Gree Electric Appliances, Inc. of Zhuhai

Zhuhai Leayun Technology Co., Ltd

Xiaoyu Luo

Chong Chen

Dong Yue

Dechao Song

Shaobin Li

Jianming Tan

Xiangwen Chen

Pengfei Wang

Wenxuan Xiao

Jiabi Deng

Chaohong Ye

The present disclosure discloses a human detection method and device, an electronic apparatus, and a storage medium. The method includes: a millimeter-wave radar signal of a target environment () is obtained; information of a moving point in the target environment () is extracted from the millimeter-wave radar signal; a micro-Doppler feature of each target in the target environment () is determined according to the information of the moving points in the target environment, wherein the target is formed by at least one moving point; and a target whose category is human in the target environment () is identified according to the micro-Doppler feature of each target in the target environment. The millimeter-wave radar technology is combined with artificial intelligence technology, so as to enable human detection in the target environment without invading human privacy, thus providing the possibility of achieving automatic control, monitoring and other operations of the target environment.

Human detection method and device, electronic apparatus and storage medium

Disclosed are a method for controlling smart home and a device for controlling smart home. The method includes the following steps: a demand database and a habit database of a user for home appliances are built; according to the built demand database, demand models of different users are trained by using a neural network, and the demands of the users during different periods of time are predicted; and according to the built habit database and a prediction regarding the demands of the users, a home appliance execution policy conforming to the habits of the users are output by using a probability statistical algorithm, and the corresponding home appliances are controlled in advance.

Method and apparatus for controlling smart home

The disclosure provides a control method and a device for an air conditioner. The method includes: a first reward matrix is constructed according to multiple sets of target operating parameters of an air conditioner, a maximum expected benefit of performing a current action in a current state is calculated based on the first reward matrix and a Q-learning algorithm, wherein the current state is represented by a current indoor environment temperature and a current outdoor environment temperature; target action parameters under the maximum expected benefit are acquired, and operation of the air conditioner is controlled based on second target action parameters, wherein the second target action parameters at least include a second target operating frequency of the compressor, a second target opening degree of the electronic expansion valve and a second target rotating speed of the external fan.

Control method for air conditioner, and device for air conditioner and storage medium

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Guangdong, China

Xiaoyu Luo