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 .
Response to Arguments
Applicant’s arguments with respect to claim(s) 1-20 have been considered but are moot because the new ground of rejection does not rely on all of the references applied in the prior rejection of record for any teaching or matter specifically challenged in the argument. The newly added reference Fei, makes up for the deficiencies in the previous office actions.
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.
Claim(s) 1, 3, 4, 6, 7, 9-14, 16-18, 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over US 20240167840 A1 to Fei et al. ("Fei") in view of US 10573183 B1 in view of (“Li”).
As to claim 1, Fei teaches a vehicle traffic monitoring system comprising: a plurality of multi-access edge computing (MEC) vehicle traffic monitoring devices; and a master vehicle traffic monitoring device to which each MEC vehicle traffic monitoring device of the plurality of MEC vehicle traffic monitoring devices is communicatively connected via a wireless cellular network on which the plurality of MEC vehicle traffic monitoring devices and the master vehicle traffic monitoring device are present, wherein the master vehicle traffic monitoring device is communicatively connected to a core network of the wireless cellular network (¶0067, The data source device includes but is not limited to a terminal, a road surface monitoring apparatus, a roadside apparatus, and the like. The roadside apparatus is configured to obtain road information, traffic road condition information, and the like in a wide geographic range, and may include an apparatus such as a roadside unit (RSU), a multi-access edge computing (MEC) device, or a sensor. For example, the roadside apparatus may be the RSU, the MEC, or the sensor, a system including the RSU and the MEC, a system including the RSU and the sensor, or a system including the RSU, the MEC, and the sensor. The road surface monitoring apparatus may be configured to collect road information and road surface traffic information, and may be a camera, a road surface gathered water detector, a lidar, a millimeter-wave radar, or the like. The terminal may obtain information such as a road and a traffic road condition through a sensor of the terminal, and may be a vehicle, an on board unit (OBU), an intelligent wearable device (for example, a sports band or a watch), a portable mobile device (for example, a mobile phone or a tablet), or another sensor or device, such as a component or a chip of the portable mobile device, that can communicate with the computing device. This is not specifically limited in embodiments of this application. In some possible embodiments, the data source device may alternatively be a device that provides traffic road condition data by a traffic management department, or the like.) Fei does not teach wherein: each respective MEC vehicle traffic monitoring device of the plurality of MEC vehicle traffic monitoring devices: views scenes outside the MEC vehicle traffic monitoring device and generates live video of the viewed scenes in at least a high-definition (HD) resolution; performs object recognition on frames of the live video in real time using computer vision techniques. Demtold teaches wherein: each respective MEC vehicle traffic monitoring device of the plurality of MEC vehicle traffic monitoring devices: views scenes outside the MEC vehicle traffic monitoring device (¶0099) and generates live video of the viewed scenes in at least a high-definition (HD) resolution; performs object recognition on frames of the live video in real time using computer vision techniques (¶0062, The object detection module 324 may comprise program code to analyses camera sensor data and perform object detection operations on the camera sensor data, ¶0102 and 540 of FIG. 5: the computing device 310 may determine compliance of a vehicle with the parking conditions of the parking area in the vicinity of post 120 and transmit the determined compliance output to the remote computing device 380, ¶0070, congestion detection on road). In view of the teachings of Detmold, it would have been obvious before the effective filing date of the invention to modify the teachings of Fei. The suggestion/motivation would be to provide cost-effective, low latency and scalable urban monitoring systems, methods and platforms.
Detmold does not teach makes one or more determinations whether there exists a potential traffic hazard, traffic issue, safety issue or particular vehicle characteristic based on the object recognition; includes in electronic reports data indicative of the one or more determinations whether there exists a potential traffic hazard, traffic issue, safety issue or particular vehicle characteristic based on the generated live video; and transmits the electronic reports to the master vehicle traffic monitoring device during an occurrence of the potential traffic hazard, traffic issue, safety issue or particular vehicle characteristic via a wireless cellular network connection module of the master vehicle traffic monitoring device.
Li however teaches makes one or more determinations whether there exists a potential traffic hazard, traffic issue, safety issue or particular vehicle characteristic based on the object recognition; includes in electronic reports data indicative of the one or more determinations whether there exists a potential traffic hazard, traffic issue, safety issue or particular vehicle characteristic based on the generated live video; and transmits the electronic reports to the master vehicle traffic monitoring device during an occurrence of the potential traffic hazard, traffic issue, safety issue or particular vehicle characteristic via a wireless cellular network connection module of the master vehicle traffic monitoring device (Column 3, lines 23-34; Figure 1B; Column 3, lines 39-53, line 64-Column 4, line 8; Column 8, lines 29-41, For example, FIG. 1B illustrates an exemplary hazard view 10 which may be displayed on display 109 of electronic device or mobile device 102. Hazard view 10 may display a live video feed of driving scenes 112 collected from camera 108 along with optional augmented reality elements to warn the user of potential hazards. The hazard view 10 may help draw the attention of the user or driver to potential hazards which the user may not have noticed. The hazard view may include interface elements such as hazard indicator 11, hazard marker 12, and hazard route overlay 13. The hazard view 10 may be triggered or activated by detection of a hazard or potential hazardous event). In view of the teachings of Li, it would have been obvious before the effective filing date of the invention to modify the teachings of Fei and Detmold. The suggestion/motivation would be vehicle-integrated safety systems that provides capabilities for identifying objects and providing appropriate alerts for the type, location, and relative motion of the objects.
As to claim 3, Fei, Detmold and Li teaches the vehicle traffic monitoring system of claim 2 wherein the wireless cellular network is a fifth-generation (5G) wireless cellular network (Li, ¶0085, The monitoring system 100 may be configured to communicate sensed data, inferences based on the sensed data, detected events or other observations or output of data processing operations to the remote computing device 380 through the gateway device 360 over the network 370. The gateway device 360 may comprise hardware and or software to enable communication between network 370 and each computing device 310 deployed in an urban area. The gateway device 360 may communicate using a wired or wireless link 361 with the computing device 310. In some embodiments, the gateway device 360 may communicate with the computing device 310 using any one or more of: Z-Wave, ZigBee, WirelessHART, Wi-Fi, Weighless, SigFox, NB-IoT, Long-Term Evolution (LTE), LoRa, Bluetooth, 2G, 3G, 4G, 5G or 6G communication protocols or networks, for example. In some embodiments, the gateway device 360 may communicate with the computing device 310 using a wired Ethernet link, a fiber optic cable link, a USB link, or a wired USB link, for example).
As to claim 4, Fei, Detmold and Li teaches the vehicle traffic monitoring system of claim 2 wherein the determination of whether to stream the generated live video to the master vehicle traffic monitoring device is made by the master vehicle traffic monitoring device based on the electronic reports (Li, Column 4, lines 48-62; Column 4, In 63-Column 5,In 19; Column 7, line 57-Column 8, line 4].
As to claim 6, Fei, Detmold and Li teaches the vehicle traffic monitoring system of claim 2 wherein the master vehicle traffic monitoring device: based on the electronic reports, causes an alert regarding the potential traffic hazard, traffic issue, safety issue or particular vehicle characteristic to be transmitted via the core network of the wireless cellular network to one or more drivers of one or more vehicles determined to be potentially affected by the potential traffic hazard, traffic issue, safety issue or particular vehicle characteristic (Li, Col 4, In 63-Col 5, ln 19, Column 4, lines 48-62; Column 4, In 63- Column 5, In 19; Column 7, line 57-Column 8, line 4).
As to claim 7, Fei, Detmold and Li teaches the vehicle traffic monitoring system of claim 6 wherein the alert includes a live video stream of the generated live video of the potential traffic hazard, traffic issue, safety issue or particular vehicle characteristic originating from the respective MEC vehicle traffic monitoring device (Li, Col 4, In 63-Col 5, ln 19, Column 4, lines 48-62; Column 4, In 63- Column 5, In 19; Column 7, line 57-Column 8, line 4).
As to claim 9, Fei, Detmold and Li teaches the vehicle traffic monitoring system of claim 1 wherein each respective MEC vehicle traffic monitoring device of the plurality of MEC vehicle traffic monitoring devices includes a resource manager, in which the resource manager: determines whether there exists enough computing resources available in the MEC vehicle traffic monitoring device to perform additional object recognition on frames of additional live video in real time using computer vision techniques and making one or more additional determinations whether there exists a potential traffic hazard, traffic issue, safety issue or particular vehicle characteristic based on the additional object recognition; and in response to a determination there does not exist enough computing resources available in the MEC vehicle traffic monitoring device to perform the additional object recognition and the making one or more additional determinations, causes the additional live video to be transmitted to one or more other respective MEC vehicle traffic monitoring devices of the plurality of MEC vehicle traffic monitoring devices to perform the additional object recognition and the making one or more additional determinations (Detmold, ¶0069-0070, The object detection module 324 may continue to
Analyze subsequently captured images to detect objects in the captured images and transmit the
object detection output to the event detection module 325. The event detection module 325 may analyses the object detection output to determine whether the previously detected vehicle is not detected anymore [. .] The object detection module 324 and the event detection module 325 may together be configured to perform various monitoring operations including congestion detection on roads").
As to claim 10, Fei, Detmold and Li teaches the vehicle traffic monitoring system of claim 9, wherein the resource manager included in the respective MEC vehicle traffic monitoring device: receives, from the one or more other respective MEC vehicle traffic monitoring devices of the plurality of MEC vehicle traffic monitoring devices, data, included in additional electronic reports, indicative of the one or more additional determinations whether there exists a potential traffic hazard, traffic issue, safety issue or particular vehicle characteristic based on the additional live video (Detmold, ¶0069-0070, The object detection module 324 may continue to Analyze subsequently captured images to detect objects in the captured images and transmit the object detection output to the event detection module 325. The event detection module 325 may analyses the object detection output to determine whether the previously detected vehicle is not detected anymore [. .] The object detection module 324 and the event detection module 325 may together be configured to perform various monitoring operations including congestion detection on roads).
As to claim 11, Fei, Detmold and Li teaches the vehicle traffic monitoring system of claim 9, wherein the master vehicle traffic monitoring device: receives, from the one or more other respective MEC vehicle traffic monitoring devices of the plurality of MEC vehicle traffic monitoring devices, data, included in additional electronic reports, indicative of the one or more additional determinations whether there exists a potential traffic hazard, traffic issue, safety issue or particular vehicle characteristic based on the additional live video; and based on the additional electronic reports, causes an additional alert regarding the potential traffic hazard, traffic issue, safety issue or particular vehicle characteristic to be transmitted via the core network of the wireless cellular network to one or more drivers of one or more vehicles determined to be potentially affected by the potential traffic hazard, traffic issue, safety issue or particular vehicle characteristic Detmold, ¶0069-0070, The object detection module 324 may continue to Analyze subsequently captured images to detect objects in the captured images and transmit the object detection output to the event detection module 325. The event detection module 325 may analyses the object detection output to determine whether the previously detected vehicle is not detected anymore [. .] The object detection module 324 and the event detection module 325 may together be configured to perform various monitoring operations including congestion detection on roads).
As to claim 12, Fei, Detmold and Li teaches the vehicle traffic monitoring system of claim 9, wherein the resource manager included in the respective MEC vehicle traffic monitoring device causes the additional live video to be transmitted to one or more other respective MEC vehicle traffic monitoring devices of the plurality of MEC vehicle traffic monitoring devices by transmitting the additional live video to the master vehicle traffic monitoring device for the master vehicle traffic monitoring device to transmit to the one or more other respective MEC vehicle traffic monitoring devices (Detmold, ¶0069-0071).
As to claim 13, Fei, Detmold and Li teaches the vehicle traffic monitoring system of claim 9 wherein: the respective MEC vehicle traffic monitoring device: determines there concurrently exists a potential traffic hazard, traffic issue, safety issue or particular vehicle characteristic in multiple different scenes around the respective MEC vehicle traffic monitoring device; and generates a separate live video stream for each potential traffic hazard, traffic issue, safety issue or particular vehicle characteristic concurrently existing in the multiple different scenes around the respective MEC vehicle traffic monitoring device, wherein each generated separate live video stream focuses on a different respective potential traffic hazard, traffic issue, safety issue or particular vehicle characteristic, wherein the additional live video includes each generated separate live video stream; and the resource manager of the respective MEC vehicle traffic monitoring device: determines there does not exist enough computing resources available in the respective MEC vehicle traffic monitoring device to continue to perform the additional object recognition and to continue the making one or more additional determinations due to the additional live video including each generated separate live video stream (Li, (Column 3, lines 23-34; Figure 1B; Column 3, line 64-Column4, line 8; Column 13, lines 37-42) .
As to claim 14, see the rejection of claim 1.
As to claim 16, see the rejection of claim 3.
As to claim 17, see the rejection of claim 4.
As to claim 18, see the rejection of claim 1.
As to claim 20, see the rejection of claim 4.
Claim(s) 2, 5, 15 and 19 is/are rejected under 35 U.S.C. 103 as being unpatentable over Detmold and Li as applied to claim 1 above, and further in view of US 20220368972 A1 to Cheraghi et al. (“Cheraghi”).
As to claim 2, Fei, Detmold and Li fails to teach the vehicle traffic monitoring system of claim 1 wherein each respective MEC vehicle traffic monitoring device of the plurality of MEC vehicle traffic monitoring devices: based on a determination whether to stream the generated live video to the master vehicle traffic monitoring device, streams the generated live video to the master vehicle traffic monitoring device via the wireless cellular network connection module of the respective MEC vehicle traffic monitoring device in real-time at no less than 24 frames per second, with at least about a 15 Mbps data rate and with a latency rate no greater than about than 50 milliseconds. Cheraghi on the other hand teaches a vehicle traffic monitoring device streaming the generated live video via the wireless cellular network connection module of the vehicle traffic monitoring device in real-time at
no less than 24 frames per second, with at least about a 15 Mbps data rate and with a latency rate
no greater than about than 50 milliseconds (¶0031, According to increased number and bandwidth of cameras/video streaming devices and the limited physical resources of the in-vehicle network 100 including the wireless in-vehicle networks for the transmission of the video streams, i.e., frequency-time resources, the video streams may be compressed before being transmitted to the in-vehicle CPU 102. That is, the video streams may be compressed to accommodate the bandwidth of the wireless in-vehicle communication. For example, an uncompressing frame of a video stream of 1280×960 pixels with 24 bits per pixel may have a bandwidth of Frame_Height)×(Frame_Width)×(Bits_Per_Pixel)=1280×960×24=29.49 megabits (Mb), and with the video stream at 30 frames per second (fps), the wireless in-vehicle may need to have 1280×960×30×24=884.74 megabits per second (Mbps) of network data transmission speed to support that one video stream alone. In some aspects, the frames of video streams may be compressed to accommodate the network bandwidth and the network data transmission speed. In some aspects, a resource allocation scheme may be provided to be adapted for compressed video streams, which may provide a more efficient distribution of resources and reduce the latency in the wireless in-vehicle communication ). In view of the teachings of Cheraghi, it would have been obvious before the effective filing date of the invention to modify the teachings of Li and Detmold. The suggestion/motivation would be to enable a more seamless display of captured traffic and resolution.
As to claim 5, Fei, Detmold and Li fails to teach the vehicle traffic monitoring system of claim 2 wherein the determination of whether to stream the generated live video to the master vehicle traffic monitoring device is made by the respective MEC vehicle traffic monitoring device. Cheraghi however teaches wherein the determination of whether to stream the generated live video to the master vehicle traffic monitoring device is made by the respective MEC vehicle traffic monitoring device (¶0031, According to increased number and bandwidth of cameras/video streaming devices and the limited physical resources of the in-vehicle network 100 including the wireless in-vehicle networks for the transmission of the video streams, i.e., frequency-time resources, the video streams may be compressed before being transmitted to the in-vehicle CPU 102. That is, the video streams may be compressed to accommodate the bandwidth of the wireless in-vehicle communication. For example, an uncompressing frame of a video stream of 1280×960 pixels with 24 bits per pixel may have a bandwidth of Frame_Height)×(Frame_Width)×(Bits_Per_Pixel)=1280×960×24=29.49 megabits (Mb), and with the video stream at 30 frames per second (fps), the wireless in-vehicle may need to have 1280×960×30×24=884.74 megabits per second (Mbps) of network data transmission speed to support that one video stream alone. In some aspects, the frames of video streams may be compressed to accommodate the network bandwidth and the network data transmission speed. In some aspects, a resource allocation scheme may be provided to be adapted for compressed video streams, which may provide a more efficient distribution of resources and reduce the latency in the wireless in-vehicle communication ). In view of the teachings of Cheraghi, it would have been obvious before the effective filing date of the invention to modify the teachings of Li and Detmold. The suggestion/motivation would be to enable a more seamless display of captured traffic and resolution.
As to claim 15, see the rejection of claim 2.
As to claim 19, see the rejection of claim 2.
Claim(s) 8 is/are rejected under 35 U.S.C. 103 as being unpatentable over Fei, Detmold and Li as applied to claim 6 above, and further in view of US 20210019645 A1 to Petrey.
As to claim 8, Fei, Detmold and Li fails to teach the vehicle traffic monitoring system of claim 6 wherein the master vehicle traffic monitoring device: receives a command from one or more drivers of the one or more vehicles determined to be potentially affected by the potential traffic hazard, traffic issue, safety issue or particular vehicle characteristic to zoom in on a particular region of a live video stream; sends the command to zoom in on a particular region of the live video stream to the respective MEC vehicle traffic monitoring device from which the generated live video of the potential traffic hazard, traffic issue, safety issue or particular vehicle characteristic originated; receives, in response to the sent command, generated live video of the particular region from the respective MEC vehicle traffic monitoring device; and sends a live video stream of the received generated live video of the particular region via the core network of the wireless cellular network to the one or more drivers from which the command was received. Petrey teaches the vehicle traffic monitoring system of claim 6 wherein the master vehicle traffic monitoring device: receives a command from one or more drivers of the one or more vehicles determined to be potentially affected by the potential traffic hazard, traffic issue, safety issue or particular vehicle characteristic to zoom in on a particular region of a live video stream; sends the command to zoom in on a particular region of the live video stream to the respective MEC vehicle traffic monitoring device from which the generated live video of the potential traffic hazard, traffic issue, safety issue or particular vehicle characteristic originated; receives, in response to the sent command, generated live video of the particular region from the respective MEC vehicle traffic monitoring device; and sends a live video stream of the received generated live video of the particular region via the core network of the wireless cellular network to the one or more drivers from which the command was received (¶0005, a system for monitoring vehicle traffic"; par. [0029]: "The computing system may analyze the images captured by the cameras and detect a license plate identifier (ID) of a vehicle"; ¶0048, The image capturing component 200 may configure one or more camera properties (e.g., zoom,
focus, etc.) to obtain a clear image of the license plates"). In view of the teachings of Petrey, it would have been obvious before the effective filing date of the invention to modify the teachings of Li and Detmold. The suggestion/motivation would be directed to a system for monitoring vehicle traffic and provides a benefit of obtaining clear images of the region of interest.
Conclusion
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/CHRISTINE A KURIEN/Examiner, Art Unit 2421
/NATHAN J FLYNN/Supervisory Patent Examiner, Art Unit 2421
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