DETAILED ACTION
Status of Claims
This action is in reply to the Applicant Remarks and Amendments filed on 06/20/2025.
Claims 1, 6, 9, 14, 17, and 19 have been amended and are hereby entered.
Claims 1-20 are currently pending and have been examined.
This action is made FINAL.
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 .
Examiner Notes
Examiner believes that the interview identified was for a difference case. However, Applicant is more than welcome to reach out to Examiner for clarification if needed.
Response to Arguments
Applicant's arguments, see Pages 10-11, filed 06/20/2025, with respect to the 35 U.S.C. 101 rejection of Claims 1-20 have been fully considered, but they are not persuasive.
Examiner respectfully disagrees with Applicant’s arguments on Page 10: “Under Step 2A Prong One, a claim with limitations that are merely based on or involve an abstract idea does not recite an abstract idea. Claim 1 recites a system including location detectors mounted to a vehicle and a device, and an approach for using the data generated by the detectors to apply a machine learning algorithm to determine time predictions and further determine whether the device will be present at a specification location within a predetermined time window, and transmit different notification based thereon. In order to recite this approach, claim 1 does include elements such as speed profile generation, model application, route generation, and distance determinations. However, these elements at most are merely based on or involve commercial interactions - they do not recite such interactions themselves. The Office Action (top of page 12) appears to agree, noting that the aforementioned elements "cover concepts that involve a commercial interaction." As the listed limitations in claim 1 are merely based on or involve commercial interactions, claim 1 does not recite a fundamental economic concept or any other abstract idea and is therefore eligible under Step 2A Prong One.”. Examiner respectfully disagrees because the limitation that covers concepts that involve commercial interaction is the abstract idea (Certain Methods of Organizing Human Activity) (See MPEP 2106.04(a)). Additionally, “location detectors mounted to a vehicle and a device” and “machine learning” are considered to be additional elements that are recited at a high level of generality and amount to mere instructions to apply the abstract idea on a generic computer (See MPEP 2106.05(f)). Therefore, the arguments are not persuasive.
Examiner respectfully disagrees with Applicant’s arguments on Pages 10-11: “The present claims recite additional elements that integrate the alleged abstract idea into a practical application under Step 2A Prong Two. Claim 1 solves a technological problem involving computers running machine learning models. Specifically, machine learning models traditionally use data sets generated from past activity to predict a future outcome. Often, such activity is unrelated to a problem corresponding to the future outcome, or is only partially related. For instance, the prior art cited in the Office Action uses statistical data from past deliveries to predict an outcome for a current delivery, even though the current delivery is unrelated to the past delivery from which the predictions obtain their training data. The technical solution recited in claim 1 generates a "time prediction based on a time difference between timestamps of two events ... associated with movement of the current delivery order," with such movement being obtained "in real time as the delivery vehicle is delivering the current delivery order." Thus, computing technology applying the claimed improvement to time predictions no longer need to rely upon past data to predict future outcomes, and instead may use real time data flowing from the technical setup recited in the claim - specifically, the ordered combination of location detectors, profile generation, feature data generation, and application of a model based on time differences between timestamps of events associated with the data generated and processed by the aforementioned features. The technical solution described above goes beyond mere "improvement of the delivery process" and "optimizing delivery routes," and instead improves how computers structure machine learning algorithms for scenarios in which such algorithms do not have straightforward access to historical data. The aforementioned technical solution is a practical application of computing technology, integrating the combination of real-time data gathering and machine learning processing into a practical approach for predicting time-based location data of a device using only the time-based location data currently available to the process. This practical application clearly integrates the underlying concepts according to the requirements of Step 2A Prong Two as discussed above, and for these reasons, claim 1 is eligible.”. Examiner respectfully disagrees because the use of real time data to predict future outcomes does not provide improvements to the functioning of a computer or to any other technology or technical filed, but instead it provides improvement to the abstract idea. See MPEP 2106.05(a)II, “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.”. Therefore, the arguments are not persuasive.
Applicant’s arguments, see Page 12, filed 06/20/2025, with respect to the 35 U.S.C. 103 rejection of Claims 1-20 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Claim Objections
Claim 9 is objected to because of the following informalities: there are duplicate limitations – “wherein two or more location detectors of the plurality of location detectors are respectively attached to the delivery vehicle and a delivery device” in receiving and first generating steps. 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 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Claims 1-20 are directed to one of the four statutory categories (process, machine, article of manufacture, or composition of matter) since the claimed invention falls into “a process” (a method for door-step time estimation delivery route optimization), “a machine” (a system for door-step time estimation delivery route optimization), and “an article of manufacture” (a computer program product for door-step time estimation delivery route optimization) categories.
Regarding Claims 1-20, the claim invention is directed to a judicial exception to patentability, an abstract idea.
Claim 1 recites the following limitations:
… to:
determine one or more locations associated with a current delivery order;
receive location data from … in real time as the delivery vehicle is delivering the current delivery order;
generate, based on the one or more locations and real-time location data associated with …, a speed profile for the current delivery order indicating a plurality of events associated with a movement of the current delivery order to a respective delivery location;
generate, based on the speed profile and the real-time location data associated with …, feature data of the respective delivery location, wherein the feature data includes descriptive information discerned from the speed profile for the current delivery order;
apply a … model to the generated feature data to output a door-step time prediction for the respective delivery location, the door-step time prediction being based on a time difference between timestamps of two events of the plurality of events associated with the movement of the current delivery order;
generate a planned delivery route for the respective delivery location based on the one or more locations and the door-step time prediction;
determine a distance between the current delivery order and the respective delivery location by comparing the location data associated with … and the planned delivery route;
…; and …
Step 2A, Prong 1: The limitations for Claim 1 described above are processes that, under their broadest reasonable interpretation, cover concepts that involve commercial interactions. The limitations of determining, receiving, generating a speed profile and feature data, applying a model, generating a planned delivery route, and determining a distance are processes that, under their broadest reasonable interpretation, cover concepts that involve a commercial interaction such as managing business relations. Therefore, other than reciting a generic computerized system, a generic database, and generic user devices, nothing in the claim elements preclude anything outside the grouping of “Certain Methods of Organizing Human Activity”. Accordingly, this claim recites an abstract idea.
Step 2A, Prong 2: This judicial exception is not integrated into a practical application. Claim 1 recites additional elements – “a system comprising: a plurality of location detectors, wherein two or more location detectors of the plurality of location detectors are respectively attached to a delivery vehicle and a delivery device; a processor; and a non-transitory memory storing instructions that, when executed, cause the processor to”, “machine learning model”, “the plurality of location detectors”, “in response to determining the distance between the current delivery order and the respective delivery location indicates the delivery order will be delivered within a corresponding window, transmit, to a user device, a first notification corresponding to the distance of the current delivery order to the respective delivery location”, and “in response to determining the distance between the current delivery order and the respective delivery location indicates the current delivery order will not be delivered within a corresponding window, transmit, to the user device, a second notification indicating the current delivery order is delayed”. The additional elements “in response to determining the distance between the delivery order and the respective delivery location indicates the delivery order will be delivered within a corresponding window” and “in response to determining the distance between the delivery order and the respective delivery location indicates the delivery order will not be delivered within a corresponding window” in the claim limitation represents mere generally linking of the use of the judicial exception (the abstract idea) to a particular technological environment or field of use (See MPEP 2106.05(h)). The claim as a whole merely describes how to generally “apply” the concept of determining, receiving, generating a speed profile and feature data, applying a model, generating a planned delivery route, and determining a distance by using generic computer components. The claimed computer components are recited at high level of generality and merely invoked as a tool to perform a process for door-step time estimation and delivery route optimization (See MPEP 2106.05(f)). The additional elements of “transmit, to a user device, a first notification corresponding to the distance of the delivery order to the respective delivery location” and “transmit, to the user device, a second notification indicating the delivery order is delayed” are merely adding insignificant extra-solution activity to the judicial exception and amount to mere data gathering (See MPEP 2106.05(g)). Accordingly, alone and in combination, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. This claim is directed to an abstract idea.
Step 2B: Claim 1 does 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 elements of using a computer system to perform a process for door-step time estimation and delivery route optimization amount to no more than how to generally “apply” the exception using a generic computer component (See MPEP 2106.05(f)) and representing mere generally linking of the use of the abstract idea to a particular technological environment or field of use (See MPEP 2106.05(h)). The step of transmitting notifications of Step 2A has been re-evaluated in Step 2B and determined to be well-understood, routine, conventional activity in the field. The Symantec, TLI, and OIP Techs court decisions cited in MPEP 2106.05(d)(II) indicate that receiving or transmitting data over a network is a well-understood, routine, and conventional function when it is claimed in a merely generic manner (as it is here). For these reasons, there is no inventive concept in the claim, and thus it is not patent eligible.
Claim 2 recites the following limitations:
The system of claim 1, wherein … is …, and the instructions further cause … to:
receive the location data from …;
associate the location data from … to the delivery order; and
process the associated location data to remove invalid location data.
Claim 2 is directed to substantially the same abstract idea as Claim 1 and is rejected for substantially the same reasons. The additional recited limitations of the dependent claim fail to establish that the claim does not recite an abstract idea because the additional recited limitations of the claim further narrow the abstract idea.
Step 2A, Prong 2: Claim 2 does not integrate the abstract idea into practical application. Claim 2 recites additional elements – “the delivery device”, “a handheld scanning device”, “the processor”, and “the plurality of location detectors”. These additional elements amount to no more than mere instructions to apply the exception using generic computer components. The limitations of this dependent claim do not integrate an abstract idea into a practical application because individually or in combination, these additional elements do not impose any meaningful limits on a practicing the abstract idea and amount to no more than mere instructions to apply the exception using a generic computer component (See MPEP 2106.05(f)).
Step 2B: Claim 2 does 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 elements of using a computer system to perform a process for door-step time estimation and delivery route optimization amount to no more than how to generally “apply” the exception using a generic computer component (See MPEP 2106.05(f)). Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. Therefore, this dependent claim is not patent eligible.
Claims 3 and 5-7 are directed to substantially the same abstract idea as Claim 1 and are rejected for substantially the same reasons. The additional recited limitations of the dependent claims fail to establish that the claims do not recite an abstract idea because the additional recited limitations of the claims further narrow the abstract idea. These dependent claims further narrow the abstract idea of Claim 1 such as by defining “wherein the instructions further cause … to generate the speed profile by applying a changepoint detection algorithm to the location data of the delivery order to determine changes in a sequence of the location data and plotted locations within the location data” in Claim 3, by defining “wherein the instructions further cause … to generate the feature data based on at least one of a dwelling-type of the delivery location and a time period the delivered order was delivered” in Claim 5, by defining “wherein the timestamps of the two events comprise a timestamp associated with a time when an ignition of a delivery vehicle transporting the delivery order is in an off-state and a timestamp associated with a time when the ignition of the delivery vehicle is in an on-state” in Claim 6, and by defining “wherein the door-step time prediction comprises a predicted duration for the two or more … of the plurality of … to be at the delivery location and is associated with a range of door-step time predictions having a mean value and prediction interval” in Claim 7.
Step 2A, Prong 2: Claims 3 and 5-7 do not integrate the abstract idea into practical application. Claim 6 does not recite additional elements, Claims 3 and 5 recites an additional element – “the processor”, and Claim 7 recite an additional element – “location detectors”. These additional elements amount to no more than mere instructions to apply the exception using generic computer components. The limitations of these dependent claims do not integrate an abstract idea into a practical application because individually or in combination, these additional elements do not impose any meaningful limits on a practicing the abstract idea and amount to no more than mere instructions to apply the exception using a generic computer component (See MPEP 2106.05(f)).
Step 2B: Claims 3 and 5-7 do not amount to significantly more than the abstract idea. Claim 6 does not recite additional elements, and Claims 3, 5, and 7 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 elements of using a computer system to perform a process for door-step time estimation and delivery route optimization amount to no more than how to generally “apply” the exception using a generic computer component (See MPEP 2106.05(f)). Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. Therefore, these claims are not patent eligible.
Claim 4 recites the following limitations:
The system of claim 1, wherein the instructions further cause … to generate the feature data by:
retrieving a history of a … associated with the respective delivery location, wherein the history indicates one or more dates and delivery windows of delivery orders, and indicates information of one or more goods included in the delivery orders; and
generating the feature data based on the speed profile, location data, weather forecasts, and history of the user that includes descriptive information associated with past delivery orders for the respective delivery location.
Claim 4 is directed to substantially the same abstract idea as Claim 1 and is rejected for substantially the same reasons. The additional recited limitations of the dependent claim fail to establish that the claim does not recite an abstract idea because the additional recited limitations of the claim further narrow the abstract idea.
Step 2A, Prong 2: Claim 4 does not integrate the abstract idea into practical application. Claim 4 recites additional elements – “the processor” and “user device”. These additional elements amount to no more than mere instructions to apply the exception using generic computer components. The limitations of this dependent claim do not integrate an abstract idea into a practical application because individually or in combination, these additional elements do not impose any meaningful limits on a practicing the abstract idea and amount to no more than mere instructions to apply the exception using a generic computer component (See MPEP 2106.05(f)).
Step 2B: Claim 4 does 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 elements of using a computer system to perform a process for door-step time estimation and delivery route optimization amount to no more than how to generally “apply” the exception using a generic computer component (See MPEP 2106.05(f)). Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. Therefore, this dependent claim is not patent eligible.
Claim 8 recites the following limitations:
The system of claim 1, wherein the instructions further cause … to:
receive delivery orders to the one or more delivery locations; and
generate the planned delivery route by allocating the received delivery orders to one or more delivery vehicles based on the one or more delivery locations, requested deliver windows to receive the delivery order, and the door-step time predictions corresponding to the one or more delivery locations.
Claim 8 is directed to substantially the same abstract idea as Claim 1 and is rejected for substantially the same reasons. The additional recited limitations of the dependent claim fail to establish that the claim does not recite an abstract idea because the additional recited limitations of the claim further narrow the abstract idea.
Step 2A, Prong 2: Claim 8 does not integrate the abstract idea into practical application. Claim 8 recites an additional element – “the processor”. This additional element amounts to no more than mere instructions to apply the exception using generic computer components. The limitations of this dependent claim do not integrate an abstract idea into a practical application because individually or in combination, this additional element does not impose any meaningful limits on a practicing the abstract idea and amount to no more than mere instructions to apply the exception using a generic computer component (See MPEP 2106.05(f)).
Step 2B: Claim 8 does 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 elements of using a computer system to perform a process for door-step time estimation and delivery route optimization amount to no more than how to generally “apply” the exception using a generic computer component (See MPEP 2106.05(f)). Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. Therefore, this dependent claim is not patent eligible.
Claim 9 recites the following limitations:
A method comprising:
determining one or more locations associated with a current delivery order;
receiving location data from … in real time as a delivery vehicle is delivering the current delivery order, wherein …;
generating, based on the one or more locations and the real-time location data associated with …, a speed profile for the current delivery order indicating a plurality of events associated with a movement of the current delivery order to a respective delivery location, wherein …;
generating, based on the speed profile and the real-time location data associated with …, feature data of the respective delivery location, wherein the feature data includes descriptive information discerned from the speed profile for the current delivery order;
applying a … model to the generated feature data to output a door-step time prediction for the respective delivery location, the door-step time prediction being based on a time difference between timestamps of two events of the plurality of events associated with the movement of the current delivery order;
generating a planned delivery route for the respective delivery location based on the one or more locations and the door-step time prediction;
determining a distance between the current delivery order and the respective delivery location by comparing the location data associated with … and the planned delivery route;
…; and …
Step 2A, Prong 1: The limitations for Claim 9 described above are processes that, under their broadest reasonable interpretation, cover concepts that involve commercial interactions. The limitations of determining, receiving, generating a speed profile and feature data, applying a model, generating a planned delivery route, and determining a distance are processes that, under their broadest reasonable interpretation, cover concepts that involve a commercial interaction such as managing business relations. Therefore, other than reciting a generic computerized system, a generic database, and generic user devices, nothing in the claim elements preclude anything outside the grouping of “Certain Methods of Organizing Human Activity”. Accordingly, this claim recites an abstract idea.
Step 2A, Prong 2: This judicial exception is not integrated into a practical application. Claim 9 recites additional elements – “a plurality of location detectors”, “two or more location detectors of the plurality of location detectors are respectively attached to the delivery vehicle and a delivery device”, “machine learning model”, and “in response to determining the distance between the current delivery order and the respective delivery location indicates the delivery order will be delivered within a corresponding window, transmitting, to a user device, a first notification corresponding to the distance of the current delivery order to the respective delivery location”, and “in response to determining the distance between the current delivery order and the respective delivery location indicates the current delivery order will not be delivered within a corresponding window, transmitting, to the user device, a second notification indicating the current delivery order is delayed”. The additional elements “in response to determining the distance between the current delivery order and the respective delivery location indicates the current delivery order will be delivered within a corresponding window” and “in response to determining the distance between the current delivery order and the respective delivery location indicates the current delivery order will not be delivered within a corresponding window” in the claim limitation represents mere generally linking of the use of the judicial exception (the abstract idea) to a particular technological environment or field of use (See MPEP 2106.05(h)). The claim as a whole merely describes how to generally “apply” the concept of determining, receiving, generating a speed profile and feature data, applying a model, generating a planned delivery route, and determining a distance by using generic computer components. The claimed computer components are recited at high level of generality and merely invoked as a tool to perform a process for door-step time estimation and delivery route optimization (See MPEP 2106.05(f)). The additional elements of “transmitting, to a user device, a first notification corresponding to the distance of the current delivery order to the respective delivery location” and “transmitting, to the user device, a second notification indicating the current delivery order is delayed” are merely adding insignificant extra-solution activity to the judicial exception and amount to mere data gathering (See MPEP 2106.05(g)). Accordingly, alone and in combination, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. This claim is directed to an abstract idea.
Step 2B: Claim 9 does 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 elements of using a computer system to perform a process for door-step time estimation and delivery route optimization amount to no more than how to generally “apply” the exception using a generic computer component (See MPEP 2106.05(f)) and representing mere generally linking of the use of the abstract idea to a particular technological environment or field of use (See MPEP 2106.05(h)). The step of transmitting notifications of Step 2A has been re-evaluated in Step 2B and determined to be well-understood, routine, conventional activity in the field. The Symantec, TLI, and OIP Techs court decisions cited in MPEP 2106.05(d)(II) indicate that receiving or transmitting data over a network is a well-understood, routine, and conventional function when it is claimed in a merely generic manner (as it is here). For these reasons, there is no inventive concept in the claim, and thus it is not patent eligible.
Claim 10 recites the following limitations:
The method of claim 9, wherein … is …, the method further comprising:
associating the location data from … to the delivery order; and
processing the associated location data to remove invalid location data.
Claim 10 is directed to substantially the same abstract idea as Claim 9 and is rejected for substantially the same reasons. The additional recited limitations of the dependent claim fail to establish that the claim does not recite an abstract idea because the additional recited limitations of the claim further narrow the abstract idea.
Step 2A, Prong 2: Claim 10 does not integrate the abstract idea into practical application. Claim 10 recites additional elements – “the delivery device”, “a handheld scanning device”, and “a plurality of location detectors”. These additional elements amount to no more than mere instructions to apply the exception using generic computer components. The limitations of this dependent claim do not integrate an abstract idea into a practical application because individually or in combination, this additional element does not impose any meaningful limits on a practicing the abstract idea and amount to no more than mere instructions to apply the exception using a generic computer component (See MPEP 2106.05(f)).
Step 2B: Claim 10 does 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 elements of using a computer system to perform a process for door-step time estimation and delivery route optimization amount to no more than how to generally “apply” the exception using a generic computer component (See MPEP 2106.05(f)). Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. Therefore, this dependent claim is not patent eligible.
Claims 11 and 13-15 are directed to substantially the same abstract idea as Claim 9 and are rejected for substantially the same reasons. The additional recited limitations of the dependent claims fail to establish that the claims do not recite an abstract idea because the additional recited limitations of the claims further narrow the abstract idea. These dependent claims further narrow the abstract idea of Claim 9 such as by defining “wherein the generating the speed profile further comprises applying a changepoint detection algorithm to the location data of the delivery order” in Claim 11, by defining “wherein the generating the feature data further comprises generating feature data based on at least one of a dwelling-type of the delivery location and a time period the delivered order was delivered” in Claim 13, by defining “wherein the timestamps of the two events comprise a timestamp associated with a time when an ignition of a delivery vehicle transporting the delivery order in an off-state and a timestamp associated with a time when the ignition of the delivery vehicle is in an on-state” in Claim 14, and by defining “wherein the timestamps of the two events comprise a timestamp associated with a time when an ignition of a delivery vehicle transporting the delivery order in an off-state and a timestamp associated with a time when the ignition of the delivery vehicle is in an on-state” in Claim 15.
Step 2A, Prong 2: These dependent claims do not integrate the abstract idea into practical application because they do not recite additional elements.
Step 2B: These dependent claims do not amount to significantly more than the abstract idea because they do not recite additional elements. Therefore, this claim is not patent eligible.
Claim 12 recites the following limitations:
The method of claim 9, wherein the generating the feature data further comprises:
retrieving a history of a customer associated with the respective delivery location, wherein the history indicates one or more dates and delivery windows of delivery orders placed by the customer, and indicates information of one or more goods included in the delivery orders; and
generating the feature data based on the speed profile, location data, and
history of the customer.
Claim 12 is directed to substantially the same abstract idea as Claim 9 and is rejected for substantially the same reasons. The additional recited limitations of the dependent claim fail to establish that the claim does not recite an abstract idea because the additional recited limitations of the claim further narrow the abstract idea.
Step 2A, Prong 2: This dependent claim does not integrate the abstract idea into practical application because it does not recite additional elements.
Step 2B: This dependent claim does not amount to significantly more than the abstract idea because it does not recite additional elements. Therefore, this claim is not patent eligible.
Claim 16 recites the following limitations:
The method of claim 9, further comprising
receiving delivery orders to the one or more delivery locations,
wherein generating the planned delivery route further comprises allocating the received delivery orders to one or more delivery vehicles based on the one or more delivery locations, requested deliver windows to receive the delivery order, and the door-step time predictions corresponding to the one or more delivery locations.
Step 2A, Prong 2: This dependent claim does not integrate the abstract idea into practical application because it does not recite additional elements.
Step 2B: This dependent claim does not amount to significantly more than the abstract idea because it does not recite additional elements. Therefore, this claim is not patent eligible.
Claim 17 recites the following limitations:
… comprising:
determining one or more locations associated with a delivery order;
receiving location data from … in real time as a delivery vehicle is delivering the current delivery order, wherein …;
generating, based on the one or more locations and the real-time location data associated with …, a speed profile for the current delivery order indicating a plurality of events associated with a movement of the current delivery order to a respective delivery location;
generating, based on the speed profile and the real-time location data associated with …, feature data of the respective delivery location, wherein the feature data includes descriptive information discerned from the speed profile for the current delivery order;
applying a … model to the generated feature data to output a door-step time prediction for the respective delivery location, the door-step time prediction being based on a time difference between timestamps of two events of the plurality of events associated with the movement of the current delivery order;
generating a planned delivery route for the respective delivery location based on the one or more locations and the door-step time prediction;
determining a distance between the current delivery order and the respective delivery location by comparing the location data associated with … and the planned delivery route;
…; and …
Step 2A, Prong 1: The limitations for Claim 17 described above are processes that, under their broadest reasonable interpretation, cover concepts that involve commercial interactions. The limitations of determining, receiving, generating a speed profile and feature data, applying a model, generating a planned delivery route, and determining a distance are processes that, under their broadest reasonable interpretation, cover concepts that involve a commercial interaction such as managing business relations. Therefore, other than reciting a generic computerized system, a generic database, and generic user devices, nothing in the claim elements preclude anything outside the grouping of “Certain Methods of Organizing Human Activity”. Accordingly, this claim recites an abstract idea.
Step 2A, Prong 2: This judicial exception is not integrated into a practical application. Claim 17 recites additional elements – “a computer program product comprising a non-transitory computer readable medium storing instructions, that, when executed by one or more processors, cause a device to perform operations”, “a plurality of location detectors”, “two or more location detectors of the plurality of location detectors are respectively attached to the delivery vehicle and a delivery device”, “machine learning model”, “in response to determining the distance between the current delivery order and the respective delivery location indicates the current delivery order will be delivered within a corresponding window, transmitting, to a user device, a first notification corresponding to the distance of the current delivery order to the respective delivery location”, and “in response to determining the distance between the current delivery order and the respective delivery location indicates the current delivery order will not be delivered within a corresponding window, transmitting, to the user device, a second notification indicating the current delivery order is delayed”. The additional elements “in response to determining the distance between the current delivery order and the respective delivery location indicates the current delivery order will be delivered within a corresponding window” and “in response to determining the distance between the current delivery order and the respective delivery location indicates the current delivery order will not be delivered within a corresponding window” in the claim limitation represents mere generally linking of the use of the judicial exception (the abstract idea) to a particular technological environment or field of use (See MPEP 2106.05(h)). The claim as a whole merely describes how to generally “apply” the concept of determining, receiving, generating a speed profile and feature data, applying a model, generating a planned delivery route, and determining a distance by using generic computer components. The claimed computer components are recited at high level of generality and merely invoked as a tool to perform a process for door-step time estimation and delivery route optimization (See MPEP 2106.05(f)). The additional elements of “transmit, to a user device, a first notification corresponding to the distance of the current delivery order to the respective delivery location” and “transmit, to the user device, a second notification indicating the current delivery order is delayed” are merely adding insignificant extra-solution activity to the judicial exception and amount to mere data gathering (See MPEP 2106.05(g)). Accordingly, alone and in combination, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. This claim is directed to an abstract idea.
Step 2B: Claim 17 does 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 elements of using a computer system to perform a process for door-step time estimation and delivery route optimization amount to no more than how to generally “apply” the exception using a generic computer component (See MPEP 2106.05(f)) and representing mere generally linking of the use of the abstract idea to a particular technological environment or field of use (See MPEP 2106.05(h)). The step of transmitting notifications of Step 2A has been re-evaluated in Step 2B and determined to be well-understood, routine, conventional activity in the field. The Symantec, TLI, and OIP Techs court decisions cited in MPEP 2106.05(d)(II) indicate that receiving or transmitting data over a network is a well-understood, routine, and conventional function when it is claimed in a merely generic manner (as it is here). For these reasons, there is no inventive concept in the claim, and thus it is not patent eligible.
Claim 18 recites the following limitations:
The computer program product of claim 17, wherein the generating the feature data further comprises:
retrieving a history of a customer associated with the respective delivery location, wherein the history indicates one or more dates and delivery windows of delivery orders placed by the customer, and indicates information of one or more goods included in the delivery orders; and
generating the feature data based on the speed profile, location data, and
history of the customer.
Claim 18 is directed to substantially the same abstract idea as Claim 17 and is rejected for substantially the same reasons. The additional recited limitations of the dependent claim fail to establish that the claim does not recite an abstract idea because the additional recited limitations of the claim further narrow the abstract idea.
Step 2A, Prong 2: This dependent claim does not integrate the abstract idea into practical application because it does not recite additional elements.
Step 2B: This dependent claim does not amount to significantly more than the abstract idea because it does not recite additional elements. Therefore, this claim is not patent eligible.
Claim 19 recites the following limitations:
The computer program product of claim 17, wherein the generating the feature data further comprises generating feature data based on at least one of a dwelling-type of the delivery location and a time period the delivered order was delivered, and
wherein the timestamps of the two events comprise a timestamp associated with a time when an ignition of a delivery vehicle transporting the delivery order is in an off-state and a timestamp associated with a time when the ignition of the delivery vehicle is in an on-state.
Claim 19 is directed to substantially the same abstract idea as Claim 17 and is rejected for substantially the same reasons. The additional recited limitations of the dependent claim fail to establish that the claim does not recite an abstract idea because the additional recited limitations of the claim further narrow the abstract idea.
Step 2A, Prong 2: This dependent claim does not integrate the abstract idea into practical application because it does not recite additional elements.
Step 2B: This dependent claim does not amount to significantly more than the abstract idea because it does not recite additional elements. Therefore, this claim is not patent eligible.
Claim 20 recites the following limitations:
The computer program product of claim 17 wherein the instructions further cause … to perform operations comprising:
receiving delivery orders to the one or more delivery locations,
wherein generating the planned delivery route further comprises allocating the received delivery orders to one or more delivery vehicles based on the one or more delivery locations, requested deliver windows to receive the delivery order, and the door-step time predictions corresponding to the one or more delivery locations.
Claim 20 is directed to substantially the same abstract idea as Claim 17 and is rejected for substantially the same reasons. The additional recited limitations of the dependent claim fail to establish that the claim does not recite an abstract idea because the additional recited limitations of the claim further narrow the abstract idea.
Step 2A, Prong 2: Claim 20 does not integrate the abstract idea into practical application. Claim 20 recites an additional element – “the device”. This additional element amounts to no more than mere instructions to apply the exception using generic computer components. The limitations of this dependent claim do not integrate an abstract idea into a practical application because individually or in combination, this additional element does not impose any meaningful limits on a practicing the abstract idea and amount to no more than mere instructions to apply the exception using a generic computer component (See MPEP 2106.05(f)).
Step 2B: Claim 20 does 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 elements of using a computer system to perform a process for door-step time estimation and delivery route optimization amount to no more than how to generally “apply” the exception using a generic computer component (See MPEP 2106.05(f)). Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. Therefore, this dependent claim is not patent eligible.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
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.
Claims 1, 4-9, and 12-20 are rejected under 35 U.S.C. 103 as being unpatentable over Radetzki et al. (US PG Pub. No. 2019/0114588 A1; hereinafter "Radetzki") in view of Dashti et al. (US PG Pub. No. 2020/0116508 A1; hereinafter "Dashti"), Scalisi et al. (US PG Pub. No. 2018/0075400 A1; hereinafter "Scalisi"), and Shroff et al. (US PG Pub. No. 2017/0262803 A1; hereinafter "Shroff").
Regarding Claim 1, Radetzki teaches a system comprising: …; a processor; and a non-transitory memory storing instructions that, when executed, cause the processor to (See Paragraphs [0016] and [0020]): generate, based on the one or more locations and the … location data associated with …, a speed profile for the current delivery order indicating a plurality of events associated with a movement of the current delivery order to a respective delivery location; generate, based on the speed profile and the … location data associated with …, feature data of the respective delivery location (See “In step 101, the historical delivery information is obtained and/or provided. In this case, the historical delivery information is associated with multiple deliveries of shipments made by one or various vehicles of the delivery service, wherein the historical delivery information for each of the deliveries of shipments associated with the historical delivery information represents at least details pertaining to a delivery route, …” in Paragraph [0120], “The historical delivery information represents one or more details characteristic of the respective delivery of shipments for each of the deliveries of shipments associated with the delivery information, for example. As disclosed above, such a detail characteristic of a delivery of shipments is intended to represent, by way of example, at least one parameter captured and/or determined by the vehicle that has made the delivery during the respective delivery, such as the energy requirement of the vehicle.” in Paragraph [0121], “It is subsequently assumed by way of example that the historical delivery information for each of the deliveries of shipments associated with the historical delivery information represents the delivery route along which the respective vehicle (i.e. the vehicle that has made the respective delivery) has been moved, …” in Paragraph [0122], “In a step 102, shipment delivery information for multiple shipments to be delivered is obtained, wherein the shipment delivery information represents, at least for each of the shipments, a detail pertaining to the delivery position for the delivery of the respective shipment.” in Paragraph [0124], “The trait that the shipment delivery information represents, at least for each of the shipments, a detail pertaining to the delivery position for the delivery of the respective shipment is intended to be understood, by way of example, such that the shipment delivery information contains a representation of the delivery position for the delivery of the respective shipment.” in Paragraph [0125], “In one exemplary embodiment of the invention, the historical delivery information for each of the deliveries of shipments associated with the delivery information further represents at least one or more of the following details: a detail pertaining to a vehicle speed and/or vehicle acceleration on the delivery route and/or on a section of the delivery route for the delivery of shipments associated with the respective delivery information, a detail pertaining to the nature of the delivery route and/or of a section of the delivery route for the delivery of shipments associated with the respective delivery information, and/or a detail pertaining to the timing of the delivery of shipments associated with the respective delivery information.” in Paragraphs [0077]-[0080], “A detail pertaining to a vehicle speed represents, by way of example, a vehicle speed of the vehicle on the delivery route and/or on a section of the delivery route that is captured and/or determined by the vehicle. For example, a detail pertaining to a vehicle speed can represent an average vehicle speed of the vehicle on the delivery route and/or on a section of the delivery route that is captured by the vehicle. Alternatively, a detail pertaining to a vehicle speed can represent a vehicle speed of the vehicle that is captured by the vehicle at a particular position on the delivery route.” in Paragraph [0081], and also see Paragraphs [0082]-[0084]), wherein the feature data includes descriptive information discerned from the speed profile for the current delivery order (See “The trait that the historical delivery information is associated with multiple deliveries of shipments made by one or various vehicle(s) (i.e. deliveries made in the past) is intended to be understood, by way of example, such that the historical delivery information for each of the deliveries of shipments associated with the delivery information represents one or more details characteristic of the respective delivery of shipments. Such a detail characteristic of a delivery of shipments represents, by way of example, a parameter capturable (e.g. captured) and/or determinable (e.g. determined) by the respective vehicle that has made the respective delivery during the respective delivery, such as the energy requirement of the respective vehicle. In this context, an energy requirement is intended to be understood to mean, by way of example, an absolute energy requirement (e.g. an energy requirement in kilowatt hours), an absolute fuel requirement (e.g. a petrol or diesel requirement in litres), a normalized energy requirement (e.g. a power in kilowatts (i.e. an energy requirement per unit time) or an energy requirement per unit distance (e.g. kilometre) or per shipment) and/or a normalized fuel requirement (e.g. a petrol or diesel requirement in litres per unit time (e.g. minute or hour) or per unit distance (e.g. kilometre) or per shipment) that has been captured and/or determined by the respective vehicle during the respective delivery.” in Paragraph [0027] and “The trait that the shipment delivery information at least for each of the shipments represents a detail pertaining to the delivery position for the delivery of the respective shipment is intended to be understood, by way of example, such that the shipment delivery information contains a representation of the delivery position for the delivery of the respective shipment. Examples of a representation of a position (e.g. of a delivery position) are address, position and/or coordinate details. An address detail is, by way of example, a representation of a postal address (e.g. of a postal address of a recipient of a shipment). A coordinate detail is, by way of example, a representation of coordinates of a position such as a delivery position (e.g. coordinates of a position according to a satellite-assisted navigation system and/or a geographical coordinate system such as the UTM (Universal Transverse Mercator) coordinate system on the basis of the geodetic reference system WGS84 (World Geodetic System 1984)).” in Paragraph [0035]); apply a machine learning model to the generated feature data to output a door-step time prediction for the respective delivery location, the door-step time prediction being based on a time difference between timestamps of two events of the plurality of events associated with the movement of the current delivery order (See Paragraph [0085], “A detail pertaining to a nature of the delivery route and/or of a section of the delivery route is intended to be understood to mean, by way of example, parameters captured and/or determined by the vehicle that are characteristic of the nature of the delivery route and/or of a section of the delivery route, such as a gradient (e.g. a maximum and/or minimum and/or average gradient) and/or a transport route surface (e.g. asphalt and/or gravel and/or earth) and/or the presence of obstacles (e.g. one or more steps, a fence, etc.) on the delivery route and/or on a section of the delivery route. Further, a detail pertaining to a nature of the delivery route and/or of a section of the delivery route can represent a capture time and/or a capture period and/or a capture position and/or a capture section, for example.” In addition, see Paragraph [0087], “A detail pertaining to the timing of the delivery of shipments associated with the respective delivery information can represent, by way of example, the timing of the delivery of shipments associated with the respective delivery information. For example, a detail pertaining to the timing of the delivery of shipments associated with the respective delivery information can represent in each case the time captured and/or determined by the vehicle at which the vehicle has reached a shipment delivery position. By way of example, this permits conclusions regarding the length of time that the vehicle has needed in order to move from one shipment delivery position to the next shipment delivery position along the delivery route.” See Paragraph [0088], which describes using this information to train the knowledge based system. See “Subsequently, in a step 1032, a possible vehicle configuration of a vehicle for delivering the shipments along the possible delivery route determined in step 1031 can be determined at least partially based on the possible delivery route determined in step 1031.” in Paragraph [0129], “The possible vehicle configuration is determined according to a predetermined vehicle configuration algorithm, for example. Such a vehicle configuration algorithm may be based on a knowledge-based system (e.g. an expert system) and/or a self-learning system, for example. Such a knowledge-based system and/or self-learning system may be based, by way of example, at least partially on the historical delivery information. For example, such a knowledge-based system and/or self-learning system can be trained based on the historical delivery information such that it determines a possible vehicle configuration for a vehicle for a possible delivery route determined in step 1031 such that it is expected that a vehicle having this possible vehicle configuration will move along this possible delivery route in as energy-efficient a manner as possible and/or that the expected energy requirement for the delivery of the shipments along this possible delivery route by a vehicle having this possible vehicle configuration will be as low as possible.” in Paragraph [0130], “The basis for the training of a knowledge-based system and/or self-learning system may be an algorithm for machine learning, for example. Machine learning can be effected, by way of example, in a form of supervised machine learning, unsupervised machine learning and/or reinforcement machine learning. Algorithms for machine learning may be based at least partially on an artificial neural network, a support vector machine, a cluster analysis or a combination of several (e.g. all) of these techniques.” in Paragraph [0131], “In a step 1033, an expected energy requirement for the delivery of the shipments along the possible delivery route determined in step 1031 by a vehicle having the possible vehicle configuration determined in step 1032 is determined.” in Paragraph [0132], and “The determining of the expected energy requirement in step 1033 can, by way of example, likewise be effected by the knowledge-based system and/or self-learning. For example, said system can be trained based on the historical delivery information such that, for a possible delivery route determined in step 1031, it determines not only a possible vehicle configuration but also an expected energy requirement for the delivery of the shipments along this delivery route by a vehicle having this vehicle configuration. In this case, steps 1032 and 1033 can also be combined in one step.” in Paragraph [0133]); and generate a planned delivery route for the respective delivery location based on the one or more locations and the door-step time prediction (See “In step 104, delivery control information is provided in order to cause delivery of the shipments along the determined delivery route by a vehicle having the determined vehicle configuration.” in Paragraph [0141], “The provided delivery control information comprises a representation of the determined vehicle configuration and/or of the determined route, for example, in order to cause the delivery of the shipments along the determined delivery route by a vehicle having the determined vehicle configuration. For example, the delivery control information is provided for retrieval by a user (e.g. a dispatcher) and/or a remote apparatus (e.g. an apparatus for selecting and/or configuring vehicles) and/or a vehicle and/or is sent to a user and/or a remote apparatus and/or a vehicle. Further, the delivery control information can be provided by outputting it to a user, for example.” in Paragraph [0142], “The causing of the delivery of the shipments along the determined delivery route by a vehicle having the determined vehicle configuration comprises, by way of example, the selecting of a vehicle having the determined vehicle configuration or, if no vehicle having the determined vehicle configuration is available, (re)configuring of a vehicle according to the determined vehicle configuration.” in Paragraph [0143], and “Further, the causing of the delivery of the shipments along the determined delivery route by a vehicle having the determined vehicle configuration can comprise the actuating of the selected and/or (re)configured vehicle such that the vehicle is caused to move along the determined delivery route to deliver the shipments. For this purpose, the determined delivery route can be programmed into a navigation unit of the vehicle, for example.” in Paragraph [0144]).
Radetzki does not explicitly teach; however, Dashti teaches determine one or more locations associated with a delivery order (See “In some examples, the management, visualization, and tracking application 206 is an application for dispatch managers, and administrators to interact with the platform according to enabled functionality through the APIs. Example functionality includes, without limitation, determining drivers location, …” in Paragraph [0026], “In some examples, the schedule correction 408 merges the latest schedule of routes along with the new routes, and uses a logistic tracking system (e.g., GPS locations, delivery status tracking) to project the location of the conveyances.” in Paragraph [0057], and “Example conveyances can include, without limitation, cars, trucks, motorcycles, scooters, bicycles, planes, trains, ships, and the like.” in Paragraph [0037]).
Although Radetzki teaches capture position (See Paragraph [0083]) and location data, Radetzki does not explicitly teach “a plurality of location detectors” and “real-time location data”. However, Dashti teaches a plurality of location detectors (See “In some examples, the mobile computing device includes GPS location capabilities. In some examples, the mobile application 202 provides example functionalities including, without limitation, sending location breadcrumbs to the platform (e.g., through a publicly exposed API), …” in Paragraph [0024] and “Moreover, a computer may be embedded in another device (e.g., a mobile telephone, …, a Global Positioning System (GPS) receiver).” in Paragraph [0077]), the real-time location data, and receive location data from the plurality of location detectors in real time as the delivery vehicle is delivering the current delivery order (See “Real-time information is received during the period (508). For example, and as described herein, data can be provided in real-time as it is generated. Example data can include, without limitation, location data of delivery conveyances (e.g., GPS data from computing devices carried by delivery personnel), …” in Paragraph [0071]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Radetzki to include determining one or more locations associated with a delivery order, a plurality of location detectors, the real-time location data, and receiving location data from the plurality of location detectors in real time as the delivery vehicle is delivering the current delivery order, as taught by Dashti, in order to predict more accurate delivery drop off time.
Radetzki in view of Dashti does not explicitly teach “wherein two or more location detectors of the plurality of location detectors are respectively attached to a delivery vehicle and a delivery device”; however, Scalisi teaches wherein two or more location detectors of the plurality of location detectors are respectively attached to a delivery vehicle and a delivery device (See “The location of a delivery vehicle 1405 can be detected using a GPS attached to the delivery vehicle 1405 or another locator connected to the delivery vehicle 1405. The delivery vehicle can be configured to transport the remote computing device 1404 and the delivery parcel 1406.” in Paragraph [0238]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Radetzki in view of Dashti to include wherein two or more location detectors of the plurality of location detectors are respectively attached to a delivery vehicle, as taught by Scalisi, in order to make the system more efficient and effective.
Radetzki in view of Dashti and Scalisi does not explicitly teach; however, Shroff teaches determine a distance between the current delivery order and the respective delivery location by comparing the location data associated with the plurality of location detectors and the planned delivery route (See “For instance, a vehicle may include a plurality of vehicle sensors, readers, cameras, and/or the like configured for generating and/or collecting telematics data indicative of various vehicle dynamics, such as engine ignition, engine speed, vehicle speed, vehicle location, and the status of various vehicle components. The vehicle sensors may be controlled by the telematics device, which may be positioned on or within the vehicle. In controlling the various vehicle sensors, the telematics device is able to capture and store telematics data from the various vehicle sensors according to a programmed logic and associate the captured telematics data with contextual data (e.g., date, time, location). The carrier computing entity 100 can determine the distance traveled between two or more serviceable points (e.g., stops) based on telematics information/data collected by the vehicle. In one embodiment, the carrier computing entity 100 determines the distance by first identifying telematics information/data that indicates the distance traveled by a delivery vehicle (e.g., odometer reading) that was captured (a) at the start of a first stop (e.g., when the vehicle's engine was turned off, when the vehicle slowed to a stop immediately prior to the start of the stop, and/or the like) or (b) at the end of the first stop (e.g., when the vehicle's engine was started, when the vehicle accelerated from standstill, and/or the like, and/or the like). Then, the carrier computing entity 100 can identify telematics information/data that indicates the distance traveled by the vehicle either to the next stop (e.g., when the vehicle's engine was turned off again, when the vehicle slowed to a stop immediately prior to the start of the next stop, and/or the like) or from the previous stop (e.g., when the vehicle's engine was started again, when the vehicle accelerated from standstill, and/or the like). The carrier computing entity 100 may then determine the distance traveled by the vehicle between the stops and store the result (e.g., 3 miles). In other embodiments, the carrier computing entity 100 may similarly determine traveled distances and/or the travel time for stops using the GPS-based techniques, map information/data, and/or the like.” in Paragraph [0070], “Prior to the delivery date, for example, two days before the delivery date, route information/data for item delivery may become available and/or know. The carrier computing entity may access that above route information/data for a particular item and use the route information/data to provide a more accurate customized estimated delivery window. For example, the carrier computing entity may identify a route of delivery for a particular item delivery. The historical information/data associated with the particular route may be used to determine a more accurate estimate for the delivery. The estimate may then be used to determine a more accurate delivery window as described above.” in Paragraph [0115]); in response to determining the distance between the current delivery order and the respective delivery location indicates the current delivery order will be delivered within a corresponding window, transmit, to a user device, a first notification corresponding to the distance of the current delivery order to the respective delivery location (See “However, once route is determined, an updated window may be provided to the customer. For example, a delivery to the 123 Main Street location may be scheduled for a Tuesday via an unknown route. Accordingly, the customer may be provided with an estimated delivery window between 11:45 PM and 3:45 PM. Once a route is determined for the delivery, the estimated window may be updated and provided to the customer via an interface or one or more notifications/messages.” in Paragraph [0067], “Prior to the delivery date, for example, two days before the delivery date, route information/data for item delivery may become available and/or know. The carrier computing entity may access that above route information/data for a particular item and use the route information/data to provide a more accurate customized estimated delivery window. For example, the carrier computing entity may identify a route of delivery for a particular item delivery. The historical information/data associated with the particular route may be used to determine a more accurate estimate for the delivery. The estimate may then be used to determine a more accurate delivery window as described above. In some implementations, the customized estimated pick-up/delivery windows are updated only if the updated delivery window differs from the original delivery window by more than a configurable threshold. The updated estimates may be saved at a local store of the carrier. Additionally the updated estimates may be sent to customers or posted on a system of the carrier for tracking items.” in Paragraph [0115]); and in response to determining the distance between the current delivery order and the respective delivery location indicates the current delivery order will not be delivered within a corresponding window, transmit, to the user device, a second notification indicating the current delivery order is delayed (See “Once an item enters the network, the carrier computing entity 100 determines if there have been any changes to the scheduled delivery date. If there is a change, the carrier computing entity 100 updates the estimated delivery window according to the following. During transit, the carrier computing entity 100 system receives updates on the status of items. The carrier computing entity 100 determines status changes for items based on the received information/data. For example, the carrier computing entity 100 may compare an existing scheduled delivery date to a revised scheduled delivery date. If the revised scheduled delivery date is different, the carrier computing entity 100 may retrieve a new estimated delivery window and update the delivery date and the estimated delivery window for the item accordingly. The revised estimates may be saved at a local store of the carrier. Additionally the revised estimates may be sent to customers or posted on a system of the carrier for tracking items.” in Paragraph [0114] and “In some implementations, if the route of delivery changes the carrier computing entity updates the associated delivery window. In some implementations, live GPS information/data associated with the delivery vehicle and/or personnel may be used to update the customized estimated delivery window. In some implementations, the customized estimated pick-up/delivery windows are updated only if the updated customized estimated delivery window differs from the original customized estimated delivery window by more than a configurable threshold. The updated estimates may be saved at a local store of the carrier. Additionally the updated estimates may be sent to customers or posted on a system of the carrier for tracking items.” in Paragraph [0116]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Radetzki in view of Dashti and Scalisi to include determining a distance between the current delivery order and the respective delivery location and sending notifications to the user device as described above, as taught by Shroff, in order to improve customer service by providing status of the delivery order.
Regarding Claim 4, Radetzki in view of Dashti, Scalisi, and Shroff teaches all the limitations of Claim 1 as described above. Radetzki also teaches wherein the instructions further cause the processor to generate the feature data by: retrieving a history of a user device associated with the respective delivery location, wherein the history indicates one or more dates and delivery windows of delivery orders, and indicates information of one or more goods included in the delivery orders; and generating the feature data based on the speed profile, location data, weather forecasts, and history of the user that includes descriptive information associated with past delivery orders for the respective delivery location (See “In step 101, the historical delivery information is obtained and/or provided. In this case, the historical delivery information is associated with multiple deliveries of shipments made by one or various vehicles of the delivery service, wherein the historical delivery information for each of the deliveries of shipments associated with the historical delivery information represents at least details pertaining to a delivery route, …” in Paragraph [0120], “The historical delivery information represents one or more details characteristic of the respective delivery of shipments for each of the deliveries of shipments associated with the delivery information, for example. As disclosed above, such a detail characteristic of a delivery of shipments is intended to represent, by way of example, at least one parameter captured and/or determined by the vehicle that has made the delivery during the respective delivery, such as the energy requirement of the vehicle.” in Paragraph [0121], “It is subsequently assumed by way of example that the historical delivery information for each of the deliveries of shipments associated with the historical delivery information represents the delivery route along which the respective vehicle (i.e. the vehicle that has made the respective delivery) has been moved, …” in Paragraph [0122], “In a step 102, shipment delivery information for multiple shipments to be delivered is obtained, wherein the shipment delivery information represents, at least for each of the shipments, a detail pertaining to the delivery position for the delivery of the respective shipment.” in Paragraph [0124], “The trait that the shipment delivery information represents, at least for each of the shipments, a detail pertaining to the delivery position for the delivery of the respective shipment is intended to be understood, by way of example, such that the shipment delivery information contains a representation of the delivery position for the delivery of the respective shipment.” in Paragraph [0125], “In one exemplary embodiment of the invention, the historical delivery information for each of the deliveries of shipments associated with the delivery information further represents at least one or more of the following details: a detail pertaining to a vehicle speed and/or vehicle acceleration on the delivery route and/or on a section of the delivery route for the delivery of shipments associated with the respective delivery information, a detail pertaining to the nature of the delivery route and/or of a section of the delivery route for the delivery of shipments associated with the respective delivery information, and/or a detail pertaining to the timing of the delivery of shipments associated with the respective delivery information.” in Paragraphs [0077]-[0080], “A detail pertaining to a vehicle speed represents, by way of example, a vehicle speed of the vehicle on the delivery route and/or on a section of the delivery route that is captured and/or determined by the vehicle. For example, a detail pertaining to a vehicle speed can represent an average vehicle speed of the vehicle on the delivery route and/or on a section of the delivery route that is captured by the vehicle. Alternatively, a detail pertaining to a vehicle speed can represent a vehicle speed of the vehicle that is captured by the vehicle at a particular position on the delivery route.” in Paragraph [0081], also see Paragraphs [0082]-[0084], “In one exemplary embodiment of the invention, the method further comprises the following steps: obtaining and/or keeping environmental information associated with the delivery of the shipments, wherein the determining of the delivery route and/or of the vehicle configuration and/or of the expected energy requirement is further based at least partially on the environmental information.” in Paragraphs [0100]-[0101], and “The environmental information can comprise, by way of example, weather information representing at least one detail pertaining to the expected weather and/or pertaining to the expected position of the sun (e.g. the expected weather and/or the expected position of the sun at atleast one delivery position from the delivery positions and/or on the delivery route and/or on a section of the delivery route). The weather information is provided by a weather service and/or at least partially based on environmental parameters captured by sensors, for example.” in Paragraph [0103]).
Regarding Claim 5, Radetzki in view of Dashti, Scalisi, and Shroff teaches all the limitations of Claim 1 as described above. Radetzki also teaches wherein the instructions further cause the processor to generate the feature data based on at least one of a dwelling-type of the delivery location and a time period the delivered order was delivered (See “A detail pertaining to the timing of the delivery of shipments associated with the respective delivery information can represent, by way of example, the timing of the delivery of shipments associated with the respective delivery information. For example, a detail pertaining to the timing of the delivery of shipments associated with the respective delivery information can represent in each case the time captured and/or determined by the vehicle at which the vehicle has reached a shipment delivery position. By way of example, this permits conclusions regarding the length of time that the vehicle has needed in order to move from one shipment delivery position to the next shipment delivery position along the delivery route.” in Paragraph [0087]).
Regarding Claim 6, Radetzki in view of Dashti, Scalisi, and Shroff teaches all the limitations of Claim 1 as described above. Radetzki in view of Dashti and Scalisi does not explicitly teach; however, Shroff teaches wherein the timestamps of the two events comprise a timestamp associated with a time when an ignition of a delivery vehicle transporting the delivery order is in an off-state and a timestamp associated with a time when the ignition of the delivery vehicle is in an on-state (See “The vehicle sensors may be controlled by the telematics device, which may be positioned on or within the vehicle. In controlling the various vehicle sensors, the telematics device is able to capture and store telematics data from the various vehicle sensors according to a programmed logic and associate the captured telematics data with contextual data (e.g., date, time, location)… In one embodiment, the carrier computing entity 100 determines the distance by first identifying telematics information/data that indicates the distance traveled by a delivery vehicle (e.g., odometer reading) that was captured (a) at the start of a first stop (e.g., when the vehicle's engine was turned off, when the vehicle slowed to a stop immediately prior to the start of the stop, and/or the like) or (b) at the end of the first stop (e.g., when the vehicle's engine was started, when the vehicle accelerated from standstill, and/or the like, and/or the like). Then, the carrier computing entity 100 can identify telematics information/data that indicates the distance traveled by the vehicle either to the next stop (e.g., when the vehicle's engine was turned off again, when the vehicle slowed to a stop immediately prior to the start of the next stop, and/or the like) or from the previous stop (e.g., when the vehicle's engine was started again, when the vehicle accelerated from standstill, and/or the like)… In other embodiments, the carrier computing entity 100 may similarly determine traveled distances and/or the travel time for stops using the GPS-based techniques, map information/data, and/or the like.” in Paragraph [0070]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Radetzki in view of Dashti and Scalisi to include wherein the timestamps of the two events comprise a timestamp associated with a time when an ignition of a delivery vehicle transporting the delivery order is in an off-state and a timestamp associated with a time when the ignition of the delivery vehicle is in an on-state, as taught by Shroff, in order to obtain more accurate data of the delivery status.
Regarding Claim 7, Radetzki in view of Dashti, Scalisi, and Shroff teaches all the limitations of Claim 1 as described above. Radetzki in view of Dashti and Scalisi does not explicitly teach; however, Shroff teaches wherein the door-step time prediction comprises a predicted duration for the two or more location detectors of the plurality of location detectors to be at the delivery location and is associated with a range of door-step time predictions having a mean value and prediction interval (See “In response to determining that sufficient historical information/data is available for a day of the week (e.g., first weekday), the process 400 may continue with determining an estimated pick-up/delivery time, window, or range for a serviceable point for each day, each service level for each day, each route for each day, combinations thereof, and/or the like. As noted, the estimated pick-up/delivery time, window, or range may be determined for each day of the week and/or delivery service level for each day of the week (410). In some implementations, when sufficient information/data is available, average estimated pick-up/delivery times can be determined for each day of the week, each delivery service level, each route, all routes, and/or the like. A delivery window may be estimated based on the determined averages (include mean, mode, median).” in Paragraph [0065], “Accordingly, the carrier computing entity may use the information/data of FIG. 5A to determine an overall estimated pick-up/delivery time based the available data for all routes and all days. For example, as shown in FIG. 5B, the overall estimated pick-up/delivery time based on all available data for all routes and all days is 2:22 PM. This estimate may be an average of all delivery times for the serviceable point.” in Paragraph [0066], “Serviceable points may be clustered according to one or more thresholds, including time, distance, or time and distance. For example, serviceable points may be clustered as shown in FIG. 7B according to the one or more thresholds of FIG. 7A. In some implementations, the one or more thresholds may be based on the distance between serviceable points, the travel times between serviceable points, and/or the distance and time between serviceable points.” in Paragraph [0068], and “In some implementations, if the route of delivery changes the carrier computing entity updates the associated delivery window. In some implementations, live GPS information/data associated with the delivery vehicle and/or personnel may be used to update the customized estimated delivery window.” in Paragraph [0116]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Radetzki in view of Dashti and Scalisi to include wherein the door-step time prediction comprises a predicted duration for the two or more location detectors of the plurality of location detectors to be at the delivery location and is associated with a range of door-step time predictions having a mean value and prediction interval, as taught by Shroff, in order to obtain more accurate data of the delivery status.
Regarding Claim 8, Radetzki in view of Dashti, Scalisi, and Shroff teaches all the limitations of Claim 1 as described above. Radetzki also teaches receive delivery orders to the one or more delivery locations (See “In the method, shipment delivery information is obtained for multiple shipments to be delivered. The shipment delivery information represents a detail pertaining to the delivery position for the delivery of the respective shipment.” in Abstract); and generate the planned delivery route by allocating the received delivery orders to one or more delivery vehicles based on the one or more delivery locations, requested deliver windows to receive the delivery order, and the door-step time predictions corresponding to the one or more delivery locations (See “In step 104, delivery control information is provided in order to cause delivery of the shipments along the determined delivery route by a vehicle having the determined vehicle configuration.” in Paragraph [0141], “The provided delivery control information comprises a representation of the determined vehicle configuration and/or of the determined route, for example, in order to cause the delivery of the shipments along the determined delivery route by a vehicle having the determined vehicle configuration. For example, the delivery control information is provided for retrieval by a user (e.g. a dispatcher) and/or a remote apparatus (e.g. an apparatus for selecting and/or configuring vehicles) and/or a vehicle and/or is sent to a user and/or a remote apparatus and/or a vehicle. Further, the delivery control information can be provided by outputting it to a user, for example.” in Paragraph [0142], “The causing of the delivery of the shipments along the determined delivery route by a vehicle having the determined vehicle configuration comprises, by way of example, the selecting of a vehicle having the determined vehicle configuration or, if no vehicle having the determined vehicle configuration is available, (re)configuring of a vehicle according to the determined vehicle configuration.” in Paragraph [0143], and “Further, the causing of the delivery of the shipments along the determined delivery route by a vehicle having the determined vehicle configuration can comprise the actuating of the selected and/or (re)configured vehicle such that the vehicle is caused to move along the determined delivery route to deliver the shipments. For this purpose, the determined delivery route can be programmed into a navigation unit of the vehicle, for example.” in Paragraph [0144]).
Claims 9 and 12-16 are method claims corresponding to method Claims 1 and 4-8. All of the limitations in Claims 9 and 12-16 are found reciting the same scopes of the respective limitations in Claims 1 and 4-8. Accordingly, Claims 9 and 12-16 are rejected by the same rationales presented in the rejection of Claims 1 and 4-8, respectively set forth above.
Claims 17-18 and 20 are product claims corresponding to system Claims 1, 4, and 8. All of the limitations in Claims 17-18 and 20 are found reciting the same scopes of the respective limitations in Claims 1, 4, and 8. Accordingly, Claims 17-18 and 20 are rejected by the same rationales presented in the rejection of Claims 1, 4, and 8, respectively set forth above.
Regarding Claim 19, Radetzki in view of Dashti, Scalisi, and Shroff teaches all the limitations of Claim 17 as described above. Radetzki also teaches wherein the generating the feature data further comprises generating feature data based on at least one of a dwelling-type of the delivery location and a time period the delivered order was delivered (See “A detail pertaining to the timing of the delivery of shipments associated with the respective delivery information can represent, by way of example, the timing of the delivery of shipments associated with the respective delivery information. For example, a detail pertaining to the timing of the delivery of shipments associated with the respective delivery information can represent in each case the time captured and/or determined by the vehicle at which the vehicle has reached a shipment delivery position. By way of example, this permits conclusions regarding the length of time that the vehicle has needed in order to move from one shipment delivery position to the next shipment delivery position along the delivery route.” in Paragraph [0087]).
Radetzki in view of Dashti and Scalisi does not explicitly teach; however, Shroff teaches wherein the timestamps of the two events comprise a timestamp associated with a time when an ignition of a delivery vehicle transporting the delivery order in an off-state and a timestamp associated with a time when the ignition of the delivery vehicle is in an on-state (See “The vehicle sensors may be controlled by the telematics device, which may be positioned on or within the vehicle. In controlling the various vehicle sensors, the telematics device is able to capture and store telematics data from the various vehicle sensors according to a programmed logic and associate the captured telematics data with contextual data (e.g., date, time, location)… In one embodiment, the carrier computing entity 100 determines the distance by first identifying telematics information/data that indicates the distance traveled by a delivery vehicle (e.g., odometer reading) that was captured (a) at the start of a first stop (e.g., when the vehicle's engine was turned off, when the vehicle slowed to a stop immediately prior to the start of the stop, and/or the like) or (b) at the end of the first stop (e.g., when the vehicle's engine was started, when the vehicle accelerated from standstill, and/or the like, and/or the like). Then, the carrier computing entity 100 can identify telematics information/data that indicates the distance traveled by the vehicle either to the next stop (e.g., when the vehicle's engine was turned off again, when the vehicle slowed to a stop immediately prior to the start of the next stop, and/or the like) or from the previous stop (e.g., when the vehicle's engine was started again, when the vehicle accelerated from standstill, and/or the like)… In other embodiments, the carrier computing entity 100 may similarly determine traveled distances and/or the travel time for stops using the GPS-based techniques, map information/data, and/or the like.” in Paragraph [0070]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Radetzki in view of Dashti and Scalisi to include wherein the timestamps of the two events comprise a timestamp associated with a time when an ignition of a delivery vehicle transporting the delivery order in an off-state and a timestamp associated with a time when the ignition of the delivery vehicle is in an on-state, as taught by Shroff, in order to obtain more accurate data of the delivery status.
Claims 2-3 and 10-11 are rejected under 35 U.S.C. 103 as being unpatentable over Radetzki in view of Dashti, Scalisi, Shroff, and Waliany et al. (US PG Pub. No. 2019/0385121 A1; hereinafter "Waliany").
Regarding Claim 2, Radetzki in view of Dashti, Scalisi, and Shroff teaches all the limitations of Claim 1 as described above. Radetzki does not explicitly teach; however, Dashti teaches and wherein the instructions further cause the processor to: receive the location data from the plurality of location detectors (See “Real-time information is received during the period (508). For example, and as described herein, data can be provided in real-time as it is generated. Example data can include, without limitation, location data of delivery conveyances (e.g., GPS data from computing devices carried by delivery personnel), …” in Paragraph [0071]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Radetzki to include receiving the location data from the plurality of location detectors, as taught by Dashti, in order to predict more accurate delivery drop off time.
Radetzki in view of Dashti does not explicitly teach; however, Scalisi teaches wherein the delivery device is a handheld scanning device (See “The delivery parcel identification code 1116 can be scanned by the delivery person, using his remote computing device 1104 or another scanner …” in Paragraph [0231]); It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Radetzki in view of Dashti to include wherein the delivery device is a handheld scanning device, as taught by Scalisi, in order to make the system more efficient and effective.
Radetzki in view of Dashti, Scalisi, and Shroff does not explicitly teach; however, Waliany teaches associate the location data from the plurality of location detectors to the delivery order; and process the associated location data to remove invalid location data (See “In one example embodiment, during the trip, the networked computer system 902 receives information (e.g., periodically) from the provider application 916 indicating the location of the provider's vehicle and/or telematics information (e.g., indications of current speed, acceleration/deceleration, events, stops, and so forth). The networked computer system 902 stores the information in the database 908 and can associate the information with the trip record.” in Paragraph [0117] wherein it can be seen that the networked computer system 902 is capable of processing the associated location data to remove invalid location data.).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Radetzki in view of Dashti, Scalisi, and Shroff to include associating the location data from the plurality of location detectors to the delivery order, and processing the associated location data to remove invalid location data, as taught by Waliany, in order to make the system more efficient and effective.
Regarding Claim 3, Radetzki in view of Dashti, Scalisi, and Shroff teaches all the limitations of Claim 1 as described above. Radetzki in view of Dashti, Scalisi, and Shroff does not explicitly teach; however, Waliany teaches wherein the instructions further cause the processor to generate the speed profile by applying a changepoint detection algorithm to the location data of the delivery order to determine changes in a sequence of the location data and plotted locations within the location data (See “As shown in FIG. 5, sequence models are capable of finding delivery provider change-points amongst a sequence of state observations. These observations comprise activities or activities fused with other modalities, such as GPS and motion sensors. Finding these change points is challenging because of noisy observations. In particular, even though, for example, Android-based activities report their confidences (e.g., confidence scores), the Android-based classifier is noisy and separation boundaries between change points may not be very clean (e.g., as shown in FIG. 5 by a still activity between the two walking activities after parking the vehicle).” in Paragraph [0063] and “In an example embodiment, a trip state model is a sequential model capable of inferring a sequence of discrete states from a sequence of noisy observations. These inferred discrete states are temporally related (e.g., order can be imposed in the states and only a finite set of state transitions are possible). For example, a delivery provider can wait at the restaurant only after they have parked the vehicle in the parking lot and walked to the restaurant. Additionally, the current state plays an important role in modeling the inferred states. For example, if the delivery provider is currently walking, they will very likely keep walking in a next timestamp.” in Paragraph [0065]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Radetzki in view of Dashti, Scalisi, and Shroff to include generating the speed profile by applying a changepoint detection algorithm to the location data of the delivery order to determine changes in a sequence of the location data and plotted locations within the location data, as taught by Waliany, in order to obtain more accurate data of the delivery status.
Claims 10-11 are method claims corresponding to system Claims 2-3. All of the limitations in Claims 10-11 are found reciting the same scopes of the respective limitations in Claims 2-3. Accordingly, Claims 10-11 are considered obvious (rejection) by the same rationales presented in the rejection of Claims 2-3, respectively set forth above.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). 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.
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/T.M.K./Examiner, Art Unit 3628
/GEORGE CHEN/Primary Examiner, Art Unit 3628
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