Codeless anchor generation for detectable features in an environment
A client device that includes a camera and an extended reality client application program is employed by a user in a physical space, such as an industrial or campus environment. The user aims the camera within the mobile device at a real-world asset, such as a computer system, classroom, or vehicle. The client device acquires a digital image via the camera and detects textual and/or pictorial content included in the acquired image that corresponds to one or more anchors. The client device queries a data intake and query system for asset content associated with the detected anchors. Upon receiving the asset content from the data intake and query system, the client device generates visualizations of the asset content and presents the visualizations via a display device.
1. A computer-implemented method, comprising:
identifying, by a mobile device from first acquired image data, an uncoded feature that is (i) detectable within a real-world environment, (ii) located at a first location within the real-world environment, and (iii) includes a reference image;
identifying asset content associated with a real-world asset, wherein:
a data intake and query system does not include a preexisting association between the asset content and the uncoded feature,
identifying the asset content includes defining a first position of the asset content in reference to the first location, and
the asset content comprises one or more visualizations that include real-time data associated with the real-world asset;
generating a triggering association between the uncoded feature and the asset content;
encrypting the reference image to generate an encrypted reference image;
transmitting, from the mobile device to an asset store server, the encrypted reference image;
receiving, by the mobile device from the asset store server, a link for the encrypted reference image;
transmitting, from the mobile device to the data intake and query system, the link to the encrypted reference image; and
causing the triggering association to be stored as a first triggering association at the data intake and query system, wherein, upon a device detecting the uncoded feature in second acquired image data, the first triggering association causes the device to display, at the first position, at least a portion of the asset content in an extended-reality (XR) environment.
2. The computer-implemented method of claim 1 , wherein the uncoded feature comprises at least one of a textual feature or a pictorial feature.
3. The computer-implemented method of claim 1 , wherein at least a portion of the real-world asset is present in the acquired image data.
4. The computer-implemented method of claim 1 , further comprising:
performing an optical character recognition (OCR) process on at least a portion of the acquired image data to identify a text string visible in the acquired image data,
wherein the uncoded feature comprises the text string.
5. The computer-implemented method of claim 1 , further comprising:
performing a perspective correction on a first portion of the acquired image data to project the first portion onto a virtual surface that is parallel to the device; and
performing an optical character recognition (OCR) process on the first portion to identify a text string visible in the acquired image data,
wherein the uncoded feature comprises the text string.
6. The computer-implemented method of claim 1 , further comprising:
performing an image analysis process on a first portion of the acquired image data to identify a symbol visible in the acquired image data,
wherein the uncoded feature comprises the symbol.
7. The computer-implemented method of claim 1 , further comprising:
performing a perspective correction on a first portion of the acquired image data to project the first portion onto a virtual surface that is parallel to the device; and
performing an image analysis process on the first portion to identify a symbol visible in the acquired image data,
wherein the uncoded feature comprises the symbol.
8. The computer-implemented method of claim 1 , wherein the data intake and query system is operable to:
transmit, to the asset store server, the link to the encrypted reference image;
receive the encrypted reference image from the asset store server;
decrypt the encrypted reference image; and
store the reference image in a key-value store in the data intake and query system.
9. The method of claim 1 , wherein the real-time data comprises one or more streams of events received in real-time from the real-world asset.
10. One or more non-transitory computer-readable storage media including instructions that, when executed by one or more processors, cause the one or more processors to perform steps of:
identifying, by a mobile device from first acquired image data, an uncoded feature that is (i) detectable within a real-world environment, (ii) located at a first location within the real-world environment, and (iii) includes a reference image;
identifying asset content associated with a real-world asset, wherein:
a data intake and query system does not include a preexisting association between the asset content and the uncoded feature,
identifying the asset content includes defining a first position of the asset content in reference to the first location, and
the asset content comprises one or more visualizations that include real-time data associated with the real-world asset;
generating a triggering association between the uncoded feature and the asset content;
encrypting the reference image to generate an encrypted reference image;
transmitting, from the mobile device to an asset store server, the encrypted reference image;
receiving, by the mobile device from the asset store server, a link for the encrypted reference image;
transmitting, from the mobile device to the data intake and query system, the link to the encrypted reference image; and
causing the triggering association to be stored as a first triggering association at the data intake and query system, wherein, upon a device detecting the uncoded feature in second acquired image data, the first triggering association causes the device to display, at the first position, at least a portion of the asset content in an extended-reality (XR) environment.
11. The one or more non-transitory computer-readable storage media of claim 10 , further comprising instructions that, when executed by the one or more processors, cause the one or more processors to perform the steps of:
performing an optical character recognition (OCR) process on at least a portion of the acquired image data to identify a text string visible in the acquired image data,
wherein the uncoded feature comprises the text string.
12. The one or more non-transitory computer-readable storage media of claim 10 , further comprising instructions that, when executed by the one or more processors, cause the one or more processors to perform the steps of:
performing a perspective correction on a first portion of the acquired image data the first portion onto a virtual surface that is parallel to the device; and
performing an optical character recognition (OCR) process on the first portion to identify a text string visible in the acquired image data,
wherein the uncoded feature comprises the text string.
13. The one or more non-transitory computer-readable storage media of claim 10 , further comprising instructions that, when executed by the one or more processors, cause the one or more processors to perform the steps of:
performing an image analysis process on a first portion of the acquired image data to identify a symbol visible in the acquired image data,
wherein the uncoded feature comprises the symbol.
14. The one or more non-transitory computer-readable storage media of claim 10 , further comprising instructions that, when executed by the one or more processors, cause the one or more processors to perform the steps of:
performing a perspective correction on a first portion of the acquired image data to project the first portion onto a virtual surface that is parallel to the device; and
performing an image analysis process on the first portion to identify a symbol visible in the acquired image data,
wherein the uncoded feature comprises the symbol.
15. A system, comprising:
a memory that includes instructions; and
a processor that is coupled to the memory and, when executing the instructions, is configured to:
identify, from first acquired image data, an uncoded feature that is (i) detectable within a real-world environment, (ii) located at a first location within the real-world environment, and (iii) includes a reference image;
identify asset content associated with a real-world asset, wherein:
a data intake and query system does not include a preexisting association between the asset content and the uncoded feature,
identifying the asset content includes defining a first position of the asset content in reference to the first location, and
the asset content comprises one or more visualizations that include real-time data associated with the real-world asset;
generate a triggering association between the uncoded feature and the asset content; and
encrypt the reference image to generate an encrypted reference image;
transmit, to an asset store server, the encrypted reference image;
receive, from the asset store server, a link for the encrypted reference image;
transmit, to the data intake and query system, the link to the encrypted reference image;
cause the triggering association to be stored as a first triggering association at the data intake and query system, wherein, upon a device detecting the uncoded feature in second acquired image data, the first triggering association causes the device to display, at the first position, at least a portion of the asset content in an extended-reality (XR) environment.
16. The system of claim 15 , wherein the data intake and query system is operable to:
transmit, to the asset store server, the link to the encrypted reference image;
receive the encrypted reference image from the asset store server;
decrypt the encrypted reference image; and
store the reference image in a key-value store in the data intake and query system.