DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
This is a non-final office action on the merits. Claims 1-20 are currently pending and are addressed below.
The examiner notes that the fundamentals of the rejection are based on the broadest reasonable interpretation of the claim language. Applicant is kindly invited to consider the reference as a whole. References are to be interpreted as by one of ordinary skill in the art rather than as by a novice. See MPEP 2141. Therefore, the relevant inquiry when interpreting a reference is not what the reference expressly discloses on its face but what the reference would teach or suggest to one of ordinary skill in the art.
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 08/28/2025 has been entered.
Response to Arguments
Applicant’s arguments with respect to the rejection of claims 1-20 under 35 U.S.C 101 have been considered but are not persuasive. It is challenged that amended independent claims 1, 4, and 15 are not features that fall within the grouping of subject matter that cover mental processes. Specifically, applicant states that “learning a pattern analysis based on the utility sensor input to predict the availability…” and “in response to the prediction…automatically notifying a remote service provider…” cannot be performed in human mind (see Applicant’s remarks, pg.1-3). The examiner has carefully considered applicant’s arguments and respectfully disagrees. The recited steps correspond to collecting information regarding a vehicle’s utility usage, making an evaluation to identify patterns, and making a prediction regarding future availability of the utility. Arguably, such activities require suggest observation, evaluation, and a simple judgement, which are forms of mental processes. A person monitoring utility levels in a recreational vehicle could observe the rate at which an on-board utility is being consumed, recognize a pattern in the overall usage over a duration, and make a judgment, or estimation of when that resource will be depleted. The incorporation of “learning a pattern analysis” does not remove the activity from the mental processes category, as the claim recitation reflects the type of reasoning that can be performed mentally, or with pen and paper given the information.
The “automatically notifying,” step merely communicates, or reports the result of the abstract idea, which is a form of insignificant extra solution activity. Automating this communication that in response causes a service provider to replenish a resource does not remove the claim from a mental process. Even assuming, arguendo, that this step cannot be practically performed in the human mind, the limitation recites an abstract idea in the form of certain methods of organizing human activity. Specifically, the step describes coordinating, or arranging a service transaction between a user and remote service provider to perform a task to replenish, or extend the availability of a resource based on the prediction. For example, a person, who determines that a utility of water will soon be depleted, could contact a service provider to arrange for servicing. The claimed step merely automates this time of human activity using generic computer components to notify a service provider in response to the prediction
Furthermore, applicant recites that the limitations are improvements in utility usage for users and in transforming data between devices. However, the examiner respectfully disagrees and believes that the claims do not recite any improvement to the functioning of a computer, sensor system, communication network, or recreational vehicle utility system. Instead, the examiner believes the claims use generic components to collect and analyze data to generate a prediction which is provided as an output in the form of a notification. These operations are considered “apply it level” where they represent the use of generic computer components to perform the abstract idea of analyzing usage information and predicting future availability. It should be noted that improvements in the efficiency of decision-making (abstract idea), or resource management based on data analysis do not constitute improvements to the technology itself. As such, the examiner respectfully disagrees and the rejection of claims 1-20 under 35 U.S.C 101 is maintained.
Applicant’s arguments with respect to claims 1-20 under 35 U.S.C 103 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 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 rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1
Claims 1, 4, and 15 are directed towards a method which falls within at least one of the statutory categories.
STEP 2A (Prong 1)
Claim 1
A method of predicting availability of at least one utility for a recreational vehicle (RV), comprising:
providing said RV with the at least one on-board utility having a measurable value related to utility usage or remaining utility available for use, said at least one on-board utility being unrelated to movement function of the RV;
obtaining a utility sensor input from the at least one on-board utility of the RV, the utility sensor input being indicative of the utility usage or the remaining utility available of the at least one on-board utility for use by a user of the recreational vehicle;
analyzing the utility sensor input
learning a pattern analysis based on the utility sensor input to predict the availability of at least one on-board utility over a future period of time for the utility usage of the at least one on-board utility by the user of the recreational vehicle
providing a graphical representation output to the user which predicts when the at least one on-board utility will no longer be usable over the future period of time
in response to the prediction that the at least one on-board utility will no longer be usable over the future period of time, automatically notifying a remote service provider that in response causes to eat1se the remote service provider to perform a task to extend the availability of the at least one on-board utility over the future period of time
The examiner submits that the foregoing bolded limitations constitute a mental process because under its broadest reasonable interpretation, the claim covers performance of limitations in the human mind. More particularly, the elements above recite certain methods of organizing human activity associated with monitoring and predicting depletion of a consumable resource and arranging a service to replenish the resources between a user and a service provider. The step of “learning” to generate a prediction of when a utility will be unavailable paired with the step of “automatically notifying” a service provider to extend the availability is equivalent to automating a human planning process which does not make the claim patent eligible. In addition, the analyzing and learning steps also consist of analyzing the utility sensor input provided by generic computer components and are equivalent to a person perceiving the pattern data of on-board utility usage and making a prediction, or forecasting the resource usage over a period of time. As such, the examiner believes that claim 1 recites at an abstract idea.
Claim 4
A method of predicting fluid usage, comprising:
at least one on-board tank having a sensor to detect a fluid level within said at least one on-board tank, the detection of the fluid level being indicative of a usage or a remaining fluid level available of the at least one on-board tank for use by a user
analyzing sensor data of the sensor over multiple time periods
learning, based on the analyzing, a pattern analysis of an amount of fluid used during the time periods by the user;
predicting when the at least one on-board tank will either require filling, or reqmre emptying
displaying a graphical representation of a predicted result to [[a]] the user on a controller, wherein said predicted result is at a future time period
in response to the prediction that the at least one on-board tank utility will no longer be usable over the future time period, automatically notifying a remote service provider that in response cause the remote service provider to perform a task to either fill or empty the at least one on-board tank utility
Similar to the analysis of claim 1, the examiner submits that the foregoing bolded limitations of claim 4 constitute an because under its broadest reasonable interpretation, the claim covers performance of the limitations in the human mind. Highlighted above, the limitations of “detecting,” “learning,” “predicting,” and “analyzing,” merely consist of analyzing the utility sensor input provided by generic computer components and are equivalent to a person perceiving the pattern data of on-board utility usage and making a prediction, or forecasting the resource usage over a period of time. Additionally, the step of “learning” to generate a prediction of when a utility will be unavailable paired with the step of “automatically notifying” a service provider to extend the availability is equivalent to automating a human planning process which does not make the claim patent eligible. Thus, the claim recites an abstract idea.
Claim 15
A method of predicting availability of a utility, comprising:
obtaining a utility sensor input from the utility, the utility sensor input being indicative of a usage of or a remaining amount of the utility for use by a user
analyzing the utility sensor input from the utility
learning a pattern analysis based on the utility sensor input to predict the availability of at least one on board the utility over a future period of time for the usage of the utility by the user
predicting when the utility will either require filling, or require emptying
providing a graphical display predicting to the user when the at least one on board utility will be exhausted and in response to the prediction that the at least one on-board utility will no longer be usable over the future period of time
automatically notifying a remote service provider that in response causes to cause the remote service provider to perform a task to extend the availability of the at least one on board utility over the future period of time
and one of suggesting a change in utility usage settings to prolong usage time or, automatically changing utility usage settings based on said suggesting or based on a selected extension of time period
Similarly to the analysis of claim 1 and 4, the examiner submits that the foregoing bolded limitations of claim 15 constitute a mental process because under its broadest reasonable interpretation, the claim covers performance of the limitations in the human mind. Highlighted above, the limitations of “suggesting,” “learning,” “predicting,” and “analyzing,” merely consist of analyzing the utility sensor input provided by generic computer components and are equivalent to a person perceiving the pattern data of on-board utility usage and making a prediction, or forecasting the resource usage over a period of time. Additionally, the step of “learning” to generate a prediction of when a utility will be unavailable paired with the step of “automatically notifying” a service provider to extend the availability is equivalent to automating a human planning process which does not make the claim patent eligible. Thus, the claim recites an abstract idea.
STEP 2A (Prong 2)
Claim 1
A method of predicting availability of at least one utility for a recreational vehicle (RV), comprising:
providing said RV with the at least one on-board utility having a measurable value related to utility usage or remaining utility available for use, said at least one on-board utility being unrelated to movement function of the RV;
obtaining a utility sensor input from the at least one on-board utility of the RV, the utility sensor input being indicative of the utility usage or the remaining utility available of the at least one on-board utility for use by a user of the recreational vehicle;
analyzing the utility sensor input
learning a pattern analysis based on the utility sensor input to predict the availability of at least one on-board utility over a future period of time for the utility usage of the at least one on-board utility by the user of the recreational vehicle
providing a graphical representation output to the user which predicts when the at least one on-board utility will no longer be usable over the future period of time
in response to the prediction that the at least one on-board utility will no longer be usable over the future period of time, automatically notifying a remote service provider that in response causes to eat1se the remote service provider to perform a task to extend the availability of the at least one on-board utility over the future period of time
The examiner submits that the identified additional limitations do not integrate the
previously discussed abstract ideas into practical applications. Regarding the additional
limitations of, “obtaining,” and “providing,” they are forms of insignificant extra- solution activity. The “obtaining” step is recited at a high level of generality (i.e. as a general means of receiving, obtaining, processing, etc., sensor data regarding an environment or vehicle metrics) and amounts to mere data gathering which is a form of insignificant extra-solution activity. The “providing” step is recited at a high level of generality (i.e. as a general means of outputting, displaying, providing etc., output data) and amounts to post solution action which is a form of insignificant extra-solution activity. As such, the additional elements of claim 1 do not integrate the abstract idea into practical application. Additionally, the examiner submits that the identified additional limitations do not integrate the previously discussed abstract ideas into practical applications.
Claim 4
A method of predicting fluid usage, comprising:
at least one on-board tank having a sensor to detect a fluid level within said at least one on-board tank, the detection of the fluid level being indicative of a usage or a remaining fluid level available of the at least one on-board tank for use by a user
analyzing sensor data of the sensor over multiple time periods
learning, based on the analyzing, a pattern analysis of an amount of fluid used during the time periods by the user;
predicting when the at least one on-board tank will either require filling, or reqmre emptying
displaying a graphical representation of a predicted result to [[a]] the user on a controller, wherein said predicted result is at a future time period
in response to the prediction that the at least one on-board tank utility will no longer be usable over the future time period, automatically notifying a remote service provider that in response cause the remote service provider to perform a task to either fill or empty the at least one on-board tank utility
Similar to the analysis of claim 1, examiner submits that the identified additional limitations do not integrate the previously discussed abstract ideas into practical applications. Regarding the additional limitation of, “displaying,” it is a form of insignificant extra-solution activity. The “displaying” step is recited at a high level of generality (i.e. as a general means of outputting, displaying, providing etc., output data) and amounts to post solution action which is a form of insignificant extra-solution activity. As such, the additional elements of claim 4 do not integrate the abstract idea into practical application. Additionally, the examiner submits that the identified additional limitations do not integrate the previously discussed abstract ideas into practical applications.
Claim 15
A method of predicting availability of a utility, comprising:
obtaining a utility sensor input from the utility, the utility sensor input being indicative of a usage of or a remaining amount of the utility for use by a user
analyzing the utility sensor input from the utility
learning a pattern analysis based on the utility sensor input to predict the availability of at least one on board the utility over a future period of time for the usage of the utility by the user
predicting when the utility will either require filling, or require emptying
providing a graphical display predicting to the user when the at least one on board utility will be exhausted and in response to the prediction that the at least one on-board utility will no longer be usable over the future period of time
automatically notifying a remote service provider that in response causes to cause the remote service provider to perform a task to extend the availability of the at least one on board utility over the future period of time
and one of suggesting a change in utility usage settings to prolong usage time or, automatically changing utility usage settings based on said suggesting or based on a selected extension of time period
The examiner submits that the identified additional limitations do not integrate the
previously discussed abstract ideas into practical applications. Regarding the additional
limitations of, “obtaining,” and “providing,” they are forms of insignificant extra- solution activity. The “obtaining” step is recited at a high level of generality (i.e. as a general means of receiving, obtaining, processing, etc., sensor data regarding an environment or vehicle metrics) and amounts to mere data gathering which is a form of insignificant extra-solution activity. The “providing” step is recited at a high level of generality (i.e. as a general means of outputting, displaying, providing etc., output data) and amounts to post solution action which is a form of insignificant extra-solution activity. As such, the additional elements of claim 15 do not integrate the abstract idea into practical application. Additionally, the examiner submits that the identified additional limitations do not integrate the previously discussed abstract ideas into practical applications.
STEP 2B
Claims 1, 4, and 15 do not include additional elements (considered individually and as an ordered combination) that are sufficient to amount to significantly more than the judicial exception for the same reasons to those discussed above. The additional elements such as a plurality of sensors and learning model to perform the steps amounts to nothing more than applying the exception using generic computer components. General application of an exception using a generic computer component cannot provide an inventive concept.
Thus, since claims 1, 4, and 15 are: (a) directed towards abstract ideas, (b) do not recite additional elements that integrate the judicial exception into a practical application, and (c) do not recite additional elements that amount to significantly more than the judicial exception, it is clear that claims 1, 15, and 18 are directed towards non-statutory subject matter.
Dependent claims 2-3, 5-14, and 16-20 do not recite any further limitations that cause the claims to be patent eligible. The limitations of the dependent claims are directed towards additional aspects of the judicial exception and/or additional elements that do not integrate the judicial exception into a practical application.
As such, claims 1-20 are rejected under 35 USC 101 as being drawn to an abstract idea without significantly more, and thus are ineligible.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1-6, 12 and 14-16 are rejected under 35 U.S.C 103 as being unpatentable over Wallis Lyle et al. (US20180350161A1), hereinafter referred to as Lyle in view of Cox Evan Gabriel Turitz et al. (US2015228129A1), hereinafter referred to as Turitz, in view of Carlesimo Daniel et al. (US20170369008A1), hereinafter referred to as Daniel, in further view of Namineni Pavi et al. (US10096176B1), hereinafter referred to as Pavi.
Regarding claim 1, Lyle discloses: a method of predicting availability of at least one on-board utility for a recreational vehicle (see at least Lyle, ¶¶ [0005]-[0008], [0053]-[0055] which discloses the management and optimization of vehicle resources, such as fuel, for a vehicle), comprising:
providing said RV with the at least one on-board utility having a measurable value related to utility usage or remaining utility available for use (see at least Lyle, ¶¶ [0057]-[0058] which discloses one of the replenishable resources of a vehicle unrelated to movement function of a vehicle, fuel and/or power consumption)
learning a pattern analysis based on the utility sensor input to predict the availability of at least one on-board utility over a future period of time for the utility usage of the at least one on-board utility by the user of the recreational vehicle (see at least ¶¶ [0004]-[0007], [0026] which discloses the diagnostic tests performed on resources (utility usage) after data is gathered from sensor fusion, an example provided is fuel and power consumption over a time interval against a threshold and whether a vehicle can perform a specific task depending on the diagnostic)
analyzing the utility sensor input (see at least Lyle, ¶¶ [0026], [0049] which discloses the sensor fusion prediction of input of objects and features of the environment of a vehicle)
Lyle is silent on, however, in the same field of endeavor, Turitz teaches: said at least one on-board utility being unrelated to movement function of the RV (see at least Turitz, ¶¶ [0029]-[0030] which discloses a vehicle monitor device that can obtain vehicle usage information of vehicle metrics (on-board utility measurable values) that may include, battery, water, air, or other information relating to the longevity of specific components; accordingly, this information is provided as output on-board diagnostic data)
obtaining a utility sensor input from the at least one on-board utility of the RV, the utility sensor input being indicative of the utility usage or the remaining utility available of the at least one on-board utility for use by a user of the recreational vehicle (see at least Turitz, ¶¶ [0029]-[0030] which discloses a vehicle monitor device that can obtain vehicle usage information of vehicle metrics (on-board utility measurable values) that may include, battery, water, air, or other information relating to the longevity of specific components; accordingly, this information is provided as output on-board diagnostic data, which means the utility sensor input being indicative of the utility usage; the system making a categorical assessment of, but not limited to, fuel level, battery level, a condition or state of the car at a particular time)
It would have been obvious to a person of ordinary skill in the art to modify Lyle to include said at least one on-board utility being unrelated to movement function of the RV, obtaining a utility sensor input from the at least one on-board utility of the RV, the utility sensor input being indicative of the utility usage or the remaining utility available of the at least one on-board utility for use by a user of the recreational vehicle. The examiner would like to note that the disclosure of Lyle provides that the vehicle provided may be a recreational vehicle, which inherently suggests that utility sensor input and resource mitigation strategies may also apply to metrics such as, battery level, or water tank usage, but it is not as explicitly discussed. The example provided in the disclosure regarding fluid level thresholds is indicative of fuel assessment, which is associated with the movement function of the vehicle. Incorporating the teaching of Turitz into the base device of Lyle would allow for a more efficient mitigation of utility usage which may be applied to a recreational vehicle like water tank levels, or waste management.
Modified Lyle is silent on, however, in the same field of endeavor, Daniel teaches: providing a graphical representation output to the user which predicts when the at least one on-board utility will no longer be usable over the future period of time (see at least Daniel, ¶¶ [0031]-[0032] which discloses an example of a notification of a vehicle fluid level being below a threshold in the form of a visual indicator)
It would have been obvious to a person of ordinary skill in the art to further change modified Lyle to include providing a graphical representation output to the user which predicts when the at least one on-board utility will no longer be usable over the future period of time. The examiner would like to note that Lyle takes into account the management and replenishing of resources, similarly to Daniel, however Lyle does not provide a visual representation to the user, thus even though the user is notified when fuel or power consumption is below a limit, there is no visual cue to this. Adding the teachings would allow for an improvement to the base device that incorporates a better projection of information to a user of a vehicle of the remaining level of a specific resource, in this instance, the fluid levels.
Further modified Lyle is silent on, however, in the same field of endeavor, Pavan teaches: in response to the prediction that the at least one on-board utility will no longer be usable over the future period of time, automatically notifying a remote service provider that in response causes the remote service provider to perform a task to extend the availability of the at least one on-board utility over the future period of time (see at least Pavan, pg.14, col.16, lines 31-38 which discloses in response to a prognosis communicate a notification to the service provider; pg.10, col.8, lines 18-29, which discloses an example of a service provider receiving notification and performing a task to extend the availability of the at least on on-board utility)
It would have been obvious to a person of ordinary skill in the art to change further modified Lyle to include in response to the prediction that the at least one on-board utility will no longer be usable over the future period of time, automatically notifying a remote service provider that in response causes the remote service provider to perform a task to extend the availability of the at least one on-board utility over the future period of time. Incorporating this teaching would allow for an improvement of further vehicle resource management where maintenance may be requested to keep a vehicle in its optimal condition over the future period of time before any kind of malfunction or hindrance can occur.
Regarding claim 2, Lyle discloses: the method of claim 1, wherein the at least one on-board utility is exhausted over said future period of time (see at least Lyle, ¶¶ [0057]-[0058] which discloses the transmitted resource data containing utilities that deplete over time and are tracked determining whether they fall below a threshold)
Regarding claim 3, Lyle discloses: the method of claim 1, wherein the at least one on-board utility is power, water, fuel, or storage space (see at least Lyle, ¶¶ [0057]-[0058] which discloses the measured resources including but not limited to power and fuel)
Regarding claim 4, Lyle discloses: a method of predicting fluid usage (see at least Lyle, ¶¶ [0005]-[0008], [0053]-[0055] which discloses the management and optimization of vehicle resources, such as fuel, for a vehicle), comprising:
at least one on-board tank having a sensor to detect a fluid level within said at least one on-board tank, the detection of the fluid level being indicative of a usage or a remaining fluid level available of the at least one on-board tank for use by a user (see at least Lyle, ¶¶ [0026], [0057]-[0058] which discloses an on-board tank (fuel) having a various vehicle sensors to perform diagnostics, monitoring, control, reporting, etc., that provide a detection of the fluid level that indicates the amount of fuel contained in a fuel tank that is being used by a user, relative to a predetermined threshold)
analyzing sensor data of the sensor over multiple time periods (see at least Lyle, ¶¶ [0026]-[0027] which discloses the use of sensor data in diagnostics and monitoring of the resources over a period of time)
learning, based on the analyzing, a pattern analysis of an amount of fluid used during the time periods by the user (see at least ¶¶ [0004]-[0007], [0026] which discloses the diagnostic tests performed on resources (utility usage) after data is gathered from sensor fusion, an example provided is fuel and power consumption over a time interval against a threshold and whether a vehicle can perform a specific task depending on the diagnostic)
predicting when the at least one on-board tank will either require filling, or emptying (see at least Lyle, ¶¶ [0026], [0057]-[0058] which discloses an on-board tank (fuel) having a various vehicle sensors to perform diagnostics, monitoring, control, reporting, etc., that provide a detection of the fluid level that indicates the amount of fuel contained in a fuel tank that is being used by a user, relative to a predetermined threshold)
Lyle is silent on, however, in the same field of endeavor, Daniel teaches: displaying a graphical representation of a predicted result to the user on a controller, wherein said predicted result is at a future time period (see at least Daniel, ¶¶ [0031]-[0032] which discloses an example of a notification of a vehicle fluid level being below a threshold in the form of a visual indicator)
It would have been obvious to a person of ordinary skill in the art to further change modified Lyle to include providing a graphical representation output to the user which predicts when the at least one on-board utility will no longer be usable over the future period of time. The examiner would like to note that Lyle takes into account the management and replenishing of resources, similarly to Daniel, however Lyle does not provide a visual representation to the user, thus even though the user is notified when fuel or power consumption is below a limit, there is no visual cue to this. Adding the teachings would allow for an improvement to the base device that incorporates a better projection of information to a user of a vehicle of the remaining level of a specific resource, in this instance, the fluid levels.
Further modified Lyle is silent on, however, in the same field of endeavor, Pavan teaches: in response to the prediction that the at least one on-board tank utility will no longer be usable over the future time period, automatically notifying a remote service provider that in response cause the remote service provider to perform a task to either fill or empty the at least one on-board tank utility (see at least Pavan, pg.14, col.16, lines 31-38 which discloses in response to a prognosis communicate a notification to the service provider; pg.10, col.8, lines 18-29, which discloses an example of a service provider receiving notification and performing a task to extend the availability of the at least on on-board utility)
It would have been obvious to a person of ordinary skill in the art to change further modified Lyle to include in response to the prediction that the at least one on-board utility will no longer be usable over the future period of time, automatically notifying a remote service provider that in response causes the remote service provider to perform a task to extend the availability of the at least one on-board utility over the future period of time. Incorporating this teaching would allow for an improvement of further vehicle resource management where maintenance may be requested to keep a vehicle in its optimal condition over the future period of time before any kind of malfunction or hindrance can occur.
Regarding claim 5, Lyle discloses: the method of claim 4 further comprising utilizing a daily use approach for learning fluid usage (see at least Lyle, ¶¶ [0003]-[0008], [0026], [0036] discloses the on-board diagnostic feature which provides the general myriad real-time system function data received from various sensors within a method for vehicle resource management, such as fuel/oil levels; )
Regarding claim 6, Lyle discloses: the method of claim 5 wherein said daily use approach analyzes the fluid usage over a daily period (see at least Lyle, ¶¶ [0003]-[0008], [0026], [0036] discloses the on-board diagnostic feature which provides the general myriad real-time system function data received from various sensors within a method for vehicle resource management, such as fuel/oil levels; )
Regarding claim 12, Lyle is silent on, however in the same field of endeavor, Daniel teaches: the method of claim 4 further wherein said displaying having said graphical representation (see at least Daniel, ¶¶ [0031]-[0032] which discloses an example of a notification of a vehicle fluid level being below a threshold in the form of a visual indicator)
It would have been obvious to a person of ordinary skill in the art to modify Lyle to include the method of claim 4 further wherein said displaying having said graphical representation as taught by Daniel. Doing so would allow for a better projection of information to a user of a vehicle of the remaining level of a specific resource, in this instance, the fluid levels. The examiner would like to note that Lyle takes into account the management and replenishing of resources, similarly to Daniel, however Lyle does not provide a visual representation to the user, thus even though the user is notified when fuel or power consumption is below a limit, there is no visual cue to this.
Regarding claim 14, Lyle discloses: the method of claim 4 further comprising applying a correction factor before said predicting (see at least Lyle, ¶¶ [0026], [0058]-[0060] which discloses the correction threshold factor applied before determination/prediction is made to resource data)
Regarding claim 15, Lyle discloses: a method of predicting availability of a utility (see at least Lyle, ¶¶ [0005]-[0008], [0053]-[0055] which discloses the management and optimization of vehicle resources, such as fuel, for a vehicle), comprising:
obtaining a utility sensor input from the utility, the utility sensor input being indicative of a usage of or a remaining amount of the utility for use by a user (see at least Lyle, ¶¶ [0057]-[0058] which discloses one of the replenishable resources of a vehicle being used by a user such as, fuel and/or power consumption; fuel and power diagnostics sensors gather data respectively and communicates the information)
analyzing the utility sensor input from the utility (see at least Lyle, ¶¶ [0026], [0049] which discloses the sensor fusion prediction of input of objects and features of the environment of a vehicle)
learning a pattern analysis based on the utility sensor input to predict the availability of at least one on board the utility over a future period of time for the usage of the utility by the user (see at least ¶¶ [0004]-[0007], [0026] which discloses the diagnostic tests performed on resources after data is gathered from sensor fusion, an example provided is fuel and power consumption over a time interval against a threshold and whether a vehicle can perform a specific task depending on the diagnostic)
suggesting a change in utility usage settings to prolong usage time or, automatically changing utility usage settings based on said suggesting or based on a selected extension of time period (see at least Lyle, ¶¶ [0002], [0059]-[0062] which discloses suggesting a change in utility usage, by conserving the optimal fuel level that ensures the vehicle has an adequate amount of resources that prolong usage in order for the vehicle to replenish its resource to meet the threshold requirement)
Lyle is silent on, however, in the same field of endeavor, Daniel teaches: providing a graphical display predicting to the user when the at least one on board utility will be exhausted and in response to the prediction that the at least one on board- utility will no longer be usable over the future period of time (see at least Daniel, ¶¶ [0031]-[0032] which discloses an example of a notification of a vehicle fluid level being below a threshold in the form of a visual indicator)
It would have been obvious to a person of ordinary skill in the art to further change modified Lyle to include providing a graphical representation output to the user which predicts when the at least one on-board utility will no longer be usable over the future period of time. The examiner would like to note that Lyle takes into account the management and replenishing of resources, similarly to Daniel, however Lyle does not provide a visual representation to the user, thus even though the user is notified when fuel or power consumption is below a limit, there is no visual cue to this. Adding the teachings would allow for an improvement to the base device that incorporates a better projection of information to a user of a vehicle of the remaining level of a specific resource, in this instance, the fluid levels.
Regarding claim 16, Lyle discloses: the method of Claim 1, wherein the learning of the pattern analysis based on the utility sensor input to predict the availability of the at least one on-board utility over the future period of time is based on a training of a neural network (see at least Lyle ¶¶ [0051] which discloses the machine learning techniques used to assist the vehicle resource management method of the embodiment including assisting in sensor integration and ground truth determination)
Modified Lyle is silent on, however, in the same field of endeavor, Pavan teaches:
predicting when the utility will either require filling, or require emptying (see at least Pavan, pg.14, col.16, lines 31-38 which discloses in response to a prognosis communicate a notification to the service provider; pg.10, col.8, lines 18-29, which discloses an example of a service provider receiving notification and performing a task to extend the availability of the at least on on-board utility by tending to a vehicle that requires filling of an on-board utility)
automatically notifying a remote service provider that in response causes to eause the remote service provider to perform a task to extend the availability of the at least one on board utility over the future period of time (see at least Pavan, pg.14, col.16, lines 31-38 which discloses in response to a prognosis communicate a notification to the service provider; pg.10, col.8, lines 18-29, which discloses an example of a service provider receiving notification and performing a task to extend the availability of the at least on on-board utility)
It would have been obvious to a person of ordinary skill in the art to change further modified Lyle to include predicting when the utility will either require filling, or require emptying and in response to the prediction that the at least one on-board utility will no longer be usable over the future period of time, automatically notifying a remote service provider that in response causes the remote service provider to perform a task to extend the availability of the at least one on-board utility over the future period of time. Incorporating this teaching would allow for an improvement of further vehicle resource management where maintenance may be requested to keep a vehicle in its optimal condition over the future period of time before any kind of malfunction or hindrance can occur.
Claims 7, 9-11, 13, and 17-20 are rejected under 35 U.S.C 103 as being unpatentable over further modified Lyle in view of Gao Zhisheng (US20180052025A1), hereinafter referred to as Zhisheng.
Regarding claim 7, further modified Lyle is silent on, however, in the same field of endeavor Zhisheng teaches: the method of claim 4 further comprising utilizing an averaging approach for learning fluid usage (see at least Zhisheng, ¶¶ [0009], [0073] discloses normalization process for fuel (fluid) consumption)
It would have been obvious to a person of ordinary skill in the art to change further modified Lyle to include the method of claim 4 further comprising utilizing an averaging approach for learning fluid usage as taught by Zhisheng. Doing so would allow for normalization of fluid/fuel consumption data.
Regarding claim 9, modified Lyle is silent on, however, in the same field of endeavor Zhisheng teaches: the method of claim 4 further comprising utilizing a neural networking approach for learning fluid usage (see at least Zhisheng, ¶¶ [0008]-[0009], [0048] which discloses the neural network approach integrated into the disclosure)
It would have been obvious to a person of ordinary skill in the art to change further modified Lyle to include the method of claim 4 further comprising utilizing a neural networking approach for learning fluid usage as taught by Zhisheng. Doing so would allow for machine learning to link fuel economy to parameters of usage.
Regarding claim 10, modified Lyle is silent on, however, in the same field of endeavor Zhisheng teaches: the method of claim 9 further comprising utilizing a plurality of input factors in a neural network in said predicting (see at least Zhisheng, ¶¶ [0048] which discloses input factors utilitzed in the neural network approach)
It would have been obvious to a person of ordinary skill in the art to further change modified Lyle to include the method of claim 9 further comprising utilizing a plurality of input factors in a neural network in said predicting as taught by Zhisheng. Doing so would allow for machine learning to link fuel economy to parameters of usage.
Regarding claim 11, modified Lyle is silent on, however, in the same field of endeavor Zhisheng teaches: the method of claim 10, said plurality of input factors including at least two of: a. outside temperature, b. outside humidity, c. inside temperature, d. inside humidity e. geographic location, f. location of nearest fill/dump site, g. planned activity, h. hours awake, i. number of people on a trip, j. calendar inputs indicating need for shower, k. personal behavior of said user, 1. diet, m. health problems (see at least Zhisheng, ¶¶ [0048])
It would have been obvious to a person of ordinary skill in the art to further change modified Lyle to include The method of claim 10, said plurality of input factors including at least two of: a. outside temperature, b. outside humidity, c. inside temperature, d. inside humidity e. geographic location, f. location of nearest fil/dump site, g. planned activity, h. hours awake, i. number of people on a trip, j. calendar inputs indicating need for shower, k. personal behavior of said user, 1. diet, m. health problems as taught by Zhisheng. Doing so would allow for machine learning to link fuel economy to parameters of usage.
Regarding claim 13, Lyle is silent on, however, in the same field of endeavor, Daniel teaches: the method of claim 11 further comprising displaying a time or a date wherein said at least one on-board tank will require servicing (see at least Daniel, ¶¶ [0033] which discloses an instance where a tank/component fails and a time is provided at which it occurred, indicating it is in need to repair/service)
It would have been obvious to a person of ordinary skill in the art to modify Lyle to include the method of claim 11 further comprising displaying a time or a date wherein said at least one tank will require servicing as taught by Daniel. Doing so would allow for a duration means of notifying the user of a utility in need of service (replenishing) or repair.
Regarding claim 17 further modified Lyle discloses: the method of claim 16, wherein the training utilizing a plurality of inputs is based on:
a. outside temperature (see at least Lyle, ¶¶ [0037] discloses weather input data)
b. outside humidity (see at least Lyle, ¶¶ [0037] discloses weather input data)
e. geographic location (see at least Lyle, ¶¶ [0049] which discloses location)
f. location of nearest fill/dump site (see at least Lyle, ¶¶ [0060] discloses refuel location)
g. planned activity (see at least Lyle, ¶¶ [0062] discloses planned location/destination travel)
Further modified Lyle is silent on, however, in the same field of endeavor, David teaches:
c. inside temperature (see at least David, ¶¶ [0113])
d. inside humidity (see at least David, ¶¶ [0282] discloses inside humidity and temperature)
h. hours awake (see at least David, ¶¶ [0113] discloses sleep patterns)
i. number of people on a trip (see at least David, ¶¶ [0148] discloses number of users of vehicle)
j. calendar inputs indicating need for shower (see at least David, ¶¶ [0200] discloses calendar appointments)
k. personal behavior of said user (see at least ¶¶ [0113]-[0114] discloses user behavior)
1. diet (see at least ¶¶ [0089] discloses diet)
m. health problems (see at least ¶¶ [0089] discloses variations in diet)
It would have been obvious to a person of ordinary skill in the art to change further modified Lyle to include wherein the training utilizing a plurality of inputs is based on: c. inside temperature d. inside humidity h. hours awake i. number of people on a trip j. calendar inputs indicating need for shower k. personal behavior of said user 1. diet and m. health problems. Doing so would allow for further improvement on the base device of further modified Lyle to consider various more inputs to train the system which provides a wider scope of prediction factors impacting vehicle resource management.
Regarding claim 18, further modified Lyle discloses: the method of claim 17, wherein the neural network is an artificial neural network or a recurrent neural network (see at least Lyle ¶¶ [0051] which discloses the machine learning techniques used to assist the vehicle resource management method of the embodiment including assisting in sensor integration and ground truth determination)
Regarding claim 19, further modified Lyle discloses: the method of claim 18, wherein the plurality of inputs to train the neural network is obtained from the utility sensor input, at least one local weather database, and a global positioning database (see at least Lyle, ¶¶ [0037] discloses weather databases; [0020] discloses global location coordinate information/navigation database)
Regarding claim 20, further modified Lyle discloses: the method of claim 19, wherein the neural network is configured to continuously generated a new weighted value for each of the plurality of inputs to define the learning of the pattern analysis such that the prediction of the availability of the at least one on-board utility over the future period of time is continuously generated for continuous prediction (see at least Lyle, ¶¶ [0036] discloses the storing of information applicable for real-time updates as so the record of reservation management; [0061] provides an example of real-time updates applied to the vehicle resource data of a replenishable resource after the vehicle resource has been deemed adequately replenished, vehicle will transmit a resource data update to server)
Claim 8 is rejected under 35 U.S.C 103 as being unpatentable over further modified Lyle in view of Leitch John (US4140996A), hereinafter referred to as John.
Regarding claim 8, modified Lyle is silent on, however, in the same field of endeavor John teaches: the method of claim 7 further comprising determining an average amount of water used (see at least John, pg.8, col.3)
It would have been obvious to a person of ordinary still in the art to change further modified Lyle to include the method of claim 7 further comprising determining an average amount of water used as taught by John. Doing so would allow for the monitoring of additional resources.
Conclusion
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/KIRSTEN JADE M SANTOS/Examiner, Art Unit 3664
/RACHID BENDIDI/Supervisory Patent Examiner, Art Unit 3664