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.
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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 1-20 are rejected under 35 U.S.C. 103 as being unpatentable over BERTOLAMI et al (2010/0287485) in view of BRODSKY et al (2022/0101607) and ARMENI et al (3D Scene Graph: A structure for unified semantics, 3D space, and camera).
As per claim 1, Bertolami teaches the claimed “system for creation of group simulated spaces,” the system comprising: “a first mobile hardware sensor array in a user group that captures a first set of images and a first set of measurements of a common physical space; a second mobile hardware sensor array in the user group that captures a second set of images and a second set of measurements of the common physical space” (Bertolami, [0025], [0037] - Device 220 and/or scene-facing detectors 226a and 226b may capture an image of physical area 230, or otherwise detect objects within physical area 230 and/or derive data from physical area 230. Physical area 230 may have within it landmarks that are detectable, including large landmarks such as tree 231 and tower 232, and/or relatively small and, in some embodiments, numerous landmarks that may be used for location determinations, such as distinctively textured portions of various scene objects or distinct and identifiable attributes of various scene objects… In many embodiments, other users will not be visible, present, and/or detectable within or proximate to physical area 230. Alternatively, one or more other users, such as user 211, may be proximate to or within physical area 230 and may be detected by scene-facing detectors 226a and 226b… The images collected by device 220 and/or device 221 may be analyzed using a variety of methods and means to determine a precise location of device 220 and/or device 221. Alternatively, groups of pixels, data representing groups of pixels, or other subsections of the images collected by device 220 and/or device 221 may be analyzed. For example, device 220 may analyze one or more images of physical area 230 as captured by scene-facing detectors 226a and/or 226b and determine that landmarks such as tree 231, tower 232, cracks on tower 232, and/or a letter on a sign proximate to tree 231 are particular landmarks within the estimated location determined by location technology configured on device 220. Alternatively, device 220 may extract one or more portions of one or more images collected of scene 220 to determine if one or more landmarks match landmark descriptors, landmark templates, or images of landmarks. Device 220 may also determine an orientation for itself and/or user 210. By analyzing the captured image(s), or by using other means, device 220 may determine that user 210 and/or device 220 is a specific distance from tower 232 and in a specific orientation. For example, device 220 may determine that device 220 is located 1500 meters southwest of tower 232, facing northeast. Likewise, device 221 may determine that device 221 is located 1000 meters northwest of tower 232, facing southeast. Further details are provided herein on methods and means of analyzing images to determine precise locations); “a remote server that includes a server memory that stores server computer instructions and a server processor that, when executing the server computer instructions, causes the remote server to: receive the first set of images and the first set of measurements of the common physical space captured by the first mobile hardware sensor array, and receive the second set of images and the second set of measurements of the common physical space captured by the second mobile hardware sensor array; system to render the first set of images and the second set of images into group images, and render the first set of measurements and the second set of measurements into group measurements; calculate a group simulated space that is a virtual representation of the common physical space using the group images and the group measurements” (Bertolami, [0050] - The use of a common coordinate system may assist in presenting realistic computer-generated or derived images to a user of an augmented reality system or application. FIG. 3 illustrates the virtual characters, users, objects and physical area 230 shown in FIG. 2 as located on common coordinate system 300 in three dimensions. In one embodiment, devices 220 and 221, users 210 and 211 operating devices 220 and 221, or an augmented reality system or application, determine that the base of tower 232, at origin point 350, will serve as the origin of a coordinate system used by both devices for interaction with an augmented reality application or system. The orientation of coordinate system 300 may also be determined by the devices or system. For example, device 220 may determine that user 210 is at point 310 facing physical area 230, and specifically tower 232. The device(s) or system may then determine that the position of user 210 relative to axes of the coordinate system, such as axes x, y, and z illustrated as part of coordinate system 300; [0059] - Once landmarks, features, or other elements are matched to mapping information known about a scene or area, an orientation and distance from the identified landmarks, features, or other elements may be determined in order to derive a precise location. This may be accomplished by analyzing the captured image(s) and calculating the distance from the identified elements and the particular angle of view or orientation towards the elements by comparing the captured image(s) to images taken at a known distance or orientation to the elements or associated data. The location of the device that captured the image may be determined in three-dimensional space or two-dimensional space. Note that in most embodiments, more than one element may be analyzed and compared to known mapping information such as feature templates or previously captured images. However, it is also contemplated that a single landmark, feature, or element may be used for location determination. Means and methods of performing these calculations may vary depending on whether the captured image is a three-dimensional image or group of images, or a two-dimensional image or group of images. All such means and methods are contemplated as within the scope of the present disclosure; [0061] - For example, a server dedicated to coordinating users in an augmented reality system may determine that a particular local point and orientation are the origin of a coordinate system (for example, the bottom northwest corner of the Empire State Building.) This information may then be transmitted to a user device. Alternatively, or in conjunction, spatial transformation data or instructions may be transmitted to a user device, such as a local-to-unified-space transformation matrix that the user device can multiply with its determined local position to obtain the position of the user device in a shared virtual space. Such transform information can be used by a user device to adjust how it constructs/displays its augmentation data and manages real and augmented data interaction. Information may be provided to a user device in any form, including matrices, software instructions, and/or Cartesian coordinates (for example, the user device is at point <3, 5, 7> and orientation <0, 0, 1> relative to the origin.) Any other type of coordinates, form of transform data, or other location information relative to an origin may be used. The location information may also be expressed in any type of units. An orientation may also be received by the user device, which may be provided in any useful manner, including cardinal orientation, an orientation matrix, or any other means of conveying an orientation. All such means and methods are contemplated as within the scope of the present disclosure); “enable creation of a group portal in a multi-dimensional fabric user interface that connects to the group simulated space; enable users that are members of the user group to access the group portal in the multi-dimensional fabric user interface and enter the group simulated space; prevent users that are not members of the user group from accessing the group portal in the multi-dimensional fabric user interface and entering the group simulated space; and enable the users of the user group to interact with virtual objects and other users of the user group in the group simulated space” (Bertolami, [0060] - These recipients of this information may be other augmented reality components operated by other users of an augmented reality system or application, and/or one or more servers or other computers that are part of or interact with an augmented reality system or application but are not user devices. In one embodiment, a designated user device is configured to determine a coordinate system for all users in an augmented reality system or application, and precise location information is transmitted to that device. In another embodiment, a server is configured to receive precise location information from all the user devices in a particular augmented reality system or application and determine a common coordinate system. Any particular device or group of devices may be designated for common coordinate system determinations, and all such embodiments are contemplated; [0094] - There are a variety of systems, components, and network configurations that may support an augmented reality system or application. For example, computing systems, communications systems, and detectors or cameras may be connected together by wired or wireless systems, by local networks, or by widely distributed networks. Currently, many networks are coupled to the Internet, which provides the infrastructure for widely distributed computing and encompasses many different networks; [0096] - Thus, the network infrastructure enables a host of network topologies such as client/server, peer-to-peer, or hybrid architectures... In a client/server architecture, particularly a networked system, a client is usually a computer that accesses shared network resources provided by another computer, e.g., a server. In the example of FIG. 7, computers 820a, 820b, etc. can be thought of as clients and computers 80a, 80b, etc. can be thought of as the server where server 80a, 80b, etc. maintains the data that is then replicated in the client computers 820a, 820b, etc).
It is noted that Bertolami does not teach “train an artificial intelligence to mesh the physical space” as claimed. However, Brodsky teaches the “mesh of the physical space” is well known in the art (Brodsky, [0128] - 3D reconstruction is a 3D computer vision technique that takes images (e.g., colored/gray scale images, depth images, or the like) as inputs and generates 3 D meshes (e.g., automatically) representing an observed scene, such as the user's environment and/or the real world. In some embodiments, the 3D mesh representing an observed scene may be called a world mesh. 3D reconstruction has many applications in virtual reality, mapping, robotics, game, filmmaking, and so forth; [0130] - FIG. 17 is a simplified flowchart illustrating a method for creating a 3D mesh of a scene using multiple frames of captured depth maps). Furthermore, Armani teaches “train an artificial intelligence to mesh the physical space” as claimed (Armeni, Figure 2 - (c) Single panorama projections are then aggregated on the 3D mesh; page 5, column 1, Multi-view consistency - Semantic labels from different panoramas are combined on the final mesh via multi-view consistency).
Thus, it would have been obvious, in view of Brodsky and Armeni, to configure Bertolami’s system as claimed by training an artificial intelligence to mesh the physical space. The motivation is to increase the robustness of learning system with framing and multi-view consistency (Armeni, 6 Conclusion).
Claim 2 adds into claim 1 “wherein the first mobile hardware sensor array and the second mobile hardware sensor array additionally capture video data” (Bertolami, [0093] - although the physical environment depicted may show the connected devices as computers, such illustration is merely exemplary and the physical environment may alternatively be depicted or described comprising various digital devices such as gaming consoles, PDAs, televisions, mobile telephones, cameras, detectors, etc., software objects such as interfaces, COM objects and the like).
Claim 3 adds into claim 1 “wherein the first and second mobile hardware sensor arrays use LIDAR to capture one or more of flat images and images with depth resolution” (Brodsky, [00130] - FIG. 17 is a simplified flowchart illustrating a method for creating a 3D mesh of a scene using multiple frames of captured depth maps. Referring to FIG. 17, a method to create a 3D model of a scene, for example, a 3D triangle mesh representing the 3D surfaces associated with the scene, from multiple frames of captured depth maps is illustrated. The method 1700 includes receiving a set of captured depth maps (1702). A captured depth map is a depth image in which each pixel has an associated depth value representing the depth from the pixel to the camera obtaining the depth image. In comparison with a colored image that can have three or more channels per pixel (e.g., RGB image with red, green and blue components), a depth map can have a single channel per pixel (i.e., pixel distance from the camera). The process of receiving the set of captured depth maps can include processing input images, for example, RGB images, to produce one or more captured depth maps, also referred to as a frame of a captured depth map. In other embodiments, the captured depth maps are obtained using a time of flight camera, a LIDAR, stereo cameras, or the like, and are thus received by the system). Thus, it would have been obvious, in view of Brodsky and Armeni, to configure Bertolami’s system as claimed by using LIDAR to capture the images of the physical space. The motivation is to increase the quality of captured image data with a LIDAR device.
Claim 4 adds into claim 1 “wherein one or more of the first mobile hardware sensor array and the second mobile hardware sensor array are incorporated into smart watches” (Bertolami, [0093] - although the physical environment depicted may show the connected devices as computers, such illustration is merely exemplary and the physical environment may alternatively be depicted or described comprising various digital devices such as gaming consoles, PDAs, televisions, mobile telephones, cameras, detectors, etc., software objects such as interfaces, COM objects and the like).
Claim 5 adds into claim 1 “wherein one or more of the first mobile hardware sensor array and the second mobile hardware sensor array are incorporated into aerial drones” (Broadsky, [00130] - FIG. 17 is a simplified flowchart illustrating a method for creating a 3D mesh of a scene using multiple frames of captured depth maps. Referring to FIG. 17, a method to create a 3D model of a scene, for example, a 3D triangle mesh representing the 3D surfaces associated with the scene, from multiple frames of captured depth maps is illustrated. The method 1700 includes receiving a set of captured depth maps (1702). A captured depth map is a depth image in which each pixel has an associated depth value representing the depth from the pixel to the camera obtaining the depth image. In comparison with a colored image that can have three or more channels per pixel (e.g., RGB image with red, green and blue components), a depth map can have a single channel per pixel (i.e., pixel distance from the camera). The process of receiving the set of captured depth maps can include processing input images, for example, RGB images, to produce one or more captured depth maps, also referred to as a frame of a captured depth map. In other embodiments, the captured depth maps are obtained using a time of flight camera, a LIDAR, stereo cameras, or the like, and are thus received by the system). It is noted that the image-captured device (camera, LIDAR, …) can be attached to a drone to capture the image data.
Claim 6 adds into claim 1 “one or more additional mobile hardware sensor arrays in the group that captures one or more additional sets of images and one or more additional sets of measurements of the common physical space” (Bertolani, [0040] - If multiple users are located in the different physical areas, and no mapping or physical area data is available for the physical areas, each user and/or user device may map their respective physical areas independently and employ their own determined coordinate system that may be defined early in the mapping process. Then, the users and/or devices may engage in a negotiation process to arrive at a unified system. The negotiation may determine a unified coordinate system unification based on fiducial markers, recognized features, compared landscape topographies, and/or arbitrarily selected local origins; [0060] - Additional information may also be transmitted, such as cartography information about the physical environment or information on the specific mapping data that matched elements in one or more scene images. These recipients of this information may be other augmented reality components operated by other users of an augmented reality system or application, and/or one or more servers or other computers that are part of or interact with an augmented reality system or application but are not user devices. In one embodiment, a designated user device is configured to determine a coordinate system for all users in an augmented reality system or application, and precise location information is transmitted to that device. In another embodiment, a server is configured to receive precise location information from all the user devices in a particular augmented reality system or application and determine a common coordinate system. Any particular device or group of devices may be designated for common coordinate system determinations, and all such embodiments are contemplated), wherein the server processor executes further server computer instructions that further cause the remote server to: “retrain the artificial intelligence system to mesh the one or more additional sets of images into the group images, and mesh the one or more additional sets of measurements into group measurements to improve the group simulated space” (Armeni, 5.2. Evaluation of Automated Pipeline - We use the best off-the-shelf Mask R-CNN model trained on the COCO dataset. Specifically, we choose Mask R-CNN with Bells & Whistles from Detectron. According to the model notes, it uses a ResNeXt-152 (32x8d) in combination with a Feature Pyramid Network (FPN). It is pre-trained on ImageNet-5K and fine-tuned on COCO. For more details on implementation and training/testing we refer the reader to Mask R-CNN and Detectron; 5.3. 2D Scene Graph Prediction - We train a ResNet34 using the segmentation masks that were automatically generated by our method, and use the medium Gibson data split. The baseline is Statistically Informed Guess extracted from the training data). It is noted that a re-train step can be perform when new information is entered. Thus, it would have been obvious, in view of Brodsky and Armeni, to configure Bertolami’s system as claimed by retrain the artificial intelligence system to mesh the physical space. The motivation is to increase the robustness of learning system with framing and multi-view consistency (Armeni, 6 Conclusion).
Claim 7 adds into claim 1 “wherein the group simulated space is one or more of a virtual reality group simulated space or an augmented reality group simulated space” (Bertolami, [0050] - The use of a common coordinate system may assist in presenting realistic computer-generated or derived images to a user of an augmented reality system or application. FIG. 3 illustrates the virtual characters, users, objects and physical area 230 shown in FIG. 2 as located on common coordinate system 300 in three dimensions. In one embodiment, devices 220 and 221, users 210 and 211 operating devices 220 and 221, or an augmented reality system or application, determine that the base of tower 232, at origin point 350, will serve as the origin of a coordinate system used by both devices for interaction with an augmented reality application or system. The orientation of coordinate system 300 may also be determined by the devices or system. For example, device 220 may determine that user 210 is at point 310 facing physical area 230, and specifically tower 232. The device(s) or system may then determine that the position of user 210 relative to axes of the coordinate system, such as axes x, y, and z illustrated as part of coordinate system 300; [0059] - Once landmarks, features, or other elements are matched to mapping information known about a scene or area, an orientation and distance from the identified landmarks, features, or other elements may be determined in order to derive a precise location. This may be accomplished by analyzing the captured image(s) and calculating the distance from the identified elements and the particular angle of view or orientation towards the elements by comparing the captured image(s) to images taken at a known distance or orientation to the elements or associated data. The location of the device that captured the image may be determined in three-dimensional space or two-dimensional space. Note that in most embodiments, more than one element may be analyzed and compared to known mapping information such as feature templates or previously captured images. However, it is also contemplated that a single landmark, feature, or element may be used for location determination. Means and methods of performing these calculations may vary depending on whether the captured image is a three-dimensional image or group of images, or a two-dimensional image or group of images. All such means and methods are contemplated as within the scope of the present disclosure; [0061] - For example, a server dedicated to coordinating users in an augmented reality system may determine that a particular local point and orientation are the origin of a coordinate system (for example, the bottom northwest corner of the Empire State Building.) This information may then be transmitted to a user device. Alternatively, or in conjunction, spatial transformation data or instructions may be transmitted to a user device, such as a local-to-unified-space transformation matrix that the user device can multiply with its determined local position to obtain the position of the user device in a shared virtual space. Such transform information can be used by a user device to adjust how it constructs/displays its augmentation data and manages real and augmented data interaction. Information may be provided to a user device in any form, including matrices, software instructions, and/or Cartesian coordinates (for example, the user device is at point <3, 5, 7> and orientation <0, 0, 1> relative to the origin.) Any other type of coordinates, form of transform data, or other location information relative to an origin may be used. The location information may also be expressed in any type of units. An orientation may also be received by the user device, which may be provided in any useful manner, including cardinal orientation, an orientation matrix, or any other means of conveying an orientation. All such means and methods are contemplated as within the scope of the present disclosure).
Claim 8 adds into claim 1 “wherein the server processor executes further server computer instructions that further cause the remote server to: enable a user that is a member of the user group to control parameters within the group simulated space” (Bertolami, [0060] - These recipients of this information may be other augmented reality components operated by other users of an augmented reality system or application, and/or one or more servers or other computers that are part of or interact with an augmented reality system or application but are not user devices. In one embodiment, a designated user device is configured to determine a coordinate system for all users in an augmented reality system or application, and precise location information is transmitted to that device. In another embodiment, a server is configured to receive precise location information from all the user devices in a particular augmented reality system or application and determine a common coordinate system. Any particular device or group of devices may be designated for common coordinate system determinations, and all such embodiments are contemplated; [0096] - Thus, the network infrastructure enables a host of network topologies such as client/server, peer-to-peer, or hybrid architectures... In a client/server architecture, particularly a networked system, a client is usually a computer that accesses shared network resources provided by another computer, e.g., a server. In the example of FIG. 7, computers 820a, 820b, etc. can be thought of as clients and computers 80a, 80b, etc. can be thought of as the server where server 80a, 80b, etc. maintains the data that is then replicated in the client computers 820a, 820b, etc).
Claim 9 adds into claim 8 “wherein one of the parameters within the group simulated space that is controllable by the user that is a member of the user group is time, and wherein the user that is a member of the user group can speed up or slow down a rate at which time passes within the group simulated space” (Bertolami, [0080] - After a unified coordinate system is determined, and images are presented to a user based on the coordinate system, a decision may be made as to whether a resynchronization of the determined coordinate system is needed at block 575. As with method 400, user devices and/or an augmented reality system or application may be configured to periodically perform the some or all of the actions described in method 500 in order to maintain a synchronized coordinate system among user devices, or may be configured to perform the actions of method 500 after detecting a trigger or other event. In some embodiments, determining coarse and precise location information may not be required to resynchronize a coordinate system. A determination regarding whether or not resynchronization is to be performed may be made at any time, and may not be made each time an image is presented. Instead, such a determination may be made only on detection of a trigger or at periodic intervals. Any method or means of initiating or participating in a resynchronization of a coordinate system is contemplated. If resynchronization is to be performed, the method returns to block 510. Alternatively, the method may return to a different block if the determinations made in other blocks are not needed to resynchronize the coordinate system. If no resynchronization is to be performed, the method returns to block 570 to further present images to a user; [0086] - At block 660, a decision may be made as to whether a resynchronization of the determined coordinate system is needed or desired. Like the other methods described herein, user devices and/or an augmented reality system or application may be configured to periodically perform the actions described in method 600 in order to maintain a synchronized coordinate system among user devices and the augmented reality system or application. Alternatively, user devices and/or the augmented reality system or application may be configured to perform the actions of method 600 after detecting a trigger or other event. Any method or means of initiating or participating in a resynchronization of a coordinate system is contemplated. If resynchronization is to be performed, at block 670 a request for location information is transmitted to user devices from the augmented reality system or application. This request may be transmitted using any communications means, including wired and wireless communications. The method then returns to block 610. Alternatively, the method may return to a different block if the determinations made in other blocks are not needed to resynchronize the coordinate system. If no resynchronization is to be performed, the method returns to block 640 to further render images or determine image data for user devices). It is noted that the “resynchronization” can affect the rendering speed which can “speed up or slow down a rate at which time passes within the group simulated space.”
Claim 10 adds into claim 1 “wherein the remote server, when executing the server computer instructions, further causes the remote server to: enable the user that is a member of the user group to look through a first side of the group portal on a personal mobile device and interact with one or more of other users of the user group, virtual objects, or virtual events in the group simulated space while the user that is a member of the user group remains in the multi-dimensional fabric user interface and does not enter the group simulated space” (Bertolami, [0060] - These recipients of this information may be other augmented reality components operated by other users of an augmented reality system or application, and/or one or more servers or other computers that are part of or interact with an augmented reality system or application but are not user devices. In one embodiment, a designated user device is configured to determine a coordinate system for all users in an augmented reality system or application, and precise location information is transmitted to that device. In another embodiment, a server is configured to receive precise location information from all the user devices in a particular augmented reality system or application and determine a common coordinate system. Any particular device or group of devices may be designated for common coordinate system determinations, and all such embodiments are contemplated; [0094] - There are a variety of systems, components, and network configurations that may support an augmented reality system or application. For example, computing systems, communications systems, and detectors or cameras may be connected together by wired or wireless systems, by local networks, or by widely distributed networks. Currently, many networks are coupled to the Internet, which provides the infrastructure for widely distributed computing and encompasses many different networks; [0096] - Thus, the network infrastructure enables a host of network topologies such as client/server, peer-to-peer, or hybrid architectures... In a client/server architecture, particularly a networked system, a client is usually a computer that accesses shared network resources provided by another computer, e.g., a server. In the example of FIG. 7, computers 820a, 820b, etc. can be thought of as clients and computers 80a, 80b, etc. can be thought of as the server where server 80a, 80b, etc. maintains the data that is then replicated in the client computers 820a, 820b, etc).
Claim 11 adds into claim 1 “wherein the remote server, when executing the server computer instructions, further causes the remote server to: prevent a user that is not a member of the user group from looking through a first side of the group portal on a personal mobile device and interacting with one or more of other users of the user group, virtual objects, or virtual events in the group simulated space while the user that is not a member of the user group remains in the multi-dimensional fabric user interface” (Bertolami, [0060] - These recipients of this information may be other augmented reality components operated by other users of an augmented reality system or application, and/or one or more servers or other computers that are part of or interact with an augmented reality system or application but are not user devices. In one embodiment, a designated user device is configured to determine a coordinate system for all users in an augmented reality system or application, and precise location information is transmitted to that device. In another embodiment, a server is configured to receive precise location information from all the user devices in a particular augmented reality system or application and determine a common coordinate system. Any particular device or group of devices may be designated for common coordinate system determinations, and all such embodiments are contemplated; [0094] - There are a variety of systems, components, and network configurations that may support an augmented reality system or application. For example, computing systems, communications systems, and detectors or cameras may be connected together by wired or wireless systems, by local networks, or by widely distributed networks. Currently, many networks are coupled to the Internet, which provides the infrastructure for widely distributed computing and encompasses many different networks; [0096] - Thus, the network infrastructure enables a host of network topologies such as client/server, peer-to-peer, or hybrid architectures... In a client/server architecture, particularly a networked system, a client is usually a computer that accesses shared network resources provided by another computer, e.g., a server. In the example of FIG. 7, computers 820a, 820b, etc. can be thought of as clients and computers 80a, 80b, etc. can be thought of as the server where server 80a, 80b, etc. maintains the data that is then replicated in the client computers 820a, 820b, etc).
Claims 12-19 and 20 claim a method and a non-transitory readable storage medium based on the system of claims 1-11; therefore, they are rejected under a similar rationale.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to PHU K NGUYEN whose telephone number is (571)272-7645. The examiner can normally be reached M-F 8-5pm.
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/PHU K NGUYEN/Primary Examiner, Art Unit 2616