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 .
Claim 1-20 are pending for examination.
Double Patenting
The non-statutory 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 non-statutory 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 non-statutory 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 non-statutory 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 non-statutory double patenting as being unpatentable over claims 1-20 of U.S. Patent No. 12273420. Although the claims at issue are not identical, they are not patentably distinct from each other because they are substantially similar in scope, recite analogous limitations, and they achieve the same overall result. The claim limitations of the instant application are anticipated by the reference US Patent no. 12273420.
The table below shows comparison between the instant application and the reference US Patent claims.
Instant application 19/064,461
US Patent no. 12273420
Claim 1. A method, comprising: determining a unique broadcasting signature of a room based on audio qualities of the room and a visual fingerprint of the room;
determining an optimal location in the room for an endpoint device based on the unique broadcasting signature of the room; and
transmitting a notification to the endpoint device that indicates the optimal location in the room.
Claim 1. A method…comprising: … determining a unique broadcasting signature of the room based on the diagnostic output, the diagnostic output comprising audio qualities of the room and a visual fingerprint of the room based on one or more identified objects in the visual recordings;
determining an optimal location in the room for the personal endpoint device based on the unique broadcasting signature of the room; and
transmitting a notification to the personal endpoint device that indicates the optimal location in the room.
Claim 2. The method of claim 1, further comprising: authenticating the endpoint device with respect to a single user account of a video communication platform.
Claim 2. The method of claim 1, further comprising: authenticating the personal endpoint device with respect to a single user account of a video communication platform.
Claim 3. The method of claim 1, further comprising: receiving diagnostic output from the endpoint device.
Claim 3. The method of claim 1, wherein receiving diagnostic output from the personal endpoint device comprises performing one or more diagnostic operations.
Claim 4. The method of claim 3, wherein determining the unique broadcasting signature of the room comprises processing the diagnostic output.
Claim 4. The method of claim 1, wherein determining the unique broadcasting signature of the room comprises processing the diagnostic output
Claim 5. The method of claim 1, further comprising: determining whether an existing optimal settings configuration is detected for the room based on the unique broadcasting signature of the room, and
configuring one or more parameters of the endpoint device based on the existing optimal settings configuration when an optimal settings configuration is detected.
Claim 5. The method of claim 1, further comprising: determining whether an existing optimal settings configuration can be detected for the room based on the unique broadcasting signature of the room, and
configuring one or more parameters of the personal endpoint device based on the existing optimal settings configuration when an optimal settings configuration is detected.
Claim 6. The method of claim 1, further comprising: determining whether an existing optimal settings configuration is detected for the room based on the unique broadcasting signature of the room; and
storing a configuration of one or more parameters of the endpoint device for future video communication in the room when the existing optimal settings configuration is not detected.
Claim 6. The method of claim 1, further comprising: determining whether an existing optimal settings configuration can be detected for the room based on the unique broadcasting signature of the room; and
storing a configuration of one or more parameters of the personal endpoint device for future video communication in the room when the existing optimal settings configuration is not detected.
Claim 7. The method of claim 1, further comprising: connecting the endpoint device to one or more additional endpoint devices over a network.
Claim 7. The method of claim 1, wherein identifying the personal endpoint device comprises communicatively connecting the personal endpoint device to one or more additional endpoint devices over a network.
Claim 8. The method of claim 1, further comprising: determining, beyond a confidence threshold, a match similarity of the room to an additional room based on at least audio and visual qualities of the additional room; and
dynamically configuring one or more parameters of the endpoint device based on a unique broadcasting signature of the additional room.
Claim 8. The method of claim 1, further comprising: determining, beyond a confidence threshold, a match similarity of the room to an additional room based on at least audio and visual qualities of the additional room; and
dynamically configuring one or more parameters of the personal endpoint device based on a unique broadcasting signature of the additional room.
Claim 9. The method of claim 1, further comprising: training one or more artificial intelligence (AI) engines on a dataset comprising various configurations of endpoint devices within rooms of differing unique broadcasting signatures; and
configuring one or more parameters of the endpoint device based on the unique broadcasting signature is executed by the one or more AI engines.
Claim 9. The method of claim 1, further comprising: training one or more artificial intelligence (Al) engines on a dataset comprising various configurations of personal endpoint devices within rooms of differing unique broadcasting signatures; and configuring one or more parameters of the personal endpoint device based on the unique broadcasting signature is executed by the one or more Al engines.
Claim 10. The method of claim 1, further comprising: detecting one or more changes to the room that alter the unique broadcasting signature of the room;
adjusting one or more parameters of the endpoint device to account for the changes to the room; and
storing the adjusted one or more parameters for future video communication in the room.
Claim 10. The method of claim 9, wherein configuring one or more parameters of the personal endpoint device based on the unique broadcasting signature comprises: detecting one or more changes to the room that alter the unique broadcasting signature of the room;
adjusting one or more parameters of the personal endpoint device to account for the changes to the room; and
storing the adjusted one or more parameters for future video communication in the room.
Claim 11. The method of claim 1, wherein one or more steps are performed in real time upon the endpoint device being identified within the room.
Claim 11. The method of claim 1, wherein one or more steps are performed in real time upon the personal endpoint device being identified within the room.
Claims 12-20 correspond to Claims 12-20 of U.S. Patent No. 12273420.
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, 3, 4, 7, 11, 12, 16 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over US 2015/0350769 (Sun et al.) in view of US 9973732 (Goetz).
Regarding Claim 1, Sun teaches a method, comprising: determining a unique broadcasting signature of a room based on audio qualities of the room… ([¶ 0002] …the sound pick-up range for the microphone depends on acoustic characteristics of the room. [¶¶ 0017-0018] Microphones best capture sound from a given one of participants if the position of the participant falls within a best sound pick-up range of the microphone, … automatically determine …the best region for microphones. [¶ 0033], determine the best region based on additional microphone-related parameters, such as voice tracking parameters and/or spatial filtering parameters. [¶ 0059], determine the best range of a microphone associated with the endpoint based on the determined Critical Distance Dc. [¶ 0062], plays a test sound signal from loudspeaker. …verified by observing a captured signal level, a signal-to-noise-ratio (SNR), or a cross-correlation between the test signal and the captured signal. [¶¶ 0068-0069] measure impulse responses of room using microphone and loudspeaker(s); estimate a reverberation time of the room, RT, using the measured impulse responses; estimate a volume of the room, V, using the measured impulse responses; …Estimates of the volume V may also be made based on reverberant speech signals, or by scanning room using camera and calculating the volume based on captured images of the scanned room. …determines an acoustic pick-up range, i.e., best sound pick-up range, for microphones based on known characteristics of the microphones and the determined Critical Distance Dc. Note: Since, Sun teaches “measure impulse responses of room”, “a reverberation time of the room”, “a volume of the room”, and “the Critical Distance Dc”. Therefore, an ordinary skill in the art would understood, Sun’s collection of room acoustic characteristics reasonably corresponds to the claimed “unique broadcasting signature of a room”);
determining an optimal location in the room for an endpoint device based on the unique broadcasting signature of the room ([¶ 0001], techniques to assist with optimal placement of participants relative to microphones of a video conference endpoint. [¶ 0013], determine, …an optimal or best sound source placement region, i.e., a "best region," [i.e., optimal location in the room] relative to one or more microphones of a video conference endpoint. [¶ 0034], determines the position and the size of the best region based on a room critical distance Dc.[ ¶ 0059] For any given room there exists a distance at which intensities of direct sound from a talking participant and reverberant sound are equal. In the field of room acoustics, this distance is defined as the Critical Distance Dc); and transmitting a notification to the endpoint device that indicates the optimal location in the room ([¶ 0018], determine and then display the best region for microphones in the self-view mode. This gives participants visual feedback as to where they are positioned in relation to the best region; the participants can move to the best region as displayed if they are not already in that region. [¶ 0072], Once the best region has been determined, …generates and displays the best region on display in the self-view mode … FIG. 11, …displays best region 1105 as a hemispherical best region image).
While Sun determines the best region for participant of video conference in a room based on acoustic characteristics of the room, however, Sun does not explicitly teach, but Goetz teaches determining a unique broadcasting signature of a room based on …a visual fingerprint of the room ([C.7:L.14-22], the user locator component 134 can receive data from one or more imaging devices to determine a layout of a zone or room [i.e., visual fingerprint of the room], and/or to determine which devices are in a zone and where they are located. …the user locator component 134 can receive data from one or more sensors capable of providing an audio signal to facilitate locating a user. [C.18:L.41-53] analyzing image data, for example, received from one or more imaging devices to determine an optimal view of persons represented in the image data. …can include utilizing one or more machine learning algorithms to determine an optimal view of a user designated as a person of interest for a conversation).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate Goetz’s image-based room layout determination into Sun’s acoustically based placement technique to supplement the room acoustic characteristics with visual information of the room, thereby enabling more robust and reliable determination of optimal endpoint placement and improving the user experience during video conferencing.
Regarding Claim 3, Sun teaches the method of claim 1, further comprising: receiving diagnostic output from the endpoint device ([¶ 0002], A video conference endpoint includes a microphone to capture sound from a participant in a room and then the endpoint transmits the captured sound to a conference server or another endpoint. [¶ 0033], determined best region results from beam forming of transduced sound signals from microphones based on initial beam forming parameters. …determines best region based on beam forming parameters. Controller may determine the best region based on additional microphone-related parameters, such as voice tracking parameters and/or spatial filtering parameters. [¶ 0062], endpoint plays a test sound signal from loudspeaker. …a microphone …captures the test signal. This may be verified by observing a captured signal level, a signal-to-noise-ratio (SNR), or a cross-correlation between the test signal and the captured signal. [¶ 0081] All of the embodiments described, may be integrated with different operational modes of the endpoint, including … a diagnostics mode).
Regarding Claim 4, Sun teaches the method of claim 3, wherein determining the unique broadcasting signature of the room comprises processing the diagnostic output ([¶ 0033], determine the best region based on additional microphone-related parameters, such as voice tracking parameters and/or spatial filtering parameters. [¶ 0059], determine the best range of a microphone associated with the endpoint based on the determined Critical Distance Dc. [¶ 0062], plays a test sound signal from loudspeaker. …verified by observing a captured signal level, a signal-to-noise-ratio (SNR), or a cross-correlation between the test signal and the captured signal. [¶¶ 0068-0069] measure impulse responses of room using microphone and loudspeaker(s); estimate a reverberation time of the room, RT, using the measured impulse responses; estimate a volume of the room, V, using the measured impulse responses; …Estimates of the volume V may also be made based on reverberant speech signals, or by scanning room using camera and calculating the volume based on captured images of the scanned room. …determines an acoustic pick-up range, i.e., best sound pick-up range, for microphones based on known characteristics of the microphones and the determined Critical Distance Dc. [¶ 0081] All of the embodiments described, may be integrated with different operational modes of the endpoint, including … a diagnostics mode).
Regarding Claim 7, Sun teaches the method of claim 1, further comprising: connecting the endpoint device to one or more additional endpoint devices over a network ([Fig. 1, ¶ 0014], Video conference environment 100 includes video conference endpoints 104 operated by local users/participants 106 and configured to establish audio-visual teleconference collaboration sessions with each other over a communication network 110).
Regarding Claim 11, Sun teaches the method of claim 1, wherein one or more steps are performed in real time upon the endpoint device being identified within the room ([¶ 0013] Sun teaches techniques for determine, display, and adjust an optimal or best sound source placement region. [¶ 0034], controller initially determines the position and the size of the best region based on a room critical distance Dc. [¶ 0065], camera/image based object-detection techniques may employed for active microphone localization. …endpoint may detect table microphone using object-detection. …verify the active microphone position obtained from triangulation. Combining object detection and triangulation yields more reliable microphone position estimation. [¶ 0072] Once the best region has been determined, controller generates and displays the best region on display. Note: Since, Sun teaches dynamically determining, displaying, and adjusting a best region during conferencing based on identified microphone position and room characteristics, therefore, it would be realized that such operation are performed in real time upon identification of the endpoint within the room.
Regarding Claim 12, the claim limitations are identical and/or equivalent in scope to claim 1, therefore Claim 12 is rejected under the same rationale as claim 1. Examiner further notes, Sun also teaches a communication system, comprising: one or more processors…. (See Sun ¶¶ 0028-0029)
Regarding Claim 16, Sun teaches the communications system of claim 12, wherein a communicatively connected central controller is configured to identify the endpoint device within the room and communicatively connect to the personal endpoint device ([¶ 0028], FIG. 4, which shows an example block diagram of a controller 408 of video conference endpoint 104 configured to perform the techniques. [¶ 0034], controller 408 initially determines the position and the size of the best region based on a room critical distance Dc. [¶ 0068], the Critical Distance Dc may be determined automatically, which includes operations to: measure impulse responses of room 204 using microphone 118(3) and loudspeaker(s) 116; estimate a reverberation time of the room, RT, using the measured impulse responses; estimate a volume of the room, V, using the measured impulse responses; and then determine the Critical Distance Dc).
Regarding Claim 20, the claim limitations are identical and/or equivalent in scope to claim 1, therefore Claim 12 is rejected under the same rationale as claim 1. Examiner further notes, Sun also teaches a non-transitory computer-readable medium containing instructions that when executed by a processor, cause the processor to perform operations …. (See, Sun ¶ 0085)
Claim 2 is rejected under 35 U.S.C. 103 as being unpatentable over the combination of Sun and Goetz, and further in view of US 10027926 (Schirdewahn et al.).
Regarding Claim 2, Sun in view of Goetz do not explicitly teach, however, Schirdewahn teaches the method of claim 1, further comprising: authenticating the endpoint device with respect to a single user account of a video communication platform ([C.14:L.29-32] upon detection of a mobile device within a proximity of a video conference endpoint and authentication of the mobile device at a server managing the video conference endpoint).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate Schirdewahn’s teachings of authenticate user device for video conferencing with the combined teachings of Sun and Goetz, because such incorporation would have ensured security and preventing unauthorize device to join the conference.
Claims 5, 6, 10, 14, 15 and 18 are rejected under 35 U.S.C. 103 as being unpatentable over the combination of Sun and Goetz, and further in view of US 2016/0277242 (Sallam et al.).
Regarding Claim 5, Sun in view of Goetz do not explicitly teach, however, Sallam teaches the method of claim 1, further comprising: determining whether an existing optimal settings configuration is detected for the room based on the unique broadcasting signature of the room, and configuring one or more parameters of the endpoint device based on the existing optimal settings configuration when an optimal settings configuration is detected ([¶ 0066] when a user joins a new online meeting, an online meeting engine of the online meeting server equipment customizes available user I/O devices based on the user behavior model [i.e., implicitly existing optimal settings] for that user. …the online meeting engine communicates with the behavior engine to refer to the user behavior model for that user and, based on the user's current location, automatically activates and configures the available user I/O devices on behalf of the user to convey user I/O between that user and other users participating in the current online meeting).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate Sallam’s teachings of using existing model to configure devices for an online meeting with the combined teachings of Sun and Goetz, because such incorporation would have allowed a custom/optimized online meeting environment without extensive configuration time and effort (Sallam, ¶ 0066).
Regarding Claim 6, Sun in view of Goetz do not explicitly teach, however, Sallam teaches the method of claim 1, further comprising: determining whether an existing optimal settings configuration is detected for the room based on the unique broadcasting signature of the room; and storing a configuration of one or more parameters of the endpoint device for future video communication in the room when the existing optimal settings configuration is not detected ([¶¶ 0056, 0061], whenever user participates in an online meeting from the corner conference room. Accordingly, the online meeting server equipment updates a user behavior model so that when that user participates in an online meeting from the corner conference room in the future, the online meeting server equipment automatically activates. …The configuration data which is collected and used to conduct the online meetings is stored in the set of online meeting databases).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate Sallam’s teachings of store room specific configuration of devices for an online meeting with the combined teachings of Sun and Goetz, because such incorporation would have allowed a custom/optimized online meeting environment without extensive configuration time and effort (Sallam, ¶ 0066).
Regarding Claim 10, Sun in view of Goetz do not explicitly teach, however, Sallam teaches the method of claim 1, further comprising: detecting one or more changes to the room that alter the unique broadcasting signature of the room; adjusting one or more parameters of the endpoint device to account for the changes to the room ([¶ 0023], acquiring new configuration data from the plurality of user I/O devices during the current online meeting…updating the user behavior model for the particular user and the other user behavior models for the other users based on the new configuration data acquired from the plurality of user I/O devices during the current online meeting. [¶ 0077], …periodically updates user behavior models by applying predictive analytics to the configuration data in the configuration database so that the models accurately reflect user preferences for future online meetings. [¶ 0096], the online meeting system adjusts camera settings based on a participant's user location. In particular, such adjustment can be based on the direction of light coming from room window (e.g., as identified by a camera in the vicinity, weather, time of day, combinations thereof, etc.) and where user's computer and chair resides. Once the system captures this knowledge, the system is able to configure the camera settings in a similar manner during future online meetings); and storing the adjusted one or more parameters for future video communication in the room ([¶ 0061], The configuration data which is collected and used to conduct the online meetings is stored in the set of online meeting databases).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate Sallam’s teachings of updating user behavior model for new configuration of devices and store the updated model for future use with the combined teachings of Sun and Goetz, because such incorporation would have been a predictable enhancement, enabling the endpoint to learn from prior session and automatically apply improved configuration when the user return to the room.
Regarding Claim 14, Sun teaches the communications system of claim 12, wherein the one or more processors are further configured to: communicatively connect the endpoint device to one or more additional endpoint devices within the room ([Fig. 1, Fig. 2, ¶ 0015] illustrates video conference endpoint include a video camera (VC) 112, a video display 114, a loudspeaker (LDSPKR) 116, and one or more microphones (MIC) 118, which may include a combination of one or more microphone arrays and one or more individual microphones. … includes spaced-apart microphone arrays 118(1) and 118(2) integrated with display 114 and a remote microphone 118(3) resting on table 206. Microphone 118(3) may be connected wirelessly or through a wired connection with endpoint 104); …dynamically adjust one or more parameters of the endpoint device ([¶ 0013] Sun teaches techniques to determine, display, and adjust an optimal or best sound source placement region).
However, Sun in view of Goetz do not explicitly teach, however, Sallam teaches detect an existing optimal settings configuration for audiovisual output quality for a pairing of the endpoint device to at least one of the additional endpoint devices; and dynamically adjust one or more parameters of the endpoint device to match the existing optimal settings configuration for audio and visual output quality of the pairing of the devices ([¶¶ 0082-0083], if a particular user is in a room for an online meeting with multiple user I/O devices available, the online meeting server equipment is able to automatically select and configure the most preferred devices based on the user's historical use of the devices [i.e., implicitly an existing optimal settings]… if there are newly discovered user I/O devices which are superior to the existing user I/O devices listed, the online meeting server equipment can be configured to suggest or offer those newly discovered devices to the user for future online meetings).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate Sallam’s teachings of automatically selecting and configuring preferred user I/O devices based on historical use of devices with the conferencing system of Sun and Goetz, because such incorporation would have predictably enabled automatic retrieval and application of existing configuration and preferences, thereby improving audiovisual quality, reducing setup time, and providing a more seamless conferencing experience.
Regarding Claim 15, Sun in view of Goetz do not explicitly teach, however, Sallam teaches the communications system of claim 12, wherein the one or more processors are further configured to: receive a selection of an automatable behavior to be performed with the room upon identifying the endpoint device within the room and beginning a video communication session; and store the selection of the automatable behavior to be automatically performed at a future session within the room upon the endpoint device being identified ([¶¶ 0055-0056], via predictive analytics, the online meeting server equipment creates an electronic understanding of the user I/O devices that each user prefers to use when participating in online meetings within the layout. In particular, for each user, the online meeting server equipment computes the frequency of use of each user I/O device which is available to that user when the user is in particular locations within the layout. Accordingly, the online meeting server equipment is able to operate as a behavioral engine to automatically activate and configure the user I/O devices which are most popular or best suited to each user. For instance, one user may routinely connect the smart television whenever that user participates in an online meeting from the corner conference room. Accordingly, the online meeting server equipment updates a user behavior model so that when that user participates in an online meeting from the corner conference room in the future, the online meeting server equipment automatically activates the smart television and joins that smart television to the online meeting. [¶ 0061], The configuration data which is collected and used to conduct the online meetings is stored in the set of online meeting databases).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate Sallam’s teachings of automatically selecting and configuring preferred user I/O devices which are most popular or best suited to each user with the conferencing system of Sun and Goetz, because such incorporation would have predictably enabled automatic retrieval and application of existing configuration and preferences, thereby improving audiovisual quality, reducing setup time, and providing a more seamless conferencing experience.
Regarding Claim 18, Sun in view of Goetz do not explicitly teach, however, Sallam teaches the communications system of claim 12, wherein the one or more processors are further configured to: determine one or more routine behaviors of a user account with respect to video communication sessions conducted with the endpoint device within the room; and configure one or more parameters of the endpoint device based on the routine behaviors ([¶¶ 0055-0056], via predictive analytics, the online meeting server equipment creates an electronic understanding of the user I/O devices that each user prefers to use when participating in online meetings within the layout. In particular, for each user, the online meeting server equipment computes the frequency of use of each user I/O device which is available to that user when the user is in particular locations within the layout. Accordingly, the online meeting server equipment is able to operate as a behavioral engine to automatically activate and configure the user I/O devices which are most popular or best suited to each user. For instance, one user may routinely connect the smart television whenever that user participates in an online meeting from the corner conference room. Accordingly, the online meeting server equipment updates a user behavior model so that when that user participates in an online meeting from the corner conference room in the future, the online meeting server equipment automatically activates the smart television and joins that smart television to the online meeting).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate Sallam’s teachings of using a user behavior model to setup devices for an online meeting into the conferencing system of Sun and Goetz, because such incorporation would have predictably enabled automatic retrieval and application of existing configuration and preferences, thereby improving audiovisual quality, reducing setup time, and providing a more seamless conferencing experience.
Claims 8 and 13 are rejected under 35 U.S.C. 103 as being unpatentable over the combination of Sun and Goetz, and further in view of US 2005/0221844 (Trethewey et al.).
Regarding Claim 8, Sun in view of Goetz do not explicitly teach, however, Trethewey teaches the method of claim 1, further comprising: determining, beyond a confidence threshold, a match similarity of the room to an additional room based on at least audio and visual qualities of the additional room; and dynamically configuring one or more parameters of the endpoint device based on a unique broadcasting signature of the additional room ([¶¶ 0045-0047], a hysteresis threshold may be incorporated to provide a level of confidence in the selected match prior to switching location profiles. …it is determined whether the highest scoring profile exceeds the threshold. If the highest scoring profile exceeds the threshold, then …the highest scoring location profile is designated as a match. [¶¶ 0038-0039], it is determined whether a match to the current location signature has been found. If it is determined that a match has been found, …the location profile settings from the matching location profile are applied to the notebook computer).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate Trethewey’s teachings of apply matching location profile settings to the computer with the combined teachings of Sun and Goetz, because such incorporation would have improved usability and reducing setup time.
Regarding Claim 13, Sun teaches the communications system of claim 12, wherein the one or more processors are further configured to: display a room configuration interface at the personal endpoint device ([¶ 0013], generates an image representative of the best region and displays the generated image representative of the best region as an overlay of the scene image. Participants thus receive intuitive visual feedback as to where they are positioned in relation to the best region. [¶ 0072] Once the best region has been determined, controller generates and displays the best region on display).
However, Sun in view of Goetz do not explicitly teach, Trethewey teaches …the room configuration interface comprising: a first control interface configured to receive a selection of an existing settings configuration for an additional room ([¶¶ 0018-0019], dialog window for a location profiler is shown in FIG. 2. Location profiler is used to enable automatic activation of system settings based upon observed WLAN access points for a specific location. … allows a user to manually select a previously defined location profile. Add New button 208 may be used to assign a name to a new location profile. Configure button 210 may be used to bring up a radio signature dialog window 300 to enable radio signatures to be captured by the user); and a second control interface configured to adjust one or more parameters of the endpoint device ([¶ 0020] Settings section 204 comprises a Configure button 212, an Activate button 214, an Automatic activate check box 216, and a Close button 218. Configure button 212 may be used to define all of the settings that apply to a location profile. Activate button 214 allows manual activation of the settings for a location profile. Activate check box 216 allows for the immediate application of the selected settings for a location profile when the profile has been selected).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate Trethewey’s teachings of user interface that allow user to select profile, update and configure settings with the combined teachings of Sun and Goetz, because such incorporation would have allowed the user an option to update settings manually as desired.
Claim 9 is rejected under 35 U.S.C. 103 as being unpatentable over the combination of Sun and Goetz, and further in view of US 2008/0299951 (Karkanias et al.).
Regarding Claim 9, Sun in view of Goetz do not explicitly teach, however, Karkanias teaches the method of claim 1, further comprising: training one or more artificial intelligence (AI) engines on a dataset comprising various configurations of endpoint devices within rooms of differing unique broadcasting signatures; and configuring one or more parameters of the endpoint device based on the unique broadcasting signature is executed by the one or more AI engines ([¶ 0006], an opportunistic network that can facilitate resource aggregation between a group of network-connected devices where each device effectively makes its resources available to other devices within the network. …an opportunistic network of devices where a device can essentially `dock` to the network which enables access and use of resource of other devices within the network. [¶ 0009], a machine learning and reasoning (MLR) component is provided that employs a probabilistic and/or statistical-based analysis to prognose or infer an action that a user desires to be automatically performed. By way of example, MLR mechanisms can be employed to make inferences that facilitate accurate and timely `docking` decisions related to a network of devices. In a specific example, an MLR component, based upon type of activity, time of day and other contextual factors, can determine which devices to select as resource aggregation devices within the opportunistic network in order to enhance the computing experience. [¶ 0069], employ classifiers that are explicitly trained as well as implicitly trained (e.g., via observing user behavior, receiving extrinsic information). For example, SVM's are configured via a learning or training phase within a classifier constructor and feature selection module. Thus, the classifier(s) can be used to automatically learn and perform a number of functions, including but not limited to determining according to a predetermined criteria how to establish a context, which devices to deem appropriate, what connection priority should be employed, which user-specific preferences to employ, etc.).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate Karkanias’s teachings of using machine learning for context-aware device selection and configuration with the combined teachings of Sun and Goetz, because such incorporation would have been a predictable enhancement, enabling the endpoint to not only determine the best region for audio pickup but also automatically select and adjust device parameters appropriate for the detected coom context.
Claim 17 is rejected under 35 U.S.C. 103 as being unpatentable over the combination of Sun, Goetz and Sallam, and further in view of US 2021/0374391 (Jorasch et al.).
Regarding Claim 17, Sun in view of Goetz do not explicitly teach, however, Sallam teaches the communications system of claim 12, wherein the one or more processors are further configured to: store one or more of the diagnostic output, the unique broadcasting signature of the room, and the configuration of the one or more parameters of the endpoint device as historical training data within a dataset ([¶ 0053] Over time, the online meeting server equipment gathers configuration data [i.e., diagnostic output], which may include pre-recorded (historical) operational data and settings, from the various user I/O devices in order to construct a geographical awareness of the layout and the user I/O devices which are available within the layout. In particular, the online meeting server equipment is able to classify particular user I/O devices as geographically static and other user I/O devices as geographically variable. Additionally, the online meeting server equipment determines which user I/O devices are shareable among multiple users, and which are used exclusively by a single user. [¶ 0061], The configuration data which is collected and used to conduct the online meetings is stored in the set of online meeting databases. [¶ 0082], the online meeting server equipment is able to automatically select and configure the most preferred devices based on the user's historical use of the devices. [¶ 0089], the online meeting server equipment able to robustly build stateful historical recordings of user actions, activities, settings, configurations as the users engage in online meetings from different locations using different devices collaborating with different people. In particular, the online meeting server equipment applies various forms of computer analytics to predict user behaviors and automatically adjust settings, configurations, etc. of the various user I/O devices which are available to those online meetings).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate Sallam’s teachings of gathering and storing the historical configuration data of the I/O devices with the combined teachings of Sun and Goetz, because such incorporation would have been a predictable enhancement, enabling the endpoint to learn from prior session and automatically apply improved configuration when the user return to the room.
Sun in view of Goetz and Sallam do not explicitly teach, however, Jorasch teaches train one or more artificial intelligence (AI) engines for future video communication sessions within the room using the historical training data within the dataset ([¶ 0696], an Artificial Intelligence (AI) module may be trained utilizing a set of attendee data from historical meetings to predict expected metrics for upcoming meetings and suggest meeting characteristics that maximize desired metrics).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate Jorasch’s teachings of train AI model using historical data to provide meeting characteristic with the combined teachings of Sun-Goetz-Sallam, because such incorporation would have been a predictable enhancement, enabling setting up equipment for an upcoming meeting using AI model.
Claim 19 is rejected under 35 U.S.C. 103 as being unpatentable over the combination of Sun, Goetz and Sallam, and further in view of US 2020/0137175 (Ganci et al.).
Regarding Claim 19, Sun in view of Goetz do not explicitly teach, however, Sallam teaches the communications system of claim 12, wherein the one or more processors are further configured to: determine one or more routine behaviors of a user account with respect to video communication sessions conducted with the endpoint device within the room; and configure one or more parameters of the endpoint device based on the routine behaviors ([¶¶ 0055-0056], via predictive analytics, the online meeting server equipment creates an electronic understanding of the user I/O devices that each user prefers to use when participating in online meetings within the layout. In particular, for each user, the online meeting server equipment computes the frequency of use of each user I/O device which is available to that user when the user is in particular locations within the layout. Accordingly, the online meeting server equipment is able to operate as a behavioral engine to automatically activate and configure the user I/O devices which are most popular or best suited to each user. For instance, one user may routinely connect the smart television whenever that user participates in an online meeting from the corner conference room. Accordingly, the online meeting server equipment updates a user behavior model so that when that user participates in an online meeting from the corner conference room in the future, the online meeting server equipment automatically activates the smart television and joins that smart television to the online meeting), wherein the one or more routine behaviors comprises an attendance of a …video communication session with a …group of other users …and wherein the one or more parameters of the endpoint device are configured based on the routine behaviors such that one or more user behaviors are detected during the communication session which can be optimized by a settings adjustment of the endpoint device ([¶ 0066], when a user joins a new online meeting, an online meeting engine of the online meeting server equipment customizes available user I/O devices based on the user behavior model for that user. In particular, the online meeting engine communicates with the behavior engine to refer to the user behavior model for that user and, based on the user's current location, automatically activates and configures the available user I/O devices on behalf of the user to convey user I/O between that user and other users participating in the current online meeting).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate Sallam’s teachings of using a user behavior model to setup devices for an online meeting into the conferencing system of Sun and Goetz, because such incorporation would have predictably enabled automatic retrieval and application of existing configuration and preferences, thereby improving audiovisual quality, reducing setup time, and providing a more seamless conferencing experience.
Sun in view of Goetz and Sallam do not explicitly teach, however, Ganci teaches the one or more routine behaviors comprises an attendance of a recurring video communication session with a specific group of other users during a specific time (emphasis added) ([¶ 0039], analyzes a user's activity to learn a user's preferences and usage patterns over time. For example, if determines that user always turns audio off on his smartphone when entering a particular conference room at her workplace or when participating in a certain recurring meeting on her calendar, the embodiment adds the pattern to the user's device preferences, converting audio alerts to a silent format without the user's having to do so manually).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate Ganci’s teachings of learning user preference and apply that for a recurring meeting into the conferencing system of Sun and Goetz, because such incorporation would have allowed a system to automatically setup equipment for recurring online meeting based on user preference.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MOHAMMAD YOUSUF A MIAN whose telephone number is (571)272-9206. The examiner can normally be reached Monday-Friday 9am-5:30pm.
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/MOHAMMAD YOUSUF A. MIAN/Examiner, Art Unit 2457
/ARIO ETIENNE/Supervisory Patent Examiner, Art Unit 2457
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