Detailed Office 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 .
This office action is in response to the communication dated 10/15/24
Claims 1-27 are pending.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
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Claims 1-27 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-24 of U.S. Patent No.12,156,293. Although the claims at issue are not identical, they are not patentably distinct from each other because Although the claims at issue are not identical, they are not patentably distinct from each other. For example, a comparison made between claims 1, 10 and 19 of the instant application and claims 1 , 9 and 17 of the Patent reveal the claims at issue define essentially the same invention in different language. Thus, one of ordinary skill in the art would conclude that the invention defined in claims 1, 10, 19 at issue is an obvious variation of the invention defined in the claims 1, 9 and 17 of the Patent. Thus, examiner asserts the difference describe a subset of all possible conditions being monitored in the Patented claims 1, 9 and 17 These differences are not sufficient to render the claims patentably distinct and therefore a terminal disclaimer is required.
Dependent claims 2-9, 11-18 and 20-27 which dependent above discussed claims 1, 10 and 19 are similar with dependent claims 2-8, 10-16 and 18-24 of the Patent though with obvious minor variations and are rejected same rational.
Instant Application 18/915-737
1. An edge computing system, comprising: one or more processors configured with processor executable instructions to:
receive a sensory feed from an optical device, wherein the received sensory feed includes video data; process the received sensory feed to generate processed sensory feed data, wherein the processing includes clipping video data into frames; analyze the processed sensory feed data to generate analysis results that include a relative position of the optical device from surrounding objects; generate mapper output results based on the analysis results, wherein the mapper output results include virtual coordinates; request and receive information from a local image database, an image database application mesh, or a cloud image database, wherein the information includes salient points of interest; compare the generated mapper output results to the received information to identify a correlation between a feature included in the processed sensory feed and a feature included in the received information;
determine whether a confidence value associated with the identified correlation exceeds a threshold value; further process the processed sensory feed locally in the edge computing system to generate and send augmented information to a renderer in response to determining that the confidence value associated with the identified correlation exceeds the threshold value, wherein the augmented information includes overlay renderings and additional sensory data; and send the processed sensory feed to a cloud object recognizer for further processing in response to determining that the confidence value associated with the identified correlation does not exceed the threshold value.
2. The edge computing system of claim 1, wherein the sensory feed received from the optical device includes additional sensor data comprising temperature, motion, and accelerometer information.
3. The edge computing system of claim 1, wherein: the one or more processors are further configured to generate overlay renderings based on the augmented information; and the overlay renderings include wire frames of existing features and annotations.
4. The edge computing system of claim 1, wherein the one or more processors are configured to compare the generated mapper output results to the received information to identify the correlation between the feature included in the processed sensory feed and the feature included in the received information by performing operations that include: using a feature matcher to identify the feature included in the received processed sensory feed; and using a geometric verifier to verify the correlation.
5. The edge computing system of claim 4, wherein the one or more processors are configured to use the geometric verifier to verify the correlation by performing a geometric verification to determine whether the confidence value associated with the identified correlation meets a predetermined threshold value.
6. The edge computing system of claim 5, wherein the one or more processors are configured to forward the augmented information to an extended reality (XR) application for rendering on an XR display in response to determining that the confidence value associated with the identified correlation exceeds the threshold value.
7. The edge computing system of claim 1, wherein the information received from the local image database, the image database application mesh, or the cloud image database includes features extracted by a feature extractor in the edge computing system.
8. The edge computing system of claim 1, wherein the one or more processors include multiple processors operating in a computing mesh or application mesh.
9. The edge computing system of claim 1, wherein the one or more processors are configured to further process the processed sensory feed locally in the edge computing system to generate and send the augmented information to the renderer by: further processing the processed sensory feed locally in the edge computing system to generate and send augmented information that causes the renderer to prepare an extended reality (XR) image for display on an XR device in response to determining that the confidence value associated with the identified correlation exceeds the threshold value.
10. A method of generating extended reality (XR) data by one or more processors in an edge computing system, the method comprising: receiving a sensory feed from an optical device, wherein the received sensory feed includes video data; processing the received sensory feed to generate processed sensory feed data, wherein the processing includes clipping video data into frames; analyzing the processed sensory feed data to generate analysis results that include a relative position of the optical device from surrounding objects; generating mapper output results based on the analysis results, wherein the mapper output results include virtual coordinates; requesting and receiving information from a local image database, an image database application mesh, or a cloud image database, wherein the information includes salient points of interest; comparing the generated mapper output results to the received information to identify a correlation between a feature included in the processed sensory feed and a feature included in the received information; determining whether a confidence value associated with the identified correlation exceeds a threshold value; further processing the processed sensory feed locally in the edge computing system to generate and send augmented information to a renderer in response to determining that the confidence value associated with the identified correlation exceeds the threshold value, wherein the augmented information includes overlay renderings and additional sensory data; and sending the processed sensory feed to a cloud object recognizer for further processing in response to determining that the confidence value associated with the identified correlation does not exceed the threshold value.
11. The method of claim 10, wherein the sensory feed received from the optical device includes additional sensor data comprising temperature, motion, and accelerometer information.
12. The method of claim 10, further comprising generating overlay renderings based on the augmented information, wherein the overlay renderings include wire frames of existing features and annotations.
13. The method of claim 10, wherein comparing the generated mapper output results to the received information to identify the correlation between the feature included in the processed sensory feed and the feature included in the received information comprises performing operations that include: using a feature matcher to identify the feature included in the received processed sensory feed; and using a geometric verifier to verify the correlation.
14. The method of claim 13, wherein using the geometric verifier to verify the correlation comprises performing a geometric verification to determine whether the confidence value associated with the identified correlation meets a predetermined threshold value.
15. The method of claim 14, further comprising forwarding the augmented information to an XR application for rendering on an XR display in response to determining that the confidence value associated with the identified correlation exceeds the threshold value.
16. The method of claim 10, wherein the information received from the local image database, the image database application mesh, or the cloud image database includes features extracted by a feature extractor in the edge computing system.
17. The method of claim 10, wherein the one or more processors include multiple processors operating in a computing mesh or application mesh.
18. The method of claim 10, wherein further processing the processed sensory feed locally in the edge computing system to generate and send the augmented information to the renderer comprises: further processing the processed sensory feed locally in the edge computing system to generate and send augmented information that causes the renderer to prepare an extended reality (XR) image for display on an XR device in response to determining that the confidence value associated with the identified correlation exceeds the threshold value.
19. A non-transitory computer readable storage medium having stored thereon processor-executable software instructions configured to cause one or more processors in an edge computing system to perform operations comprising: receiving a sensory feed from an optical device, wherein the received sensory feed includes video data; processing the received sensory feed to generate processed sensory feed data, wherein the processing includes clipping video data into frames; analyzing the processed sensory feed data to generate analysis results that include a relative position of the optical device from surrounding objects; generating mapper output results based on the analysis results, wherein the mapper output results include virtual coordinates; requesting and receiving information from a local image database, an image database application mesh, or a cloud image database, wherein the information includes salient points of interest; comparing the generated mapper output results to the received information to identify a correlation between a feature included in the processed sensory feed and a feature included in the received information; determining whether a confidence value associated with the identified correlation exceeds a threshold value; further processing the processed sensory feed locally in the edge computing system to generate and send augmented information to a renderer in response to determining that the confidence value associated with the identified correlation exceeds the threshold value, wherein the augmented information includes overlay renderings and additional sensory data; and sending the processed sensory feed to a cloud object recognizer for further processing in response to determining that the confidence value associated with the identified correlation does not exceed the threshold value.
20. The non-transitory computer readable storage medium of claim 19, wherein the sensory feed received from the optical device includes additional sensor data comprising temperature, motion, and accelerometer information.
21. The non-transitory computer readable storage medium of claim 19, wherein the stored processor-executable instructions are configured to cause the one or more processors to perform operations further comprising generating overlay renderings based on the augmented information, wherein the overlay renderings include wire frames of existing features and annotations.
22. The non-transitory computer readable storage medium of claim 19, wherein the stored processor-executable instructions are configured to cause the one or more processors to perform operations such that comparing the generated mapper output results to the received information to identify the correlation between the feature included in the processed sensory feed and the feature included in the received information comprises performing operations that include: using a feature matcher to identify the feature included in the received processed sensory feed; and using a geometric verifier to verify the correlation.
23. The non-transitory computer readable storage medium of claim 22, wherein the stored processor-executable instructions are configured to cause the one or more processors to perform operations such that using the geometric verifier to verify the correlation comprises performing a geometric verification to determine whether the confidence value associated with the identified correlation meets a predetermined threshold value.
24. The non-transitory computer readable storage medium of claim 23, wherein the stored processor-executable instructions are configured to cause the one or more processors to perform operations further comprising forwarding the augmented information to an XR application for rendering on an XR display in response to determining that the confidence value associated with the identified correlation exceeds the threshold value.
25. The non-transitory computer readable storage medium of claim 19, wherein the information received from the local image database, the image database application mesh, or the cloud image database includes features extracted by a feature extractor in the edge computing system.
26. The non-transitory computer readable storage medium of claim 19, wherein the one or more processors include multiple processors operating in a computing mesh or application mesh.
27. The non-transitory computer readable storage medium of claim 19, wherein the stored processor-executable instructions are configured to cause the one or more processors to perform operations such that further processing the processed sensory feed locally in the edge computing system to generate and send the augmented information to the renderer comprises: further processing the processed sensory feed locally in the edge computing system to generate and send augmented information that causes the renderer to prepare an extended reality (XR) image for display on an XR device in response to determining that the confidence value associated with the identified correlation exceeds the threshold value.
Patent No.12156293
1. An edge computing system, comprising: one or more processors configured with processor executable instructions to:
receive a processed sensory feed from a user device, wherein the received processed sensory feed includes temperature and video data; analyze the received processed sensory feed to generate predictive analysis results; generate mapper output results based on the generated analysis results; request and receive information from one or more of a local image database, an image database application mesh, or a cloud image database; compare the generated mapper output results to the received information to identify a correlation between a feature included in the received processed sensory feed and a feature included in the received information; determine whether a confidence value associated with the identified correlation exceeds a threshold value; further process the received processed sensory feed locally in the edge computing system, and send the further processed sensory feed to the user device for rendering on an electronic display of the user device, in response to determining that the confidence value associated with the identified correlation exceeds the threshold value; and send the received processed sensory feed to a cloud component for further processing and sending to the user device for rendering in response to determining that the confidence value associated with the identified correlation does not exceed the threshold value.
2. The edge computing system of claim 1, wherein the one or more processors are included in an edge device.
3. The edge computing system of claim 1, wherein the one or more processors comprise multiple processors in multiple edge devices configured to operate in at least one of a computing mesh, an application mesh, or a connectivity mesh.
4. The edge computing system of claim 1, wherein the one or more processors are configured run at least one of a computing mesh, an application mesh, or a connectivity mesh in a container.
5. The edge computing system of claim 1, wherein the one or more processors are configured with processor executable instructions to: generate the analysis results, generate the mapper output results, and identify the correlation in a first processor in a first edge device in the edge computing system; and further process the received processed sensory feed in a second processor in a second edge device in the edge computing system.
6. The edge computing system of claim 1, wherein the one or more processors are configured with processor executable instructions to: generate the analysis results to include a relative position of the user device from surrounding objects identified in the processed sensory feed; generate the mapper output results to include virtual coordinates; and request and receive the information from one or more of the local image database, the image database application mesh, or the cloud image database to receive information including salient points of interest.
7. The edge computing system of claim 1, wherein the one or more processors are configured with processor executable instructions to further process the received processed sensory feed locally in the edge computing system in response to determining that the confidence value associated with the identified correlation exceeds the threshold value by: determining overlay renderings and additional sensory data; and generating augmented information based on the determined overlay renderings and additional sensory data.
8. The edge computing system of claim 7, wherein the one or more processors are configured with processor executable instructions to generate the augmented information to include: images of items and features that do not exist; wire frame of existing features; an annotation; and audio and visual confirmation information.
9. A method of offloading portions of an application from a user device to an edge device, the method comprising: receiving, in one or more processors in an edge computing system, a processed sensory feed from the user device, wherein the received processed sensory feed includes temperature and video data; analyzing, in the one or more processors in the edge computing system, the received processed sensory feed to generate predictive analysis results; generating, in the one or more processors in the edge computing system, mapper output results based on the generated analysis results; requesting and receiving, in the one or more processors in the edge computing system, information from one or more of a local image database, an image database application mesh, or a cloud image database; comparing, in the one or more processors in the edge computing system, the generated mapper output results to the received information to identify a correlation between a feature included in the received processed sensory feed and a feature included in the received information; determining, in the one or more processors in the edge computing system, whether a confidence value associated with the identified correlation exceeds a threshold value; further processing, in the one or more processors in the edge computing system, the received processed sensory feed locally in the edge computing system, and send the further processed sensory feed to the user device for rendering on an electronic display of the user device, in response to determining that the confidence value associated with the identified correlation exceeds the threshold value; and sending, by the one or more processors in the edge computing system, the received processed sensory feed to a cloud component for further processing and sending to the user device for rendering in response to determining that the confidence value associated with the identified correlation does not exceed the threshold value.
10. The method of claim 9, wherein the one or more processors in the edge computing system are included in an edge device.
11. The method of claim 9, wherein the one or more processors in the edge computing system include multiple processors in multiple edge devices configured to operate in at least one of a computing mesh, an application mesh, or a connectivity mesh.
12. The method of claim 9, further comprising run at least one of a computing mesh, an application mesh, or a connectivity mesh in a container.
13. The method of claim 9, wherein: generating the analysis results, generating the mapper output results, and identifying the correlation comprise generating the analysis results, generating the mapper output results, and identifying the correlation by a first processor in a first edge device in the edge computing system; and further processing the received processed sensory feed comprises further processing the received processed sensory feed by a second processor in a second edge device in the edge computing system.
14. The method of claim 9, wherein: analyzing the received processed sensory feed to generate the analysis results comprises analyzing the received processed sensory feed to generate the analysis results to include a relative position of the user device from surrounding objects identified in the processed sensory feed; generating the mapper output results based on the generated analysis results comprises generating the mapper output results to include virtual coordinates; and requesting and receiving the information from one or more of the local image database, the image database application mesh, or the cloud image database comprises requesting and receiving information that includes including salient points of interest from one or more of the local image database, the image database application mesh, or the cloud image database.
15. The method of claim 9, wherein further processing the received processed sensory feed locally in the edge computing system in response to determining that the confidence value associated with the identified correlation exceeds the threshold value comprises: determining overlay renderings and additional sensory data; and generating augmented information based on the determined overlay renderings and additional sensory data.
16. The method of claim 15, wherein generating augmented information based on the determined overlay renderings and additional sensory data comprises generating the augmented information to include: images of items and features that do not exist; wire frame of existing features; an annotation; and audio and visual confirmation information.
17. A non-transitory computer readable storage medium having stored thereon processor-executable software instructions configured to cause one or more processors in an edge computing system to perform operations comprising: receiving a processed sensory feed from a user device, wherein the received processed sensory feed includes temperature and video data; analyzing the received processed sensory feed to generate predictive analysis results; generating mapper output results based on the generated analysis results; requesting and receiving information from one or more of a local image database, an image database application mesh, or a cloud image database; comparing the generated mapper output results to the received information to identify a correlation between a feature included in the received processed sensory feed and a feature included in the received information; determining whether a confidence value associated with the identified correlation exceeds a threshold value; further processing the received processed sensory feed locally in the edge computing system, and sending the further processed sensory feed to the user device for rendering on an electronic display of the user device, in response to determining that the confidence value associated with the identified correlation exceeds the threshold value; and sending the received processed sensory feed to a cloud component for further processing and sending to the user device for rendering in response to determining that the confidence value associated with the identified correlation does not exceed the threshold value.
18. The non-transitory computer readable storage medium of claim 17, wherein the one or more processors in an edge computing system are included in an edge device.
19. The non-transitory computer readable storage medium of claim 17, wherein one or more processors in an edge computing system comprise multiple processors in multiple edge devices configured to operate in at least one of a computing mesh, an application mesh, or a connectivity mesh.
20. The non-transitory computer readable storage medium of claim 17, wherein the stored processor-executable instructions are configured to cause the one or more processors in an edge computing system to perform operations further comprising running at least one of a computing mesh, an application mesh, or a connectivity mesh in a container.
21. The non-transitory computer readable storage medium of claim 17, wherein the stored processor-executable instructions are configured to cause the one or more processors in an edge computing system to perform operations such that: generating the analysis results, generating the mapper output results, and identifying the correlation comprise generating the analysis results, generating the mapper output results, and identifying the correlation by a first processor in a first edge device in the edge computing system; and further processing the received processed sensory feed comprises further processing the received processed sensory feed by a second processor in a second edge device in the edge computing system.
22. The non-transitory computer readable storage medium of claim 17, wherein the stored processor-executable instructions are configured to cause the one or more processors in an edge computing system to perform operations such that: analyzing the received processed sensory feed to generate the analysis results comprises analyzing the received processed sensory feed to generate the analysis results to include a relative position of the user device from surrounding objects identified in the processed sensory feed; generating the mapper output results based on the generated analysis results comprises generating the mapper output results to include virtual coordinates; and requesting and receiving the information from one or more of the local image database, the image database application mesh, or the cloud image database comprises requesting and receiving information that includes including salient points of interest from one or more of the local image database, the image database application mesh, or the cloud image database.
23. The non-transitory computer readable storage medium of claim 17, wherein the stored processor-executable instructions are configured to cause the one or more processors in an edge computing system to perform operations such that further processing the received processed sensory feed locally in the edge computing system in response to determining that the confidence value associated with the identified correlation exceeds the threshold value comprises: determining overlay renderings and additional sensory data; and generating augmented information based on the determined overlay renderings and additional sensory data.
24. The non-transitory computer readable storage medium of claim 23, wherein the stored processor-executable instructions are configured to cause the one or more processors in an edge computing system to perform operations such that generating augmented information based on the determined overlay renderings and additional sensory data comprises generating the augmented information to include: images of items and features that do not exist; wire frame of existing features; an annotation; and audio and visual confirmation information.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ABDULLAHI ELMI SALAD whose telephone number is (571)272-4009. The examiner can normally be reached 9:30AM-6:PM.
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/ABDULLAHI E SALAD/Primary Examiner, Art Unit 2466
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