract idea without a practical application. (Step 2A-Prong 2: NO. The additional claimed elements are 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 because, when considered separately and as an ordered combination, they do not add significantly more (also known as an “inventive concept”) to the exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of using a computer hardware amounts to no more than mere instructions to apply the exception using a generic computer component. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. See Applicant’s specification para. [0091] about implementation using general purpose or special purpose computing devices (FIG. 1 depicts at 100 a computer-implemented environment wherein users 102 can interact with a system 104 hosted on one or more servers 106 through a network 108. The system 104 contains software operations or routines. The users 102 can interact with the system 104 through a number of ways, such as over one or more networks 108. One or more servers 106 accessible through the network(s) 108 can host system 104. It should be understood that the system 104 could also be provided on a stand-alone computer for access by a user.) and MPEP 2106.05(f) where applying a computer as a tool is not indicative of significantly more. Accordingly, these additional elements, when considered separately and as an ordered combination, do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. Thus claims 1 and 11 are not patent eligible. (Step 2B: NO. The claims do not provide significantly more)
Dependent claims 2-10 and 12-20 further define the abstract idea that is present in their respective independent claims 1 and 11 and thus correspond to Certain Methods of Organizing Human Activity and/or Mental Processes and hence are abstract for the reasons presented above. The dependent claims do not include any additional elements that integrate the abstract idea into a practical application or are sufficient to amount to significantly more than the judicial exception when considered both individually and as an ordered combination. The dependent claims include steps or processes which are similar to that disclosed in MPEP 2106.05(d), (f), (g), and/or (h) which include activities and functions the courts have determined to be well-understood, routine, and conventional when claimed in a generic manner, or as insignificant extra solution activity, or as merely indicating a field of use or technological environment in which to apply the judicial exception.
Claims 2, 3, 12, and 13 correspond to MPEP 2106.05(d)II. iv. Storing and retrieving information in memory, Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015); OIP Techs., 788 F.3d at 1363, 115 USPQ2d at 1092-93;
Claims 4, 10, 14 and 20 are equitable to MEPE 2106.05(f)(2) v. Requiring the use of software to tailor information and provide it to the user on a generic computer, Intellectual Ventures I LLC v. Capital One Bank (USA), 792 F.3d 1363, 1370-71, 115 USPQ2d 1636, 1642 (Fed. Cir. 2015);
Claims 5, 6, 15, and 16 are covered by MPEP 2106.05(f)(2) i. A commonplace business method or mathematical algorithm being applied on a general purpose computer, Alice Corp. Pty. Ltd. V. CLS Bank Int’l, 573 U.S. 208, 223, 110 USPQ2d 1976, 1983 (2014); Gottschalk v. Benson, 409 U.S. 63, 64, 175 USPQ 673, 674 (1972); Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015);
Claims 7 and 17 are similar to MPEP 2106.05(f)(2) i. A commonplace business method or mathematical algorithm being applied on a general purpose computer, Alice Corp. Pty. Ltd. V. CLS Bank Int’l, 573 U.S. 208, 223, 110 USPQ2d 1976, 1983 (2014); Gottschalk v. Benson, 409 U.S. 63, 64, 175 USPQ 673, 674 (1972); Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015); and 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);
Claims 8 and 18 correspond to 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);
Claims 9 and 19 are comparable to MPEP 2106.05(d)II. ii. Performing repetitive calculations, Flook, 437 U.S. at 594, 198 USPQ2d at 199 (recomputing or readjusting alarm limit values); Bancorp Services v. Sun Life, 687 F.3d 1266, 1278, 103 USPQ2d 1425, 1433 (Fed. Cir. 2012) ("The computer required by some of Bancorp’s claims is employed only for its most basic function, the performance of repetitive calculations, and as such does not impose meaningful limits on the scope of those claims.");
Therefore, the claims 2-10 and 12-20 are directed to an abstract idea. Thus, the claims 1-20 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 (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 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(s) 1-6 and 11-16 is/are rejected under 35 U.S.C. 103 as being unpatentable over Porter et al. U.S. Publication 2018/0033079 A1 (hereafter Porter) in view of Octagon I/O Ltd. WO 2025/080321 A1 (hereafter Octagon).
Regarding claim 1, Porter discloses collecting first data from a first data source (see at least [0002] based on information related to the resources, such as resources located within a building structure, based on information collected in databases and/or by robots having indoor location determination devices to guide their movements in the building structure.);
collecting second data from a second data source (see at least [0002] based on information related to the resources, such as resources located within a building structure, based on information collected in databases and/or by robots having indoor location determination devices to guide their movements in the building structure.);
generating an indexed data store comprising at least a portion of the first data and at least a portion of the second data (see at least [0109] capturing operation data of the robots, including photo images obtained using cameras of the robots; storing, in the database, status data of the spaces and the operation data of the robots; combining, by the server connected to the database, the status data and the operation data of the robots to generate a prediction of availability of the spaces; [0051] the scanning of the RFID tags allow the robot (101) to determine the presence of a particular item that is available for purchase at a particular location within a particular retailer store. The information is indexed for search, such that a user can quickly locate the item for inspection.) ; and
forecasting a resource availability based on data in the indexed data store (see at least [0109] combining, by the server connected to the database, the status data and the operation data of the robots to generate a prediction of availability of the spaces; and providing a user interface to present the prediction.).
Porter does not cover the use of multiple protocols which are different.
Octagon discloses, in the same field of invention, the use of multiple protocols for extracting data from different sources where some data is gathered from a first data source using a first protocol (see at least [0226] Data extraction from communications devices, for example connected devices with communications capabilities, may be achieved through the use of communications protocols. For example MQTT, may be used for real-time data extraction. Devices may be configured to transmit data directly to servers using HTTP/HTTPS protocols.); and
a second data source using a second protocol different from the first (see at least [0226] Devices may be configured to transmit data directly to servers using HTTP/HTTPS protocols. HTTP/HTTPS is different from MQTT) therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to use the resource availability forecast as disclosed by Porter with the multiple protocols for data collection as taught by Octagon as combination of know prior art elements yields predictable results (KSR A).
Regarding claim 2, the combination of Porter and Octagon discloses wherein the first data source comprises at least one of an enterprise resource planning (ERP) system, an accounts payable and credit management system, a human capital management system, a case management system, a customer relationship management (CRM) system, or a point-of-sale system (see at least Octagon [0216] This may include integration with existing enterprise resource planning (ERP) systems for example, to ingest inventory records and compliance documentation.).
Regarding claim 3, the combination of Porter and Octagon discloses wherein the second data source is different from the first data source and the second data source comprises at least one of the enterprise resource planning (ERP) system, the accounts payable and credit management system, the human capital management system, the case management system, the customer relationship management (CRM) system, or the point-of-sale system (see at least Porter [0089] Examples of data that can be used to identify and quantify the risk include: space type (inline, big box, kiosk etc.), tenant type (boutique, fast fashion, food retail, restaurant etc.), occupancy ratio, leasing revenue, lease term, sales information, accounts receivable data (balance outstanding, overdue etc.), tenant financial health, brand sentiment/market sentiment data, and design and construction schedules for tenant build-outs.).
Regarding claim 4, the combination of Porter and Octagon discloses wherein the collecting the first and second data comprises a database ingestion pattern, a flat file ingestion pattern, an application programming interfaces / software as a service (API/SaaS) ingestion pattern (see at least Porter [0050] the robot (101) is programmed to un-dock at a defined frequency, collect/record mall data, re-dock and upload new content to be consumed via API remotely.), or a data exchange ingestion pattern.
Regarding claim 5, the combination of Porter and Octagon discloses wherein the resource availability is forecasted using an artificial intelligence (AI) model (see at least Octagon [0091] the server 200 may deploy one or more machine learning (ML) models to perform the operations described herein. To this end, the server 200 may include a machine learning (ML) module 208 comprising circuitry configured to ingest data, such as a multivariate N-dimensional space of time-series data where N is the number of different measurement types (e.g., data of different types) and, via a various ML and/or artificial intelligence techniques described hereafter, and output location determinations, interaction determination, state determination, and/or spatio-temporal sequences. [0229] the methods herein may be implemented using one or a plurality of Artificial Intelligence (AI) Models. This may be any kind of Model named herein and/or any model one skilled in the art may understand to be an AI Model. In such a case, the methods herein may comprise training the AI Model to generate desired outputs. Training may include two parts: preparing a training dataset for ingestion; and the implementation of one or a plurality of training techniques, methods or procedures, which in some embodiments may comprise a training utility function. Choice of the latter may include any technique described herein and/or any training technique recognized as such by one skilled in the art.).
Regarding claim 6, the combination of Porter and Octagon discloses further comprising forecasting a personalized resource availability and providing the personalized forecasted resource availability to a user via an AI interactive platform (see at least Porter [0090] the interactive plan (231) is configured to present planned availability and unplanned availability. Planned availability is the actual space availability that occurs in between tenant expiries and new tenant RCDs. Unplanned Availability is the predicted vacancy of “at-risk” tenants that would result in lost cash flow. The server (139) is configured to compute the value of planned availability of retailer spaces based on the downtime between coming and going tenants and incorporating an achievable rental rate (e.g., rent per unit area of a retail space ($/sf)) for pop-up shops as specified by the leasing department.).
Claim 11 is substantially similar to claim 1 and therefore rejected under the same rationale.
Claim 12 is substantially similar to claim 2 and therefore rejected under the same rationale.
Claim 13 is substantially similar to claim 3 and therefore rejected under the same rationale.
Claim 14 is substantially similar to claim 4 and therefore rejected under the same rationale.
Claim 15 is substantially similar to claim 5 and therefore rejected under the same rationale.
Claim 16 is substantially similar to claim 6 and therefore rejected under the same rationale.
Allowable Subject Matter
Claims 7-10, 17-20 are allowed. The following is a statement of reasons for the indication of allowable subject matter:
7. The computer-implemented method of claim 6, wherein providing the personalized forecasted resource availability to the user comprises:
exporting historical user interaction data from an analytics platform to a data store;
interacting with the user while tracking user interactions via a tag;
submitting the user interaction event to a cloud computing infrastructure; and
providing the personalized resource availability to the user.
8. The computer-implemented of claim 7, wherein the user interacts with the platform via voice or chat.
9. The computer-implemented method of claim 1, wherein forecasting the resource availability comprises identifying available pantries as food sources in response to food demand.
10. The computer-implemented method of claim 6, wherein forecasting the personalized resource availability comprises conducting user location-based search, conducting resource mapping, using search filters, conducting equitable resource mapping, and providing recommendations and suggestions, and user reviews and ratings, and information regarding forecasted resource availability.
Claim 17 is substantially similar to claim 7 and therefore rejected under the same rationale.
Claim 18 is substantially similar to claim 8 and therefore rejected under the same rationale.
Claim 19 is substantially similar to claim 8 and therefore rejected under the same rationale.
Claim 20 is substantially similar to claim 10 and therefore rejected under the same rationale.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. The cited prior art generally refers to resource allocation forecasting and associated methods and systems.
U.S. Publication 2014/0058794 A1 - A system, a computer program product, and a method for order planning and optimization are disclosed. A first data is received, where the first data represents historical shipment data of an item from a distributor to a location. The received first data is processed and a model for at least one shipping pattern of the item from the distributor to the location is determined based on the processed received first data. A forecast for a future shipping demand of the item by the location is generated based on the determined model. At least one shipping pattern of the item from the distributor to the location is optimized based on the generated forecast.
U.S. Publication 2023/0267484 A1 - A system and method for providing a robust and effective solution for forecasting inventory for a warehouse/fulfilment centre (FC) at a product batch level. The method includes calculating a demand forecast data based on a forecast algorithm, correcting the calculated demand forecast data based on one or more exogenous variable, categorizing the inventory into different buckets at a product batch level, forecasting a warehouse level inventory demand for a predefined time based on the categorization, and sending an alert to one or more users based on the categorization. The method further includes predicting a demand forecast data for one or more upcoming weeks.
U.S. Publication 2017/0024751 A1 - In some embodiments, methods and systems of forecasting consumer demand for products at fresh food departments of a grocery store include determining an actual past demand for the product by obtaining a total number of the product sold by the fresh food department in one or more weeks preceding a current week, then calculating a seasonality index for the one or more weeks, deseasonalizing the total number of the product sold in the one or more weeks based on the calculated seasonal index to obtain an initial weekly demand forecast for the product during a single week following the current week, and adding a buffer quantity of the product to the initial weekly demand forecast for the product during the single week following the current week to obtain a refined weekly demand forecast for the product for the single week following the current week.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to DYLAN C WHITE whose telephone number is (571)272-1406. The examiner can normally be reached M-F 7:30-4:00 EST.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Beth Boswell can be reached at (571)272-6737. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/DYLAN C WHITE/Primary Examiner, Art Unit 3625 June 10, 2026
Prosecution Insights