DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Status of Claims
Claims 1-9 were previously pending and subject to a non-final rejection dated July 30, 2025. In Response, submitted October 15, 2025, claims 1, 4, and 7 were amended, and claims 10 and 11 were added. No new subject matter was introduced in these amendments. Therefore, claims 1-11 are currently pending and subject to the following final rejection.
Response to Arguments
Applicant’s remarks on Page 15 of the Response regarding the previous claim objection, have been fully considered. The objection is withdrawn in light of the amended claims.
Applicant’s remarks on Pages 15-26 of the Response, regarding the previous rejection of the claims under 35 U.S.C. 101, have been fully considered and are not found persuasive.
On Pages 15-17 of the Response, Applicant argues “Applicant respectfully disagrees with the Examiner's contentions, and humbly submits that amended claims 1-11 are directed to patent eligible subject matter at least for the reasons below. … Step 2A- Prong 2: Claims recite a method for prioritizing inbound containers in a supply chain thereby integrate the exception into practical application based on combination of additional elements.
Applicant asserts that integration of judicial exception into the practical application is achieved in terms of implementing a judicial exception with, or using a judicial exception in conjunction with, a particular machine or manufacture that is integral to the claim, as discussed in MPEP § 2106.05(b) with the capability of generating a rolling list of dynamically prioritized inbound containers by accounting dynamically changing demand, multiple network constraints & supply chain costs, predicting inbound containers based on container status such as ready-for-pickup which is obtained by a feed from the carrier or from a retailer's customs agent and not-ready-for-pickup using a trained AI model. The AI model is trained based on a plurality of features associated with the container status, as, ‘dynamically determining via the one or more hardware processors, individual scores of a plurality of factors impacting inbound container prioritization of the plurality of FCLs for the stipulated timeframe based on one or more of a plurality of parameters that are either computed, derived, or obtained from a plurality of external resources or a plurality of internal resources, wherein a container status of each of the plurality of FCLs is one of(i) ready-for-pickup and (ii) not-ready-for-pickup, wherein the container status ready-for-pickup is obtained by a feed from the carrier or from a retailer's customs agent, wherein a regression based artificial intelligence models are trained based on a plurality of features associated with the container status to predict the inbound containers that are not ready for pickup,’ Applicant's published application at paragraphs [0067- 0068] discloses, ‘The plurality of factors and corresponding individual score computation is described below in steps (a) though (f). Computation of the individual score for each of the plurality of factors is based on one or more of a plurality of parameters that are either computed, derived, or obtained from various external/internal resources. CONTStatus= The status of the container (E.g.: “Ready for Pickup” or “not-ready-for-pick- up, e.g., Awaiting Customs”, etc.). Ready for Pickup status can be obtained by the feed from the carrier or from the retailer's customs agent. All the containers that do not fall under 'ready to pick up' status can be tagged as “Not ready for pickup.” Similarly, regression based Artificial Intelligence models,well known in the art are trained based on features associated with container status to predict containers that will not be ready for pick up.’”
Examiner notes, “prioritizing inbound containers in a supply chain” and “generating a rolling list of dynamically prioritized inbound containers by accounting dynamically changing demand, multiple network constraints & supply chain costs, predicting inbound containers based on container status such as ready-for-pickup which is obtained by a feed from the carrier or from a retailer's customs agent and not-ready-for-pickup using a trained … model. The … model is trained based on a plurality of features associated with the container status” are recitations of the abstract idea, and are therefore unhelpful in bringing the claims to eligibility and cannot themselves “integrate the exception into practical application” as they are themselves the exception. As discussed further in the detailed rejection below, the limitations quoted in this argument reflect the inventions capabilities of performing these abstract ideas, which amount to merely processing and generating data, and the recitation of additional elements along side these abstract ideas does not inherently equate to “implementing [the] judicial exception with, or using [the] judicial exception in conjunction with, a particular machine or manufacture that is integral to the claim”. In the case of the instant claims, additional elements of “one or more hardware processors” and “Artificial Intelligence models” are recited at such high levels of generality (the processors described generically as “one or more microprocessors, microcomputers, microcontrollers, digital signal processors, central processing units, state machines, logic circuitries, and/or any devices that manipulate signals based on operational instructions”. See PG publication, Para. 49. The Artificial Intelligence models receive an even broader description of being “well known in the art”. See PG publication, Para. 67.) such that the serve merely as tools to perform the abstract idea (i.e. “apply it”) or to generally link the abstract idea to the field of machine learning modeling, which, consistent with court findings, fail to integrate the judicial exception into a practical application. See MPEP 2106.04(d)(I).
On Pages 17-18 of the Response, Applicant argues “Applicant asserts that integration of judicial exception into the practical application is achieved in terms of the claim as a whole is more than a drafting effort designed to monopolize the exception, as discussed in MPEP §2106.05(e) with the capability of the system communicating ranking list to the retailer and receiving last minute requirements revised by the retailer upon receiving the ranking list and dynamically updating the ranking list based on the last minute requirements revised by the retailer and finally tagging the inbound container from the updated ranking list to the carrier as, ‘communicating the ranking list of ready for pickup followed by not-ready-for-pickup FCLs to the retailer; receiving- last minute requirements, a carriers list for picking- up and associated driver contacts from the retailer, upon receiving- the ranking- list; dynamically recomputing the ranking list by updating the ranking list based on the last minute requirements revised by the retailer; tagging the inbound container from the updated ranking list to the carrier from the carriers list received from the retailer and notifying the corresponding driver via an end communication device with information of the inbound container identification and location to be picked up;’ Applicant's published application at paragraphs [0043-0045], [0165] and Fig. 1A discloses, ‘Communicate ranking list for 'ready for pick up' followed by not ready for pick up' FCLs/LCLs to the retailer. Dynamically compute updated ranking-list based on last minute requirements/choices/weightages revised by the retailer. Tag the container from the ranking- list to a carrier from the carrier list received from the retailer and notify corresponding- driver via and end communication device with information of the container to be picked up. However, for any last moment failure of any carrier, the system 100 can identify next in line carrier to continue the task without major glitches. The information of container includes the container location, identification etc. Upon generation of the ranking list, in one example implementation, the system 100 then communicates ranking list of 'ready for pick up' followed by not ready for pick up'FCLs/LCLs to the retailer. Further, the system 100 recomputes updated ranking list based on last minute requirements/choices/weightages revised by the retailer. The system 100 also receives list of carriers and associated driver contacts. Thereafter, the system 100 tags the container from the ranking list to a carrier from the carrier list and notifies corresponding driver via an end communication device such as mobile device with information of the container to be picked up, such as container identification, location and so on. However, for any last moment failure of any carrier, the system 100 can identify next in line carrier to continue the task without major glitches. Once container details are received, the carrier picks up the goods freight from tagged container for delivery to the warehouse of the retailer.’
Examiner notes, similar to the discussion above, “communicating ranking list to the retailer and receiving last minute requirements revised by the retailer upon receiving the ranking list and dynamically updating the ranking list based on the last minute requirements revised by the retailer and finally tagging the inbound container from the updated ranking list to the carrier” is a recitation of the abstract idea and are therefore unhelpful in bringing the claims to eligibility. As discussed further in the detailed rejection below, the limitations quoted in this argument reflect the inventions capabilities of performing this abstract idea, which amounts to merely communication, processing, and outputting of data. While not explicitly mentioned in the quoted limitations of the claim, the “one or more hardware processors” which perform many aspects of the quoted abstract idea, has been discussed above, and therefore will not be reanalyzed here. The additional element of “an end communication device” is discussed generically as “a mobile device”. See PG Publication Para. 165. Therefore, at such a high level of generality this additional element merely serves as a tool for performing the recited abstract idea of “notifying the corresponding driver with information of the inbound container identification and location to be picked up” (i.e., “apply it”).
On Pages 18-19 of the Response, Applicant argues “Applicant asserts that integration of judicial exception into the practical application is achieved in terms of an improvement to computing technology and/or improving the functionality of the computer (MPEP §§ 2106.04(d)(1) and 2106.05(a)) with the capability of identifying a next inline carrier to continue the task without glitches in response to determining the last moment failure of the carrier (machine) and picking freight from the tagged inbound container by the carrier upon obtaining information of the next inline carrier tagged to the inbound container for delivery to the warehouse of the retailer as, ‘determining a last moment failure of the carrier; identifying a next inline carrier to continue the task without glitches in response to determining the last moment failure, wherein information of the next inline carrier tagged to the inbound container includes the inbound container location and identification, wherein locating the inbound container is through utilization of a GPS receiver; and picking freight from the tagged inbound container by the carrier upon obtaining information of the next inline carrier tagged to the inbound container for delivery to the warehouse of the retailer’”
Examiner notes, “identifying a next inline carrier to continue the task without glitches in response to determining the last moment failure of the carrier … and picking freight from the tagged inbound container by the carrier upon obtaining information of the next inline carrier tagged to the inbound container for delivery to the warehouse of the retailer” is a recitation of the abstract idea. As discussed further in the detailed rejection below, the limitations quoted in this argument reflect the inventions capabilities of performing this abstract idea, which amounts to merely communication, processing, and outputting of data. Addressing the Applicant’s assertion of the carrier as “a machine”, BRI does not limit the carrier to being interpreted as a machine and allows for interpretation of “carrier” to mean a person or a business entity, neither of which are machines or additional elements. Further no special definition is provided to the term carrier within the Applicant’s specification to limit its interpretation to only a machine. Regarding the referenced limitations of the claims, the only additional elements recited is ”a GPS receiver”, this additional element is recited at such a high level of generality that it is merely a tool used for performing the abstract idea of “locating the inbound container” (i.e., “apply it”). The alleged improvements found in these limitations are confined the to the abstract ideas (such as “determining a last moment failure …identifying a next in line carrier, [and] picking freight from the tagged inbound container by the carrier upon obtaining information of the next inline carrier”), rather than to the additional elements or the technologies themselves. An improvement to the abstract idea is not an improvement to the technology. See MPEP 2106.05(a)(II).
On Pages 19-20 of the Response, Applicant argues “Applicant asserts that integration of judicial exception into the practical application is achieved in terms of an improvement to computing technology and/or improving the functionality of the computer (MPEP §§ 2106.04(d)(1) and 2106.05(a)) with the capability of using components configured to gather or extract data from external or internal resources and process the gathered data for computing priority score for each container, further generate the ranking list of the containers as, ‘wherein a plurality of components configured for computing the priority score for each inbound container and generating the ranking list of the inbound containers include a spotting agent, an open weather agent, a google traffic agent, a demand sensing agent, an inventory tracking agent, a cost manager and a master data integrator, wherein the spotting agent locates a purchase order or container product in the supply chain through interactive visual route maps and pop-up reports on specific ports enroute the destination and when the carrier has a GPS device on the inbound container or an ELD (Electronic Loqqing Devices) devices on the inbound container, then the spotting agent feeds current location coordinates to compute the lead time prediction’
Examiner notes, the additional elements recited in these limitations of the claim (i.e., a plurality of components, a spotting agent, an open weather agent, a google traffic agent, a demand sensing agent, an inventory tracking agent, a cost manager and a master data integrator) are described broadly in PG Publication Para. 52 as “a plurality of modules … to gather or extract data from external or internal resources and process the gathered data”. That is, these additional elements are merely modules stored in the memory to be used as tools for performing the abstract ideas of “gather[ing] or extract[ing] data from external or internal resources and process[ing] the gathered data”, i.e. “apply it”. Further the “GPS device on the inbound container” “an ELD (Electronic Loqqing Devices) devices on the inbound container” are not positively recited and are instead recited as descriptive information regarding the inbound containers. Therefore, any alleged improvement is confined the abstract ideas performed by the additional elements and not to the additional elements or their technologies themselves.
On Pages 21-23 of the Response, Applicant argues “Referring to Example 42 ‘Method for Transmission of Notifications When Medical Records Are Updated’ in Subject Matter Eligibility Examples: Abstract ideas, Applicant referred to pages 17-19 stating that under Step-2A analysis it is explicitly mentioned that ‘The claim recites a combination of additional elements including storing information, providing remote access over a network, converting updated information that was input by a user in a non-standardized form to a standardized format, automatically generating a message whenever updated information is stored, and transmitting the message to all of the users. The claim as a whole integrates the method of organizing human activity into a practical application. Specifically, the additional elements recite a specific improvement over prior art systems by allowing remote users to share information in real time in a standardized format regardless of the format in which the information was input by the user. Thus, the claim is eligible because it is not directed to the recited judicial exception (abstract idea). In-line with this Example 42, the claimed subject matter the system communicating ranking list to the retailer and receiving last minute requirements revised by the retailer upon receiving the ranking list and dynamically updating the ranking list based on the last minute requirements revised by the retailer and finally tagging the inbound container from the updated ranking list to the carrier. … Therefore, the ordered combination of claimed elements integrates the exception into practical application. Thus, the claim is eligible because it is not directed to the recited judicial exception (abstract idea) under Step 2A-Prong 2 of the revised guidance for assessing the Patent Subject Mater Eligibility. The Applicant requests the Examiner to consider the above-mentioned arguments and submissions on merits. Further, based on the 2019 Revised Patent Subject Mater Eligibility Guidance, it is to be noted that Step 2A-Prong 2 does not evaluate whether the additional elements are conventional to determine whether the abstract idea is integrated into a practical application.
Examiner notes, contrary to the Example 42, no specific technical problem or solution is specified within the body of the claims, for example the specification does not set forth that due to formatting issues of the various systems, it was impossible for the various systems of the claimed invention to communicate and share information prior to the claimed invention. Rather, the application alleges an improved way of processing the data gathered by these systems (such as “communicating ranking list to the retailer and receiving last minute requirements revised by the retailer upon receiving the ranking list and dynamically updating the ranking list based on the last minute requirements revised by the retailer and finally tagging the inbound container from the updated ranking list to the carrier”), which is an improvement to the abstract idea and not a technical improvement. Therefore, after full and proper analysis under Step 2A, Prong Two the claims remain ineligible.
On Pages 23-26 of the Response, Applicant argues “the Applicant respectfully submits that claimed elements/limitations recites patent eligible subject matter. More specifically, features of amended claim 1 provides method for prioritizing inbound containers in a supply chain, ‘dynamically determining via the one or more hardware processors, individual scores of a plurality of factors impacting inbound container prioritization of the plurality of FCLS for the stipulated timeframe based on one or more of a plurality of parameters that are either computed, derived, or obtained from a plurality of external resources or a plurality of internal resources, wherein a container status of each of the plurality of FCLs is one of (i) readyfor-pickup and (ii) not-ready-for-pickup, wherein the container status ready-for-pickup is obtained by a feed from the carrier or from a retailer's customs agent, wherein a regression based artificial intelligence models are trained based on a plurality of features associated with the container status to predict the inbound containers that are not ready for pick up,’ ‘generating via the one or more hardware processors, a ranking list of the inbound containers comprising the plurality of FCLs in the order of the priority scores with container status ready for pickup followed by not-ready-for-pickup; communicating the ranking list of ready for pickup followed by not-ready-for-pickup FCLs to the retailer: receiving last minute requirements, a carriers list for picking up and associated driver contacts from the retailer, upon receiving the ranking list; dynamically recomputing the ranking list by updating the ranking list based on the last minute requirements revised by the retailer; tagging the inbound container from the updated ranking list to the carrier from the carriers list received from the retailer and notifying the corresponding driver via an end communication device with information of the inbound container identification and location to be picked up; determining a last moment failure of the carrier; identifying a next inline carrier to continue the task without glitches in response to determining the last moment failure, wherein information of the next inline carrier tagged to the inbound container includes the inbound container location and identification, wherein locating the inbound container is through utilization of a GPS receiver; and picking freight from the tagged inbound container by the carrier upon obtaining information of the next inline carrier tagged to the inbound container for delivery to the warehouse of the retailer, wherein a plurality of components configured for computing the priority score for each inbound container and generating the ranking list of the inbound containers include a spotting agent, an open weather agent, a google traffic agent, a demand sensing agent, an inventory tracking agent, a cost manager and a master data integrator, wherein the spotting agent locates a purchase order or container product in the supply chain through interactive visual route maps and pop-up reports on specific ports enroute the destination and when the carrier has a GPS device on the inbound container or an ELD (Electronic Logging Devices) devices on the inbound container, then the spotting agent feeds current location coordinates to compute the lead time prediction’. … Applicant's claimed invention recites the technical advancement in terms of identifying a next inline carrier to continue the task without glitches in response to determining the last moment failure of the carrier (machine) and picking freight from the tagged inbound container by the carrier upon obtaining information of the next inline carrier tagged to the inbound container for delivery to the warehouse of the retailer. Hence, the presently amended claims amount to significantly more than the abstract idea. In view of the foregoing, the Applicant asserts that the Applicant claimed subject matter provides technical advancement of prioritizing inbound containers in a supply chain (refer paragraphs [0043-0045], [0052-0058], [0067-0100] and [0165]). Therefore, taking all the claim elements individually, or in combination, the claim as a whole amounts to "significantly more" than an abstract idea of itself (Step 2B: Yes). The Applicant requests the examiner to consider the above-mentioned arguments and submissions on merits. By means of the aforementioned claim amendments and submissions, Applicant humbly and respectfully submits that the subject matter claimed does not merely constitute an abstract idea and constitutes significantly more than an abstract idea. Accordingly, the Applicant respectfully requests the withdrawal of the rejection of claims 1-11 under 35 U.S.C § 101.”
Examiner directs Applicant to the extensive discussion above regarding the cited limitations of the claims as well as to the detailed rejection below. Both instances provide a clear description of the recited abstract idea, as well as discussion regarding the analysis of each additional element and why when analyzed both individually and as a whole/ordered combination they amount to merely “apply it” or generally linking the abstract idea to a field of technology. This same analysis applies at Step 2B, as the courts have found that “apply it” and generally linking the abstract idea to a field of use/technology does not qualify as “significantly more” at Step 2B. See MPEP 2106.05(I)(A).
Examiner further notes, that “identifying a next inline carrier to continue the task without glitches in response to determining the last moment failure of the carrier … and picking freight from the tagged inbound container by the carrier upon obtaining information of the next inline carrier tagged to the inbound container for delivery to the warehouse of the retailer” and “prioritizing inbound containers in a supply chain” are recitations of the abstract idea (Applicant is here directed to the previous discussion regarding BRI of “carrier” above) and is not a technical advancement. As these are recitations of the abstract idea, they are unhelpful in bringing the claims to eligibility at Step 2B.
Claim Objections
Claims 1, 4, and 7 is objected to because of the following informalities: limitations 2, 5, and 2, respectively, of the claims recite “a regression based artificial intelligence models” and should recite “regression based artificial intelligence models”. Additionally, limitations 19, 22, and 19, respectively, of the same claims recite “an ELD (Electronic Logging Devices) devices” and should recite “an ELD (Electronic Logging Device[[s]]) device[[s]]”. Appropriate correction is required.
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 1-9 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1
Claims 1-3 are directed to a method (i.e., a process); claims 4-6 are directed to a system (i.e., a machine); claims 7-9 are directed to a non-transitory machine-readable information storage medium (i.e., article of manufacture). Therefore, claims 1-9 all fall within the one of the four statutory categories of invention.
Step 2A, Prong One
Independent claim 1, 4, and 7 substantially recites predicting a set of the inbound containers arriving at a port of dispatch within a stipulated timeframe for a plurality of products ordered by a retailer, wherein the set of inbound containers comprise a combination of a plurality of Full Container Loads (FCLs) and a plurality of Less than Container Loads (LCLs);
dynamically determining individual scores of a plurality of factors impacting inbound container prioritization of the plurality of FCLs for the stipulated timeframe based on one or more of a plurality of parameters that are either computed, derived, or obtained from a plurality of external resources or a plurality of internal resources, wherein a container status of each of the plurality of FCLs is one of (i) ready-for-pickup and (ii) not-ready-for-pickup, wherein the container status ready-for-pickup is obtained by a feed from the carrier or from a retailer's customs agent, wherein a regression based models are trained based on a plurality of features associated with the container status to predict the inbound containers that are not ready for pick up, wherein the plurality of factors comprising:
a Port Lead Time factor (PLTfact) scored based on a time required for requesting a carrier to pick up the FCL and time required for the carrier to move from a current location to the port;
a Product Demand fulfilment factor (PDshortage) scored based on a demand shortage for each product in the FCL container to determine if a required demand can be met within a buffer time to a warehouse of the retailer, wherein number of products with the demand shortage and a seasonality of the products contribute to value of the PDshortage;
a delivery Route Clearance factor (RCfact) scored by validating traffic, weather, and shortest path from the port to a destination set by the retailer using geographic coordinates of the warehouse;
a destination Distribution Centre (DC) Dock availability factor (DCDfact) scored by validating congestion at a warehouse docking gate;
a destination DC Resource availability factor (DCRfact) scored by predicting absentees among employees for better labor planning and shift allocation at a fulfilment center, machine breakdowns, warehouse outages and capacity constraints; and
a destination Port Demurrage cost factor (PDMcost) scored by calculating a dwell time of an inbound container and multiplying by the number of days over and above an agreed free days at the port of dispatch;
computing a priority score for each of the plurality of FCLs having container status as ready-for-pickup and not-ready- for-pick-up, wherein the priority score is a ratio of integrated individual scores obtained for each the plurality of factors to a total number of FCLs with associated container status, wherein the priority score is based on lead time prediction and computed using information of location of the inbound container, climatic disruptions in the location of the inbound container, demurrage and detention charges, product characteristics information including seasonality, perishability, and product cost details,
generating a ranking list of the inbound containers comprising the plurality of FCLs in the order of the priority scores with container status ready for pickup followed by not-ready-for-pickup;
communicating the ranking list of ready for pickup followed by not-ready- for-pickup FCLs to the retailer;
receiving last minute requirements, a carriers list for picking up and associated driver contacts from the retailer, upon receiving the ranking list;
dynamically recomputing the ranking list by updating the ranking list based on the last minute requirements revised by the retailer;
tagging the inbound container from the updated ranking list to the carrier from the carriers list received from the retailer and notifying the corresponding driver with information of the inbound container identification and location to be picked up;
determining a last moment failure of the carrier;
identifying a next inline carrier to continue the task without glitches in response to determining the last moment failure, wherein information of the next inline carrier tagged to the inbound container includes the inbound container location and identification, [and] locating the inbound container; and
picking freight from the tagged inbound container by the carrier upon obtaining information of the next inline carrier tagged to the inbound container for delivery to the warehouse of the retailer,
computing the priority score for each inbound container and generating the ranking list of the inbound containers,
locating a purchase order or container product in the supply chain through interactive visual route maps and pop-up reports on specific ports enroute the destination and when the carrier has a GPS device on the inbound container or an ELD (Electronic Logging Devices) devices on the inbound container, then feeding current location coordinates to compute the lead time prediction.
Independent claims 4 and 7 substantially recite predicting a set of the inbound containers arriving at a port of dispatch within a stipulated timeframe for a plurality of products ordered by a retailer, wherein the set of inbound containers comprise a combination of a plurality of Full Container Loads (FCLs) and a plurality of Less than Container Loads (LCLs);
dynamically determining individual scores of a plurality of factors impacting inbound container prioritization of the plurality of FCLs for the stipulated timeframe based on one or more of a plurality of parameters that are either computed, derived, or obtained from a plurality of external resources or a plurality of internal resources, wherein a container status of each of the plurality of FCLs is one of (i) ready-for-pickup and (ii) not-ready-for-pickup, wherein the container status ready-for-pickup is obtained by a feed from the carrier or from a retailer's customs agent, wherein a regression based models are trained based on a plurality of features associated with the container status to predict the inbound containers that are not ready for pick up, wherein the plurality of factors comprising:
a Port Lead Time factor (PLTfact) scored based on a time required for requesting a carrier to pick up the FCL and time required for the carrier to move from a current location to the port;
a Product Demand fulfilment factor (PDshortage) scored based on a demand shortage for each product in the FCL container to determine if a required demand can be met within a buffer time to a warehouse of the retailer, wherein number of products with the demand shortage and a seasonality of the products contribute to value of the PDshortage;
a delivery Route Clearance factor (RCfact) scored by validating traffic, weather, and shortest path from the port to a destination set by the retailer using geographic coordinates of the warehouse;
a destination Distribution Centre (DC) Dock availability factor (DCDfact) scored by validating congestion at a warehouse docking gate;
a destination DC Resource availability factor (DCRfact) scored by predicting absentees among employees for better labor planning and shift allocation at a fulfilment center, machine breakdowns, warehouse outages and capacity constraints; and
a destination Port Demurrage cost factor (PDMcost) scored by calculating a dwell time of an inbound container and multiplying by the number of days over and above an agreed free days at the port of dispatch;
computing a priority score for each of the plurality of FCLs having container status as ready-for-pickup and not-ready- for-pick-up, wherein the priority score is a ratio of integrated individual scores obtained for each the plurality of factors to a total number of FCLs with associated container status, wherein the priority score is based on lead time prediction and computed using information of location of the inbound container, climatic disruptions in the location of the inbound container, demurrage and detention charges, product characteristics information including seasonality, perishability, and product cost details,
generating a ranking list of the inbound containers comprising the plurality of FCLs in the order of the priority scores with container status ready for pickup followed by not-ready-for-pickup;
communicating the ranking list of ready for pickup followed by not-ready- for-pickup FCLs to the retailer;
receiving last minute requirements, a carriers list for picking up and associated driver contacts from the retailer, upon receiving the ranking list;
dynamically recomputing the ranking list by updating the ranking list based on the last minute requirements revised by the retailer;
tagging the inbound container from the updated ranking list to the carrier from the carriers list received from the retailer and notifying the corresponding driver with information of the inbound container identification and location to be picked up;
determining a last moment failure of the carrier;
identifying a next inline carrier to continue the task without glitches in response to determining the last moment failure, wherein information of the next inline carrier tagged to the inbound container includes the inbound container location and identification, [and] locating the inbound container; and
picking goods/freight from the tagged inbound container by the carrier upon obtaining information of the next inline carrier tagged to the inbound container for delivery to the warehouse of the retailer,
computing the priority score for each inbound container and generating the ranking list of the inbound containers,
locating a purchase order or container product in the supply chain through interactive visual route maps and pop-up reports on specific ports enroute the destination and when the carrier has a GPS device on the inbound container or an ELD (Electronic Logging Devices) devices on the inbound container, then feeding current location coordinates to compute the lead time prediction.
The limitations stated above are processes/functions that under broadest reasonable interpretation covers “certain methods of organizing human activity” (commercial or legal interactions) of container prioritization in supply chain management. Therefore, the claim recites an abstract idea.
Step 2A, Prong Two
The judicial exception is not integrated into a practical application. Claims 1, 4, and 7 as a whole amount to: (i) merely invoking generic components as a tool to perform the abstract idea or “apply it” (or an equivalent), and (ii) generally links the use of a judicial exception to a particular technological environment or field of use. The claim recites the additional elements of: (i) one or more hardware processors (claims 1, 4), (ii) one or more Input/Output (I/O) interfaces (claim 4), (iii) a memory storing instructions (claim 4), (iv) an end communication device (claims 1, 4, 7), (v) a GPS receiver (claims 1, 4, 7), (vi) artificial intelligence models (claims 1, 4, 7), (vii) a plurality of components (claims 1, 4, 7), (viii) a spotting agent (claims 1, 4, 7), (ix) an open weather agent (claims 1, 4, 7), (x) a google traffic agent (claims 1, 4, 7), (xi) a demand sensing agent (claims 1, 4, 7), (xii) an inventory tracking agent (claims 1, 4, 7), (xiii) a cost manager (claims 1, 4, 7), and (xiv) a master data integrator (claims 1, 4, 7).
The additional elements of (i) one or more hardware processors, (ii) one or more Input/Output (I/O) interfaces, (iii) a memory storing instructions, (iv) an end communication device, (v) a GPS receiver, (vii) a plurality of components, (viii) a spotting agent, (ix) an open weather agent, (x) a google traffic agent, (xi) a demand sensing agent, (xii) an inventory tracking agent, (xiii) a cost manager, and (xiv) a master data integrator are recited at a high level of generality (see [0031] of the Applicants’ PG Publication discussing the one or more hardware processors, [0032] discussing the one or more Input/Output (I/O) interfaces, [0033] discussing the memory, [0047] discussing the end communication device, [0034] discussing the GPS receiver, [0052] discussing the plurality of components, [0053] discussing the spotting agent, [0054] discussing the open weather agent, [0055] discussing the google traffic agent and the demand sensing agent, [0056] discussing the inventory tracking agent, [0057] discussing the cost manager, and [0058] discussing the master data integrator) such that, when viewed as whole/ordered combination, it amounts to no more than mere instruction to apply the judicial exception using generic computer components or “apply it” (See MPEP 2106.05(f)).
The additional element of (vi) artificial intelligence models are recited at a high level of generality (See [0068] of the Applicant' s PG Publication discussing the artificial intelligence models) such that when viewed as whole/ordered combination, do no more than generally link the use of the judicial exception to a particular technological environment or field of use (i.e., machine learning modeling) (See MPEP 2106.05(h)).
Accordingly, these additional elements, when viewed as a whole/ordered combination [See Figures 1A & 1B showing all the additional (i) one or more hardware processors, (ii) one or more Input/Output (I/O) interfaces, (iii) a memory storing instructions, (iv) an end communication device, (v) a GPS receiver, (vi) artificial intelligence models, (vii) a plurality of components, (viii) a spotting agent, (ix) an open weather agent, (x) a google traffic agent, (xi) a demand sensing agent, (xii) an inventory tracking agent, (xiii) a cost manager, and (xiv) a master data integrator in combination], do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. Thus, the claim is directed to an abstract idea.
Step 2B
As discussed above with respect to Step 2A Prong Two, the additional elements amount to no more than: (i) “apply it” (or an equivalent), and (ii) generally link the use of a judicial exception to a particular technological environment or field of use, and are not a practical application of the abstract idea. The same analysis applies here in Step 2B, i.e., (i) merely invoking the generic components as a tool to perform the abstract idea or “apply it” (See MPEP 2106.05(f)); and (ii) generally linking the use of a judicial exception to a particular technological environment or field of use (See MPEP 2106.05(h)), does not integrate the abstract idea into a practical application at Step 2A or provide an inventive concept at Step 2B. Thus, even when viewed as a whole/ordered combination, nothing in the claims adds significantly more (i.e., an inventive concept) to the abstract idea. Thus, the claims 1, 4, and 7 are ineligible.
Dependent Claims 2, 3, 5, 6, 8, and 9 merely narrow the previously recited abstract idea limitations. For reasons described above with respect to claims 1, 4, and 7 these judicial exceptions are not meaningfully integrated into a practical application or significantly more than the abstract idea. Thus, claims 2, 3, 5, 6, 8, and 9 are also ineligible.
Step 2A, Prong Two
12. Dependent Claim 10 further narrows the previously recited abstract idea limitations, further substantially reciting the additional abstract ideas of: identifying the climatic disruptions by utilizing the inbound container location to automatically scale temperature and weather to ensure that uncertainties are reported and assist the container status prediction by feeding in disruptions data, wherein when there are any disruptions, then a delay is fed back to a lead time prediction algorithm to factor the delay caused by nature,
geo-locating the inbound container in a road by manually feeding coordinates and assisting in predicting the lead time from the port of dispatch or destination to the final warehouse,
importing a four-day rolling and four-week rolling demand planning and sales forecast generated by a retailer's inventory replenishment systems and a demand data is used in calculating a demand gap for the inbound container prioritization,
connecting in near real-time with a retailer to track on-shelf availability at a relevant warehouses and the data is then fed into the inbound container prioritization for calculating the demand gap along with demand forecast data,
calculating a variable cost involved in the supply chain by integrating actuals from retailer's Enterprise resource planning (ERP) systems, external time sensitive costs including demurrage and detention charges, wherein an input data is sourced directly from a shipping port depending on the availability and the input data is fed for the inbound container prioritization computation and determining the priority score of each inbound container, and
integrating a product, location, supplier, and master data from the retailer's systems once a day, wherein an input data containing product characteristics information including seasonality, perishability, and product cost details are used in the inbound container prioritization to validate a shelf life of the product.
Claim 10 also recites the additional elements of a retailer’s inventory system, which is recited at a high-level of generality (See [0052] of the Applicants PG Publication disclosing the retailer’s inventory system) such that, when viewed as whole/ordered combination, it amounts to no more than mere instruction to apply the judicial exception using generic computer components or “apply it” (See MPEP 2106.05(f)).
13. Accordingly, the additional elements, when viewed individually and as a whole/ordered combination, do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. Thus, the claims are directed to an abstract idea.
Step 2B
4. As discussed above with respect to Step 2A Prong Two, the additional element amounts to no more than: “apply it” (or an equivalent), and is not a practical application of the abstract idea. The same analysis applies here in Step 2B, i.e., (i) merely invoking the generic components as a tool to perform the abstract idea or “apply it” (See MPEP 2106.05(f)), does not integrate the abstract idea into a practical application at Step 2A or provide an inventive concept at Step 2B.
15. Therefore, the additional element of a retailer’s inventory system does not integrate the abstract idea into a practical application at Step 2A or provide an inventive concept at Step 2B. Thus, even when viewed as a whole/ordered combination, nothing in the claim adds significantly more (i.e., an inventive concept) to the abstract idea. Thus, claim 10 is ineligible.
Step 2A, Prong Two
12. Dependent Claim 11 further narrows the previously recited abstract idea limitations, further substantially reciting the additional abstract ideas of: wherein the plurality of parameters includes a cost incurred in the time taken for the inbound container to reach the port of dispatch and the time for a carrier planned by the retailer, a weight of importance in calculating port lead time for ready-for-pickup inbound containers, a weight of importance in calculating port lead time for not-ready-for-pickup inbound containers, a supplier manufacturing lead time in days, a supplier agent customs lead time at port of loading in days, total time of the inbound container in the ocean in days, the retailer's agent customs lead time at Port of dispatch in days, an inbound container dwell time at the port of dispatch in days, a weight of importance in calculating a product demand for the 'ready- for-pickup inbound containers which can or cannot fulfil the demand in surplus, a weight of importance in calculating the product demand for the not-ready-for-pickup inbound containers which can or cannot fulfil the demand in surplus, a cost incurred in forecasting potential delays in outbound due to predicted traffic disruptions and weather catastrophe, a time taken by the carrier in hours from source to the destination, a status of the outbound route retrieved to identify traffic and weather predictions, a weight of importance in calculating resource availability.
Claim 11 also recites the additional elements of Google APIs, which is recited at a high-level of generality (See [0087-0088] of the Applicants PG Publication disclosing the Google APIs) such that when viewed as whole/ordered combination, the additional elements do no more than generally link the use of the judicial exception to a particular technological environment or field of use (i.e., Application Programming Interfaces) (See MPEP 2106.05(h)).
13. Accordingly, the additional elements, when viewed individually and as a whole/ordered combination, do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. Thus, the claims are directed to an abstract idea.
Step 2B
14. As discussed above with respect to Step 2A Prong Two, the additional element amounts to no more than: generally linking the use of a judicial exception to a particular technological environment or field of use, and is not a practical application of the abstract idea. The same analysis applies here in Step 2B, i.e., (i) generally linking the use of a judicial exception to a particular technological environment or field of use (See MPEP 2106.05(h)), does not integrate the abstract idea into a practical application at Step 2A or provide an inventive concept at Step 2B.
15. Therefore, the additional element of Google APIs does not integrate the abstract idea into a practical application at Step 2A or provide an inventive concept at Step 2B. Thus, even when viewed as a whole/ordered combination, nothing in the claim adds significantly more (i.e., an inventive concept) to the abstract idea. Thus, claim 11 is ineligible.
Novel and Non-Obvious Over the Prior Art
Claims 1-9 are novel and non-obvious over the prior art; however, these claims are subject to the above rejections.
The closest prior art is U.S. Patent Application No. 2022/0292455 to Gabrielson (hereafter Gabrielson). Gabrielson discloses container prioritization at a port within a supply chain factoring in readiness for pickup of inbound containers containing a plurality of products ordered by a retailer, product demand fulfillment, assessing route clearance based on traffic and weather, determining priority scores for containers based on a plurality of factors, and creating a ranking list based on prioritization scores
The next closest prior art is Chinese Patent No. 108,451,329 to Fu (hereafter Fu). Fu discloses container sortation factoring in port lead time based on waiting time for carrier to pick up the containers from the port.
The next closest prior art is W.I.P.O. Patent Application No. 2021/183044 to Gueta (hereafter Gueta). Gueata discloses determining FCLs for a specified time frame, and prioritizing containers in consideration of demurrage costs.
The next closest prior art is U.S. Patent Application No. 2019/0287066 to Kellaway (hereafter Kellaway). Kellaway discloses distribution center resource availability and capac