DETAILED ACTION
Notice of Pre-AIA or AIA Status
1. 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 Application
2. This application, filed November 26, 2024, is a continuation of U.S. Patent Application No. 18/377,663, filed October 6, 2023, which issued as U.S. Patent No. US 12,154,325 B2 on November 26, 2024. Claims 1-20 are pending in the application.
Double Patenting
3. The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer.
4. Claim 1 is rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1, 4, and 7 of U.S. Patent No. US 11,783,574 B1. Although the claims at issue are not identical, they are not patentably distinct from each other because claims 1, 4, and 7 of US 11,783,574 disclose, teach, and suggest all the limitations of claim 1 of the current application.
Claims 2-7 are rejected for the same reasons as claim 1 because claims 2-7 depend from claim 1.
Claim 8 is rejected on the ground of nonstatutory double patenting as being unpatentable over claims 6 and 7 of U.S. Patent No. US 11,783,574 B1. Although the claims at issue are not identical, they are not patentably distinct from each other because claims 6 and 7 of US 11,783,574 disclose, teach, and suggest all the limitations of claim 8 of the current application.
Claims 9-15 are rejected for the same reasons as claim 8 because claims 9-15 depend from claim 8.
Claim 16 is rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1, 4, 7, and 12 of U.S. Patent No. US 11,783,574 B1. Although the claims at issue are not identical, they are not patentably distinct from each other because claims 1, 4, 7, and 12 of US 11,783,574 disclose, teach, and suggest all the limitations of claim 16 of the current application.
Claims 17-20 are rejected for the same reasons as claim 16 because claims 17-20 depend from claim 16.
Claim Rejections - 35 USC § 103
5. 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.
6. Claims 1-8 and 10-20 are rejected under 35 U.S.C. 103 as being unpatentable over Wells et al. (US 2021/0233198 A1).
Regarding claim 1, Wells discloses:
a method for determining whether a personal mobility vehicle (PMV) is parked correctly ([0003]), comprising:
sensing, by one or more sensors of the PMV, a signal corresponding to an orientation of the PMV ([0018]);
receiving, by a server or an application on a user device, the signal corresponding to an orientation of the PMV ([0013], [0018], [0032]; FIG. 1; FIG. 2: 243);
determining, by the server or an application on the user device, a sensed orientation of the PMV ([0032]; FIG. 3A; FIG. 3B);
determining, by the server or an application on the user device, based on the sensed orientation, whether the PMV satisfies one or more parking rules ([0013], [0018]),
Wells does not explicitly disclose that at least one of the parking rules is that the PMV is in an upright position, but Wells does disclose parking rules ([0013], ([0026]); Wells does disclose determining whether a vehicle is parked in a permissible location or orientation ([0016], [0018]); and Wells does disclose that a vehicle parked upright is parked in a permissible area and orientation ([0032]; FIG. 3A), all of which suggests that the method of Wells comprises that at least one of the parking rules is that the PMV is in an upright position for the benefit of issuing an alert when the vehicle is impermissibly parked on the ground ([0022], [0032]);
it would have been obvious to one of ordinary skill in the art before the effective filing date of the application to have configured the method of Wells in the foregoing manner because that would have enabled the method to issue an alert when the vehicle is impermissibly parked on the ground; and
Wells does not explicitly disclose providing, by the server to a user application, an indication of the upright position to the user, but Wells does disclose that the method comprises a client device that executes an application and communicates with a micro-mobility service ([0011], [0013]; FIG. 1: 110, 140); Wells does disclose that the machine learning model outputs whether an image shows a validly parked vehicle ([0019], [0020]); Wells does disclose issuing an alert to a client device when the method determines that a vehicle is impermissibly parked ([0022]); Wells does disclose that the method penalizes a user when the user impermissibly parks a vehicle; and Wells does disclose that the method logs an indication in a user profile database that the user did, or did not, repark a vehicle in a permissible location following an alert ([0022]); all of which suggests that the method of Wells comprises providing, by the server to a user application, an indication of the upright positions to the user for the benefit of notifying the user that the user has complied with the rules of the method and will not be penalized;
it would have been obvious to one of ordinary skill in the art before the effective filing date of the application to have configured the method of Wells in the foregoing manner because that would have enabled the method to notify a user that the user has complied with the rules of the method and will not be penalized.
Regarding claim 2, Wells discloses obtaining, by an application on a user device, an image of the PMV ([0017]); inputting, by the server or the application on the user device, the image into a machine learning model ([0019], [0026]); and wherein determining whether the PMV satisfies the one or more parking rules includes determining, by the server or the application, based on the image and the signal, whether the PMV is in an upright position ([0020], [0026]).
Regarding claim 3, Wells discloses that the indication comprises a completion indication. ([0019], [0022], [0026])
Regarding claim 4, Wells discloses that the indication comprises an instruction to repark the parked PMV because the parked PMV does not satisfy one or more of the one or more parking rules. ([0030])
Regarding claim 5, Wells discloses: obtaining, by the application on a user device, a second image of the parked PMV ([0017]); generating, by the server or the application on the user device, and the machine learning model, a second indication of whether the parked PMV satisfies the one or more parking rules ([0020], [0026]); and providing, by the application, the second indication of whether the parked PMV satisfies the one or more parking rules to a display of the user device ([0013], [0018], [0032]).
Regarding claim 6, Wells discloses that signal comprises data from a gyroscope of the PMV. ([0018]; Wells discloses an accelerometer, and a gyroscope is a type of accelerometer.)
Regarding claim 7, Wells discloses that the signal comprises data from an accelerometer of the PMV. ([0018])
Regarding claim 8, Wels discloses:
a method for validating the upright position of a parked personal mobility vehicle (PMV) ([0003]), comprising:
capturing, by an application on a user device, an image of the parked PMV using a camera ([0017], [0019]);
processing, by a server or the application on the user device, the captured image using a machine learning model to identify the PMV’s position and orientation ([0019], [0020]);
determining, by a server or the application on the user device, whether the PMV is upright based on the identified position and orientation ([0018], [0032]; FIG. 3A; FIG. 3B); and
providing, by the application on the user device, a validation result indicating whether the PMV is upright ([0020], [0022]).
Wells does not explicitly disclose providing, by the application on the suer device, a validation result indicating whether the PMV is upright, but Wells does disclose that the method comprises a client device that executes an application and communicates with a micro-mobility service ([0011], [0013]; FIG. 1: 110, 140); Wells does disclose that the machine learning model outputs whether an image shows a validly parked vehicle ([0019], [0020]); Wells does disclose issuing an alert to a client device when the method determines that a vehicle is impermissibly parked ([0022]); Wells does disclose that the method penalizes a user when the user impermissibly parks a vehicle; and Wells does disclose that the method logs an indication in a user profile database that the user did, or did not, repark a vehicle in a permissible location following an alert ([0022]); all of which suggests that the method of Wells comprises providing, by the application on the user device, a validation result indicating whether the PMV is upright for the benefit of notifying the user that the user has complied with the rules of the method and will not be penalized;
it would have been obvious to one of ordinary skill in the art before the effective filing date of the application to have configured the method of Wells in the foregoing manner because that would have enabled the method to notify a user that the user has complied with the rules of the method and will not be penalized.
Regarding claim 10, Wells discloses that the validation result comprises a completion indication. ([0019], [0022], [0026])
Regarding claim 11, Wells discloses that the validation result comprises an instruction to repark the parked PMV because the parked PMV does not satisfy one or more parking rules. ([0030])
Regarding claim 12, Wells discloses obtaining, by the application on a user device, a second image of the parked PMV ([0017]); generating, by the server or the application on the user device, and the machine learning model, a second indication of whether the parked PMV satisfies the one or more parking rules ([0020], [0026]); and providing, by the application, the second indication of whether the parked PMV satisfies the one or more parking rules to a display of the user device ([0013], [0018], [0032]).
Regarding claim 13, Wells discloses obtaining, by the server or the application on a user device, sensor data from one or more sensors of the parked PMV ([0017], [0018]); inputting, by the server or the application on the user device, the sensor data into the machine learning model ([0019]); and wherein determining whether the PMV satisfies one or more parking rules includes determining, by the server or the application, based on the sensor data and the image, whether the PMV is in an upright position ([0018], [0032]).
Regarding claim 14, Wells discloses that sensor data comprises data from a gyroscope of the PMV. ([0018]; Wells discloses an accelerometer, and a gyroscope is a type of accelerometer.)
Regarding claim 15, Wells discloses 15. The method of claim 13, wherein the sensor data comprises data from an accelerometer of the PMV. ([0018])
Regarding claim 16, Wells discloses a non-transitory computer-readable medium comprising a series of instructions to perform a method. ([0035], [0036])
The remainder of claim 16 is rejected as claim 1.
Claims 17 is rejected as claim 2.
Claim 18 is rejected as claim 4.
Claim 19 is rejected as claim 5.
Regarding claim 20, Wells discloses obtaining, by the server or the application on a user device, sensor data from one or more sensors of the parked PMV ([0017], [0018]); inputting, by the server or the application on the user device, the sensor data into the machine learning model ([0019]); and wherein determining whether the PMV satisfies the one or more parking rules includes determining, by the server or the application, based on the sensor data and the image, whether the PMV is in an upright position ([0018], [0032]).
7. Claim 9 is rejected under 35 U.S.C. 103 as being unpatentable over Wells in view of Liu et al. (US 2020/0279489 A1).
Regarding claim 9, Wells discloses a machine learning model is trained on a dataset of images depicting parked vehicles in various orientations ([0019], [0020]).
Wells does not disclose a convolutional neural network.
Liu, addressing the same problem of how to configure a machine learning model for application to parking a vehicle, teaches a method, system, and computer program for determining the location of a parked vehicle using video and vehicle sensor analysis ([0001]), wherein the method comprises a convolutional neural network ([0031]) for the benefit of generating a trained parking scene recognition model that determines if a vehicle is in a parking scene or not ([0031]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the application to have combined the teachings of Liu with the method of Wells because that would have enabled the method to generate a trained parking scene recognition model that determines if a vehicle is in a parking scene or not.
Conclusion
8. Any inquiry concerning this communication or earlier communications from the examiner should be directed to JOHN F MORTELL whose telephone number is (571)270-1873. The examiner can normally be reached Monday - Friday 10-7 ET.
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/JOHN F MORTELL/Primary Examiner, Art Unit 2689