IP Library Granted Patent US 11,836,674
Granted Patent B2
US 11,836,674 · App. 17/464,313 · Granted Dec 5, 2023

Automated inspection system

Inventors: Brandon Johnsen (Rogers, AR); Terry Osbon (Fayetteville, AR); Riley Turben (Bentonville, AR); Joshua Bohling (Centerton, AR); Craig Trudo (Centerton, AR)
Assignee: Walmart Apollo, LLC
G06Q10/087G01N33/02G06F16/24564H04W4/35H04W4/38
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Quick Facts
Patent No.
US 11,836,674
App. No.
17/464,313
Granted
Dec 5, 2023
Kind
B2
Abstract

Examples of the disclosure provide for an automated inspection system. The system includes an inspection component implemented on at least one computing device with at least one sensor configured to capture data about a good; and a communication component communicatively coupled to the computing device and configured to receive information regarding regulations and quality control standards associated with the good, and transmit the information regarding the acceptability of a good to an inventory system.

Claims (55)

1. A computing system for inspecting one or more goods, the computing system comprising:

at least one sensor configured to scan the one or more goods, the one or more goods being perishable food items comprising at least one of fruits and vegetables;

a memory device storing data associated with one or more rule sets and computer-executable instructions, the one or more rule sets governing acceptable parameters of the one or more goods;

a database configured to store electronic identifying information associated with the one or more goods; and

a processor configured to execute the computer-executable instructions to:

obtain the electronic identifying information associated with the one or more goods from the database;

generate sensor data associated with a first good based on a scan of the one or more goods by the at least one sensor;

analyze the sensor data obtained by the at least one sensor in association with the first good of the one or more goods;

identify the first good of the one or more goods based on analysis, by the processor, of the sensor data in view of the electronic identifying information associated with the first good obtained from the database;

generate an inspection score for the first good using the one or more rule sets, the inspection score being one of a numerical character and an alphabetic character; and

based on a determination by the processor that the generated inspection score for the identified first good meets or exceeds a predetermined quality control threshold value, output a notification for the identified first good, the notification indicating that the identified first good is deemed acceptable by the computing system.

2. The computing system of claim 1 , wherein the processor is further configured to execute the computer-executable instructions to analyze the sensor data to generate one or more of a first recommendation for selecting the first good from the one or more goods, or a second recommendation for inspecting the first good.

3. The computing system of claim 1 , wherein the processor is further configured to identify context-specific data associated with the first good.

4. The computing system of claim 1 , wherein the processor is further configured to generate one or more observation metrics associated with the first good.

5. The computing system of claim 4 , wherein the processor is further configured to execute the computer-executable instructions to analyze the one or more observation metrics to generate a recommendation for storing the first good.

6. The computing system of claim 4 , wherein the processor is further configured to:

analyze the one or more rule sets to determine a first rule set; and

analyze one or more parameters included in the first rule set to generate one or more grades associated with the one or more observation metrics.

7. The computing system of claim 6 , wherein the processor is further configured to execute the computer-executable instructions to determine whether to modify the first rule set.

8. A computer-implemented method for inspecting one or more goods, the computer-implemented method comprising:

providing at least one sensor configured to scan the one or more goods, the one or more goods being perishable food items comprising at least one of fruits and vegetables;

providing a memory device storing data associated with one or more rule sets and computer-executable instructions, the one or more rule sets governing acceptable parameters of the one or more goods;

providing a database configured to store electronic identifying information associated with the one or more goods; and

via a processor configured to execute the computer-executable instructions:

obtaining the electronic identifying information associated with the one or more goods from the database;

generating sensor data associated with a first good based on a scan of the one or more goods by the at least one sensor;

analyzing the sensor data obtained by the at least one sensor in association with the first good of the one or more goods;

identifying the first good of the one or more goods based on analysis, by the processor, of the sensor data in view of the electronic identifying information associated with the first good obtained from the database;

generating an inspection score for the first good using the one or more rule sets, the inspection score being one of a numerical character and an alphabetic character; and

based on a determination by the processor that the generated inspection score for the identified first good meets or exceeds a predetermined quality control threshold value, outputting a notification for the identified first good, the notification indicating that the identified first good is deemed acceptable by the computing system.

9. The computer-implemented method of claim 8 , further comprising, via the processor executing the computer-executable instructions, analyzing the sensor data to generate one or more of a first recommendation for selecting the first good from the one or more goods, or a second recommendation for inspecting the first good.

10. The computer-implemented method of claim 8 , further comprising, via the processor executing the computer-executable instructions, identifying context-specific data associated with the first good.

11. The computer-implemented method of claim 8 , further comprising, via the processor executing the computer-executable instructions, generating one or more observation metrics associated with the first good.

12. The computer-implemented method of claim 11 , further comprising, via the processor executing the computer-executable instructions, analyzing the one or more observation metrics to generate a recommendation for storing the first good.

13. The computer-implemented method of claim 11 , further comprising, via the processor executing the computer-executable instructions,

analyzing the one or more rule sets to determine a first rule set;

analyzing one or more parameters included in the first rule set to generate one or more grades associated with the one or more observation metrics.

14. The computer-implemented method of claim 13 , further comprising, via the processor executing the computer-executable instructions, determining whether to modify the first rule set.

15. One or more computer storage media embodied with computer-executable instructions, the one or more computer storage media comprising:

an inspection component that, upon execution by at least one processor, is configured to:

obtain sensor data associated with a first good based on a scan of one or more goods by at least one sensor, the one or more goods being perishable food items comprising at least one of fruits and vegetables;

analyze the sensor data obtained by the at least one sensor in association with the first good of the one or more goods;

retrieve data associated with one or more rule sets governing acceptable parameters of the one or more goods;

obtain the electronic identifying information associated with the one or more goods from the database;

identify the first good of the one or more goods based on analysis, by the at least one processor, of the sensor data associated with the first good in view of the electronic identifying information associated with the first good;

generate an inspection score for the first good using the one or more rule sets, the inspection score being one of a numerical character and an alphabetic character; and

based on a determination by the at least one processor that the generated inspection score for the identified first good meets or exceeds a predetermined quality control threshold value, output a notification for the identified first good, the notification indicating that the identified first good is deemed acceptable by the computing system.

16. The one or more computer storage media of claim 15 , wherein the inspection component, upon execution by at least one processor, is configured to analyze the sensor data to generate one or more of a first recommendation for selecting the first good from the one or more goods, or a second recommendation for inspecting the first good.

17. The one or more computer storage media of claim 15 , wherein the inspection component, upon execution by at least one processor, is configured to identify context-specific data associated with the first good.

18. The one or more computer storage media of claim 15 , wherein the inspection component, upon execution by at least one processor, is configured to generate one or more observation metrics associated with the first good.

19. The one or more computer storage media of claim 18 , wherein the inspection component, upon execution by at least one processor, is configured to analyze the one or more observation metrics to generate a recommendation for storing the first good.

20. The one or more computer storage media of claim 18 , wherein the inspection component, upon execution by at least one processor, is configured to:

analyze the one or more rule sets to determine a first rule set;

analyze one or more parameters included in the first rule set to generate one or more grades associated with the one or more observation metrics; and

determine whether to modify the first rule set.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Oct 8, 2021
From: JOHNSEN, BRANDON; OSBON, TERRY; TURBEN, RILEY; BOHLING, JOSHUA; TRUDO, CRAIG
To: WALMART APOLLO, LLC
Reel/Frame 057738/0452 →
Continuity (3)
Continuation 15970300 · May 3, 2018
Provisional Application 62509945 · May 23, 2017
Related Publication 20210398065A1 · Dec 23, 2021
Cited By (1)
US 12,450,564