Midea Group Co., Ltd.

Microsoft Technology Licensing, LLC

Hua Zhou

Xin Chen

Dongyan Wang

Thomas R Young

Zhicai Ou

Xiaochun Li

Linnan Zhu

Yu Zhu

Yuxiang Gao

Jeff B Widergren

Rubao Ma

Jackson Tung

Kai Chee Li

Hao Guo

Francis A Palita

Aosen Wang

An air conditioning system includes one or more cameras, one or more air conditioning operation units, and an air conditioner control unit that obtains, via the one or more cameras, images of a surrounding environment of the air conditioning operation units, and determines a first set of factors, including a layout of the surrounding environment, based on analysis of the images through predefined machine learning models. The control unit, in accordance with the first set of factors that has been determined based on the analysis of the images through the predefined machine learning models, selects a first operation profile from a plurality of predefined operation profiles to control the air conditioning operation units.

Method and system for providing air conditioning

A rice cooker assembly uses machine learning models to identify and classify different types of food stored. The rice cooker has a chamber including different compartments for storing different types of food. A camera is positioned to view an interior of the chamber. The camera captures images of the contents of the chamber. From the images, the machine learning model classifies the different types of food stored. The rice cooker determines a mixture of different types of food based on nutrition value and/or taste. The rice cooker creates the mixture and controls the cooking process accordingly. The one or more machine learning models may be resident in the rice cooker or it may be accessed via a network.

Multi-purpose smart rice cookers

A face recognition system of a residential environment identifies an individual present in the residential environment. The residential environment include a plurality of home devices and is associated with a group of different persons. The face recognition system identifies which person in the group is the individual and generate an operating instruction for a home device based on identity of the individual. For example, the face recognition system captures an image set of the individual's head and face and applies the image set to a machine learning model that is trained to distinguish between the different persons based on images of their heads and faces. The face recognition system can retrieve a personal profile of the identified individual, which includes settings of the home device for the identified individual. The face recognition system generates the operating instruction based on the personal profile.

Face recognition in a residential environment

Laundry appliances use machine learning models and/or personalization to provide better treatments. As one example, a laundry appliance has a chamber in which laundry items are placed for treatment. Sensor(s) are positioned to sense contents of the chamber or to sense the laundry items as they are loaded into the chamber. The machine learning model uses data from these sensors to determine various attributes of the laundry items and/or the treatment, such as the type of fabric and/or how dirty the items are, and the treatment process is controlled accordingly. Personalized data, such as an individual's preferences for laundry treatments or his sensitivities and allergies, may also be used to personalize the treatment process.

Personalized laundry appliance

Disclosed are methods and systems for tracking which data tiles have changed within an image frame. In an embodiment, each cell of a tile change list buffer may contain a frame number and updated when a tile is received from encoder. The frame number may be used as a base pointer for a particular frame buffer. When a frame is decoded, the contents of the tile change list buffer may be copied from the current tile change list buffer to the next buffer. This process may reduce memory traffic because the unchanged tile data does not have to be copied from frame to frame.

Image frame buffer management

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San Jose, CA, United States of America

Hua Zhou