US 12,664,758 B2Granted

Detecting device component defects and generating corresponding recommendations using artificial intelligence techniques

AssigneeDell Products L.P.

InventorsRavi Shukla, Jeffrey Scott Vah, Wilson Tetsuia Kitsunai, Aaron Sanchez

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Abstract

Methods, apparatus, and processor-readable storage media for detecting device component defects and generating corresponding recommendations using artificial intelligence techniques are provided herein. An example computer-implemented method includes obtaining image data of one or more device components and user input pertaining to at least a portion of the device component(s); predicting at least one defect associated with the device component(s) by processing at least a portion of the image data and the user input using a first set of artificial intelligence techniques; determining, using a second set of artificial intelligence techniques, that the at least one predicted defect is repairable; generating recommendation(s) for repairing the defect(s) by processing, using the second set artificial intelligence techniques, the at least a portion of the image data, the at least a portion of the user input, and information pertaining to the defect(s); and performing automated actions based on the recommendation(s).

Claims20

Dependent claims

A computer-implemented method comprising:

obtaining image data of one or more device components and user input pertaining to at least a portion of the one or more device components;
predicting at least one defect associated with the one or more device components by processing at least a portion of the image data and at least a portion of the user input using a first set of one or more artificial intelligence techniques;
determining, using a second set of one or more artificial intelligence techniques, that the at least one predicted defect is repairable;
generating one or more recommendations for repairing the at least one predicted defect by processing, using the second set of one or more artificial intelligence techniques, the at least a portion of the image data, the at least a portion of the user input, and information pertaining to the at least one predicted defect;
and
performing one or more automated actions based at least in part on the one or more generated recommendations, wherein performing the one or more automated actions comprises one or more of (i) automatically training at least a portion of the first set of one or more artificial intelligence techniques using feedback related to the one or more generated recommendations, and (ii) automatically training at least a portion of the second set of one or more artificial intelligence techniques using the feedback related to the one or more generated recommendations;
wherein the method is performed by at least one processing device comprising a processor coupled to a memory.

4 more elements

A non-transitory processor-readable storage medium having stored therein program code of one or more software programs, wherein the program code when executed by at least one processing device causes the at least one processing device:

to obtain image data of one or more device components and user input pertaining to at least a portion of the one or more device components;
to predict at least one defect associated with the one or more device components by processing at least a portion of the image data and at least a portion of the user input using a first set of one or more artificial intelligence techniques;
to determine, using a second set of one or more artificial intelligence techniques, that the at least one predicted defect is repairable;
to generate one or more recommendations for repairing the at least one predicted defect by processing, using the second set of one or more artificial intelligence techniques, the at least a portion of the image data, the at least a portion of the user input, and information pertaining to the at least one predicted defect;
and
to perform one or more automated actions based at least in part on the one or more generated recommendations, wherein performing the one or more automated actions comprises one or more of (i) automatically training at least a portion of the first set of one or more artificial intelligence techniques using feedback related to the one or more generated recommendations, and (ii) automatically training at least a portion of the second set of one or more artificial intelligence techniques using the feedback related to the one or more generated recommendations.

3 more elements

An apparatus comprising:

at least one processing device comprising a processor coupled to a memory;
the at least one processing device being configured:
to obtain image data of one or more device components and user input pertaining to at least a portion of the one or more device components;
to predict at least one defect associated with the one or more device components by processing at least a portion of the image data and at least a portion of the user input using a first set of one or more artificial intelligence techniques;
to determine, using a second set of one or more artificial intelligence techniques, that the at least one predicted defect is repairable;
to generate one or more recommendations for repairing the at least one predicted defect by processing, using the second set of one or more artificial intelligence techniques, the at least a portion of the image data, the at least a portion of the user input, and information pertaining to the at least one predicted defect;
and
to perform one or more automated actions based at least in part on the one or more generated recommendations, wherein performing the one or more automated actions comprises one or more of (i) automatically training at least a portion of the first set of one or more artificial intelligence techniques using feedback related to the one or more generated recommendations, and (ii) automatically training at least a portion of the second set of one or more artificial intelligence techniques using the feedback related to the one or more generated recommendations.

5 more elements

Dependencies are inferred from the claim text.

Facts

Application: 18/422,797Filed 25 Jan 2024
Published: US 2025/0245813 A131 Jul 2025
Granted: 23 Jun 2026
Term ends: Not estimatedThe source records don’t support an estimate.

Classification14 codes

G06V 10/764
Using pattern recognition or machine learning: using classification, e.g. of video objects
G06T 7/0004
Inspection of images, e.g. flaw detection: industrial image inspection
G06T 7/0008
Industrial image inspection: checking presence/absence
G06T 11/60
Two-dimensional [2D] image generation: creating or editing images; Combining images with text