Haier US Appliance Solutions, Inc.

General Electric Company

Khalid Jamal Mashal

Je Kwon Yoon

Hoyoung Lee

Hyeonsoo Moon

JaeHyo Lee

Nemetalla Salameh

Suzy Kwak

Myunggeon Chung

John Alexander Gardner

Christopher Styn

Alexander Boris Leibman

Jeonghoon Lee

David Scott Dunn

Wonmyung Seo

Seung-Yeong Park

Lorina June White

Jose Efren Rodriguez Munoz

Martin Scott Mershon

Juan Manuel Huerta

Geoffrey Lee Ranard

Alexis Christina Taylor

Austin Horn

Noushin Mir

Joseph Michael Hauser

Jonah Connelly

Minsu Kim

Oluwatosin Fagbuyi

An appliance, system, and method for operating an appliance and determining presence of water softener at water provided to an appliance is provided. The system is configured to obtain a first water hardness value; obtain a second water hardness value based on a location of the appliance; determine a ratio of the first water hardness value and the second water hardness value; compare the ratio of the first water hardness value and the second water hardness value to a threshold limit; transmit a first water hardness signal when the threshold limit is exceeded, wherein the first water hardness signal corresponds to the first water hardness value; transmit, to the database storage device, a second water hardness signal when the ratio is within the threshold limit; and adjust operation of the appliance based on whether the first water hardness signal or the second water hardness signal is transmitted.

System and method for determining presence of water softener

A method of operating a washing machine appliance may include obtaining one or more images of the washing machine appliance from a camera assembly of a remote device spaced apart from the cabinet. The method may also include receiving a plurality of angle readings from the remote device and determining a position of the remote device relative to the washing machine appliance based on the plurality of angle readings. The method may further include determining a set camera angle for the camera assembly is met based on the determined position of the remote device. The method may still further include analyzing at least one obtained image using a machine learning image recognition process, estimating a load attribute of a load of clothes within the washing machine appliance based on the analysis, and directing a wash cycle within the washing machine appliance based on the estimated load attribute.

Systems and methods using image recognition processes and determined device orientation for improved operation of a laundry appliance

A method may include obtaining one or more images of the washing machine appliance from a camera assembly of a remote device and detecting a fiducial reference on a front portion of the washing machine appliance within the one or more images. The method may also include comparing the detected fiducial reference to a two-dimensional reference shape in an obtained image of the images and determining a set camera angle for the camera assembly is met based on the comparison in the obtained image. The method may further include analyzing the obtained image using a machine learning image recognition process and estimating a load attribute of a load of clothes within the washing machine appliance based on the analysis. The method may still further include directing a wash cycle within the washing machine appliance based on the estimated load attribute.

Systems and methods using image recognition processes for improved operation of a laundry appliance

A washing machine appliance may include a wash tub, a wash basket, a dispensing assembly, a water hardness sensor, a camera assembly, and a controller. The wash tub may be positioned within a cabinet. The water hardness sensor may be mounted in fluid communication with the wash tub. The camera assembly may be spaced apart from the wash tub. The controller may be communicatively coupled to the water hardness sensor and the camera assembly. The controller may be configured to direct a washing operation. The washing operation may include identifying a wash additive provided to the washing machine appliance, determining a water hardness level of water provided to the washing machine appliance, determining a cycle additive volume based on the identified wash additive and the determined water hardness level, and dispensing the determined cycle additive volume within the wash tub.

Washing machine appliance and methods for varying dispensing based on water hardness

A washing machine appliance includes a wash basket that is rotatably mounted within a wash tub and that defines a wash chamber for receiving a load of clothes. A dispensing assembly selectively dispenses wash fluid through a discharge nozzle into the wash tub and a camera assembly is used to monitor the wash fluid and diagnose issues related to the detergent quantity. Specifically, a controller of the washing machine appliance uses the camera assembly to obtain one or more images of the load of clothes as fresh water is dispensed to determine whether detergent was added manually. The controller further determines whether a smart dispense feature is activated or deactivated and implements a responsive action in response to determining that either 1) detergent is present and the smart dispense feature is activated or 2) detergent is not present and the smart dispense feature is deactivated.

Systems and methods for using artificial intelligence for detergent diagnostics in a washing machine appliance

A washing machine appliance includes a wash basket that is rotatably mounted within a wash tub and that defines a wash chamber for receiving a load of clothes. A camera assembly is used to monitor articles for washing within the wash basket. Specifically, a controller of the washing machine appliance uses the camera assembly to obtain a reference image and one or more test images, which utilize image recognition to assess turn-over of the articles for washing during a given wash cycle. When turn-over performance is inadequate, a controller may adjust one or more operating parameters of the wash cycle to improve performance. Turn-over performance of the wash cycle is determined to be adequate once the image recognition process fails to find adequate correlation between the reference image and the test image a predetermined number of times.

Systems and methods for monitoring turn-over performance

An appliance, a controller, and a method for dispensing fluid are provided. The appliance including a fluid station configured to dispense water, cleaning agent, or a combination thereof, and a signal receiver device configured to receive signals from a user. A controller is operably coupled to the signal receiver device. The controller is configured to detect, via the signal receiver device, a gesture signal corresponding to a desired operating mode of the appliance, and command a function at the washing machine appliance based on the gesture signal.

Gesture control method and system for fluid dispensing apparatus

A washing machine appliance includes a wash basket that is rotatably mounted within a wash tub and that defines a wash chamber for receiving a load of clothes. A water supply adds water to the wash tub during a fill cycle and a camera assembly is used to monitor the water level. Specifically, the camera assembly obtains one or more images of the wash chamber during and/or after a fill cycle and a controller analyzes the images using a machine learning image recognition process to determine when the water within the wash tub has reached a predetermined water level, e.g., optimized based on load size or other load parameters. If the water in the wash tub is below or above the predetermined water level, the controller may implement responsive action, e.g., by adjusting at least one operating parameter of the washing machine appliance.

Method of using image recognition processes for improved operation of a laundry appliance

A washing machine appliance includes a camera assembly mounted in view of a wash chamber for obtaining images of the wash chamber. The lens of the camera assembly is positioned adjacent a water outlet of a water dispenser and a controller is configured to facilitate an automated cleaning method for the camera assembly, the method including obtaining one or more images of the wash chamber using the camera assembly, analyzing the one or more images to determine an image quality, determining that the image quality has dropped below a quality threshold, and operating the water dispenser to perform a lens cleaning operation in response to determining that the image quality has dropped below the quality threshold.

Automated lens cleaning for a camera assembly based on image recognition in a washing machine appliance

A laundry appliance includes a basket rotatably mounted within a cabinet and defining a chamber configured for receiving a load of clothes, and a camera assembly mounted within the cabinet in view of the chamber. A controller of the laundry appliance implements a method for detecting living things in the chamber and initiates a responsive action, for example, by disturbing the chamber by adjusting at least one operating parameter of the laundry appliance, obtaining one or more images of the chamber using the camera assembly, and determining that there is movement in the chamber based at least in part on the one or more images using an image processing algorithm and a machine learning image recognition process.

Child detection algorithm for a laundry appliance

A laundry appliance, such as a washing machine or dryer appliance, includes a basket that is rotatably mounted within a tub and that defines a chamber for receiving a load of clothes. A camera assembly is mounted within the tub for taking images of the load of clothes and a controller is operably coupled to the camera assembly for determining that a limited access mode is activated, receiving a start command for an operating cycle, obtaining and transmitting images or a live stream of the chamber to a remote device, and receiving user input related to a responsive action, such as a cycle authorization or operating parameter adjustment.

System and method for remote monitoring and control of a laundry appliance

A laundry appliance includes a basket that is rotatably mounted within a cabinet and that defines a chamber for receiving a load of clothes. A camera assembly is mounted within the cabinet for taking images of the chamber and a controller obtains an image of the chamber when the basket is empty and not rotating. The image is analyzed using an autoencoder neural network process to determine an image quality and a responsive action is implemented when an image quality drops below a quality threshold.

Image quality detection for a camera assembly in a laundry appliance

A washing machine appliance includes a wash basket that is rotatably mounted within a wash tub and that defines a wash chamber for receiving a load of clothes. A basket speed sensor monitors the speed of the wash basket and a camera assembly is mounted within the wash tub for taking images of the load of clothes during and/or after a wash or rinse cycle. A controller determines the basket speed, adjusts a frame rate of the camera assembly to match the basket speed, obtains a still image from the camera assembly, analyzes the image using a machine learning image recognition process to determine a remaining moisture content (RMC) of the load of clothes, and adjusts at least one operating parameter of the washing machine appliance based on the remaining moisture content, e.g., such as ending the drain cycle when a target RMC is reached.

A method of operating a washing machine appliance may include obtaining one or more images of an external basket spaced apart from the washing machine appliance from a camera assembly and analyzing an obtained image of the one or more images using an image recognition process to estimate a fill level of a load of clothes within the external basket. The method may further include matching the estimated fill level to an estimated load size and directing a wash cycle within the washing machine appliance based on the estimated load size.

Systems and methods using image recognition processes and determined device orientation for laundry load size determinations

A washing machine appliance includes a wash basket that is rotatably mounted within a wash tub and that defines a wash chamber for receiving a load of clothes. A motor assembly selectively rotates the wash basket, a drain pump assembly selectively drains wash fluid from the wash tub, and a camera assembly is used to monitor an out-of-balance value to minimize out-of-balance issues. Specifically, a controller of the washing machine appliance uses the camera assembly to obtain one or more images of the wash chamber, analyze the one or more images using a machine learning image recognition process to determine the out-of-balance value of the load of clothes in the wash basket, and perform a cloth redistribution process based at least in part on determining that the out-of-balance value is greater than a predetermined out-of-balance threshold.

Growing community of inventors

Louisville, KY, United States of America

Khalid Jamal Mashal