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 .
Specification
In the next communication, please update the information under CROSS-REFERENCE TO RELATED APPLICATIONS (paragraph [0001]) to include the updated U.S. Patent No. 12,230,136 for U.S. Patent Application No. 17/572,528; U.S. Patent No. 11,222,537 for U.S. Patent Application No. 16/923,996; and U.S. Patent No. 10,789,846 for U.S. Patent Application No. 16/823,849.
Double Patenting
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.
Claims 1-20 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-20 of U.S. Patent No. 12,230,136 and over claims 1-20 of U.S. Patent No. 11,222,537. Although the claims at issue are not identical, they are not patentably distinct from each other because they all claimed the same subject matter. See mapping below.
Instant Application
US Pat. No.12,230,136
US Pat. No. 11,222,537
1. A computer-implemented method for performing presence detection within a defined area, comprising: receiving a live digital input corresponding to a monitored area within a building environment and its associated premises; detecting a human in the live digital input using a trained machine learning model; identifying a file digital item associated with the detected human by comparing the live digital input to one or more file digital items within a list of digital items, wherein the identifying includes determining that the identity of the human in the file digital item is the same as the identity of the live digital input; and displaying, in a graphical user interface, a representation of the monitored area, including a person indicator corresponding to the identified human.
1. A computer-implemented method for performing room presence detection, comprising: receiving
a live digital image corresponding to a room in a building; detecting a human in the live digital image using a trained machine learning model; identifying a file digital image corresponding to the human by comparing the live digital image to one or more file digital images within a list of digital images, wherein the identifying includes determining that the identity of the human in the file digital image is the same as the identity of the live digital image; and displaying, in a graphical user interface, a room map corresponding to the room including a person indicator corresponding to the identified human.
1. A computer-implemented method for performing room presence detection, comprising: receiving
a live photograph corresponding to a room in a building, detecting a human in the live photograph using a trained machine learning model, identifying a file photograph corresponding to the human by comparing the live photograph to one or more file photographs within a list of photographs; and
displaying, in a graphical user interface, a room map
corresponding to the room including a person indicator corresponding to the identified human.
2. The computer-implemented method of claim 1, wherein displaying the representation of the monitored area includes receiving, via the graphical user interface, a selection of a user corresponding to the representation of the monitored area within the building and its associated premises.
2. The computer-implemented method of claim 1, wherein displaying the room map includes receiving, via the graphical user interface, a selection of a user corresponding to the room map room of the building.
2. The computer-implemented method of claim 1, wherein displaying the room map
includes receiving, via the graphical user interface, a selection of a user corresponding to the room map room of the building.
3. The computer-implemented method of claim 1, wherein detecting the human in the live digital input includes detecting activity associated with human presence and motion in the live digital input
3. The computer-implemented method of claim 1, wherein detecting the human in the live digital image includes detecting motion in the digital image.
3. The computer-implemented method of claim 1, wherein detecting the human in
the live photograph includes detecting motion in the photograph.
4. The computer-implemented method of claim 1, wherein identifying the file digital item associated with the human by comparing the live digital input to one or more file digital items includes searching the one or more file digital items in a priority order.
4. The computer-implemented method of claim 1, wherein identifying the file digital image corresponding to the human by comparing the live digital image to one or more file digital images includes searching the one or more file digital images in a priority order.
4. The computer-implemented method of claim 1, wherein identifying a file photograph corresponding to the human by comparing the live photograph to one or more file photographs includes searching the one or more file photographs in a priority order.
5. The computer-implemented method of claim 1, further comprising: counting the number of humans in the monitored area and storing the count in an electronic database.
5. The computer-implemented method of claim 1, further comprising: counting the number of humans in the room and storing the count in an electronic database.
5. The computer-implemented method of claim 1, further comprising:
counting the number of humans in the room and storing the count in an electronic database.
6. The computer-implemented method of claim 1, further comprising: in response to receiving, via the graphical user interface, a selection of the person indicator, displaying, via the graphical user interface, the identity of the identified human in proximity to the person indicator.
6. The computer-implemented method of claim 1, further comprising: in response to receiving, via the graphical user interface, a selection of the person indicator, displaying, via the graphical user interface, the identity of the identified human in proximity to the person indicator.
6. The computer-implemented method of claim 1, further comprising: in response to receiving, via the graphical user interface, a selection of the person indicator, displaying, via the graphical user interface, the identity of the identified human in proximity to the person indicator.
7. The computer-implemented method of claim 1, further comprising: displaying, via the graphical user interface, statuses or operational information of one or more devices, systems, or resources within the monitored area
7. The computer-implemented method of claim 1, further comprising: displaying, via the graphical user interface, a status of one or more telephone devices within the room.
7. The computer-implemented method of claim 1, further comprising: displaying, via the graphical user interface, a status of one or more telephone devices
within the room.
8. A room presence computing system, comprising: one or more processors; and a memory storing instructions that, when executed by the one or more processors, cause the system to: receive a live digital input corresponding to the monitored area within a building environment and its associated premises; detect a human in the live digital input using a trained machine learning model; identify a file digital item associated with the human by comparing the live digital input to one or more file digital items within a list of digital items, wherein the identifying includes determining that the identity of the human in the file digital item is the same as the identity of the live digital input; and displaying, in a graphical user interface, a representation of the monitored area, including a person indicator corresponding to the identified human.
8. A room presence computing system, comprising: one or more processors; and a memory storing instructions that, when executed by the one or more processors,
cause the system to:
receive a live digital image corresponding to a room in a building;
detect a human in the live digital image using a trained machine learning model;
identify a file digital image corresponding to the human by comparing the live
digital image to one or more file digital images within a list of digital images, by
determining that the identity of the human in the file digital image is the same as the
identity of the live digital image; and
display, in a graphical user interface, a room map corresponding to the room
including a person indicator corresponding to the identified human.
8. A room presence computing system, comprising: one or more processors; and a memory storing instructions that, when executed by the one or more processors,
cause the system to:
receive a live photograph corresponding to a room in a building,
detect a human in the live photograph using a trained machine learning model,
identify a file photograph corresponding to the human by comparing the live photograph
to one or more file photographs within a list of photographs; and
display, in a graphical user interface, a room map corresponding to the room including a person indicator corresponding to the identified human.
9. The room presence computing system of claim 8, the memory storing further instructions that, when executed by the one or more processors, cause the system to: receive, via the graphical user interface, a selection of a user corresponding to the representation of the monitored area within the building and its associated premises.
9. The room presence computing system of claim 8, the memory storing further instructions that, when executed by the one or more processors, cause the system to:
receive, via the graphical user interface, a selection of a user corresponding to the room map room of the building.
9. The room presence computing system of claim 8, the memory storing further instructions that, when executed by the one or more processors, cause the system to:
receive, via the graphical user interface, a selection of a user corresponding to the room map room of the building.
10. The room presence computing system of claim 8, the memory storing further instructions that, when executed by the one or more processors, cause the system to: detect activity associated with human presence and motion in the live digital input.
10. The room presence computing system of claim 8, the memory storing further instructions that, when executed by the one or more processors, cause the system to: detect motion in the digital image.
10. The room presence computing system of claim 8, the memory storing further instructions that, when executed by the one or more processors, cause the system to: detect motion in the photograph.
11. The room presence computing system of claim 8, the memory storing further instructions that, when executed by the one or more processors, cause the system to: search the one or more file digital items in a priority order.
11. The room presence computing system of claim 8, the memory storing further instructions that, when executed by the one or more processors, cause the system to: search the one or more file digital images in a priority order.
11. The room presence computing system of claim 8, the memory storing further instructions that, when executed by the one or more processors, cause the system to: search the one or more file photographs in a priority order.
12. The room presence computing system of claim 8, the memory storing further instructions that, when executed by the one or more processors, cause the system to: count the number of humans in the monitored area and store the count in an electronic database.
12. The room presence computing system of claim 8, the memory storing further instructions that, when executed by the one or more processors, cause the system to: count the number of humans in the room and store the count in an electronic database.
12. The room presence computing system of claim 8, the memory storing further instructions that, when executed by the one or more processors, cause the system to: count the number of humans in the room and store the count in an electronic database.
13. The room presence computing system of claim 8, the memory storing further instructions that, when executed by the one or more processors, cause the system to: receive, via the graphical user interface, a selection of the person indicator; and display, via the graphical user interface, the identity of the identified human in proximity to the person indicator.
13. The room presence computing system of claim 8, the memory storing further instructions that, when executed by the one or more processors, cause the system to: receive, via the graphical user interface, a selection of the person indicator; and display, via the graphical user interface, the identity of the identified human in proximity to the person indicator.
13. The room presence computing system of claim 8, the memory storing further instructions that, when executed by the one or more processors, cause the system to:
receive, via the graphical user interface, a selection of the person indicator; and display, via the graphical user interface, the identity of the identified human in proximity
to the person indicator.
14. The room presence computing system of claim 8, the memory storing further instructions that, when executed by the one or more processors, cause the system to: display, via the graphical user interface, statuses or operational information of one or more devices, systems, or resources within the monitored area.
14. The room presence computing system of claim 8, the memory storing further instructions that, when executed by the one or more processors, cause the system to: display, via the graphical user interface, a status of one or more telephone devices within the room.
14. The room presence computing system of claim 8, the memory storing further instructions that, when executed by the one or more processors, cause the system to: displaying, via the graphical user interface, a status of one or more telephone devices
within the room.
15. A non-transitory computer readable medium containing program instructions that when executed, cause a computer to: receive a live digital input corresponding to a monitored area within a building environment and its associated premises; detect a human in the live digital input using a trained machine learning model; identify a file digital image associated with by comparing the live digital input to one or more file digital items within a list of digital items, wherein the identifying includes determining that the identity of the human in the file digital item is the same as the identity of the live digital input; and display, in a graphical user interface, a representation of the monitored area, including a person indicator corresponding to the identified human.
15. A non-transitory computer readable medium containing program instructions that when executed, cause a computer to: receive a live digital image corresponding to a room in a building; detect a human in the live digital image using a trained machine learning model; identify a file digital image corresponding to the human by comparing the live digital image to one or more file digital images within a list of digital images, by determining that the identity of the human in the file digital image is the same as the identity of the live digital image; and display, in a graphical user interface, a room map corresponding to the room including a person indicator corresponding to the identified human.
15. A non-transitory computer readable medium containing program instructions that
when executed, cause a computer to: receive a live photograph corresponding to a room in a building,
detect a human in the live photograph using a trained machine learning model,
identify a file photograph corresponding to the human by comparing the live photograph
to one or more file photographs within a list of photographs; and
display, in a graphical user interface,
a room map corresponding to the room including a
person indicator corresponding to the identified human.
16. The non-transitory computer readable medium of claim 15 storing further program instructions that when executed, cause the computer to: receive, via the graphical user interface, a selection of a user corresponding to the representation of the monitored area within the building and its associated premises.
16. The non-transitory computer readable medium of claim 15
storing further program instructions that when executed, cause the computer to:
receive, via the graphical user interface, a selection of a user corresponding to the room map room of the building.
16. The non-transitory computer readable medium of claim 15 storing further program instructions that when executed, cause a computer to:
receive, via the graphical user interface, a selection of a user corresponding to the room map room of the building.
17. The non-transitory computer readable medium of claim 15 storing further program instructions that when executed, cause the computer to: detect activity associated with human presence and motion in the live digital input.
17. The non-transitory computer readable medium of claim 15
storing further
program instructions that when executed, cause the computer to:
detect motion in the digital image.
17. The non-transitory computer readable medium of claim 15 storing further program instructions that when executed, cause a computer to: detect motion in the photograph.
18. The non-transitory computer readable medium of claim 15 storing further program instructions that when executed, cause the computer to: search the one or more file digital items in a priority order.
18. The non-transitory computer readable medium of claim 15
storing further program instructions that when executed, cause the computer to: search the one or more file digital images in a priority order.
18. The non-transitory computer readable medium of claim 15 storing further program instructions that when executed, cause a computer to: search the one or more file photographs in a priority order.
19. The non-transitory computer readable medium of claim 15 storing further program instructions that when executed, cause the computer to: count the number of humans in the monitored area and store the count in an electronic database.
19. The non-transitory computer readable medium of claim 15
storing further
program instructions that when executed, cause the computer to:
count the number of humans in the room and store the count in an electronic database.
19. The non-transitory computer readable medium of claim 15 storing further program instructions that when executed, cause a computer to: count the number of humans in the room and store the count in an electronic database.
20. The non-transitory computer readable medium of claim 15 storing further program instructions that when executed, cause the computer to: receive, via the graphical user interface, a selection of the person indicator; and display, via the graphical user interface, the identity of the identified human in proximity to the person indicator.
20. The non-transitory computer readable medium of claim 15
storing further
program instructions that when executed, cause the computer to: receive, via the graphical user interface, a selection of the person indicator; and display, via the graphical user interface, the identity of the identified human in proximity to the person indicator.
20. The non-transitory computer readable medium of claim 15 storing further program instructions that when executed, cause a computer to: receive, via the graphical user interface, a selection of the person indicator; and display, via the graphical user interface, the identity of the identified human in proximity to the person indicator.
Response to Arguments
Applicant state that a terminal disclaimer is submit herewith in the Applicant Arguments/Remarks filed on 06/11/2026; however, the terminal disclaimer was not formally submitted.
Conclusion
THIS ACTION IS MADE FINAL. 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 TOAN NGOC PHAM whose telephone number is (571)272-2967. The examiner can normally be reached M - F (7 AM - 3:30 PM).
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Quan-Zhen Wang can be reached at (571) 272-3114. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/TOAN N PHAM/Primary Examiner, Art Unit 2685 7/23/26
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