System and Methods for Identifying an Action of a Forklift Based on Sound Detection

• US 20180077509A1
• Filed: 09/06/2017
• Published: 03/15/2018
• Est. Priority Date: 09/13/2016
• Status: Active Grant

• Current Assignee: Walmart Apollo, LLC (WalMart Inc.)
• Original Assignee: Wal-Mart Stores Texas LLC (WalMart Inc.)
• Inventors: Jones, Matthew Allen, Vasgaard, Aaron James, Jones, Nicholaus Adam, Taylor, Robert James
• Granted Patent: US 10,070,238 B2
• Time in Patent Office: Days
• CPC Class Codes: H04R 1/406 microphones
• CPC Class Codes: H04R 27/00 Public address systems circuits for preventing acoustic reaction H04R3/02; circuits for distributing signals to loudspeakers H04R3/12; monitoring or testing arrangements for public address systems H04R29/007; amplifiers H03F
• CPC Class Codes: H04R 29/008 Visual indication of individual signal levels visual indication of stereophonic sound image H04S7/40
• CPC Class Codes: H04R 3/005 for combining the signals of two or more microphones specially adapted for hearing aids H04R25/407

Abstract

Described in detail herein are methods and systems for identifying actions performed by a forklift based on detected sounds in a facility. An array of microphones can be disposed in a facility. The microphones can detect various sounds and encode the sounds in an electrical signal and transmit the sounds to a computing system. The computing system can determine the sound signature of each sound and based on the sound signature the chronological order of the sounds and the time interval in between the sounds the computing system can determine the action being performed by the forklift which is causing the sounds.

Claims

1. A system for identifying actions of a forklift based on detected sounds produced by the forklift or an environment within which the forklift is operated, the system comprising:

an array of microphones disposed in a first area of a facility, the microphones being configured to detect sounds and output time varying electrical signals upon detection of the sounds; and

a computing system operatively coupled to the array of microphones, the computing system programmed to;

receive the time varying electrical signals associated with the sounds detected by at least a subset of the microphones; and

detect an operation being performed by the forklift based on parameters of the time varying electrical signals, a location of the subset of the microphones, and a time at which the time varying electrical signals are produced, wherein at least one of the parameters of the time varying electrical signals is indicative of whether a forklift is carrying a load.

2. The system in claim 1, wherein the microphones are further configured to detect intensities of the sounds and encode the intensities of the sound in the time varying electrical signals.

3. The system in claim 2, wherein the computing system is further programmed to locate the forklift based on based on the intensities of the sounds encoded in the time varying electrical signals.

4. The system in claim 1, wherein the computing system generates sound signatures for the sounds based on the time varying electric signals.

5. The system of claim 4, wherein at least one of the sound signatures correspond to one or more of:

a fork of the forklift being raised laden;

a fork of the forklift being raised empty;

a fork of the forklift being lowered laden, a fork of the forklift being lowered empty, a forklift being driven laden, a forklift being driven empty, a speed at which the forklift is being driven, and a problem with the operation of the forklift.

6. The system in claim 1, wherein the computing system determines a chronological order in which the time varying electrical signals associated with the sounds are received by the computing system.

7. The system in claim 1, wherein amplitudes and frequencies of the sounds detected by the subset of the microphones are encoded in the time varying electrical signals.

8. The system in claim 7, wherein the computing system determines sound signatures for the sounds based on the amplitude and the frequency encoded in the time varying electrical signals.

9. The system in claim 8, wherein the computing system is programmed to determine the activity of the forklift based on the sound signatures.

10. The system in claim 9, wherein the computing system is programmed to determine whether the activity corresponds to an expected activity of the forklift based on a location at which the forklift is detected, a time at which the activity is occurring, and a sequence of the sound signatures.

13. The method in claim 2, further comprising locating the forklift based on the intensities of the sounds encoded in the time varying electrical signals.

11. A method for identifying actions of a forklift based on detected sounds produced by the forklift or an environment within which the forklift is operated, the method comprising:

detecting sounds via an array of microphones disposed in a first area of a facility receiving, via a computing system operatively coupled to the array of the microphones, time varying electrical signals output by at least a subset of the microphones in response to detection of the sounds; and

detecting an operation being performed by the forklift based on parameters of the time vary electrical signals, a location of the subset of the microphones, and a time at which the time varying electrical signals are produced, wherein at least one of the parameters of the time varying electrical signals is indicative of whether a forklift is carrying a load.

12. The method in claim 11, further comprising:

detecting, via the microphones, intensities of the sounds; and

encoding the intensities of the sound in the time varying electrical signals.

14. The method in claim 11, further comprising generating, via the computing system, sound signatures for the sounds based on the time varying electric signals.

15. The method of claim 14, wherein at least one of the sound signatures correspond to one or more of:

a fork of the forklift being raised laden;

a fork of the forklift being raised empty;

a fork of the forklift being lowered laden, a fork of the forklift being lowered empty, a forklift being driven laden, a forklift being driven empty, a speed at which the forklift is being driven, and a problem with the operation of the forklift.

16. The method in claim 11, further comprising determining, via a computing system, a chronological order in which the time varying electrical signals associated with the sounds are received by the computing system.

17. The method in claim 11, further comprising:

detecting, via the microphones, amplitudes and frequencies of the sounds; and

encoding the amplitudes and frequencies in the time varying electrical signals.

18. The method in claim 17, further comprising determining, via a computing system, sound signatures for the sounds based on the amplitudes and the frequencies encoded in the time varying electrical signals.

19. The method in claim 18, further comprising determining, via a computing system, the activity of the forklift based on the sound signatures.

20. The method in claim 19, further comprising determining, via a computing system, whether the activity corresponds to an expected activity of the forklift based on a location at which the forklift is detected, a time at which the activity is occurring, and a sequence of the sound signatures.