DETAILED ACTION
1. This communication is in response to the amendments filed on May 20, 2026 for Application No. 18/136,285 in which Claims 1-5, 8-12, and 15-18 are presented for examination.
Notice of Pre-AIA or AIA Status
2. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Arguments
3. The amendments filed on May 20, 2026 have been considered. Claims 1, 5, 8, and 15-18 have been amended. Claims 6-7, 13-14, and 19-20 have been canceled. Thus, Claims 1-5, 8-12, and 15-18 are pending and presented for examination.
4. Applicant’s arguments filed May 20, 2026 with respect to the 35 U.S.C. 112(b) rejection have been fully considered and are persuasive. Thus, the 35 U.S.C. 112(b) rejection has been withdrawn.
5. Applicant's arguments filed May 20, 2026 with respect to the 35 U.S.C. 101 signals per se rejection have been fully considered and are persuasive. Thus, the 35 U.S.C. 101 signals per se rejection has been withdrawn.
6. Applicant's arguments filed May 20, 2026 with respect to the 35 U.S.C. 101 abstract idea rejection have been fully considered but they are not persuasive.
Applicant’s Arguments on Pgs. 9-10 of Arguments/Remarks state:
“When viewed as a whole, the claims recite a specific technological solution to a concrete problem in intermodal cargo shipment tracking and prediction. In particular, the claims do not merely recite an abstract concept but instead define a particular technical architecture and processing methodology that improves the functioning of computer systems used for logistics prediction.
The specification describes significant problems with conventional approaches to cargo shipment tracking. In particular, conventional systems lack the ability to accurately model the complex transitions that occur at intermodal facilities where cargo moves between different transportation modes. As the specification explains, "each facility may distinguish between corresponding events of transportation and dray events," and the system must account for transitions "such as a dray move from the destination port to a rail facility (e.g., a rail ramp), a dwell at the rail ramp and a transition from rail ramp to rail" (see paragraph [0071]). The specification further describes that conventional approaches fail to capture the structural complexity of real-world logistics networks where multiple transportation modes converge at single locations.
The claims address these technical problems through a specific technical implementation. In particular, the claims require constructing location nodes with a particular structure that includes mode inputs, dray inputs, mode outputs, and dray outputs, which forms a four-gate structure that enables the system to model intermodal transitions that conventional systems cannot accurately represent.
The amended claims further specify that processing the shipment events occurs "by traversing the graph to solve for a shortest path that minimizes a metric combining transit times with a likelihood of traversing each edge of the graph." This is not a mental process that could be performed with pen and paper. The specification describes that the system processes real shipment data through a graph structure with potentially thousands of nodes and edges representing real-world logistics networks. The specification explains that the graph structure enables "each location (e.g., port, railyard, airport, etc.) may be represented by an individual graph that includes mode-specific facilities having a number (e.g., four) of gates representing inputs and outputs" (see paragraph [0079]). The computational complexity of traversing such graphs while simultaneously optimizing multiple metrics and computing edge traversal likelihoods is beyond practical human mental capacity.
The claims improve the functioning of computer systems used for logistics prediction. The specification describes that the claimed approach enables more accurate prediction of transit times by properly modeling the intermodal transitions that occur at logistics facilities. The specific node structure with dray inputs and outputs allows the system to distinguish between different types of cargo movements at a single facility, which improves prediction accuracy.
The additional elements impose meaningful limits on any alleged abstract idea. The claims do not merely recite instructions to apply prediction on a generic computer. Instead, the claims require a specific graph structure with location nodes having particular inputs and outputs, the addition of these nodes to a graph, and processing through graph traversal with specific optimization criteria. These elements define a particular technical implementation rather than a result-oriented abstraction.
The ordered combination of elements works together to achieve a technical result. The construction of location nodes with specific input and output structures enables proper modeling of intermodal transitions. Adding these nodes to a graph creates a computational structure that represents the logistics network. Receiving shipment events provides real data for processing. Processing through graph traversal with optimization criteria produces accurate predictions. Each element contributes to the technical solution, and the combination achieves results that no single element could achieve alone.
For the foregoing reasons, the claims integrate any alleged judicial exception into a practical application. The claims recite a specific technical solution to a concrete problem in intermodal logistics prediction, implemented through a particular graph structure and processing methodology that improves the functioning of computer systems used for cargo tracking. The claims therefore satisfy Step 2A, Prong Two and are patent-eligible under 35 U.S.C. § 101.”
Examiner respectfully disagrees. Although Applicant alleges that the instant claims recite a specific technological improvement, Examiner asserts that this improvement is not reflected into the currently drafted claim language. While Applicant’s specification may detail the supposed improvements that the invention provides, the instant claim language is still recited at a high-level of generality and amounts to merely constructing a plurality of location nodes, adding the nodes to a graph, and then processing received shipment events using said graph. The claim language still recites an abstract idea at Step 2A Prong 1, as the aforementioned limitations may be feasibly performed by a combination of mental and mathematical process (See 35 U.S.C. 101 rejection below for specific examples). The claim does not detail the use of any machine learning models, nor any training/configuration/architecture that would be associated with such models and/or the claimed graph model. Instead, the claim language is recited at a high-level of generality and does not provide an inventive concept.
Further, regarding the newly added limitation that processing the shipment events occurs “by traversing the graph to solve for a shortest path that minimizes a metric combining transit times with a likelihood of traversing each edge of the graph”, Examiner asserts that this limitation may still be feasibly performed manually by a user and/or by mathematical process. The instant claim language does not specify that the graph comprises thousands of nodes and edges, moreover, Applicant’s Figure 4C similarly supports a simple interpretation of such a graph – traversing a graph such as the one presented by Applicant’s Figure 4C may be feasibly performed by a user, with the aid of pen and paper. Alternatively, this limitation may also be performed by mathematical process, utilizing an algorithm such as a modified Dijkstra’s traversal, similarly supported by Applicant’s specification Par. [0092].
Furthermore, regarding Applicant’s assertion that the claims require a specific graph structure with location nodes representing a logistics network, Examiner respectfully disagrees. The Independent claims merely state that a plurality of location nodes are constructed corresponding to a real-world location, including a mode input/output and a dray input/output (which merely specify intermodal transitions between transportation modes) and then adds these nodes to a generic “graph” without significantly more. This, again, still recites an abstract idea and simply specifying inputs/outputs of the graph seemingly does not equate to a “specific graph structure”.
Applicant’s Arguments on Pgs. 10-12 of Arguments/Remarks state:
“Even if the claimed invention were found to be directed to a judicial exception under Step 2A, it nonetheless satisfies Step 2B because it includes additional elements that amount to significantly more than the abstract idea itself, including specific limitations that amount to an inventive concept.
The claims recite constructing location nodes with a specific structure that includes "a mode input, a dray input, a mode output, and a dray output, wherein the dray input and the dray output enable modeling of intermodal transitions between different transportation modes at the real-world location." This is not a generic data structure but a specific technical architecture disclosed in the specification that enables the system to distinguish between different types of cargo movements at intermodal facilities. The specification explains that a container departing "via a non-ocean mode (e.g., truck, rail, etc.)" is "conceptually modeled as transiting via the dray out-gate node 306B" (see paragraph [0073]). This specific node architecture is not well-understood, routine, or conventional in the field of logistics prediction systems.
The claims further recite processing the shipment events "by traversing the graph to solve for a shortest path that minimizes a metric combining transit times with a likelihood of traversing each edge of the graph." This processing step is not a generic computer function but a specific algorithmic approach that combines multiple optimization criteria in a non- conventional manner. The specification describes that the graph structure enables "each location (e.g., port, railyard, airport, etc.) may be represented by an individual graph that includes mode-specific facilities having a number (e.g., four) of gates representing inputs and outputs, wherein at least one of the inputs is a dray in-gate and at least one of the outputs is a dray out-gate" (see paragraph [0079]). The combination of graph traversal with simultaneous optimization of transit times and edge traversal likelihoods represents a specific technical implementation that is not routine or conventional.
The ordered combination of elements provides a technical solution that differs from conventional approaches. The specification describes that the system must account for complex transitions "such as a dray move from the destination port to a rail facility (e.g., a rail ramp), a dwell at the rail ramp and a transition from rail ramp to rail" and that "each facility may distinguish between corresponding events of transportation and dray events" (see paragraph [0071]). The claimed combination of constructing location nodes with specific input and output structures, adding these nodes to a graph, receiving shipment events, and processing through graph traversal with specific optimization criteria achieves a technical result that no single element could achieve alone. Even if individual elements such as graph structures or shortest path algorithms may be known in isolation, their specific combination as claimed is non-conventional and yields the technical benefit of accurately modeling intermodal transitions at logistics facilities.
The OA characterizes the additional elements as mere instructions to apply an abstract idea on a computer or as generic computer components. However, the OA does not provide evidentiary support for the assertion that the specific node structure with mode inputs, dray inputs, mode outputs, and dray outputs is well-understood, routine, or conventional. The OA does not cite any evidence that the specific combination of graph traversal with optimization of transit times and edge traversal likelihoods is conventional. The OA fails to properly consider the specific implementation described in the specification, instead characterizing the claims at a high level of abstraction that does not reflect the actual claim language.
The claims do not merely append well-understood, routine, or conventional activities to any alleged judicial exception. Instead, the claims recite a specific and non-conventional arrangement of elements that provides the technical benefit of accurately modeling and predicting outcomes for intermodal cargo shipments. The ordered combination of constructing location nodes with specific input and output structures, adding these nodes to a graph, receiving shipment events, and processing through graph traversal with specific optimization criteria represents a technical solution that is not conventional in the field of logistics prediction.
Accordingly, representative claim 1 recites significantly more than any alleged abstract idea, and Applicant respectfully submits that claims 1-5, 8-12, and 15-18 are patent eligible. Therefore, Applicant respectfully submits that the rejection under 35 U.S.C. § 101 is overcome and requests that the rejection be withdrawn.”
Examiner respectfully disagrees for substantially the same reasons as stated above. Applicant asserts that the node architecture presented is not well-understood, routine, conventional, however, this is not what is asserted by Examiner. Instead, the node architecture and construction of the nodes are considered to be mental process at Step 2A Prong 1, as highlighted in the response to arguments above. Further, regarding the newly added limitation “by traversing the graph to solve for […]”, this limitation is not considered to be generic computer function, but instead considered mental/mathematical process at Step 2A Prong 1, as also highlighted in the response to arguments above.
Although Applicant claims that the ordered combination of elements provide a technical solution that differs from conventional approaches, this ordered combination of elements is still recited at a high-level of generality and does not preclude the instant limitations from being practically performed by mental/mathematical process.
Applicant is encouraged to provide further technical details regarding the training/architecture/configuration of the graph structure and its corresponding location nodes, as well as the processing performed using the graph structure, such that the instant limitations are not interpreted as mere mental/mathematical process.
Thus, the 35 U.S.C. 101 rejection is maintained.
7. Applicant’s arguments filed May 20, 2026 with respect to the 35 U.S.C. 103 rejection have been fully considered and are persuasive. Thus, the 35 U.S.C. 103 rejection has been withdrawn. Note: However, Claims 1-5, 8-12, and 15-18 are still rejected under 35 U.S.C. 101 – abstract idea.
Claim Rejections - 35 USC § 101
8. 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.
9. Claims 1-5, 8-12, and 15-18 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Regarding Claim 1:
Step 1: Claim 1 is a method type claim. Therefore, Claims 1-7 are directed to either a process, machine, manufacture, or composition of matter.
2A Prong 1: If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation by mathematical calculation but for the recitation of generic computer components, then it falls within the “Mathematical Concepts” grouping of abstract ideas.
[…] predict target outcomes corresponding to a cargo shipment (mental process – other than reciting “using machine learning”, predicting target outcomes corresponding to a cargo shipment may be performed manually by a user observing/analyzing a plurality of features related to the cargo shipment (such as origin, destination, and shipment events) and accordingly using judgement/evaluation to cast a prediction regarding target outcomes (such as net transit time, net transit cost, net emissions) based on said analysis)
constructing […] a plurality of location nodes, wherein each of the location nodes corresponds to a respective location type, wherein each of the location nodes corresponds to a respective real-world location, and wherein each of the location nodes includes a mode input, a dray input, a mode output, and a dray output, wherein the dray input and they dray output enable modeling of intermodal transitions between different transportation modes at the real-world location (mental process – other than reciting “via one or more processors”, constructing a plurality of location nodes may be performed manually by a user constructing a plurality of nodes of a graph with the aid of pen and paper, where each node corresponds to a respective real-world location, location type, and includes a mode input, dray input, mode output, and dray output. For example, a user may construct the plurality of location nodes including mode input, dray input, mode output, and a dray output enabling modeling of intermodal transitions, as illustrated by Applicant’s Figure 4C, with the aid of pen and paper)
adding […] the plurality of location nodes to the graph (mental process – other than reciting “via one or more processors”, adding the plurality of location nodes to the graph may be performed manually by a user observing/analyzing the plurality of location nodes and accordingly using judgement/evaluation to add the plurality of location nodes to the graph with the aid of pen and paper – See Applicant’s Figures 4C & 4D for examples)
processing […] the shipment events by traversing the graph to solve for a shortest path that minimizes a metric combining transit times with a likelihood of traversing each edge of the graph to determine one or more target outcomes corresponding to the cargo shipment (mental process/mathematical process – other than reciting “via one or more processors”, processing the shipment events using the graph to determine one or more target outcomes may be performed manually by a user observing/analyzing the shipment events and graph and accordingly using judgement/evaluation to process the shipment events using the graph (by traversing the graph to solve for a shortest path that minimizes a metric combining transit times with a likelihood of traversing each edge, with the aid of pen and paper) which may enable the user to determine one or more target outcomes (i.e., net transit time per instant claim 4) corresponding to the cargo shipment. Alternatively, the processing of shipment events by traversing the graph to solve for a shortest path that minimizes a metric combining transit times with a likelihood of traversing each edge to determine one or more target outcomes may also be performed by mathematical process, utilizing an algorithm such as Dijkstra’s traversal – see Applicant’s specification Par. [0092])
2A Prong 2: This judicial exception is not integrated into a practical application.
Additional elements:
a computer-implemented method of using a graph to predict target outcomes corresponding to a cargo shipment (recited at a high-level of generality (i.e., as a generic method using generic components) such that it amounts to no more than mere instructions to apply the exception using generic computer components)
[…] via one or more processors […] (recited at a high-level of generality (i.e., as a generic one or more processors configured to perform the specific operations of claim 1) such that it amounts to no more than mere instructions to apply the exception using generic computer components)
receiving, via one or more processors, an origin input parameter, a destination input parameter, and one or more shipment events corresponding to the cargo shipment (Adding insignificant extra-solution activity to the judicial exception – see MPEP 2106.05(g))
2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
Additional elements:
a computer-implemented method of using a graph to predict target outcomes corresponding to a cargo shipment (mere instructions to apply the exception using generic computer components cannot provide an inventive concept)
[…] via one or more processors […] (mere instructions to apply the exception using generic computer components cannot provide an inventive concept)
receiving, via one or more processors, an origin input parameter, a destination input parameter, and one or more shipment events corresponding to the cargo shipment (MPEP 2106.05(d)(II) indicates that merely “Receiving or transmitting data over a network” is a well-understood, routine, conventional function when it is claimed in a merely generic manner (as it is in the present claim). Thereby, a conclusion that the claimed limitation is well-understood, routine, conventional activity is supported under Berkheimer)
For the reasons above, Claim 1 is rejected as being directed to an abstract idea without significantly more. This rejection applies equally to dependent claims 2-5. The additional limitations of the dependent claims are addressed below.
Regarding Claim 2:
Step 2A Prong 1:
See the rejection of Claim 1 above, which Claim 2 depends on.
Step 2A Prong 2 & Step 2B:
wherein each respective location type is selected from the group consisting of (i) seaport, (ii) railyard and (iii) airport (Field of Use – limitations that amount to merely indicating a field of use or technological environment in which to apply a judicial exception does not amount to significantly more than the exception itself, and cannot integrate a judicial exception into a practical application; in this case specifying the location types does not integrate the exception into a practical application nor amount to significantly more – See MPEP 2106.05(h))
Accordingly, under Step 2A Prong 2 and Step 2B, these additional elements do not integrate the abstract idea into practical application because they do not impose any meaningful limits on practicing the abstract idea, as discussed above in the rejection of claim 1.
Regarding Claim 3:
Step 2A Prong 1:
See the rejection of Claim 1 above, which Claim 3 depends on.
Step 2A Prong 2 & Step 2B:
wherein the one or more shipment events include at least one of (i) a transit event, (ii) a dwell event or (iii) a dray event (Field of Use – limitations that amount to merely indicating a field of use or technological environment in which to apply a judicial exception does not amount to significantly more than the exception itself, and cannot integrate a judicial exception into a practical application; in this case specifying the types of shipment events does not integrate the exception into a practical application nor amount to significantly more – See MPEP 2106.05(h))
Accordingly, under Step 2A Prong 2 and Step 2B, these additional elements do not integrate the abstract idea into practical application because they do not impose any meaningful limits on practicing the abstract idea, as discussed above in the rejection of claim 1.
Regarding Claim 4:
Step 2A Prong 1:
See the rejection of Claim 1 above, which Claim 4 depends on.
Step 2A Prong 2 & Step 2B:
wherein the target outcomes include at least one of (i) a net transit time of the cargo shipment, (ii) a net transit cost of the cargo shipment, (iii) a net emissions measure of the cargo shipment (Field of Use – limitations that amount to merely indicating a field of use or technological environment in which to apply a judicial exception does not amount to significantly more than the exception itself, and cannot integrate a judicial exception into a practical application; in this case specifying the target outcomes does not integrate the exception into a practical application nor amount to significantly more – See MPEP 2106.05(h))
Accordingly, under Step 2A Prong 2 and Step 2B, these additional elements do not integrate the abstract idea into practical application because they do not impose any meaningful limits on practicing the abstract idea, as discussed above in the rejection of claim 1.
Regarding Claim 5:
Step 2A Prong 1:
See the rejection of Claim 1 above, which Claim 5 depends on.
Step 2A Prong 2 & Step 2B:
training, via one or more processors, a machine learning model using historical data to predict information related to at least one segment of the cargo shipment (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.05(f) – Examiner' s note: high level recitation of training a machine learning model with previously determined data without significantly more. This cannot provide an inventive concept)
Accordingly, under Step 2A Prong 2 and Step 2B, these additional elements do not integrate the abstract idea into practical application because they do not impose any meaningful limits on practicing the abstract idea, as discussed above in the rejection of claim 1.
Independent Claim 8 recites substantially the same limitations as Claim 1, in the form of a system, including generic computer components. The claim is also directed to performing mental processes without significantly more, therefore it is rejected under the same rationale.
For the reasons above, Claim 8 is rejected as being directed to an abstract idea without significantly more. This rejection applies equally to dependent claims 9-12. The additional limitations of the dependent claims are addressed below.
Claim 9 recites substantially the same limitations as Claim 2, in the form of a system, including generic computer components. The claim is also directed to performing mental processes without significantly more, therefore it is rejected under the same rationale.
Claim 10 recites substantially the same limitations as Claim 3, in the form of a system, including generic computer components. The claim is also directed to performing mental processes without significantly more, therefore it is rejected under the same rationale.
Claim 11 recites substantially the same limitations as Claim 4, in the form of a system, including generic computer components. The claim is also directed to performing mental processes without significantly more, therefore it is rejected under the same rationale.
Claim 12 recites substantially the same limitations as Claim 5, in the form of a system, including generic computer components. The claim is also directed to performing mental processes without significantly more, therefore it is rejected under the same rationale.
Independent Claim 15 recites substantially the same limitations as Claim 1, in the form of a non-transitory computer-readable medium, including generic computer components. The claim is also directed to performing mental processes without significantly more, therefore it is rejected under the same rationale.
For the reasons above, Claim 15 is rejected as being directed to an abstract idea without significantly more. This rejection applies equally to dependent claims 16-18. The additional limitations of the dependent claims are addressed below.
Claim 16 recites substantially the same limitations as Claim 2, in the form of a computer-readable medium, including generic computer components. The claim is also directed to performing mental processes without significantly more, therefore it is rejected under the same rationale.
Claim 17 recites substantially the same limitations as Claim 3, in the form of a computer-readable medium, including generic computer components. The claim is also directed to performing mental processes without significantly more, therefore it is rejected under the same rationale.
Claim 18 recites substantially the same limitations as Claim 5, in the form of a computer-readable medium, including generic computer components. The claim is also directed to performing mental processes without significantly more, therefore it is rejected under the same rationale.
Allowable Subject Matter
10. No prior art rejection is made for Claims 1-5, 8-12, and 15-18. However, these claims are rejected under 35 U.S.C. 101 – abstract idea.
11. Examiner has disclosed Balster et al. (“An ETA Prediction Model for Intermodal Transport Networks Based on Machine Learning”), Wei et al. (“A Modified Dijkstra’s Algorithm for Solving the Problem of Finding the Maximum Load Path”), and Sun et al. (“Optimizing Transportation by Inventory Routing and Workload Balancing: Optimizing Daily Dray Operations Across an Intermodal Freight Network”), which are the closest prior art as compared to the instant application. Balster discloses an estimated time of arrival (ETA) prediction model for intermodal freight transport networks, in which schedule-based and non-schedule-based transports are combined, based on machine learning. Wei teaches path optimization including the use of Dijkstra’s algorithm for solving the problem of finding the shortest path and modifying Dijkstra’s algorithm to solve the problem of finding the maximum load path for improving freight efficiency. Sun discloses optimizing daily dray operations across an intermodal freight network using set-partitioning formulation and column-generation heuristics. However, Balster, Wei, and Sun seemingly do not disclose the specific limitations of Independent Claims 1, 8, and 15 including “constructing, via one or more processors, a plurality of location nodes, wherein each of the location nodes corresponds to a respective location type, wherein each of the location nodes corresponds to a respective real-world location, and wherein each of the location nodes includes a mode input, a dray input, a mode output, and a dray output, wherein the dray input and the dray output enable modeling of intermodal transitions between different transportation modes at the real- world location” and “processing, via one or more processors, the shipment events by traversing the graph to solve for a shortest path that minimizes a metric combining transit times with a likelihood of traversing each edge of the graph to determine one or more target outcomes corresponding to the cargo shipment” in combination with the remaining limitations of the Independent claims.
Conclusion
12. THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
13. Any inquiry concerning this communication or earlier communications from the examiner should be directed to Devika S Maharaj whose telephone number is (571)272-0829. The examiner can normally be reached Monday - Thursday 8:30am - 5:30pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Alexey Shmatov can be reached at (571)270-3428. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/DEVIKA S MAHARAJ/Examiner, Art Unit 2123
/ALEXEY SHMATOV/Supervisory Patent Examiner, Art Unit 2123
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