Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Status of the Claims
Claims 1-20 are currently pending.
Response to Arguments
Applicant’s amendments overcome rejections made under 112 (b), therefore the rejection is withdrawn.
Applicant’s arguments with respect to rejections made under 101 have been fully considered but are not persuasive. Applicant argues that the claims are integrated into a practical application because it improves the relevant technology e.g. ship navigation ( remarks pg. 7).
Examiner respectfully disagrees and notes that applicant did not provide a specific element that provides technological improvements . See October 2019 Update: Subject Matter Eligibility, pg. 12. ("if the specification explicitly sets forth an improvement but in a conclusory manner (i.e., a bare assertion of an improvement without the detail necessary to be apparent to a person of ordinary skill in the art), the examiner should not determine the claim
improves technology"). "[I]mproving a user's experience while using a computer application is not, without more, sufficient to render the claims directed to an improvement in computer functionality." Customedia Technologies v. Dish Network, 951 F.3d 1359, 1365 (Fed. Cir. 2020). See also Trading Techs. Int'l, Inc. v. IBG LLC, 921 F.3d 1084, 1092-93 (Fed. Cir. 2019) (the purported improvement in user experience from an interface did not "improve the functioning of the computer, make it operate more efficiently, or solve any technological problem.") Accordingly, the rejection is maintained.
Applicant’s arguments with respect to rejections made under 102/103 have been fully considered but are moot in view of new grounds of rejections.
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.
Step 1
Claims 1-13 are directed to a method (i.e., a process); Claims 14-19 are directed to a system (i.e., a machine), and claim 20 is directed to a non-transitory computer readable medium (i.e., a machine). Therefore, claims 1- 20 all fall within the one of the four statutory categories of invention.
Step 2A, Prong One:
Independent claims 1, 14, and 20 substantially recite: generating simulated shipping routes, including a first simulated route under a first environmental condition and a second simulated route under a second environmental condition; generating an uncertainty score for each of the one or more simulated shipping routes; determining, using the uncertainty scores, (1) a first ship to traverse the first simulated route of the simulated shipping routes and (2) a second ship to traverse the second simulated route of the simulated shipping routes; generating a first candidate network and a second candidate network, wherein the first candidate network includes an indication of (1) the first ship to traverse the first simulated route and (2) the second ship to traverse the second simulated route and the second candidate network includes an indication of multiple ships to traverse multiple simulated routes; comparing the first candidate network and the second candidate network under two or more different environmental conditions; determining, using the comparison, the first candidate network as an optimal candidate network; and providing data indicating the optimal candidate network to one or more ships.
The limitations stated above are processes/ functions that under broadest reasonable interpretation covers (determining an optimal route for a ship) certain methods of organizing human activity” (managing personal behavior or relationships or interactions between people and commercial or legal interactions (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; business relations). Therefore, the claim recites an abstract idea.
Step 2A, Prong Two
The judicial exception is not integrated into a practical application. Claims 1, 14 and 20 as a whole amount to: (i) merely invoking generic components as a tool to perform the abstract idea or “apply it” (or an equivalent)
The additional elements of (i) one or more computers and one or more storage devices, when executed by the one or more computers, to cause the one or more computers to perform operations, one or more non-transitory computer storage media encoded with instructions, are recited at a high-level of generality (See [0031] system of one or more computers can be configured to perform particular operations or actions by virtue of having software, firmware, hardware, or a combination of them installed on the system that in operation causes or cause the system to perform the actions.[0199]Computers suitable for the execution of a computer program include, by way of example, general or special purpose microprocessors or both, or any other kind of central processing unit. Generally, a central processing unit will receive instructions and data from a read-only memory or a random-access memory or both. The essential elements of a computer are a central processing unit for performing or executing instructions and one or more memory devices for storing instructions and data. [0200-203] ), such that, when viewed as whole/ordered combination, it amounts to no more than mere instruction to apply the judicial exception using generic computer components or “apply it” (See MPEP 2106.05(f)).
Accordingly, these additional elements, when viewed as a whole/ordered combination, do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. Thus, the claims are directed to an abstract idea.
Step 2B
As discussed above with respect to Step 2A Prong Two, the additional elements amount to no more than: (i) “apply it” (or an equivalent), and (ii) generally link the use of a judicial exception to a particular technological environment or field of use, are not a practical application of the abstract idea.
The same analysis applies here in Step 2B, i.e., (i) merely invoking the generic components as a tool to perform the abstract idea or “apply it” (See MPEP 2106.05(f)); and (ii) generally linking the use of a judicial exception to a particular technological environment or field of use (See MPEP 2106.05(h)), does not integrate the abstract idea into a practical application at Step 2A or provide an inventive concept at Step 2B.
Therefore, the additional elements of: (i) one or more computers and one or more storage devices, when executed by the one or more computers, to cause the one or more computers to perform operations, one or more non-transitory computer storage media encoded with instructions, do not integrate the abstract idea into a practical application at Step 2A or provide an inventive concept at Step 2B. Thus, even when viewed as a whole/ordered combination (as shown in Fig.1), nothing in the claims adds significantly more (i.e., an inventive concept) to the abstract idea. Thus, the claims are ineligible.
Dependent Claims Step 2A:
The limitations of the dependent claims but for those addressed below merely set forth further refinements of the abstract idea without changing the analysis already presented. Additionally, for the same reasons as above, the limitations fail to integrate the abstract idea into a practical application because they use the same general technological environment and instructions to implement the abstract idea (e.g. using computers to communicate data). Claims 2 and 15 recite “ocean model”, which fail to integrate the abstract idea into a practical application because merely invoking the generic components as a tool to perform the abstract idea or “apply it”. Accordingly, the claims are ineligible under step 2A.
Dependent Claims Step 2B:
The dependent claims merely use the same general technological environment and instructions to implement the abstract idea. Claims 2 and 15 recite “ocean model”, is recited at a high-level of generality see specification ([0077] the process 100 includes one or more operations performed by an ocean circulation model. For example, the ML model 102 can be a form of ocean circulation model. In some implementations, an ocean circulation model solves partial differential equations using data as initial and boundary conditions—e.g., weather forecasts, satellite data, sensor data, among others. In some implementations, the ocean circulation model is enhanced. For example, the ocean circulation model can be enhanced using techniques from machine learning, such as Bayesian optimization, among others. Enhanced can refer to modifying some parameters of a physical model, e.g., the ocean circulation model, using local observations, e.g., local weather or weather sensor data)- this does not amount to significantly more for the same reasons it fails to integrate the abstract idea into a practical application. Accordingly, the dependent claims are not directed to significantly more than the exception itself, and are not eligible subject matter under § 101.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claim(s) 1-10 and 13-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Chen (US20100280750 ) in view of Kocis (US 20100287073 A1)
As per claim 1, Chen teaches:
A method comprising: generating simulated shipping routes, including a first simulated route under a first environmental condition and a second simulated route under a second environmental condition; ( see at least: Abstract, Fig.9 [0119] the process begins by identifying a start point and an end point for a ship (operation 900). The process then obtains a number of forecasts of weather conditions for a period of time to travel from the start point to the end point (operation 902). The number of forecasts may comprise an ensemble weather forecast that includes weather forecasts, as well as wave, tide, and wind forecasts. [0121] A probability of reaching the end point from the start point is generated for a number of routes from the start point to the end point for the ship within the period of time using the number of forecasts of weather conditions (operation 904) [environmental conditions]. A number of probabilities are formed by operation 904. These probabilities may be generated by probability process 408 in route analysis and planning tool 400 in FIG. 4.)
generating an uncertainty score for each of the one or more simulated shipping routes; ( see at least: [0121] A probability [uncertainty score] of reaching the end point from the start point is generated for a number of routes from the start point to the end point for the ship within the period of time using the number of forecasts of weather conditions (operation 904). A number of probabilities are formed by operation 904. These probabilities may be generated by probability process 408 in route analysis and planning tool 400 in FIG. 4.)
determining, using the uncertainty scores, (1) a first ship to traverse the first simulated route of the simulated shipping routes and (2) first ship to traverse the second simulated route of the simulated shipping routes; ( see at least: Fig.1, [ [0058] Route analysis and planning tool 300 is a program or application designed to plan routes for vessels to optimize time to reach desired destinations using conditions, such as forecasts of weather conditions, waves, tides, currents, winds, and/or other conditions. [0062] Route analysis and planning tool 300 uses ship performance models 308 in determining whether various conditions that are present and forecasted may affect ship 304 in its route to a destination. The same weather conditions at sea affect different types of ships in different ways. )
Chen does not explicitly teach second ship to traverse the route, however, Kocis teaches the second ship ( see at least: [0021] determines the optimal routes to be performed and, for each optimized transportation route, the stops (e.g., supply/demand locations, canals, refueling, etc.) each vehicle makes in the route, and the specific vehicle assigned to the voyage [0059] determines the optimal solution to maximize total net margin for routing, scheduling, and assignment of vehicles in an available fleet to move cargo during a planned period [0080] method provides the transportation scheduler with the following information: (1) the feasible vehicles for each assignment (based on timing, capacity, etc.), selected from a plurality of available vehicles; (2) a recommendation for the vehicle/voyage assignments)
It would have been obvious for one ordinary skilled in the art before the effective filing date of present invention to incorporate the second ship feature for the same reasons its useful in Kocis - namely, to maximize total net margin for routing, scheduling, and assignment of vehicles in an available fleet to move cargo during a planned period ( par.59). This is merely a combination of old elements related to improving maritime transportation efficiency and in the combination no elements would serve a purpose other than it already did independently and one skill in the art would have recognized that the combination could have been implemented through routine engineering producing predictable results.
Chen further teaches generating a first candidate network and a second candidate network ( see at least: [0102] Grid of routes 602 includes all possible segments of routes for a voyage from start point 608 to end point 610. In this illustrative example, grid of routes 602 includes solution routes 612 [a first candidate network] and non-solution routes 614 [second candidate network]. Solution routes 612 are routes that meet user-defined criteria and/or are generated by an optimization process, such as optimization process 406 in FIG. 4. [0103] Non-solution routes 614 are the routes within all possible routes in grid of routes 602 that do not meet the user-defined criteria and/or are not generated as optimal solutions by optimization process 406)
wherein the first candidate network includes an indication of (1) the first ship to traverse the first simulated route and (2) the first ship to traverse the second simulated route; ( see at least: [ examiner interprets the first and second ship to be the different ships ] [0084] In identifying number of routes 424, optimization process 406 uses conditions 433. Conditions 433, in these examples, include, for example, without limitation, forecast of weather conditions 434 for period of time 420 and model 436 of ship 422 [0119] [0062] Route analysis and planning tool 300 uses ship performance models 308 in determining whether various conditions that are present and forecasted may affect ship 304 in its route to a destination. The same weather conditions at sea affect different types of ships in different ways. )
Chen does not explicitly teach second ship to traverse the route, however, Kocis teaches the second ship ( see at least: [0021] determines the optimal routes to be performed and, for each optimized transportation route, the stops (e.g., supply/demand locations, canals, refueling, etc.) each vehicle makes in the route, and the specific vehicle assigned to the voyage [0059] determines the optimal solution to maximize total net margin for routing, scheduling, and assignment of vehicles in an available fleet to move cargo during a planned period [0080] method provides the transportation scheduler with the following information: (1) the feasible vehicles for each assignment (based on timing, capacity, etc.), selected from a plurality of available vehicles; (2) a recommendation for the vehicle/voyage assignments)
It would have been obvious for one ordinary skilled in the art before the effective filing date of present invention to incorporate the second ship for the same reasons its useful in Kocis - namely, to maximize total net margin for routing, scheduling, and assignment of vehicles in an available fleet to move cargo during a planned period ( par.59). This is merely a combination of old elements related to improving maritime transportation efficiency and in the combination no elements would serve a purpose other than it already did independently and one skill in the art would have recognized that the combination could have been implemented through routine engineering producing predictable results.
While Chen teaches the second candidate network ( [0102] Grid of routes 602 includes all possible segments of routes for a voyage from start point 608 to end point 610. non-solution routes 614 ), Chen does not explicitly teach an indication of multiple ships to traverse multiple simulated routes, however, this is taught by Kocis ( see at least: [0019] a method for optimizing various decisions associated with a transportation schedule for a plurality of transportation vehicles transporting cargo to and from various locations and moving the plurality of transportation vehicles according to the optimized decisions. More particularly, the decisions include the transportation routes (i.e., voyages), the timing and order in which the transportation routes are performed, and the ships assigned to perform each route according to the schedule and the type and amount of cargo pickup and delivery within set parameters.[0092] The second step involves the optimal selection of voyages, assignment of vehicles to voyages, and optimal assignment of load-events and discharge-events to selected voyages-vehicle assignments as one integrated solution step so as to maximize the total net margin)
It would have been obvious for one ordinary skilled in the art before the effective filing date of present invention to incorporate the multiple ships traverse multiple simulated routes for the same reasons its useful in Kocis - namely, to maximize total net margin for routing, scheduling, and assignment of vehicles in an available fleet to move cargo during a planned period ( par.59). This is merely a combination of old elements related to improving maritime transportation efficiency and in the combination no elements would serve a purpose other than it already did independently and one skill in the art would have recognized that the combination could have been implemented through routine engineering producing predictable results.
Chen further teaches comparing the first candidate network and the second candidate network under two or more different environmental conditions;( see at least: [0144-146] The process begins by obtaining weather forecasts for a period of time during which a segment is to be traversed (operation 1300). A segment is selected from segments of a route (operation 1302). Ensemble forecasting is then performed for the selected segment using the forecasts from the different sources (operation 1304). In these illustrative examples, ensemble forecasting is a numerical prediction method used to generate a representative sample of feature states, such as weather conditions.)
Chen further teaches determining, using the comparison, the first candidate network as an optimal candidate network; ( see at least: [0149] A number of probabilities of reaching the end point from the start point for a number of routes for the voyage are generated using the ensemble weather forecast (operation 1404). [0150] Thereafter, the process selects a route within the number of routes with an acceptable probability in the number of probabilities for arriving at the end point on time (operation 1406)[optimal candidate network]. The process then executes the voyage using the selected route)
Chen further teaches providing data indicating the optimal candidate network to the one or more ships. ( see at least: Fig. 3 [67-68] Route analysis and planning tool 300 generates a route for ship 304 based on the navigation information, forecasting information, and the ship performance model. This route is sent as route data 314 to ship 304 When received, route data 314 is processed by navigation system 316. Navigation system 316 is an example of software that may be executed on a data processing system, such as data processing system 200 in FIG. 2, on ship 304. [0150] the process selects a route within the number of routes with an acceptable probability in the number of probabilities for arriving at the end point on time (operation 1406)[optimal candidate network]. The process then executes the voyage using the selected route )
As per claim 2, Chen in view of Kocis teaches claim 1 as above. Chen further teaches:
wherein the two or more different environmental conditions are generated using an ocean model that predicts current or weather events. (see at least: Fig. 4 # 433, [0014] Program code is also present for obtaining a number of forecasts of weather conditions for a period of time to travel from the start point to the end point [0058] Route analysis and planning tool 300 is a program or application designed to plan routes for vessels to optimize time to reach desired destinations using conditions, such as forecasts of weather conditions, waves, tides, currents, winds, and/or other conditions [0144-146] ensemble forecasting is a numerical prediction method used to generate a representative sample of feature states, such as weather conditions. an ensemble weather forecast may include a number of forecasts for a number of weather phenomena such as, for example, without limitation, weather conditions, winds, waves, tides, currents, and/or other suitable phenomena [0122] The probability is estimated by the cumulative probability that the ship can make the speed up to the maximum wave height, Hmax, based on the type of probability distribution and parameters derived from the output of ensemble forecast models.)
As per claim 3, Chen in view of Kocis teaches claim 1 as above. Chen further teaches:
wherein the simulated shipping routes include shipping ports ( see at least: Fig.6 Fig.4, [0120] Operation 903 generates the number of routes as a subset of all possible routes from the start point to the end point [ shipping ports], [0116-117]).
Chen does not explicitly teach three or more shipping ports, however, this is taught by Kocis ( see at least: [0021] the optimal routes to be performed and, for each optimized transportation route, the stops (e.g., supply/demand locations, canals, refueling, etc.) each vehicle makes in the route, [0062] Each voyage definition can include visits to multiple supply locations and multiple demand locations and can have a cargo that includes multiple types (e.g., different grades of crude oil)
It would have been obvious for one ordinary skilled in the art before the effective filing date of present invention to incorporate the three or more shipping ports for the same reasons its useful in Kocis - namely, to provides a marine transportation scheme for each voyage consists of multiple loading ports and multiple discharging ports ( par.11). This is merely a combination of old elements related to improving maritime transportation efficiency and in the combination no elements would serve a purpose other than it already did independently and one skill in the art would have recognized that the combination could have been implemented through routine engineering producing predictable results.
As per claim 4, Chen in view of Kocis teaches claim 1 as above. Chen further teaches:
The first ship ( see at least: Fig. 1, [0062] [0033] ships are watercraft such as, for example, without limitation, tankers, bulk carriers, container vessels, passenger ships, and/or other suitable types of watercraft)
Chen does not explicitly teach determining cargo to be transported by the first ship and the second ship. However, this is taught by Kocis ( see at least: [0021] The method determines the optimal routes to be performed and, for each optimized transportation route, the stops (e.g., supply/demand locations, canals, refueling, etc.) each vehicle makes in the route, the amount and type of cargo loaded at each supply stop, the amount and type of cargo discharged at each demand stop, the schedule for loading/discharging cargo, the estimated freight cost, and the specific vehicle assigned to the voyage. In addition, the method may determine, for each grouping of cargo at each demand location, the inventory profile and other limiting constraints on delivery (including, for example, suggested blend-down ratio of bulk material cargo). [0055] The plurality of transportation decisions to be optimized includes transportation routes for the plurality of transportation vehicles, allocation of cargo to be transported to one or more demand locations by the plurality of transportation vehicles within set parameters, nomination of cargo pickup from one or more supply locations by the plurality of transportation vehicles within set parameters, the use of special transportation locations, and vehicle assignments for each of the plurality of vehicles.)
It would have been obvious for one ordinary skilled in the art before the effective filing date of present invention to incorporate the cargo determination feature for the same reasons its useful in Kocis - namely, to determine the optimal routes ( par.66 and par.55). This is merely a combination of old elements. In the combination no elements would serve a purpose other than it already did independently and one skill in the art would have recognized that the combination could have been implemented through routine engineering producing predictable results.
As per claim 5, Chen in view of Kocis teaches claim 1 as above. Chen further teaches:
obtaining data from the first ship prior to determining the first ship to traverse the first simulated route of the one or more simulated shipping routes. ( see at least: Fig. 3, [0061] Ship 304 transmits position data 306 to route analysis and planning tool 300. Position data 306 includes a location of ship 304. This data may be obtained through a global positioning system on ship 304. The position information also may include a velocity or speed of ship 304. This information is used by route analysis and planning tool 300 to identify the location of ship 304 in determining whether changes in the route of ship 304 may be suggested. [0067] the routing analysis may be performed in response to an event, such as a request from ship 304 or a change in current or predicted weather conditions. Route analysis and planning tool 300 generates a route for ship 304 based on the navigation information, forecasting information, and the ship performance model.)
As per claim 6, Chen in view of Kocis teaches claim 5. Chen further teaches:
wherein the data obtained from the first ship includes data indicating one or more locations along the first simulated route. ( see at least: Fig.3 [0061] Ship 304 transmits position data 306 to route analysis and planning tool 300. Position data 306 includes a location of ship 304. This data may be obtained through a global positioning system on ship 304 This information is used by route analysis and planning tool 300 to identify the location of ship 304 in determining whether changes in the route of ship 304 may be suggested. [0067] the routing analysis may be performed in response to an event, such as a request from ship 304 or a change in current or predicted weather conditions. Route analysis and planning tool 300 generates a route for ship 304 based on the navigation information, forecasting information, and the ship performance model.)
As per claim 7, Chen in view of Kocis teaches claim 5. Chen further teaches:
wherein the data obtained from the first ship includes route preferences of the first ship. ( see at least: [0102] Solution routes 612 are routes that meet user-defined criteria [0104] Window 618 provides an identification of probabilities that are associated with solution routes 612. Bars 620 are presented in window 618. Each bar in bars 620 corresponds to a route in solution routes 612.[0114] Ship operators may use the different advantageous embodiments to plan and execute voyages in a manner that may meet various conditions. These conditions may include, for example, without limitation, reducing fuel consumption, avoiding conditions that may exceed safe operating limits, and reaching an end point on time )
As per claim 8, Chen in view of Kocis teaches claim 1 as above. Chen further teaches:
wherein generating an uncertainty score for each of the one or more simulated shipping routes comprises: generating an uncertainty score for the first simulated route including generating one or more distributions representing the first environmental condition of the first simulated route. ( see at least: [0122] the probability in operation 904 may be calculated as the product of the probabilities of the individual links from start to end points. For example, P=P1*P2*P3*P4 . . . Pn for n such links. Pi is the probability that the ship can make the speed and heading under the forecast characterized by the mean wave height and standard deviation, subjected to the constraints that the safe operating limits are not exceeded and the ship has enough horsepower to overcome the resistance. The probability is estimated by the cumulative probability that the ship can make the speed up to the maximum wave height, Hmax, based on the type of probability distribution and parameters derived from the output of ensemble forecast models.)
As per claim 9, Chen in view of Kocis teaches claim 8. Chen further teaches:
wherein the first environmental condition of the first simulated route includes wait times at port or weather events. ( see at least [0122] The probability is estimated by the cumulative probability that the ship can make the speed up to the maximum wave height, Hmax, based on the type of probability distribution and parameters derived from the output of ensemble forecast models [ weather events])
As per claim 10, Chen in view of Kocis teaches claim 1. Chen further teaches:
generating one or more distributions representing an effect of environmental conditions of the two or more different environmental conditions on the first simulated route and the second simulated route. ( see at least: [0121] A probability of reaching the end point from the start point is generated for a number of routes from the start point to the end point for the ship within the period of time using the number of forecasts of weather conditions (operation 904). A number of probabilities are formed by operation 904. [ different environment conditions for different routes] [0122] the probability in operation 904 may be calculated as the product of the probabilities of the individual links from start to end points. For example, P=P1*P2*P3*P4 . . . Pn for n such links. Pi is the probability that the ship can make the speed and heading under the forecast characterized by the mean wave height and standard deviation, subjected to the constraints that the safe operating limits are not exceeded and the ship has enough horsepower to overcome the resistance. The probability is estimated by the cumulative probability that the ship can make the speed up to the maximum wave height, Hmax, based on the type of probability distribution and parameters derived from the output of ensemble forecast models. )
As per claim 13, Chen in view of Kocis teaches claim 1. Chen further teaches:
wherein the two or more different environmental conditions include nominal and off-nominal conditions. ( see at least: [0145-146] These different forecasts may be analyzed to generate a probability of a certain event occurring. This event may be, for example, a storm, clear conditions, high winds, and/or other events [ nominal and off-nominal conditions]. In other words, an ensemble weather forecast may include a number of forecasts for a number of weather phenomena such as, for example, without limitation, weather conditions, winds, waves, tides, currents, and/or other suitable phenomena.)
Claims 14-20 recite similar limitations as claims 1-6, therefore they are rejected over the same rationales.
Claim(s) 11-12 is/are rejected under 35 U.S.C. 103 as being unpatentable over Chen in view of Kocis in further view of Beaurepaire (US 20210341300 A1)
As per claim 11, Chen in view of Kocis teaches claim 1.
Chen does not explicitly teach:
comparing a previously determined network and the optimal candidate network, wherein the previously determined network includes one or more of (1) a route of the first ship different than the first simulated route or the previously determined network includes a route of the second ship different than the second simulated route.
While Chen teaches optimal candidate network, first simulated route, second simulated route ( see at least: [0121] A probability of reaching the end point from the start point is generated for a number of routes [first and second simulated routes] from the start point to the end point for the ship within the period of time using the number of forecasts of weather conditions (operation 904) [0150] the process selects a route within the number of routes with an acceptable probability in the number of probabilities for arriving at the end point on time (operation 1406)[optimal candidate network]. The process then executes the voyage using the selected route (operation 1408)))
Beaurepaire teaches comparing a previously determined route with the optimal candidate route for a vehicle that includes a route that is different than a simulated route or the previously determined network includes a route of the second ship different than the second simulated route ( see at least: [0027] the system 100 enables users to relevantly compare a computed navigation route (e.g., to a selected destination) with personal and historical routes that the user has already traveled, hence are relatively more familiar. For example, the system 100 can determine the optimal route (or route segment) to refer to in a route comparison (e.g., by using a navigation routing engine). The system 100 can then rank historical routes based on relevance to the computed optimal route. Historical routes, for instance, include but are not limited to routes recorded as previously traveled or known to the user (e.g., a route previously presented to the user) [0066] the comparison module 203 compares each of the user's historical navigation routes against the optimal navigation to determine the similarity between the respective routes.).
It would have been obvious for one ordinary skilled in the art before the effective filing date of present invention to incorporate the comparison of the routes feature for the same reasons its useful in Beaurepaire - namely, to determine the similarity between the respective routes ( par.66). This is merely a combination of old elements. In the combination no elements would serve a purpose other than it already did independently and one skill in the art would have recognized that the combination could have been implemented through routine engineering producing predictable results.
As per claim 12, Chen in view of Kocis and Beaurepaire teaches claim 11.
Chen does not teach performing the comparison of the previously determined network and the optimal candidate network under the two or more different environmental conditions.
While Chen teaches compare the optimal candidate network under the two or more different environmental conditions. ( see at least: [0121] A probability of reaching the end point from the start point is generated for a number of routes [first and second simulated routes] from the start point to the end point for the ship within the period of time using the number of forecasts of weather conditions (operation 904) [0150] the process selects a route within the number of routes with an acceptable probability in the number of probabilities for arriving at the end point on time (operation 1406)[optimal candidate network].
Beaurepaire teaches performing the comparison of the previously determined route and the optimal candidate network under different environmental conditions ( see at least: [0034] the system 100 determines the user's most relevant historical route by ranking the historical routes based on the number or degree of similarities shared among the computed navigation routes, the optimal computed navigation route, and/or the historical routes [0047] the 100 can determine the corresponding information or data based on one or more of the following questions, Do the routes have comparable weather ? [0078] 100 generates the UI 401 such that it includes one or more inputs 419 so that the user may fine tune which factors or attributes the system 100 analyzes when determining the most relevant historic route among the users historic routes to use for the comparative analysis, as depicted in FIG. 4B. In this example, the inputs 419 include factors or attributes such as “weather” (e.g., rain, sun, snow, wind, temperature, etc.))
It would have been obvious for one ordinary skilled in the art before the effective filing date of present invention to incorporate the comparison of the routes feature for the same reasons its useful in Beaurepaire - namely, to determine the similarity between the respective routes ( par.66). This is merely a combination of old elements. In the combination no elements would serve a purpose other than it already did independently and one skill in the art would have recognized that the combination could have been implemented through routine engineering producing predictable results.
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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MANAL A. ALSAMIRI whose telephone number is (571)272-5598. The examiner can normally be reached M-F: 9:00 am - 5:00 pm.
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/M.A.A./Examiner, Art Unit 3628
/SHANNON S CAMPBELL/Supervisory Patent Examiner, Art Unit 3628