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 .
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.
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on December 29, 2025 has been entered.
Status of Claims
This office action is in response to applicant’s amendments and remarks filed on December 29, 2025. Claims 1, 8, and 15 have been amended. Claims 6, 13, and 20 have been cancelled. Thus, Claims 1-5, 7-12, and 14-19 are presently pending.
Response to Remarks/Arguments
Applicant’s amendments and remarks, filed on December 29, 2025, with respect to the previous 35 U.S.C. 103 rejections have been fully considered and are partially persuasive as described below:
Independent Claims 1/8/15:
Regarding the statement that Li does not teach that the vehicle’s onboard electronic device can adjust an “operation instruction parameter” since “the constraining operations in Li are generated by the remote driver and then transmitted from the remote driver to the vehicle for the vehicle to implement” (Remarks, Page 11-12), the examiner respectfully disagrees. This is because Li further notes that the vehicle itself may initiate and perform the operation constraints (Paragraph n0057 of the previously attached English translation, “When the remote control operator is unable to effectively control the driving status of the remote-controlled vehicle, the remote-controlled vehicle automatically limits its speed to prevent accidents caused by high-speed driving in a state of loss of control, thus improving the safety of the remote-controlled vehicle when the network signal is poor”). The step of automatically limiting its speed is reasonably interpreted as the vehicle being configured to actively adjust an operation instruction parameter (e.g. speed) and therefore not required to be instructed by an external device.
Regarding the statement that Li does not teach proactive adjustments before a first time (Remarks, Page 8), while the examiner respectfully considers Li as including features that reasonably allow for preventative adjustments (Paragraph n0043 of the previously attached English translation describes receiving an indication of poor network quality from surrounding vehicles, e.g. from a vehicle ahead), the examiner understands the concerns for explicitly teaching a proactive adjustment based on predicted network quality. Therefore, upon further search and consideration, a new grounds of 35 U.S.C. rejection has been made in view of newly cited art Magzimof (US11618439B2).
Original claims 6/13/20:
Regarding the statement that Hande is insufficient to teach transmitting a notification message to a server because Hande’s user equipment, which is responsible for notifying the server entity regarding a change in burst rate, is not also responsible for “changing the burst rate or causing the reduction of the burst rate” (Remarks, Page 12), the examiner respectfully notes that the addressed limitation is directed towards transmitting a notification message of an adjusted parameter, and as the features for changing the plurality of traveling parameters are taught by other art, it is the examiner’s position that one cannot show non-obviousness by addressing references individually where the rejections are based on a combination of references (MPEP 2145(IV)). Nonetheless, newly cited art Magzimof has been found to additionally teach the feature for transmitting a notification message to a server, and replaces Hande to teach the subject matter.
Examiner notes that the new grounds of rejection for independent claims 1/8/15 as necessitated by the amendments are applied as shown further below.
Claim Rejections - 35 USC § 103
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 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.
Claims 1-3, 5, 7-10, 12, 14-17 and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Rosenzweig et al. (US20210281511A1; hereinafter Rosenzweig) in view of Zielinski (US20200107212A1; hereinafter Zielinski), Alalao et al. (EP3605257A1) and Magzimof et al. (US11618439B2; hereinafter Magzimof).
Regarding Claims 1, 8 and 15, Rosenzweig discloses techniques for adapting teleoperation of a vehicle (Paragraph 0102, “vehicle-controlled system 120”) based on a predicted network quality (see at least Abstract and Paragraph 0080) comprising:
(claim 1) a remote driving control method performed by an electronic device mounted on a vehicle / (claim 8) a processor and a memory, wherein the memory stores computer-executable instructions that, when executed by the processor, cause the electronic device to perform a remote driving control method / (claim 15) a non-transitory computer-readable storage medium, comprising computer-executable instructions, wherein the computer-executable instructions, when executed by a processor of an electronic device mounted on a vehicle, cause the electronic device to perform a remote driving control method (Figure 1A and Paragraph 0024, “The controlled system 120 is controlled by a teleoperator using the teleoperator system 130. In an embodiment, the controlled system 120 includes a data transmission unit (DTU) 125…the data transmission unit 125 is configured to perform one or more of the disclosed embodiments”; Paragraphs 0088-0090, “The data transmission unit 125 includes a processing circuitry 810 coupled to a memory 820, a storage 830, a network interface 840, and one or more network authorization devices 850… The instructions, when executed by the processing circuitry 810, cause the processing circuitry 810 to perform the various processes described herein”);
determining, based on the predicted information, a control policy of the vehicle at the first time (Paragraph 0084 describes a control policy based on a predicted network condition (“At S730, based on the future network condition, encoder parameters are modified. In an embodiment, the encoder parameters are modified such that a connection is maintained if and when the future network condition is present”));
adjusting a plurality of traveling parameters of the vehicle based on the control policy before the first time, wherein the plurality of traveling parameters include (i) a backhaul data parameter for controlling quality of backhaul data between the vehicle and a remote driving server (Paragraph 0086 describes adjusting a video feed based on the control policy (“At S740, a video feed is encoded according to the modified encoder parameters”); Examiner notes that adjusting data transmission between a teleoperator and a controlled system is reasonably indicative of adjusting parameters for controlling quality of backhaul data); and
controlling the vehicle to travel in the first area at the first time through remote driving in accordance with the adjusted plurality of traveling parameters (Paragraphs 0101-0102 describes the controlled system as being a vehicle remotely controlled by a teleoperator (“The network interface 940 allows the teleoperator device 130 to communicate with the data transmission unit 125 for the purpose of, for example, receiving data, sending data, and the like…The user interface devices 950 allow a user to provide inputs including, but not limited to, inputs needed for determining commands to send to the controlled system 120. As a non-limiting example, such inputs may be used to determine and send commands to control movement of a vehicle-controlled system 120”); Examiner notes that controlling a vehicle based on an adjusted video feed (Paragraph 0086) is reasonably indicative of controlling a vehicle based on adjusted traveling parameters).
While Rosenzweig further discloses features for determining prediction information (Paragraphs 0081-0082, “At S710, current network data is obtained… At S720, a predicted future network condition is determined”), Rosenzweig does not explicitly recite: obtaining prediction information of wireless network in a first area from a core network device, the prediction information indicating network quality of the wireless network in the first area at a first time when the vehicle is scheduled to travel in the first area at the first time.
Nevertheless, Zielinski teaches a method for predicting network quality (Abstract, “…method for predicting a quality of service for a communication about at least one communication link of at least one communication device”; Figure 4 and Paragraphs 0036 and 0088 describes communication device (“FIG. 4 shows a diagram illustrating an exemplary message exchange between a communication device and the apparatus for predicting a quality of service”) being associated with a vehicle (“vehicle 10”)) comprising:
obtaining prediction information of wireless network in a first area from a core network device (Paragraph 0041 describes a server sending prediction information to a vehicle (“…predicting the quality of service in the communication service prediction server and sending back a quality of service prediction response message to the communication device”); Paragraph 0082, describes the server as being a core network device (“The prediction function may be implemented in a backend server or located in the core of a mobile radio network…. A further alternative position is a communication service prediction server 220 at the core network EPC”)),
the prediction information indicating network quality of the wireless network in the first area at a first time when the vehicle is scheduled to travel in the first area at the first time (Paragraphs 0043-0049 describe how the prediction of network quality is based on at least a time and position along a planned route (“…the QoS prediction request message (QPREQ) comprises in a payload section information entries for at least a planned travel route of the communication device and the communication link capacity requirements for a service the communication device is planning to make use of, wherein the payload section may optionally include an information entry for the planned starting time…the apparatus further comprises a channel modelling prediction block that predicts a communication channel model profile which is forwarded to the QoS prediction function block…When the communication device is moving along the travel route, the channel model changes with time and position. Therefore, the best way to adapt the prediction function correspondingly is supplying the prediction function with a channel model profile comprising different channel model for different times and places”)).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the Rosenzweig invention to include a core network device for predicting a network quality, as taught by Zielinski, for the benefit of reducing computational load of a vehicle device by allowing processes to be outsourced to an external device.
However, Rosenzweig as currently modified still does not explicitly recite that the adjustable parameters may include at least: (ii) vehicle status information indicating gear information of the vehicle and speed information of the vehicle collected by sensors on the vehicle.
Nevertheless, Alalao teaches a vehicle that can variably adjust the quality of information being communicated (Paragraph 0165, “The autonomous vehicle 1304A can dynamically vary the information that is included in the request 1604 based on the quality metric associated with the network connection”) including:
vehicle status information indicating gear information of the vehicle and speed information of the vehicle collected by sensors on the vehicle (Paragraph 0164 describes the uploaded information as including vehicle information (“As an example, the request 1604 can include vehicle telemetry data, such as that described with respect to FIGS. 13-15. For instance, vehicle telemetry data can include data obtained using one or more imaging sensors (e.g., videos or images), information regarding a current condition of the autonomous vehicle (e.g., the autonomous vehicle's location, speed, altitude, and/or heading or orientation, a status of the autonomous vehicle and/or one more of its subcomponents, etc.)”); Examiner notes that subcomponents reasonably comprise gear information (see at least example devices in Paragraph 0080, “gears”)).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have further modified the Rosenzweig invention to expand the features for adjusting encoder parameters (see at least Paragraph 0086, “At S740, a video feed is encoded according to the modified encoder parameters”) to include data such as vehicle speed and subcomponent health, as taught by Alalao, for the benefit of improving effectiveness of communication (Alalao, Paragraph 0173).
However, Rosenzweig as currently modified still does not explicitly recite that the adjustable parameters may include at least: (iii) an operation instruction parameter transmitted by the remote driving server to the vehicle via the wireless network nor transmitting a notification message to the remote driving server, wherein the notification message is used for notifying the remote driving server that the plurality of traveling parameters of the vehicle have been adjusted based on the control policy.
Nevertheless, Magzimof teaches features for setting operational restrictions for safe teleoperation of vehicles (Figure 1 and Page 3, Lines 50-51 describe a vehicle system (“The connected vehicle 102 comprises a vehicle safety system 105”)) for adjusting operational parameters comprising:
(iii) an operation instruction parameter transmitted by the remote driving server to the vehicle via the wireless network (Claim 1 describes a vehicle safety system determining a speed limit based on at least a predicted network latency (“…obtaining network latency information indicative of latency introduced under detected or predicted network conditions…determining, based on the vehicle motion state, the network latency information, the array of precomputed speed limits, and a set of obstacles including the mobile obstacle and the static obstacle, a speed limit for limiting speed of the vehicle during the teleoperation session that enables safe teleoperation of the vehicle when traversing the plurality of road segments”); Examiner notes that the vehicle safety system determines the acceptable speed range for teleoperating the vehicle, which is reasonably indicative of restricting an operation instruction parameter (e.g. a speed instruction));
transmitting a notification message to the remote driving server, wherein the notification message is used for notifying the remote driving server that the plurality of traveling parameters of the vehicle have been adjusted based on the control policy (Figure 1 and Paragraph 0044, “…the remote support server 101 may provide an indicator on the teleoperation workstation 103 that alerts a human teleoperator to the speed limit”; Examiner notes that a remote server alerting a teleoperator of the speed limit reasonably indicates that the remote server received the speed limit determined by the vehicle’s safety system).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have further modified the Rosenzweig invention to expand the features for adjusting encoder parameters (see at least Paragraph 0086, “At S740, a video feed is encoded according to the modified encoder parameters”) to include data such as operation instructions, as taught by Magzimof, for the benefit of improving teleoperation safety (Magzimof, Claim 1).
Regarding Claims 2, 9 and 16, Rosenzweig as currently modified teaches Claim 1, 8 and 15. While Rosenzweig further discloses adjusting the plurality of traveling parameters of the vehicle based on the control policy before the first time (Paragraphs 0084-0086) and prediction information (Paragraphs 0082-0083), Rosenzweig does not explicitly disclose: when the prediction information indicates that the network quality is lower than a first threshold, adjusting, based on the control policy, the backhaul data parameter of the vehicle to a first backhaul data parameter, wherein the first backhaul data parameter is used for controlling the vehicle to transmit low-quality data through a wireless communication network at the first time; and when the prediction information indicates that the network quality is higher than a second threshold, adjusting, based on the control policy, the backhaul data parameter of the vehicle to a second backhaul data parameter, wherein the second backhaul data parameter is used for controlling the vehicle to transmit high-quality data through the wireless communication network at the first time.
Nevertheless, Alalao further teaches:
[when] the network quality is lower than a first threshold, adjusting, based on the control policy, the backhaul data parameter of the vehicle to a first backhaul data parameter, wherein the first backhaul data parameter is used for controlling the vehicle to transmit low-quality data through a wireless communication network at the first time (Paragraph 0173, “In some embodiments, the autonomous vehicle 1304A varies the information that is included in the request 1604 according to multiple different levels, tiers, or grades. For instance, if the quality of the network connection corresponds to a highest level (e.g., associated with a quality metric greater than or equal to a first threshold level), the autonomous vehicle 1304A can include a first portion of information having the most information (e.g., the most detailed data, data that is largest in size, and/or data that is most complex). If the quality of the network connection corresponds to a lower level (e.g., associated with a quality metric less than the first threshold level, but greater than or equal to a lower second threshold level), the autonomous vehicle 1304A can include a second portion of information having a smaller amount of data (e.g., less detailed data, data that is smaller in size, and/or data that is less complex. If the quality of the network connection corresponds to an even lower level (e.g., associated with a quality metric less than the second threshold level, but greater than or equal to a lower third threshold level), the autonomous vehicle 1304A can include a third portion of information having even smaller amount of data (e.g., even less detailed data, data that is even smaller in size, and/or data that is even less complex). Any number of levels, tiers, or grades can be defined in this manner (e.g., two, three, four, or more)”; Examiner notes that the quality metric being less than a second threshold level is reasonably analogous to the network quality being less than a first threshold as described in the instant claim, as both indicate low network quality),
[when] the network quality is higher than a second threshold, adjusting, based on the control policy, the backhaul data parameter of the vehicle to a second backhaul data parameter, wherein the second backhaul data parameter is used for controlling the vehicle to transmit high-quality data through the wireless communication network at the first time (Paragraph 0173, “In some embodiments, the autonomous vehicle 1304A varies the information that is included in the request 1604 according to multiple different levels, tiers, or grades. For instance, if the quality of the network connection corresponds to a highest level (e.g., associated with a quality metric greater than or equal to a first threshold level), the autonomous vehicle 1304A can include a first portion of information having the most information (e.g., the most detailed data, data that is largest in size, and/or data that is most complex”; Examiner notes that the quality metric being greater than a first threshold level is reasonably analogous to the network quality being higher than a second threshold as described in instant claim, as both indicate high network quality).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have further modified the Rosenzweig invention to expand the features for adjusting encoder parameters (see at least Paragraphs 0084-0086) to include thresholds that can be used to indicate network quality, as taught by Alalao, for the benefit of allowing automatic adjustments for varying the quality of information being uploaded by the vehicle when there is a substantial change to network quality (Paragraph 0173, “In this manner, the transmission of data between the autonomous vehicle 1302a and the computer system 1300 can be dynamically varied based on the quality of the network connection between them, thereby improving the effectiveness of communications”).
Regarding Claims 3, 10 and 17, Rosenzweig as currently modified teaches claims 2, 9 and 16. Rosenzweig does not explicitly disclose: wherein a requirement for the network quality when the vehicle transmits the low-quality data is lower than a requirement for the network quality when the vehicle transmits the high-quality data.
Nevertheless, Alalao further teaches:
wherein a requirement for the network quality when the vehicle transmits the low-quality data is lower than a requirement for the network quality when the vehicle transmits the high-quality data (Paragraph 0165, “The autonomous vehicle 1304A can dynamically vary the information that is included in the request 1604 based on the quality metric associated with the network connection. For example, if the quality of a network connection between the computer system 1300 and an autonomous vehicle 1302a is higher (e.g., associated with one or more higher quality metrics corresponding to higher available bandwidth, lower latency, and/or higher reliability), the autonomous vehicle 1304A can include a greater amount of information (e.g., more detailed data, data that is larger in size, and/or data that is more complex). As another example, if the quality of the network connection between the computer system 1300 and an autonomous vehicle 1302a is lower (e.g., associated with a lower quality metric corresponding to lower bandwidth, higher latency, and/or lower reliability), the autonomous vehicle 1304A can include a smaller amount of information (e.g., less detailed data, data that is smaller in size, and/or data that is less complex)”; Examiner notes that lower threshold levels (e.g. second threshold level) have less requirements for network quality (e.g. lower bandwidth, higher latency and/or lower reliability) in comparison to higher threshold levels (e.g. first threshold level)).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have further modified the Rosenzweig invention to expand the features for adjusting encoder parameters (see at least Paragraphs 0084-0086) by setting lower requirements for network quality when transmitting low-quality data, as taught by Alalao, for the benefit of ensuring that the vehicle only transmits data that corresponds to the network quality (Paragraph 0173, “In this manner, the transmission of data between the autonomous vehicle 1302a and the computer system 1300 can be dynamically varied based on the quality of the network connection between them, thereby improving the effectiveness of communications”).
Regarding Claims 5, 12 and 19, Rosenzweig as currently modified teaches claims 1, 8 and 15. Rosenzweig does not explicitly disclose: the network quality is indicated by at least one of the following parameters: transmission bandwidth, transmission delay, transmission reliability, and delay jitter of uplink transmission.
Nevertheless, Alalao further teaches:
wherein the network quality is indicated by at least one of the following parameters: transmission bandwidth, transmission delay, transmission reliability, and delay jitter of uplink transmission (Paragraph 0161, “In some embodiments, the autonomous vehicle 1302a and/or the computer system 1300 determines one or more quality metrics (e.g., one or more numerical scores, or other objective or subjective descriptors) representing the quality of the network connection between the autonomous vehicle 1302a and the computer system 1300. As an example, if the quality metric is a numerical score, higher available bandwidth, lower latency, and higher reliability can correspond to a higher quality metric. Inversely, lower available bandwidth, higher latency, and lower reliability can correspond to a lower quality metric. In some embodiments, multiple quality metrics can be determined, with each quality metric corresponding to a different respective aspect of the quality of the network connection (e.g., available bandwidth, latency, reliability, etc.)”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have further modified the Rosenzweig invention to expand the features for adjusting encoder parameters (see at least Paragraphs 0084-0086) by including additional measurements of network quality for parameters, such as bandwidth, as taught by Alalao, for the benefit of allowing for a more comprehensive determination of network quality.
Regarding Claims 7 and 14, Rosenzweig as currently modified teaches claims 1 and 8. While Rosenzweig discloses determining prediction information (Paragraphs 0081-0082, “At S710, current network data is obtained… At S720, a predicted future network condition is determined”), Rosenzweig does not explicitly recite: wherein the prediction information is determined by the core network device based on a parameter of the wireless communication network and traveling information of the vehicle based on a parameter of the wireless communication network and traveling information of the vehicle.
Nevertheless Zielinski further teaches:
wherein the prediction information is determined by the core network device based on a parameter of the wireless communication network and traveling information of the vehicle based on a parameter of the wireless communication network and traveling information of the vehicle (Paragraph 0041 describes a server sending prediction information to a vehicle (“…predicting the quality of service in the communication service prediction server and sending back a quality of service prediction response message to the communication device”); Paragraph 0082, describes the server as being a core network device (“The prediction function may be implemented in a backend server or located in the core of a mobile radio network…. A further alternative position is a communication service prediction server 220 at the core network EPC”; Paragraphs 0083-0087 describe the predicted quality of service being based on at least a parameter of the network (“predicted channel model”) and traveling information of the vehicle (“mobile communication cells along the path following the planned route of the requesting vehicle will be determined”)).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the Rosenzweig invention to include a core network device for predicting a network quality, as taught by Zielinski, for the benefit of reducing computational load of a vehicle device by allowing processes to be outsourced to an external device.
Claims 4, 11 and 18 are rejected under 35 U.S.C. 103 as being unpatentable over Rosenzweig in view of Zielinski, Alalao and Magzimof and further in view of Xiao (WO2015010544A1; hereinafter Xiao).
Regarding Claims 4, 11 and 18, Rosenzweig as currently modified teaches claims 2, 9 and 16. While Rosenzweig as currently modified teaches prediction information indicating network quality (Rosenzweig, Paragraphs 0082-0083) and wherein the second threshold is greater than the first threshold (Alalao, Paragraph 0173, “In some embodiments, the autonomous vehicle 1304A varies the information that is included in the request 1604 according to multiple different levels, tiers, or grades”; Examiner notes that each threshold level indicates a different quality metric value, wherein the first threshold level as seen in claim 2 (analogous to the second threshold described in the instant claims) is greater than the second threshold level as seen in claim 2 (analogous to the first threshold described in the instant claims)), Rosenzweig as currently modified still does not explicitly teach: when the prediction information indicates that the network quality is between the first threshold and the second threshold, the adjusting a traveling parameter of the vehicle based on the control policy before the first time comprising: keeping, based on the control policy, the backhaul data parameter of the vehicle unchanged.
Nevertheless, Xiao teaches a method for adjusting travelling parameters based on network quality (Claim 1, “A computer-implemented method for adjusting video quality of a video communication over a network connection… comprising: acquiring, at the server, a network status parameter from the first client terminal, wherein the network status parameter indicates a condition of the network connection; selecting a video quality control strategy according to the received network status parameter; and transmitting to the first client terminal an adjustment command according to the selected video quality control strategy, wherein the video quality of the video communication is adjusted according to the transmitted adjustment command”) comprising:
[when the] network quality is between the first threshold and the second threshold, the adjusting a traveling parameter of the vehicle based on the control policy before the first time comprising: keeping, based on the control policy, the backhaul data parameter of the vehicle unchanged (Claim 4, “Generating the adjustment command for maintaining the video quality of the video communication upon determining that the acquired network status parameter is between a first threshold value and a second threshold value, wherein the first threshold value is less than the second threshold value”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have further modified the Rosenzweig invention to expand the features for adjusting encoder parameters (see at least Paragraphs 0084-0086) to keep a parameter unchanged if the network quality is between a first and second threshold, as taught by Xiao, for the benefit of preventing constant switching between parameters in response to small fluctuations in network quality.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to EISEN YIM whose telephone number is (703)756-5976. The examiner can normally be reached M-F 9:30 AM - 5:30 PM EST.
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/EISEN YIM/Examiner, Art Unit 3669
/Erin M Piateski/Supervisory Patent Examiner, Art Unit 3669
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