Abstract: A laundry treatment appliance includes a cabinet; a wash tub; a wash basket; and a controller provided within the cabinet to direct a laundry operation. The laundry operation includes receiving a plurality of wash requests from a plurality of unique users, wherein each wash request of the plurality of wash requests comprises an image of a unique laundry load; analyzing, by one or more computing devices using a machine learning image recognition model, each image to evaluate one or more laundry load characteristics of a first unique laundry load and a second unique laundry load; matching a first unique user and a second unique user from the plurality of users, the first user and the second user having a matching laundry load characteristic from the one or more laundry load characteristics; and generating a joint washing cycle subsequent to matching the first and second unique users.

Abstract: A washing machine appliance or method of the same may include obtaining one or more images of a container in which a wash additive is stowed from a camera assembly of a remote device spaced apart from a cabinet of the washing machine appliance. The method may also include determining a position of the remote device relative to the container and analyzing an obtained image of the one or more images using an image recognition process to identify the wash additive. The method may further include directing a wash cycle within the washing machine appliance based on the identified wash additive.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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 is mechanically coupled to the wash basket for selectively rotating the wash basket and a camera assembly is mounted within the cabinet in view of the wash chamber. A controller is configured to obtain a first image of the load of clothes using the camera assembly, operate the motor assembly to tumble the load of clothes, obtain a second image of the load of clothes using the camera assembly, analyze the first image and the second image using an image recognition process to identify one or more outlier garments, and implement a responsive action in response to identifying the one or more outlier garments.

Abstract: 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.

Abstract: 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.

Abstract: 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 load of clothes and diagnose the presence of excessive bubbles after a wash cycle. Specifically, a controller of the washing machine appliance uses the camera assembly to obtain one or more images of the load of clothes after the drain phase of the wash cycle and analyzes the one or more images using a machine learning image recognition process to determine a bubble level within the wash tub. If the bubble level is greater than a predetermined bubble threshold, corrective action is taken to reduce the bubbles and detergent concentration.