IP Library › Granted Patent US 12,026,766
Granted Patent B2
US 12,026,766 · App. 17/449,644 · Granted Jul 2, 2024

Method, medium, and system for analyzing products and determining alternatives using artificial intelligence

Inventors: Todd Russell Whitman (Bethany, CT); John P. Perrino (Hedgesville, WV); Robert Eugene Coon (Bossier City, LA); Robert Ryan Gavin (Chicago, IL); Gary L. Osburn (Bernalillo, NM)
Assignee: Kyndryl, Inc.
G06Q30/0631G06Q30/0641
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Quick Facts
Patent No.
US 12,026,766
App. No.
17/449,644
Granted
Jul 2, 2024
Kind
B2
Abstract

A product analyzing system and method may include receiving a scan of a product, retrieving a plurality of individual data of one or more individuals, determining how the product will affect the plurality of individual data of the one or more individuals and whether the product complies with the individual data of the one or more individuals, generating an alert corresponding to the product based on the determining, and sending the alert to a user device before purchase of the product.

Claims (82)

1. A method comprising:

receiving, by one or more processors of a computer system, a scan of a product;

retrieving, by the one or more processors of the computer system, a plurality of individual data corresponding to one or more individuals, the plurality of individual data including one or more medical conditions and an indication of one or more medications for at least one individual of the one or more individuals, wherein the one or more individuals is a defined group of individuals;

determining, by an artificial intelligence (AI) system of the one or more processors of the computer system, how the product will affect the plurality of individual data of each individual of the defined group of individuals including the one or more medical conditions and one or more medications and whether the product will comply with the plurality of individual data of the one or more individuals of the defined group of individuals, by processing, by the AI system of the one or more processors of the computer system the retrieved plurality of individual data;

correlating, by the AI system of the one or more processors of the computer system, the one or more medical conditions and one or more medications against potential negative and positive impacts of the products, wherein the potential negative and positive impacts comprise at least a negative side effect caused by an interaction between the product and the one or more medical conditions or the one or more medications;

dynamically reassigning processing resources from a shared pool of the one or more processors based on a monitored demand;

initially training the AI system using data from at least one database including a multiple factor analytics database, the at least one database having the correlations between the one or more medical conditions and one or more medications against potential negative and positive impacts of the products, the at least one database comprising information relating to the potential negative and positive impacts of the products for the range of possible medical conditions and personal preferences;

generating, by the one or more processors of the computer system, an alert corresponding to the product based on the determining;

sending, by the one or more processors of the computer system, the alert to a user device before purchase of the product;

generating, by the one or more processors of the computer system, a recommendation for an alternative product based on the determining;

receiving, by the one or more processors of the computer system, a selection choice between the product and the alternative product; and

further training the AI system to identify one or more preferred products of the one or more individuals, the training including iteratively processing, by the AI system, previously received selection choices to train, update, and optimize the AI system to identify the one or more preferred products based on correlations between previously generated alerts corresponding to the product and the previously received selection choices.

2. The method of claim 1 , further comprising:

retrieving, by the one or more processors of the computer system, a previously received selection choice made by a user, the previously received selection choice being between the product and the alternative product; and

executing the AI system of the one or more processors to train the computer system to identify a plurality of alternative products for recommendation based on the retrieved previously received selection choices made by the user.

3. The method of claim 1 , further comprising:

iteratively processing, by the AI system of the one or more processors of the computer system, updated previously received selection choices to train, update, and optimize the AI system to identify preferred products or preferred alternative products based on correlations between previously generated alerts corresponding to the product or previously generated recommendations of alternative products, and updated previously received selection choices.

4. The method of claim 1 , further comprising, receiving, by the one or more processors of the computer system, the plurality of individual data of the one or more individuals.

5. The method of claim 1 , further comprising:

receiving, by the one or more processors of the computer system, an updated plurality of individual data of the one or more individuals,

wherein the determining includes determining, by the one or more processors of the computer system, how the product will affect the updated plurality of individual data of the one or more individuals and whether the product will comply with the updated plurality of individual data of the one or more individuals.

6. The method of claim 1 , wherein the product is a grocery item, wherein the plurality of individual data includes medical data, dietary preferences, and personal goals of the one or more individuals, and wherein the medical data includes one or more medical data selected from a group of medical data consisting of medical health conditions of the one or more individuals, medications taken by the one or more individuals, lab test results for the one or more individuals, and allergies of the at least one individual,

wherein the dietary preferences include one or more dietary preferences selected from a group of dietary preferences consisting of religious dietary restrictions of the one or more individuals, vegan dietary restrictions of the one or more individuals, vegetarian dietary restrictions of the one or more individuals, diet plan restrictions of the one or more individuals, organic ingredient preferences of the one or more individuals, and natural ingredient preferences of the one or more individuals, and

wherein the personal goals include one or more personal goals selected from a group of goals consisting of weight loss goals of the one or more individuals, medical health condition improvement of the one or more individuals, and health condition maintenance of the one or more individuals.

7. The method of claim 1 , wherein the product is a grocery item, wherein the plurality of individual data includes medical data, dietary preferences, and personal goals of each individual of the defined group of individuals, and wherein the medical data includes one or more medical data selected from a group of medical data consisting of medical health conditions of each individual of the defined group of individuals, medications taken by each individual of the defined group of individuals, lab test results for each individual of the defined group of individuals, and allergies of each individual of the defined group of individuals,

wherein the dietary preferences include one or more dietary preferences selected from a group of dietary preferences consisting of religious dietary restrictions of each individual of the defined group of individuals, vegan dietary restrictions of each individual of the defined group of individuals, vegetarian dietary restrictions of each individual of the defined group of individuals, diet plan restrictions of each individual of the defined group of individuals, organic ingredient preferences of each individual of the defined group of individuals, and natural ingredient preferences of each individual of the defined group of individuals; and

wherein the personal goals include one or more personal goals selected from a group of goals consisting of weight loss goals of each individual of the defined group of individuals, medical health condition improvement of each individual of the defined group of individuals, and health condition maintenance of each individual of the defined group of individuals.

8. A computer system comprising:

one or more processors;

one or more memory devices coupled to the one or more processors; and

one or more computer readable storage devices coupled to one or more processors,

wherein the one or more storage devices contain program code executable by the one or more processors via the one or more memory devices to implement a method of analyzing products using an artificial intelligence (AI) system of the one or more processors of the computer system, the method comprising:

receiving, by one or more processors of the computer system, a scan of a product;

retrieving, by the one or more processors of the computer system, a plurality of individual data corresponding to one or more individuals, the plurality of individual data including one or more medical conditions and an indication of one or more medications for at least one individual of the one or more individuals, wherein the one or more individuals is a defined group of individuals;

determining, by the AI system of the one or more processors of the computer system, how the product will affect the plurality of individual data of each individual of the defined group of individuals including the one or more medical conditions and one or more medications and whether the product will comply with the plurality of individual data of the one or more individuals of the defined group of individuals, by processing, by the AI system of the one or more processors of the computer system the retrieved plurality of individual data;

correlating, by the AI system of the one or more processors of the computer system, the one or more medical conditions and one or more medications against potential negative and positive impacts of the products, wherein the potential negative and positive impacts comprise at least a negative side effect caused by an interaction between the product and the one or more medical conditions or the one or more medications;

dynamically reassigning processing resources from a shared pool of the one or more processors based on a monitored demand;

initially training the AI system using data from at least one database including a multiple factor analytics database, the at least one database having the correlations between the one or more medical conditions and one or more medications against potential negative and positive impacts of the products, the at least one database comprising information relating to the potential negative and positive impacts of the products for the range of possible medical conditions and personal preferences;

generating, by the one or more processors of the computer system, an alert corresponding to the product based on the determining;

sending, by the one or more processors of the computer system, the alert to a user device before purchase of the product;

generating, by the one or more processors of the computer system, a recommendation for an alternative product based on the determining;

receiving, by the one or more processors of the computer system, a selection choice between the product and the alternative product; and

further training the AI system to identify one or more preferred products of the one or more individuals, the training including iteratively processing, by the AI system, previously received selection choices to train, update, and optimize the AI system to identify the one or more preferred products based on correlations between previously generated alerts corresponding to the product and the previously received selection choices.

9. The computer system of claim 8 , wherein the method further comprises:

receiving, by the one or more processors of the computer system, an updated plurality of individual data of the one or more individuals,

wherein the determining includes determining, by the one or more processors of the computer system, how the product will affect the updated plurality of individual data of the one or more individuals and whether the product will comply with the updated plurality of individual data of the one or more individuals.

10. The computer system of claim 8 , the method further comprising:

retrieving, by the one or more processors of the computer system, a previously received selection choice made by a user, the previously received selection choice being between the product and the alternative product; and

executing the AI system of the one or more processors to train the computer system to identify a plurality of alternative products for recommendation based on the retrieved previously received selection choices made by the user.

11. The computer system of claim 8 , the method further comprising:

iteratively processing, by the AI system of the one or more processors of the computer system, previously received selection choices to train, update, and optimize the AI system to identify preferred alternative products based on correlations between previously generated alerts corresponding to previously generated recommendations of alternative products and previously received selection choices.

12. A computer program product, comprising a computer readable hardware storage device storing a computer readable program code, the computer readable program code comprising an algorithm that when executed by one or more processors of a computer system implements a method for analyzing products using an artificial intelligence (AI) system of the one or more processors of the computer system, the method comprising:

receiving, by one or more processors of a computer system, a scan of a product;

retrieving, by the one or more processors of the computer system, a plurality of individual data corresponding to one or more individuals, the plurality of individual data including one or more medical conditions and an indication of one or more medications for at least one individual of the one or more individuals, wherein the one or more individuals is a defined group of individuals;

determining, by the AI system of the one or more processors of the computer system, how the product will affect the plurality of individual data of each individual of the defined group of individuals including the one or more medical conditions and one or more medications and whether the product will comply with the plurality of individual data of the one or more individuals of the defined group of individuals, by processing, by the AI system of the one or more processors of the computer system the retrieved plurality of individual data;

correlating, by the AI system of the one or more processors of the computer system, the one or more medical conditions and one or more medications against potential negative and positive impacts of the products, wherein the potential negative and positive impacts comprise at least a negative side effect caused by an interaction between the product and the one or more medical conditions or the one or more medications;

dynamically reassigning processing resources from a shared pool of the one or more processors based on a monitored demand;

initially training the AI system using data from at least one database including a multiple factor analytics database, the at least one database having the correlations between the one or more medical conditions and one or more medications against potential negative and positive impacts of the products, the at least one database comprising information relating to the potential negative and positive impacts of the products for the range of possible medical conditions and personal preferences;

generating, by the one or more processors of the computer system, an alert corresponding to the product based on the determining;

sending, by the one or more processors of the computer system, the alert to a user device before purchase of the product;

generating, by the one or more processors of the computer system, a recommendation for an alternative product based on the determining;

receiving, by the one or more processors of the computer system, a selection choice between the product and the alternative product; and

further training the AI system to identify one or more preferred products of the one or more individuals, the training including iteratively processing, by the AI system, previously received selection choices to train, update, and optimize the AI system to identify the one or more preferred products based on correlations between previously generated alerts corresponding to the product and the previously received selection choices.

13. The computer program product of claim 12 , wherein the method further comprises:

receiving, by the one or more processors of the computer system, an updated plurality of individual data of the one or more individuals,

wherein the determining includes determining, by the one or more processors of the computer system, how the product will affect the updated plurality of individual data of the one or more individuals and whether the product will comply with the updated plurality of individual data of the one or more individuals.

14. The computer program product of claim 12 , the method further comprising:

retrieving, by the one or more processors of the computer system, a previously received selection choice made by a user, the previously received selection choice being between the product and the alternative product; and

executing the AI system of the one or more processors of the computer system to train the computer system to identify a plurality of alternative products for recommendation based on the retrieved previously received selection choices made by the user.

15. The computer program product of claim 12 , the method further comprising:

iteratively processing, by the AI system of the one or more processors of the computer system, previously received selection choices to train, update, and optimize the AI system to identify preferred alternative products based on correlations between previously generated alerts corresponding to previously generated recommendations of alternative products, and previously received selection choices.

16. The computer program product of claim 12 , wherein the product is a grocery item, wherein the plurality of individual data includes medical data, dietary preferences, and personal goals of the one or more individuals, and wherein the medical data includes one or more medical data selected from a group of medical data consisting of medical health conditions of the one or more individuals, medications taken by the one or more individuals, lab test results for the one or more individuals, and allergies of the at least one individual,

wherein the dietary preferences include one or more dietary preferences selected from a group of dietary preferences consisting of religious dietary restrictions of the one or more individuals, vegan dietary restrictions of the one or more individuals, vegetarian dietary restrictions of the one or more individuals, diet plan restrictions of the one or more individuals, organic ingredient preferences of the one or more individuals, and natural ingredient preferences of the one or more individuals, and

wherein the personal goals include one or more personal goals selected from a group of goals consisting of weight loss goals of the one or more individuals, medical health condition improvement of the one or more individuals, and health condition maintenance of the one or more individuals.

17. The computer system of claim 8 , wherein the product is a grocery item, wherein the plurality of individual data includes medical data, dietary preferences, and personal goals of the one or more individuals, and wherein the medical data includes one or more medical data selected from a group of medical data consisting of medical health conditions of the one or more individuals, medications taken by the one or more individuals, lab test results for the one or more individuals, and allergies of the at least one individual,

wherein the dietary preferences include one or more dietary preferences selected from a group of dietary preferences consisting of religious dietary restrictions of the one or more individuals, vegan dietary restrictions of the one or more individuals, vegetarian dietary restrictions of the one or more individuals, diet plan restrictions of the one or more individuals, organic ingredient preferences of the one or more individuals, and natural ingredient preferences of the one or more individuals, and

wherein the personal goals include one or more personal goals selected from a group of goals consisting of weight loss goals of the one or more individuals, medical health condition improvement of the one or more individuals, and health condition maintenance of the one or more individuals.

18. The method of claim 1 , wherein initially training the AI system comprises using data corresponding to the plurality of individual data of the one or more individuals of the defined group of individuals including medical data, dietary preferences, and personal goals of the one or more individuals of the defined group of individuals, wherein the medical data includes the indication of the one or more medications.

19. The computer system of claim 8 , wherein the initially training the AI system includes using data corresponding to the plurality of individual data of the one or more individuals of the defined group of individuals including medical data, dietary preferences, and personal goals of the one or more individuals of the defined group of individuals, wherein the medical data includes the indication of the one or more medications.

20. The computer system of claim 8 , wherein the product is a grocery item, wherein the plurality of individual data includes medical data, dietary preferences, and personal goals of each individual of the defined group of individuals, and wherein the medical data includes one or more medical data selected from a group of medical data consisting of medical health conditions of each individual of the defined group of individuals, medications taken by each individual of the defined group of individuals, lab test results for each individual of the defined group of individuals, and allergies of each individual of the defined group of individuals,

wherein the dietary preferences include one or more dietary preferences selected from a group of dietary preferences consisting of religious dietary restrictions of each individual of the defined group of individuals, vegan dietary restrictions of each individual of the defined group of individuals, vegetarian dietary restrictions of each individual of the defined group of individuals, diet plan restrictions of each individual of the defined group of individuals, organic ingredient preferences of each individual of the defined group of individuals, and natural ingredient preferences of each individual of the defined group of individuals; and

wherein the personal goals include one or more personal goals selected from a group of goals consisting of weight loss goals of each individual of the defined group of individuals, medical health condition improvement of each individual of the defined group of individuals, and health condition maintenance of each individual of the defined group of individuals.

Assignments (2)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Nov 18, 2021
From: INTERNATIONAL BUSINESS MACHINES CORPORATION
To: KYNDRYL, INC.
Reel/Frame 058213/0912 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Sep 30, 2021
From: WHITMAN, TODD RUSSELL; PERRINO, JOHN P.; COON, ROBERT EUGENE; GAVIN, ROBERT RYAN; OSBURN, GARY L.
To: INTERNATIONAL BUSINESS MACHINES CORPORATION
Reel/Frame 057663/0098 →