DETAILED ACTION
Status of Claims
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
This action is a non-final, first office action in response to the Applicant's Request for Continued Prosecution filed 12 November 2025.
Claims 1, 14, and 20 have been amended.
The previous 112 (a) rejection for claims 1-20 has been overcome by amendments.
Claims 1-20 are currently pending and have been examined.
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 12 November 2025 has been entered.
Response to Arguments
Applicant's arguments filed 12 November 2025 with regards to the 101 rejection have been fully considered but they are not persuasive.
With respect to the claims, the Applicant argues on page 14 of their response, “The system and its accompanying functionality provides a concrete technological solution that ‘automatically generate[s]’ map routing so that ‘each stop along the route presents a good opportunity for the business to generate sales and connect with an optimal number of customers,’ mirroring the specification's disclosure (specification paragraph, [0040], sentences 3-4), and uses the disclosed forecasting inputs (specification paragraph, [0038], sentences 1-3; [0040], sentences 1-2, 5-6). The system is not merely organizing human activity or displaying information. The real-time recomputation in response to changing sensor-driven inputs and the maximization of expected opportunity to form a multi-stop route reflect a specific improvement in computer-implemented routing on digital maps.” The Examiner respectfully disagrees with the Applicant’s interpretation of the requirements under 35 USC 101, the bounds of the claimed invention, and the grounds of the previous and current rejection. First, with respect to the Applicant’s argument that, “the system and its accompanying functionality provides a concrete technological solution that ‘automatically generate[s]’ map routing so that ‘each stop along the route presents a good opportunity for the business to generate sales and connect with an optimal number of customers,’” and, “uses the disclosed forecasting inputs,” the Examiner is not persuaded. In this case, generating routing on a digital map was shown in paragraph 22 of the previous Final Rejection, as reciting an abstract idea. Specifically, the Final Rejection stated, “In addition, generating predictions/forecasts for future locations of the food truck, generating a proposed trip, and presenting a proposed route on a map; encompasses the performance of marketing, and managing the behaviors and interactions between people.” In this case, the Applicant has failed to refute the stated rejected, merely referring to a technological solution. It is noted that MPEP 2106.05(a) states, “In determining patent eligibility, examiners should consider whether the claim "purport(s) to improve the functioning of the computer itself" or "any other technology or technical field." Alice Corp. Pty. Ltd. v. CLS Bank Int’l, 573 U.S. 208, 225, 110 USPQ2d 1976, 1984 (2014). This consideration has also been referred to as the search for a technological solution to a technological problem. See e.g., DDR Holdings, LLC. v. Hotels.com, L.P., 773 F.3d 1245, 1257, 113 USPQ2d 1097, 1105 (Fed. Cir. 2014); Amdocs (Israel), Ltd. v. Openet Telecom, Inc., 841 F.3d 1288, 1300-01, 120 USPQ2d 1527, 1537 (Fed. Cir. 2016).” (Emphasis added). In this case, the Applicant has asserted that the claims provide a technological solution, however they have failed to identify a technological problem that the solution is for. Notably, MPEP 2106.05(a)(II) states, “Notably, the court did not distinguish between the types of technology when determining the invention improved technology. However, it is important to keep in mind that an improvement in the abstract idea itself (e.g. a recited fundamental economic concept) is not an improvement in technology. For example, in Trading Technologies Int’l v. IBG, 921 F.3d 1084, 1093-94, 2019 USPQ2d 138290 (Fed. Cir. 2019), the court determined that the claimed user interface simply provided a trader with more information to facilitate market trades, which improved the business process of market trading but did not improve computers or technology.” (Emphasis added). As shown here, an improvement in the abstract idea, is not an improvement in technology. With respect to the Applicant’s argument, the Applicant has failed to show a technological problem that is solved by a technological solution, which is recited within the claims. Second, with regards to the Applicant’s argument that, “the real-time recomputation in response to changing sensor-driven inputs and the maximization of expected opportunity to form a multi-stop route reflect a specific improvement in computer-implemented routing on digital maps,” the Examiner is not persuaded. With regards to this argument, it is noted that the Applicant has failed to provide a written description support for, “the real-time recomputation in response to changing sensor-driven inputs and the maximization of expected opportunity to form a multi-stop route reflect a specific improvement in computer-implemented routing on digital maps,” and as such, the specific claim elements amended in the claim are rejected under 112a. Additionally, with regards to the Applicant’s argument that recomputing routing responsive to changes in a prediction or forecast and the customer location, is deemed further reciting an abstract of generating a route for a delivery vehicle based on collected information. With regards to the argument that this reflects reflect a specific improvement in computer-implemented routing on digital maps, the Examiner is not persuaded, as the Applicant has failed to articulate the specific improvement in generating routes on digital maps achieved with the claimed elements, and instead, has merely made a conclusory statement of an improvement. MPEP 2106.05(a) states, “If it is asserted that the invention improves upon conventional functioning of a computer, or upon conventional technology or technological processes, a technical explanation as to how to implement the invention should be present in the specification. That is, the disclosure must provide sufficient details such that one of ordinary skill in the art would recognize the claimed invention as providing an improvement. The specification need not explicitly set forth the improvement, but it must describe the invention such that the improvement would be apparent to one of ordinary skill in the art. Conversely, if the specification explicitly sets forth an improvement but in a conclusory manner (i.e., a bare assertion of an improvement without the detail necessary to be apparent to a person of ordinary skill in the art), the examiner should not determine the claim improves technology. An indication that the claimed invention provides an improvement can include a discussion in the specification that identifies a technical problem and explains the details of an unconventional technical solution expressed in the claim, or identifies technical improvements realized by the claim over the prior art. For example, in McRO, the court relied on the specification’s explanation of how the particular rules recited in the claim enabled the automation of specific animation tasks that previously could only be performed subjectively by humans, when determining that the claims were directed to improvements in computer animation instead of an abstract idea. McRO, 837 F.3d at 1313-14, 120 USPQ2d at 1100-01. In contrast, the court in Affinity Labs of Tex. v. DirecTV, LLC relied on the specification’s failure to provide details regarding the manner in which the invention accomplished the alleged improvement when holding the claimed methods of delivering broadcast content to cellphones ineligible. 838 F.3d 1253, 1263-64, 120 USPQ2d 1201, 1207-08 (Fed. Cir. 2016).” (Emphasis added). In this case, the Applicant’s argument has merely asserted the claims recite an improvement in generating route on digital maps; however they have failed to provide a technical description in their specification that would show how to implement the claimed element of, “dynamically recompute the routing in real time responsive to changes in at least one of the prediction or forecast and the customer device location,” nor have they disclosed that such an element is an technological improvement. As such, the Applicant’s argument is deemed conclusory, and not persuasive; therefore, the Examiner maintains that this rejection is proper.
The Applicant continues on page 14 of their response, “With regard to Step 2A, Prong Two: Even if the Office were to view the commercial objective (connecting with customers) as abstract, the claims integrate that objective into a practical application that improves the functioning of the computer-implemented mapping/routing system. The claimed system requires particular machine processing: GPS-based vehicle location, customer device sensor signals, generation and rendering of a digital map with specific layers (vehicle(s), other vehicles, customer device), and an automatic routing engine that selects a subset of stops via a maximization procedure and recomputes the route dynamically in real time when the forecast or customer device location changes. The foregoing is far more than ‘collect/analyze/display’, the system transforms inputs into a route output that is continuously recomputed as inputs change.” The Examiner respectfully disagrees with the Applicant’s interpretation of the requirements under 35 USC 101, the bounds of the claimed invention, and the grounds of the previous and current rejection. First, with respect to the Applicant’s argument that the claims require particular machine processing, the Examiner is not persuaded. In this case, claim 1 recites the use generic computer elements, particularly, “at least one global positioning sensor positioned in proximity to a vehicle,” and “a memory that stores instructions; a processor that executes instructions.” Notably, these components are not particular machines, but instead merely generic computer elements and machines being used as tools. It is noted that MPEP 2106.05(b) states, “The particularity or generality of the elements of the machine or apparatus, i.e., the degree to which the machine in the claim can be specifically identified (not any and all machines). One example of applying a judicial exception with a particular machine is Mackay Radio & Tel. Co. v. Radio Corp. of America, 306 U.S. 86, 40 USPQ 199 (1939). In this case, a mathematical formula was employed to use standing wave phenomena in an antenna system. The claim recited the particular type of antenna and included details as to the shape of the antenna and the conductors, particularly the length and angle at which they were arranged. 306 U.S. at 95-96; 40 USPQ at 203. Another example is Eibel Process, in which gravity (a law of nature or natural phenomenon) was applied by a Fourdrinier machine (which was understood in the art to have a specific structure comprising a headbox, a paper-making wire, and a series of rolls) arranged in a particular way to optimize the speed of the machine while maintaining quality of the formed paper web. Eibel Process Co. v. Minn. & Ont. Paper Co., 261 U.S. 45, 64-65 (1923).” (Emphasis added). The section continues, “It is important to note that a general purpose computer that applies a judicial exception, such as an abstract idea, by use of conventional computer functions does not qualify as a particular machine. Ultramercial, Inc. v. Hulu, LLC, 772 F.3d 709, 716-17, 112 USPQ2d 1750, 1755-56 (Fed. Cir. 2014). See also TLI Communications LLC v. AV Automotive LLC, 823 F.3d 607, 613, 118 USPQ2d 1744, 1748 (Fed. Cir. 2016) (mere recitation of concrete or tangible components is not an inventive concept); Eon Corp. IP Holdings LLC v. AT&T Mobility LLC, 785 F.3d 616, 623, 114 USPQ2d 1711, 1715 (Fed. Cir. 2015) (noting that Alappat’s rationale that an otherwise ineligible algorithm or software could be made patent-eligible by merely adding a generic computer to the claim was superseded by the Supreme Court’s Bilski and Alice Corp. decisions). If applicant amends a claim to add a generic computer or generic computer components and asserts that the claim recites significantly more because the generic computer is 'specially programmed' (as in Alappat, now considered superseded) or is a 'particular machine' (as in Bilski), the examiner should look at whether the added elements integrate the exception into a practical application or provide significantly more than the judicial exception. Merely adding a generic computer, generic computer components, or a programmed computer to perform generic computer functions does not automatically overcome an eligibility rejection. Alice Corp. Pty. Ltd. v. CLS Bank Int’l, 573 U.S. 208, 223-24, 110 USPQ2d 1976, 1983-84 (2014). See In re Alappat, 33 F.3d 1526, 1545, 31 USPQ2d 1545, 1558 (Fed. Cir. 1994); In re Bilski, 545 F.3d 943, 88 USPQ2d 1385 (Fed. Cir. 2008).” (Emphasis added). In this case, merely invoking the use of generic computer elements and machines to carry out the abstract idea and generic computer functions, does not overcome the eligibility rejection. Additionally, it is noted that the claims further recite that these components interact with a “graphical user interface,” “customer device,” “sensor of the customer device,” and “digital map;” which are merely further generic computer elements and machines. Notably, MPEP 2106.05(f) states, “Whether the claim invokes computers or other machinery merely as a tool to perform an existing process. Use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not integrate a judicial exception into a practical application or provide significantly more. See Affinity Labs v. DirecTV, 838 F.3d 1253, 1262, 120 USPQ2d 1201, 1207 (Fed. Cir. 2016) (cellular telephone); TLI Communications LLC v. AV Auto, LLC, 823 F.3d 607, 613, 118 USPQ2d 1744, 1748 (Fed. Cir. 2016) (computer server and telephone unit). Similarly, "claiming the improved speed or efficiency inherent with applying the abstract idea on a computer" does not integrate a judicial exception into a practical application or provide an inventive concept. Intellectual Ventures I LLC v. Capital One Bank (USA), 792 F.3d 1363, 1367, 115 USPQ2d 1636, 1639 (Fed. Cir. 2015).” (Emphasis added). In this case, the mere use of these generic computer and machine elements to perform an existing process, and in their ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) shows that they do not integrate the recited abstract idea into a practical application. Second, with regards to the Applicant’s argument regarding “specific layers” and an “automatic routing engine,” it is noted that these elements are not recited in the claims, and thus would be beyond the scope of the claims, and would not be relevant to determining if the claims are directed to non-patent eligible subject matter or not. Third, with regards to the Applicant’s argument that, “the system transforms inputs into a route output that is continuously recomputed as inputs change,” and this is more than “collect/analyze/display,” and thus integrates the abstract idea into a practical application, the Examiner is not persuaded. In this case, it is noted that generating a route for a proposed trip through stops that connect an optimal number of customers, determining an expected opportunity for each of a plurality of candidate stops to connect with an optimal number of customers, selecting a subset of the candidate stops, and rendering the routing through the subset of the candidate stops on a map; are all elements that recite an abstract idea of generating a service map for a mobile merchant that maximizes potential audiences, which is merely managing commercial activity and human behavior. In addition, dynamically recompute the routing in real time responsive to changes in at least one of the prediction or forecast and the customer device location; encompasses merely adjusting the route to a new route based on new information, which further repeats the described abstract idea, and improves on it, which is insufficient to integrate an abstract idea into a practical application. Therefore, the Examiner maintains that this rejection is proper.
The Applicant continues on pages 14 and 15 of their response, “Additionally, the claims are not practicable as mental steps: computing expected opportunity across candidate stops from event/search/activity/query-based prediction signals, maximizing that expected opportunity subject to routing constraints, rendering a multi-stop route, and dynamically recomputing it in real time as sensor and forecast inputs change cannot be performed "with pen and paper." The recited operations produce a concrete result within the mapping system (a computed route through a selected subset of stops that is re-rendered in real time as inputs change), not merely a user instruction or advice.” The Examiner respectfully disagrees with the Applicant’s interpretation of the requirements under 35 USC 101, the bounds of the claimed invention, and the grounds of the previous and current rejection. With regards to the Applicant’s argument that the claims cannot practically be performed as mental steps, the Examiner notes that the previous rejection (see paragraph 22 of the previous Final Rejection), did not state that the claims recited an abstract idea in the “Mental Processes” grouping of abstract ideas; and thus, the Applicant’s argument regarding this grouping is not persuasive, as it is not reflective of the specifically given rejection. Therefore, the Examiner maintains that this rejection is proper.
The Applicant continues on page 15 of their response, “With regard to Step 2B, the additional elements, viewed as an ordered combination, amount to significantly more than any alleged abstract concept. The claims do not merely invoke generic computers. They recite a specific implementation: (i) vehicle GPS sensors and customer device sensors to obtain live positional signals; (ii) computing, for candidate stops, an expected opportunity to connect with an optimal number of customers based on event/search/activity/query inputs; (iii) selecting a subset of stops by maximizing that expected opportunity; (iv) rendering on a digital map; and (v) dynamically recomputing the routing in real time in response to changes in the forecast and/or the customer device location. This is a defined rule-based technique that changes how the mapping/routing system operates and how it updates route outputs in real time. Claims 14 and 20 include similar recitations as found in amended claim 1 and the arguments for claim 1 are applied to claims 14 and 20.” The Examiner respectfully disagrees with the Applicant’s interpretation of the requirements under 35 USC 101, the bounds of the claimed invention, and the grounds of the previous and current rejection. First, with respect to the Applicant’s argument that the claims do not merely invoke generic computers, the Examiner is not persuaded. Notably, this argument was addressed above, and the response is incorporated here. Second, with respect to the Applicant’s argument that the claims, viewed as an ordered combination, amount to significantly more than any alleged abstract concept, the Examiner is not persuaded. Notably, the Applicant has not provided any reasoning as to why the claim elements, when taken in an ordered combination, amount to significantly more than the abstract idea; that is, in accordance with MPEP 2106.05, and instead, they have merely asserted that this is the case in a conclusory manner. As such, merely referring to the combination itself, without identifying any reasoning found in MPEP 2106.05, the Examiner is not persuaded. Third, with respect to the Applicant’s argument that the recited steps provide “a defined rule-based technique that changes how the mapping/routing system operates and how it updates route outputs in real time,” it is noted that this is merely reciting steps conducted when conducting the abstract idea. Notably, updating a generated route for a mobile merchant to follow, as discussed above, merely invokes repeating the abstract idea, which is insufficient to integrate the abstract idea into a practical application, or add significantly more to the abstract idea itself. Therefore, the Examiner maintains that this rejection is proper.
The Applicant continues on page 15 of their response, “Finally, in the Alice Corp. opinion, the court indicated that the claims in Alice Corp. were drawn to the abstract idea of intermediated settlement, and that merely requiring generic computer implementation fails to transform that abstract idea into a patent-ineligible invention. Notably, however, Alice Corp. does not state that all claims that recites a generic computer implementation are necessarily patent ineligible. Instead, the Alice Corp. opinion indicates that only ifa claim has been determined to be drawn to an "abstract idea" as that term "abstract idea" was used in the Alice Corp. opinion, then that particular claim cannot be made to be patent eligible merely by reciting a generic computer implementation in the claim. Since claims 1, 14, and 20 are not drawn to an abstract idea as indicated in the Alice Corp. opinion, then claims 1, 14, and 20 are patent eligible irrespective of whether the claims recite a generic computer implementation.” The Examiner respectfully disagrees with the Applicant’s interpretation of the requirements under 35 USC 101, the bounds of the claimed invention, and the grounds of the previous and current rejection. The Examiner notes that this argument was previously addressed in paragraph 12 of the Final Rejection mailed 12 May 2025, paragraph 14 of the Non-Final Rejection mailed 31 July 2024, and paragraph 10 of the Final Rejection mail 23 October 2023, which is incorporated herein. Thus, the Applicant’s argument is found not persuasive, as set forth in the response to the identical argument responded to in the previous rejection. Therefore, the Examiner maintains that this rejection is proper.
Applicant's arguments filed 12 November 2025 with respect to the prior art disclosing determining an expected opportunity for candidate stops to connect with optimal number of customers, selecting a subset of the stops, rendering a route through the subset, and dynamically recomputing the route have been fully considered but they are not persuasive.
With respect to claims 1, 14, and 20, the Applicant argued on page 17 of their response, “Notably, Grigg and Rao, alone or in combination with Nordstrom, fails to disclose ‘determine, based at least in part on the prediction or forecast, an expected opportunity for each of a plurality of candidate stops to connect with an optimal number of customers; select, by maximizing the expected opportunity to connect with an optimal number of customers, a subset of the candidate stops; render, on the digital map, the routing through the subset of the candidate stops; and dynamically recompute the routing in real time responsive to changes in at least one of the prediction or forecast and the customer device location,’ as claimed in amended claim 1. These recitations are expressly supported in the specification at least at specification paragraph [0038] (forecasting inputs) and specification paragraph [0040], sentences 3-4 (‘routing on a map may be automatically generated so that each stop along the route presents a good opportunity connect with an optimal number of customers’).” The Examiner respectfully disagrees with the Applicant’s interpretation of the cited prior art of record and the broadest reasonable interpretation of the claimed invention. First, the Examiner notes that with regards to the support for the argued claim amendments (which have been newly added to the claims), the Applicant generally references paragraphs 38 and 40 of their specification for support; however, as shown below with respect to the new 112a rejection, the Applicant lacks support in their original written description, and thus, the Examiner is not persuaded as to the general statement of support for the elements. Second, with regards to the Applicants argument, it is noted that the Applicant has argued here, and on pages 17-19, generally against Nordstrom, Grigg, and Rao individually. In response to applicant's arguments against the references individually, one cannot show nonobviousness by attacking references individually where the rejections are based on combinations of references. See In re Keller, 642 F.2d 413, 208 USPQ 871 (CCPA 1981); In re Merck & Co., 800 F.2d 1091, 231 USPQ 375 (Fed. Cir. 1986). Regarding the newly amended elements, it is noted that Rao describes in paragraphs 26-28 retrieving location information of a mobile merchant, and identifying events in the surrounding areas. In addition, Rao has described in paragraphs 33 and 34 receiving customer input, which includes trajectory information and interests, and wherein this input can be automatically retrieved or manually inputted. Rao continues in paragraph 40 predicting prime locations for a merchant to travel to based on user trajectories and forecasted travel. Rao continues in paragraph 41 predicting events that would be of interest to travel to for the merchant based on searches and social media. Rao continues in paragraphs 44-46 predicting user flows through an area based on user input, user locations, user trajectories, events in the area, and calendar information; wherein the system identifies a subset of routes through an area which have a high match with user profiles and the merchant profile. Additionally, paragraph 49 continues that only a subset of the top routes that more users can be received, are then selected. Rao continues in paragraph 51 that halting points are identified on the subset of routes. Rao continues in paragraphs 55-59 presenting the routes and halting spots on a digital map for the merchant to analyze, wherein the routes can be ranked based on their matching score. As such, Rao has described the argued, “determine, based at least in part on the prediction or forecast, an expected opportunity for each of a plurality of candidate stops to connect with an optimal number of customers; select, by maximizing the expected opportunity to connect with an optimal number of customers, a subset of the candidate stops; render, on the digital map, the routing through the subset of the candidate stops.” With regards to, “dynamically recompute the routing in real time responsive to changes in at least one of the prediction or forecast and the customer device location,” it is noted that Nordstrom has disclosed collecting real-time information of user locations (see paragraphs 58, 80, 82, 83, 100-113, and 115), and using this to determine routing options for vendors (see paragraphs 100-113, 126, 133-151, 275-278), wherein the routing options are for reaching an optimal number of customers as the customer and vendor locations change, and wherein the routing options include stops for the vendor to reach the customers. As such, Nordstrom discloses, “dynamically recompute the routing in real time responsive to changes in at least one of the prediction or forecast and the customer device location.” Therefore, the Examiner maintains that this rejection is proper.
Applicant's arguments filed 12 November 2025 with respect to the motivation to combine the references have been fully considered but they are not persuasive.
With respect to claims 1, 14, and 20, the Applicant has argued on page 19 of their response, “Even if Nordstrom, Grigg, and Rao are combined, the Office has not articulated, and the art does not supply, a reasoned motivation to modify Nordstrom's food-truck mapping and Grigg's audience targeting with Rao's spatio-temporal predictions to arrive at the specifically claimed sequence: After generating the forecast from the particular in-app inputs, determine an expected opportunity per candidate stop to ‘connect with an optimal number of customers,’ select a subset of stops by maximizing that expected opportunity; render the resulting route; and then dynamically recompute the route "in real time" when "at least one of the prediction or forecast and the customer device location" changes.” The Examiner notes that the Applicant’s argument is with regards to elements that have been newly added in the response filed 12 November 2025, which is after the mailing of last Office action, which was the Final Rejection mailed 12 May 2025. As such, the Applicant has argued that the previous office action was deficient for elements that were not previously under examination. Therefore, the Applicant’s arguments are found moot, and it is noted that said elements are rejected below.
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claims 1-20 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention.
With respect to claim 1, the Applicant has amended the claim to state, “determine, based at least in part on the prediction or forecast, an expected opportunity for each of a plurality of candidate stops to connect with an optimal number of customers; select, by maximizing the expected opportunity to connect with an optimal number of customers, a subset of the candidate stops; render, on the digital map, the routing through the subset of the candidate stops; and dynamically recompute the routing in real time responsive to changes in at least one of the prediction or forecast and the customer device location.” The Applicant has failed to provide a written description in their original specification that would support the currently recited amendment. In particular, the Applicant has failed to provide written description support for selecting a subset of the candidate stops by maximizing the expected opportunity to connect with an optimal number of customers, rendering the routing through the subset of the candidate stops on the map, and dynamically recomputing the routing in real time responsive to changes in at least one of the prediction or forecast and the customer device location. Notably, paragraph 40 of the Applicant’s submitted specification states:
“In certain embodiments, the application may provide a social calendar, which may allow customers to schedule a time to meet with other customers at a vehicle 115 of a particular food option. The application may also provide forecasting around particular holidays, religious holidays, or events as well. Such forecasting may be utilized to generate recommendations for locating a vehicle 115 at an optimal location for success for the business. The application may also generate a proposed cross-country trip for the vehicle 115 and the business based on forecasting. The routing on a map may be automatically generated so that each stop along the route presents a good opportunity for the business to generate sales and connect with an optimal number of customers. In certain embodiments, the application may determine where events are being held and may recommend to the business to relocate their vehicles 115 in proximity to locations associated with such events. Data that powers the recommendations generated by the application may be crowdsourced via other applications, such as via third party API integration with such applications, which may provide customer data and preferences to the application. In certain embodiments, when a vehicle 115 runs out of ingredients and/or supplies, the application may provide a check-off list to refill the ingredients and/or supplies in the application itself. The application can track inventory and integrate with supplier applications and/or devices to automatically reorder ingredients and/or supplies (e.g. propane, tires, gas, etc.) for the vehicle 115 and/or business.” (Emphasis added).
As shown and emphasized here, the Applicant has disclosed making forecasts as to where a business should locate their vehicle to conduct sales and connect with an optimal number of people. In addition, as shown and emphasized here, the Applicant has disclosed generating a proposed cross country trip, automatically generating a route on a map so that each stop along the route presents a good opportunity for the business to generate sales and connect with an optimal number of customers. This disclosure does not disclose selecting a subset of the candidate stops by maximizing the expected opportunity to connect with an optimal number of customers, rendering the routing through the subset of the candidate stops on the map, and dynamically recomputing the routing in real time responsive to changes in at least one of the prediction or forecast and the customer device location. Appropriate correction is required. Claims 14 and 20 recite similar limitations and are rejected for similar reasons. Claims 2-13 and 15-19 depend upon claims 1 and 14 and therefore are rejected for inheriting their deficiencies.
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 an abstract idea without significantly more. The claims recite providing a food truck option via a graphical user interface of an application; determining, by utilizing the at least one global positioning sensor positioned in proximity to the vehicle, a location of the vehicle associated with the food truck option; providing, via the application, the location of a vehicle associated with the food truck option to a customer device accessing the application; receiving a signal from a sensor of the customer device indicating a customer device location of the customer device; generating a digital map including the location of the vehicle associated with the food truck option and locations of other vehicles associated with other food truck options, wherein the digital map further provides, based on the signal, a visual indication of the customer device location relative to the location of the vehicle and the locations of the other vehicles associated with the other food truck options; displaying, via the graphical user interface, the location of the vehicle associated with the food truck option on a map where locations of other vehicles associated with other food truck options are displayed; enabling the customer device to access a food truck profile of the food truck option that includes content associated with the food truck option; generating a prediction or forecast for at least one future location of the vehicle based at least in part on one or more of: (i) an identification of at least one future event to be held, (ii) activity conducted via the application using the customer device, (iii)searches conducted via the application, and (iv) queries made via the customer device; generating a proposed trip for the vehicle based on the prediction or forecast; automatically generating routing on the digital map for the proposed trip, wherein the routing comprises stops that present at least one opportunity to connect with an optimal number of customers; determining, based at least in part on the prediction or forecast, an expected opportunity for each of a plurality of candidate stops to connect with an optimal number of customers; selecting, by maximizing the expected opportunity to connect with an optimal number of customers, a subset of the candidate stops; rendering, on the digital map, the routing through the subset of the candidate stops; dynamically recomputing the routing in real time responsive to changes in at least one of the prediction or forecast and the customer device location.
The limitations of providing a food truck option, determining a location of the vehicle associated with the food truck option, providing a location of a vehicle associated with the food truck option to a customer device, receiving customer location information, generating a map including the location of vehicles associated with food truck options and customer device locations, displaying the location of the vehicle associated with the food truck option on a map where locations of other vehicles associated with other food truck options are displayed, enabling the customer device to access a food truck profile of the food truck option that includes content associated with the food truck option, generating a prediction or forecast for at least one future location of the vehicle based on events or customer input, generating routing on the digital map for the proposed trip that comprises stops that present opportunities to connect with an optimal number of customers, determining an expected opportunity for each candidate stop to connect with an optimal number of customers, selecting a subset of the candidate stops by maximizing the expected opportunities, rendering the routing through the subset stops on the map; and recomputing the routing responsive to changes in at least one of the prediction or forecast and the customer device location; as drafted, under the broadest reasonable interpretation, encompasses the management of commercial activities (marketing, sales activities, managing business relations) with the use of generic computer elements as tools. That is, other than reciting the use of generic computer elements (memory, processor, graphical user interface, customer device, application, GPS sensor, sensor of customer device), the claim recites an abstract idea. For example, the elements of providing food truck options, providing locations of food trucks relative to the user’s location to a user on a map display, and enabling a user to view food truck profiles, encompasses providing a customer service provider options to browse and view, wherein the customer can select a service provider to view and place orders with; thus, elements which recite marketing, sales activities, managing business relations. In addition, generating predictions/forecasts for future locations of the food truck, generating a proposed trip, and presenting a proposed route on a map; encompasses the performance of marketing, and managing the behaviors and interactions between people. In addition, determining an expected opportunity for each candidate stop to connect with an optimal number of customers, selecting a subset of the candidate stops by maximizing the expected opportunities, rendering the routing through the subset stops on the map; and recomputing the routing responsive to changes in at least one of the prediction or forecast and the customer device location; encompass determining optimal opportunities to route merchants to potential customers, generating the optimal route, and updating the route based on new information; thus, elements which recite marketing, sales activities, managing business relations, and managing human behavior. Therefore, the claims recite elements that fall into the “Certain Methods of Organizing Human Activity” grouping of abstract ideas. The claims recite an abstract idea.
This judicial exception is not integrated into a practical application. The claims do not recite additional elements that improve the functioning of a computer, another technology, or technical field. The claims do not recite the use of, or apply the abstract idea with, a particular machine, the claims do not recite the transformation of an article from one state or thing into another. Finally, the claims do not recite additional elements that apply or use the abstract idea in some other meaningful way beyond generally linking the use of the abstract idea to a particular technological environment. Instead, the claims recite the use of generic computer elements (memory, processor, graphical user interface, customer device, application, GPS sensor, sensor of customer device) as tools to carry out the abstract idea. In addition, the claims further recite the use of a GPS in proximity to a vehicle to determine the location of the vehicle, which merely narrows the field of use by defining where generic GPS sensors are located, and further recites using generic computer elements in their ordinary capacity (GPS sensors for recording locations), and thus does not integrate the abstract idea into a practical application. In addition, the claims recite receiving customer location information, which is deemed extrasolution activity of data gathering. The claims are directed to an abstract idea.
The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of using generic computer elements and machines to perform the steps 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. In addition, the claims recite extrasolution of data gathering encompassing collecting customer location information, which is also deemed well-understood, routine, and conventional activity (MPEP 2106.05(d), “Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); 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)”). The claims are directed to non-patent eligible subject matter.
The dependent claims 2-13 and 15-19, taken individually and in combination do not recite additional elements that integrate the abstract idea into a practical application, or add significantly more to the abstract idea itself. In particular, claims further recite that the GPS sensor is part of the merchant’s smartphone or vehicle, which merely narrows the field of use by defining where a generic GPS sensor is located, and further recites using generic computer elements in their ordinary capacity (GPS sensor for recording locations), and thus does not integrate the abstract idea into a practical application, or add significantly more to the abstract idea itself (claims 2 and 3). In addition, the claims further recite allowing a customer to place an order with the truck or reserve the truck itself, which is the performance of commercial interactions (sales activities, business relations), and therefore further recites elements that fall into the “Certain Methods of Organizing Human Activity” grouping of abstract ideas (claims 4 and 7). In addition, the claims further recite displaying menus, prices, food truck information, or reviews, which encompasses marketing and sales activities, and therefore further recites elements that fall into the “Certain Methods of Organizing Human Activity” grouping of abstract ideas (claim 5). In addition, the claims further recite displaying location information of the service providers to a customer as the customer moves, which merely narrows the field of use by defining when content is displayed, and thus does not integrate the abstract idea into a practical application, or add significantly more to the abstract idea itself (claim 6). In addition, the claims further recite providing future locations of the vehicle, which encompasses marketing and sales activities, and therefore further recites elements that fall into the “Certain Methods of Organizing Human Activity” grouping of abstract ideas (claim 8). In addition, the claims further recite allowing a customer to provide feedback or reviews for a service, which encompasses the management of business relations, and therefore further recites elements that fall into the “Certain Methods of Organizing Human Activity” grouping of abstract ideas (claim 9). In addition, the claims recite providing updates to related to the food truck, such as menu updates, which merely further, which encompasses marketing and sales activities, and therefore further recites elements that fall into the “Certain Methods of Organizing Human Activity” grouping of abstract ideas (claim 10). In addition, the claims further recite enabling third party API’s to be used, which further recites the use of generic computer elements, in their ordinary capacity, as tools, and thus does not integrate the abstract idea into a practical application, or add significantly more to the abstract idea itself (claim 11). In addition, the claims further recite displaying a wait time for items, which encompasses marketing and sales activities, and therefore further recites elements that fall into the “Certain Methods of Organizing Human Activity” grouping of abstract ideas (claim 12). In addition, the claims further recite initiating food preparation based on the customer location, which encompasses managing sales activities and business relations, and therefore further recites elements that fall into the “Certain Methods of Organizing Human Activity” grouping of abstract ideas (claim 13). In addition, the claims further recite receiving expected future locations of customers, and setting an optimal location for vehicles based on the future locations, which encompasses managing marketing and business relations of food trucks based on customer movement, and therefore further recites elements that fall into the “Certain Methods of Organizing Human Activity” grouping of abstract ideas (claims 15 and 16). In addition, the claims further recite providing customers alternate provider options, which encompasses marketing and sales activities, and therefore further recites elements that fall into the “Certain Methods of Organizing Human Activity” grouping of abstract ideas (claim 17). In addition, the claims further recite allowing customers to maker business profiles with their preferences, which encompasses managing business relations, and therefore further recites elements that fall into the “Certain Methods of Organizing Human Activity” grouping of abstract ideas (claim 18). In addition, the claims further recite forecasting demand for a business based on customer data, which encompasses managing business relations, and therefore further recites elements that fall into the “Certain Methods of Organizing Human Activity” grouping of abstract ideas (claim 19).
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
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.
Claims 1, 2, 4-6, 9, 10, 14, 17, 18, and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Nordstrom (US 2013/0027227 A1) (hereinafter Nordstrom), in view of Grigg et al. (US 2013/0046635 A1) (hereinafter Grigg), and further in view of Rao et al. (US 2020/0386565 A1) (hereinafter Rao).
With respect to claims 1, 14, and 20, Nordstrom teaches:
At least one global positioning sensor positioned in proximity to a vehicle (See at least paragraphs 34, 61, 62, 68, 69, 91, 92, 115-124, and 463 which describe customers using an application to search for food trucks using a user interface, wherein the locations of the food trucks are tracked in real-time using an associated GPS device, and wherein the locations of the trucks are displayed on a map to the customer).
A memory that stores instructions; and a processor that executes the instructions to configure the processor to (See at least paragraphs 28, 30, 33, 34, and 76 which describe user devices that stores and run applications on memory).
Providing a food truck option via a graphical user interface of an application (See at least paragraphs 34, 61, 62, 68, 69, and 115-124 which describe customers using an application to search for food trucks using a user interface).
Determine, by utilizing the at least one global positioning sensor positioned in proximity to the vehicle, a location of the vehicle associated with the food truck option (See at least paragraphs 34, 61, 62, 68, 69, 91, 92, 115-124, and 463 which describe customers using an application to search for food trucks using a user interface, wherein the locations of the food trucks are tracked in real-time using an associated GPS device, and wherein the locations of the trucks are displayed on a map to the customer).
Providing, via the application, a location of a vehicle associated with the food truck option to a customer device accessing the application, wherein the location of the vehicle is provided via a global positioning sensor in proximity to the vehicle (See at least paragraphs 34, 61, 62, 68, 69, 91, 92, 115-124, and 463 which describe customers using an application to search for food trucks using a user interface, wherein the locations of the food trucks are tracked in real-time using an associated GPS device, and wherein the locations of the trucks are displayed on a map to the customer).
Receive a signal from a sensor of the customer device indicating a customer device location of the customer device (See at least paragraph 34 which describes receiving requests for food services, wherein the requests from customers include the locations of customers querying for services based on the customer’s GPS location).
generate a prediction or forecast for at least one future location of the vehicle based at least in part on one or more of: (i) an identification of at least one future event to be held, (ii) activity conducted via the application using the customer device, (iii) searches conducted via the application, and (iv) queries made via the customer device
Generate a digital map including the location of the vehicle associated with the food truck option and locations of other vehicles associated with other food truck options, wherein the digital map further provides, based on the signal, a visual indication of the customer device location relative to the location of the vehicle and the locations of the other vehicles associated with the other food truck options (See at least paragraphs 34, 61, 62, 68, 69, 91, 92, 115-124, and 463 which describe customers using an application to search for food trucks using a user interface, wherein the locations of the food trucks are tracked in real-time using an associated GPS device, and wherein the locations of the trucks are displayed on a map to the customer).
Displaying, via the graphical user interface, the location of the vehicle associated with the food truck option on the digital map where the locations of the other vehicles associated the with other food truck options are displayed (See at least paragraphs 34, 61, 62, 68, 69, 91, 92, 115-124, and 463 which describe customers using an application to search for food trucks using a user interface, wherein the locations of the food trucks are tracked in real-time using an associated GPS device, and wherein the locations of the trucks are displayed on a map to the customer).
Enabling the customer device to access a food truck profile of the food truck option that includes content associated with the food truck option (See at least paragraphs 86-99, 115-124, 168, 299, 517, and 518 which describe vendor profiles that are provided to customers upon selection, including menus, pricing, and the ability to order from the trucks).
Dynamically recompute the routing in real time responsive to changes in at least one of the prediction or forecast and the customer device location (See at least paragraphs 58, 80, 82, 83, 100-113, 115, 126, 133-151, and 275-278 which describe computing a route for a vendor to reach optimal number of customers, wherein the route includes stops and is based on customer locations and requests, and wherein the real time changes causes the routes on the vendors map to be updated in real time).
Nordstrom discloses all of the limitations of claims 1, 14, and 20 as stated above. Nordstrom does not explicitly disclose the following, however Grigg teaches:
Generate a prediction or forecast for at least one future location of the vehicle based at least in part on one or more of: (i) an identification of at least one future event to be held, (ii) activity conducted via the application using the customer device, (iii) searches conducted via the application, and (iv) queries made via the customer device (See at least paragraphs 3-7, 25, 44, and 101-104 which describe generating a recommendation of future locations for a food truck, wherein the future locations are based on transaction information, GPS measurements, customer requests, time of day, calendar day, and the type of items sold).
It would have been obvious to one of ordinary skill in the art at the time of filing the claimed invention to combine the system and method of tracking food trucks with GPS enabled devices, wherein the locations of the vehicles are provided to interested customers of Nordstrom, with the system and method of generating a recommendation of future locations for a food truck, wherein the future locations are based on transaction information, GPS measurements, customer requests, time of day, calendar day, and the type of items sold of Grigg. By determining recommended future locations for a merchant using various criteria, and broadcasting advertisements to interested customers in the estimated future location, customers will predictably be able to plan for food trucks to order from, as well as encouraging future commercial interactions.
The combination of Nordstrom and Grigg discloses all of the limitations of claims 1, 14, and 20 as stated above. Nordstrom and Grigg do not explicitly disclose the following, however Rao teaches:
Generate a prediction or forecast for at least one future location of the vehicle based at least in part on one or more of: (i) an identification of at least one future event to be held, (ii) activity conducted via the application using the customer device, (iii)searches conducted via the application, and (iv) queries made via the customer device; generate a proposed trip for the vehicle based on the prediction or forecast; automatically generate routing on the digital map for the proposed trip, wherein the routing comprises stops that present at least one opportunity to connect with an optimal number of customers (See at least paragraphs 26-28, 33, 34, 40, 45, 46, 51-59, and 65 which describe a server receiving food truck profile and location information, and users’ profile and location information, wherein the information includes current and historical locations of the food truck and users, forecasted events, and activities of the user devices, wherein the server generates a prediction of future locations for the food truck and suggests a route and stops for the food truck to reach an optimal group of users, and wherein the route is presented on a map of the food truck).
Determine, based at least in part on the prediction or forecast, an expected opportunity for each of a plurality of candidate stops to connect with an optimal number of customers; select, by maximizing the expected opportunity to connect with an optimal number of customers, a subset of the candidate stops; render, on the digital map, the routing through the subset of the candidate stops (See at least paragraphs 26-28, 33, 34, 40, 41, 44-46, 49, 51, and 55-59 which describe determining candidate stops to connect with customers, wherein routes are generated for the stops in a manner that reaches the maximum number of customers that have interest in the vendors goods, and wherein the routes are presented on a user interface).
It would have been obvious to one of ordinary skill in the art at the time of filing the claimed invention to combine the system and method of tracking food trucks with GPS enabled devices, wherein the locations of the vehicles are provided to interested customers of Nordstrom, with the system and method of generating a recommendation of future locations for a food truck, wherein the future locations are based on transaction information, GPS measurements, customer requests, time of day, calendar day, and the type of items sold of Grigg, with the system and method of a server receiving food truck profile and location information, and users’ profile and location information, wherein the information includes current and historical locations of the food truck and users, forecasted events, and activities of the user devices, wherein the server generates a prediction of future locations for the food truck and suggests a route and stops for the food truck to reach an optimal group of users, wherein expected opportunities for each stop are identified and stops that reach the most potential customers are determined, and wherein the route with the identified subset of stops is presented on a map of the food truck of Rao. By predicting future locations for a food truck based on collected food truck and customer location, and presenting an optimal route to the food truck, including where to stop, a planning service will predictably enable food trucks to attract the optimal number of customers, and thus generate the highest revenue via increased service.
With respect to claim 2, the combination of Nordstrom, Grigg, and Rao discloses all of the limitations of claim 1 as stated above. In addition, Nordstrom teaches:
Wherein the processor is further configured to share the location of the vehicle associated with the food truck option via a smartphone including a global positioning sensor of the at least one global positioning sensor that is in proximity to the vehicle (See at least paragraphs 91-93, 463, 472-476, and 480-482 which describe tracking food trucks using a GPS enabled device, such as their smartphone, and reporting this location to customers).
With respect to claim 4, Nordstrom/Grigg/Montague discloses all of the limitations of claim 1 as stated above. In addition, Nordstrom teaches:
Wherein the processor is further configured to enable the customer device to make an order for a food item provided by a business associated with the vehicle and the food truck option (See at least paragraphs 320-325, 343-348, 407, and 417-422 which describe a user using the application to remotely place an order with a food truck).
With respect to claim 5, Nordstrom/Grigg/Rao discloses all of the limitations of claim 1 as stated above. In addition, Nordstrom teaches:
Wherein the processor is further configured to display a menu, pricing information, food truck information, business information, a review, or a combination thereof, when the food truck profile of the food truck option is accessed by the customer device (See at least paragraphs 86-99, 115-124, 168, 299, 517, and 518 which describe vendor profiles that are provided to customers upon selection, including menus, pricing, reviews, and business information).
With respect to claim 6, Nordstrom/Grigg/Rao discloses all of the limitations of claim 1 as stated above. In addition, Nordstrom teaches:
Wherein the processor is further configured to display the location of the vehicle relative to the locations of the other vehicles associated with the other food truck options on the map in real time as a customer device location of the customer device changes in real time (See at least paragraphs 34, 61, 62, 68, 69, 91, 92, 115-124, and 463 which describe customers using an application to search for food trucks using a user interface, wherein the locations of the food trucks are tracked in real-time using an associated GPS device, and wherein the locations of the trucks are displayed on a map to the customer as the customer changes locations).
With respect to claim 9, Nordstrom/Grigg/Rao discloses all of the limitations of claim 1 as stated above. In addition, Nordstrom teaches:
Wherein the processor is further configured to enable a user associated with the customer device to provide feedback, a review, commentary, or a combination thereof, associated with the food truck option via the application (See at least paragraphs 399-405 which describe an application allowing users to provide feedback and reviews for food trucks, wherein the information is received and provided to other customers).
With respect to claim 10, Nordstrom/Grigg/Rao discloses all of the limitations of claim 1 as stated above. In addition, Nordstrom teaches:
Wherein the processor is further configured to provide an update relating to the food truck option, wherein the update comprises an update to a menu of the food truck option, an update to pricing of a food item of the menu, an update to the location of the vehicle, an update to information associated with the food truck option, an update associated with a business associated with the food truck option, an update relating to an amount of demand for services provided by the business, an update relating to additional future locations for the vehicle associated with the food truck option, an update relating to an availability of the food time, an update relating to a weather condition in an environment in which the vehicle is located, an update relating to a booking of the vehicle, any other update, or a combination thereof (See at least paragraphs 115-124, 86-99, and 168 which describe providing users with food truck vendor feedback, including changes in menu, locations, and availability).
With respect to claim 17, Nordstrom/Grigg/Rao discloses all of the limitations of claim 14 as stated above. In addition, Nordstrom teaches:
Enabling the application to provide an alternate food truck option if the food truck option is unavailable to the customer device (See at least paragraphs 115-124, and 168 which describe alerting customers to food truck options upon being searched, wherein the alert includes favorited food trucks and other vendors when the favorite is not in the customer’s searched area).
With respect to claim 18, Nordstrom/Grigg/Rao discloses all of the limitations of claim 14 as stated above. In addition, Nordstrom teaches:
Enabling a user of the customer device to establish a user profile including preferences associated with food items, locations, pricing, weather conditions, or a combination thereof, preferred by the user (See at least paragraphs 67, 100-113, 168, 182-186, and 410 which describe customers creating customer profiles, wherein the profiles include preferences for food items, locations, and specific vendors).
Claim 3 is rejected under 35 U.S.C. 103 as being unpatentable over Nordstrom, Grigg, and Rao as applied to claim 1 as stated above, and further in view of Garden et al. (US 2020/0070717 A1) (hereinafter Garden).
With respect to claim 3, Nordstrom/Grigg/Rao discloses all of the limitations of claim 1 as stated above. Nordstrom, Grigg, and Rao do not explicitly disclose the following, however Garden teaches:
Wherein the processor is further configured to share the location of the vehicle associated with the food truck option via a global positioning sensor of the at least one global positioning sensor of the vehicle itself (See at least paragraphs 78 and 110, which describe mobile vendors, wherein the vendors’ trucks include GPS sensors and report their location to a managing service).
It would have been obvious to one of ordinary skill in the art at the time of filing the claimed invention to combine the system and method of tracking food trucks with GPS enabled devices, wherein the locations of the vehicles are provided to interested customers of Nordstrom, with the system and method of generating a recommendation of future locations for a food truck, wherein the future locations are based on transaction information, GPS measurements, customer requests, time of day, calendar day, and the type of items sold of Grigg, with the system and method of a server receiving food truck profile and location information, and users’ profile and location information, wherein the information includes current and historical locations of the food truck and users, forecasted events, and activities of the user devices, wherein the server generates a prediction of future locations for the food truck and suggests a route and stops for the food truck to reach an optimal group of users, and wherein the route is presented on a map of the food truck of Rao, with the system and method of tracking mobile vendors’ trucks using a built in GPS device of the truck of Garden. By tracking vehicle movements using a built in GPS sensor, a vendor would predictably have a means to report its location, without requiring the use of additional equipment.
Claim 7 is rejected under 35 U.S.C. 103 as being unpatentable over Nordstrom, Grigg, and Rao as applied to claim 1 as stated above, and further in view of S, RH. (2014). Food truck rentals: The new strategies. Restaurant Hospitality, , n/a. Retrieved from https://dialog.proquest.com/professional/docview/1519976735?accountid=131444 (hereinafter RH).
With respect to claim 7, Nordstrom/Grigg/Rao discloses all of the limitations of claim 1 as stated above. Nordstrom, Grigg, and Rao do not explicitly disclose the following, however RH teaches:
Wherein the processor is further configured to enable a user of the customer device to book the food truck option and the vehicle for a selected period of time (See page 1 which describes an application service that allows for customers to browse a listing of available food trucks, and book a food truck for an event).
It would have been obvious to one of ordinary skill in the art at the time of filing the claimed invention to combine the system and method of tracking food trucks with GPS enabled devices, wherein the locations of the vehicles are provided to interested customers of Nordstrom, with the system and method of generating a recommendation of future locations for a food truck, wherein the future locations are based on transaction information, GPS measurements, customer requests, time of day, calendar day, and the type of items sold of Grigg, with the system and method of a server receiving food truck profile and location information, and users’ profile and location information, wherein the information includes current and historical locations of the food truck and users, forecasted events, and activities of the user devices, wherein the server generates a prediction of future locations for the food truck and suggests a route and stops for the food truck to reach an optimal group of users, and wherein the route is presented on a map of the food truck of Rao, with the system and method of an application service that allows for customers to browse a listing of available food trucks, and book a food truck for an event of RH. By allowing customers to browse and book food trucks for a period of time, such as an event, a management will predictably encourage additional commerce by providing food trucks an easy revenue stream.
Claims 8, 12, and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Nordstrom, Grigg, and Rao as applied to claims 1 and 14 as stated above, and further in view of Resheff et al. (US 2021/0035196 A1) (hereinafter Resheff).
With respect to claim 8, Nordstrom/Grigg/Rao discloses all of the limitations of claim 1 as stated above. Nordstrom, Grigg, and Rao do not explicitly disclose the following, however Resheff teaches:
Wherein the processor is further configured to provide, via the application, additional future locations of the vehicle associated with the food truck option over a period of time (See at least paragraphs 23, 31, and 49 which describe collecting location information for mobile merchants, wherein the location information is used to predict future locations of the merchant, and providing this information to potential customers).
It would have been obvious to one of ordinary skill in the art at the time of filing the claimed invention to combine the system and method of tracking food trucks with GPS enabled devices, wherein the locations of the vehicles are provided to interested customers of Nordstrom, with the system and method of generating a recommendation of future locations for a food truck, wherein the future locations are based on transaction information, GPS measurements, customer requests, time of day, calendar day, and the type of items sold of Grigg, with the system and method of a server receiving food truck profile and location information, and users’ profile and location information, wherein the information includes current and historical locations of the food truck and users, forecasted events, and activities of the user devices, wherein the server generates a prediction of future locations for the food truck and suggests a route and stops for the food truck to reach an optimal group of users, and wherein the route is presented on a map of the food truck of Rao, with the system and method of collecting location information for mobile merchants, wherein the location information is used to predict future locations of the merchant, and providing this information to potential customers of Resheff. By determining future locations of food trucks and providing these locations to customers, customers will predictably be able to identify locations where trucks will be, and thus determine the optimal location merchant to pick that aligns with their planned travel.
With respect to claim 12, Nordstrom/Grigg/Rao discloses all of the limitations of claim 1 as stated above. Nordstrom, Grigg, and Rao do not explicitly disclose the following, however Resheff teaches:
Wherein the processor is further configured to display a wait time for a user of the customer device to obtain an order of a food item (See at least paragraph 49 which describes providing customers with wait times for food trucks).
It would have been obvious to one of ordinary skill in the art at the time of filing the claimed invention to combine the system and method of tracking food trucks with GPS enabled devices, wherein the locations of the vehicles are provided to interested customers of Nordstrom, with the system and method of generating a recommendation of future locations for a food truck, wherein the future locations are based on transaction information, GPS measurements, customer requests, time of day, calendar day, and the type of items sold of Grigg, with the system and method of a server receiving food truck profile and location information, and users’ profile and location information, wherein the information includes current and historical locations of the food truck and users, forecasted events, and activities of the user devices, wherein the server generates a prediction of future locations for the food truck and suggests a route and stops for the food truck to reach an optimal group of users, and wherein the route is presented on a map of the food truck of Rao, with the system and method of providing customers with wait times for food trucks of Resheff. By providing customers with food truck information, such as wait times, a customer will predictably be able to make the optimal choice for selecting a food truck to conduct business with, as they will find the merchants that satisfy their preferences.
With respect to claim 19, Nordstrom/Grigg/Rao discloses all of the limitations of claim 14 as stated above. Nordstrom, Grigg, and Rao do not explicitly disclose the following, however Resheff teaches:
Forecasting demand for a business associated with the food truck option based on aggregated data from a plurality of customer devices including the customer device that have ordered from the business (See at least paragraphs 23, 26, 31, 49, 50, and 172 which describe determining expected wait times (e.g. demand) and service locations based on transaction data of user devices and merchant data).
It would have been obvious to one of ordinary skill in the art at the time of filing the claimed invention to combine the system and method of tracking food trucks with GPS enabled devices, wherein the locations of the vehicles are provided to interested customers of Nordstrom, with the system and method of generating a recommendation of future locations for a food truck, wherein the future locations are based on transaction information, GPS measurements, customer requests, time of day, calendar day, and the type of items sold of Grigg, with the system and method of a server receiving food truck profile and location information, and users’ profile and location information, wherein the information includes current and historical locations of the food truck and users, forecasted events, and activities of the user devices, wherein the server generates a prediction of future locations for the food truck and suggests a route and stops for the food truck to reach an optimal group of users, and wherein the route is presented on a map of the food truck of Rao, with the system and method of determining expected wait times (e.g. demand) and service locations based on transaction data of user devices and merchant data of Resheff. By providing customers with food truck information, such as wait times, a customer will predictably be able to make the optimal choice for selecting a food truck to conduct business with, as they will find the merchants that satisfy their preferences.
Claim 11 is rejected under 35 U.S.C. 103 as being unpatentable over Nordstrom, Grigg, and Rao as applied to claim 1 as stated above, and further in view of Amin et al. (US 2014/0129951 A1) (hereinafter Amin)
With respect to claim 11, Nordstrom/Grigg/Rao discloses all of the limitations of claim 1 as stated above. Nordstrom, Grigg, and Rao do not explicitly disclose the following, however Amin teaches:
Wherein the processor is further configured to enable third party application programming interface integration with the application (See at least paragraph 93 which describe a system and method of allowing a customer to search for services using an application, wherein the application enables third party APIs to be integrated within it).
It would have been obvious to one of ordinary skill in the art at the time of filing the claimed invention to combine the system and method of tracking food trucks with GPS enabled devices, wherein the locations of the vehicles are provided to interested customers of Nordstrom, with the system and method of generating a recommendation of future locations for a food truck, wherein the future locations are based on transaction information, GPS measurements, customer requests, time of day, calendar day, and the type of items sold of Grigg, with the system and method of a server receiving food truck profile and location information, and users’ profile and location information, wherein the information includes current and historical locations of the food truck and users, forecasted events, and activities of the user devices, wherein the server generates a prediction of future locations for the food truck and suggests a route and stops for the food truck to reach an optimal group of users, and wherein the route is presented on a map of the food truck of Rao, with the system and method of allowing a customer to search for services using an application, wherein the application enables third party APIs to be integrated within it of Amin. By implementing third party APIs into an application, the food truck finder of Nordtrom will predictably be able to receive input and information using known methods.
Claim 13 is rejected under 35 U.S.C. 103 as being unpatentable over Nordstrom, Grigg, and Rao as applied to claim 1 as stated above, and further in view of Goldberg et al. (US 2019/0050952 A1) (hereinafter Goldberg).
With respect to claim 13, Nordstrom/Grigg/Rao discloses all of the limitations of claim 1 as stated above. Nordstrom, Grigg, and Rao does not explicitly disclose the following, however Goldberg teaches:
Wherein the processor is configured to initiate preparation of a food item ordered via the application based on a current customer device location of the customer device of a user (See at least paragraphs 56-57 and 62 which describe a food truck initiating food preparation for an order based on the location of the customer device and the ETA to the food truck).
It would have been obvious to one of ordinary skill in the art at the time of filing the claimed invention to combine the system and method of tracking food trucks with GPS enabled devices, wherein the locations of the vehicles are provided to interested customers of Nordstrom, with the system and method of generating a recommendation of future locations for a food truck, wherein the future locations are based on transaction information, GPS measurements, customer requests, time of day, calendar day, and the type of items sold of Grigg, with the system and method of a server receiving food truck profile and location information, and users’ profile and location information, wherein the information includes current and historical locations of the food truck and users, forecasted events, and activities of the user devices, wherein the server generates a prediction of future locations for the food truck and suggests a route and stops for the food truck to reach an optimal group of users, and wherein the route is presented on a map of the food truck of Rao, with the system and method of a food truck initiating food preparation for an order based on the location of the customer device and the ETA to the food truck of Goldberg. By initiating food preparation for an order based on the customer location and ETA to the truck, a vendor will predictably be able to determine the optimal time for cooking food, and thus, provide food to customers at the optimal temperature.
Claims 15 and 16 are rejected under 35 U.S.C. 103 as being unpatentable over Nordstrom, Grigg, and Montague as applied to claim 14 as stated above, and further in view of Postrel (US 2012/0271717 A1) (hereinafter Postrel).
With respect to claim 15, Nordstrom/Grigg/Rao discloses all of the limitations of claim 14 as stated above. Nordstrom, Grigg, and Rao do not explicitly disclose the following, however Postrel teaches:
Generating a signal indicating expected future locations of a plurality of customer devices including the customer device (See at least paragraphs 56, 61, 63, 67, and 68 which describe tracking customer real-time locations, wherein the location information is used to predict future locations and a destination, and wherein the management system generates incentives and advertisements for merchants in proximity of the predicted future locations).
It would have been obvious to one of ordinary skill in the art at the time of filing the claimed invention to combine the system and method of tracking food trucks with GPS enabled devices, wherein the locations of the vehicles are provided to interested customers of Nordstrom, with the system and method of generating a recommendation of future locations for a food truck, wherein the future locations are based on transaction information, GPS measurements, customer requests, time of day, calendar day, and the type of items sold of Grigg, with the system and method of a server receiving food truck profile and location information, and users’ profile and location information, wherein the information includes current and historical locations of the food truck and users, forecasted events, and activities of the user devices, wherein the server generates a prediction of future locations for the food truck and suggests a route and stops for the food truck to reach an optimal group of users, and wherein the route is presented on a map of the food truck of Rao, with the system and method of tracking customer real-time locations, wherein the location information is used to predict future locations and a destination, and wherein the management system generates incentives and advertisements for merchants in proximity of the predicted future locations of Postrel. By predicting future locations and using this information to determine vendor incentives and advertisements, a managing system will predictably be able to determine optimal vendors to advertise to a user in a manner that would encourage additional commercial actions.
With respect to claim 16, the combination of Nordstrom, Grigg, Rao, and Postrel discloses all of the limitations of claims 14 and 15 as stated above. In addition, Nordstrom teaches:
Setting an optimal future location of the vehicle associated with the food truck option based on the expected future locations of the plurality of customer devices (See at least paragraphs 34, 37, 38, 136, 139, 146, and 147 which describes determining the optimal position of a food truck based on customer searches and potential customer location information).
Conclusion
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Michael Harrington
Primary Patent Examiner
2 February 2026
Art Unit 3628
/MICHAEL P HARRINGTON/Primary Examiner, Art Unit 3628