A method for generating a setting for laundry appliance that treats a load of laundry items, the method comprising: capturing, by a sensor group associated with the laundry appliance, sensor data for one or more laundry items in the load, the sensor group comprising one or more sensors; receiving, by a machine learning model, the sensor data, and determining a treatment attribute related to the treatment of the load by the laundry appliance based on the sensor data; generating, by a controller, a setting for the laundry appliance based on the treatment attribute determined by the machine learning model; and controlling, by the controller, the laundry appliance to treat the load according to the generated setting, characterized in that the sensor group includes a tactile surface sensor, and the method further comprises: sensing, by the tactile surface sensor, a surface of one of the one or more laundry items through contact with the laundry item when the laundry item is pressed against the tactile surface sensor during loading of the laundry item into the laundry appliance, wherein the sensor data includes surface characteristics of the laundry item sensed by the tactile surface sensor; and determining, by the machine learning model, the treatment attribute based on the surface characteristics; the tactile surface sensor is located on a front lip of the laundry appliance and laundry item makes contact with and is sensed by the tactile surface sensor when moving across the front lip of the laundry appliance into a washing chamber of the laundry appliance. capturing, by a sensor group associated with the laundry appliance, sensor data for one or more laundry items in the load, the sensor group comprising one or more sensors; receiving, by a machine learning model, the sensor data, and determining a treatment attribute related to the treatment of the load by the laundry appliance based on the sensor data; generating, by a controller, a setting for the laundry appliance based on the treatment attribute determined by the machine learning model; and controlling, by the controller, the laundry appliance to treat the load according to the generated setting, characterized in that the sensor group includes a tactile surface sensor, and the method further comprises: sensing, by the tactile surface sensor, a surface of one of the one or more laundry items through contact with the laundry item when the laundry item is pressed against the tactile surface sensor during loading of the laundry item into the laundry appliance, wherein the sensor data includes surface characteristics of the laundry item sensed by the tactile surface sensor; and determining, by the machine learning model, the treatment attribute based on the surface characteristics; the tactile surface sensor is located on a front lip of the laundry appliance and laundry item makes contact with and is sensed by the tactile surface sensor when moving across the front lip of the laundry appliance into a washing chamber of the laundry appliance. sensing, by the tactile surface sensor, a surface of one of the one or more laundry items through contact with the laundry item when the laundry item is pressed against the tactile surface sensor during loading of the laundry item into the laundry appliance, wherein the sensor data includes surface characteristics of the laundry item sensed by the tactile surface sensor; and determining, by the machine learning model, the treatment attribute based on the surface characteristics; the tactile surface sensor is located on a front lip of the laundry appliance and laundry item makes contact with and is sensed by the tactile surface sensor when moving across the front lip of the laundry appliance into a washing chamber of the laundry appliance.