CN111219857B - Method and system for controlling air conditioner based on face dynamic information - Google Patents
Method and system for controlling air conditioner based on face dynamic information Download PDFInfo
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- CN111219857B CN111219857B CN201911182896.9A CN201911182896A CN111219857B CN 111219857 B CN111219857 B CN 111219857B CN 201911182896 A CN201911182896 A CN 201911182896A CN 111219857 B CN111219857 B CN 111219857B
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F11/00—Control or safety arrangements
- F24F11/50—Control or safety arrangements characterised by user interfaces or communication
- F24F11/56—Remote control
- F24F11/58—Remote control using Internet communication
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F11/00—Control or safety arrangements
- F24F11/62—Control or safety arrangements characterised by the type of control or by internal processing, e.g. using fuzzy logic, adaptive control or estimation of values
- F24F11/63—Electronic processing
- F24F11/64—Electronic processing using pre-stored data
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/16—Human faces, e.g. facial parts, sketches or expressions
- G06V40/172—Classification, e.g. identification
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F2120/00—Control inputs relating to users or occupants
- F24F2120/10—Occupancy
Abstract
The invention provides a method for controlling an air conditioner based on face dynamic information, which comprises the following steps: acquiring a real-time dynamic image of a face of an air conditioner user, acquiring face dynamic information and uploading the face dynamic information to a cloud; matching and identifying the dynamic information of the human face through a deep learning cyclic neural network model at the cloud end, identifying the body state information of the air conditioner user and generating a corresponding control instruction; feeding back the body state information of the identified air conditioner user and the corresponding control instruction to the air conditioner main controller; the air conditioner main controller sends the corresponding control instruction to a user to request the user to confirm whether to execute the corresponding control instruction; the air conditioner main controller carries out intelligent automatic adjustment according to the feedback information of the user. The invention also provides a system for controlling the air conditioner based on the dynamic information of the human face. The invention can detect the periodic change of the human face, recognize the requirements of human behavior state and the like on the environment through the change of the human face, and intelligently carry out automatic comfort regulation by the air conditioner according to the requirements of users.
Description
Technical Field
The invention relates to a method and a system for controlling an air conditioner, in particular to a method and a system for controlling the air conditioner based on human face dynamic information.
Background
At present, along with the rapid development of the field of artificial intelligence and the increasing demands of people on intelligent monitoring, intelligent home and novel human-computer interaction. At present, voice interaction technology is mature, and the application of voice interaction to household appliances, such as voice air conditioners, is increasing. The application of the image-based non-inductive interaction technology in the household appliance industry is gradually appeared, and the image technology is combined with the control of voice to meet new opportunities. Generally, all intelligent household products are controlled by voice or gestures, users have stronger requirements on more humanized intelligent control products, and hope that the air conditioner automatically adjusts the air conditioner according to the needs of the bodies of the users without manual control. In addition, the requirement change of users to the room environment in the existing product needs to be adjusted every time, and the air conditioner can not be intelligently adjusted.
Disclosure of Invention
In view of this, the present invention provides a method for controlling an air conditioner based on face dynamic information, including:
s1, acquiring a real-time dynamic image of the face of the air conditioner user, acquiring face dynamic information and uploading the face dynamic information to a cloud;
s2, matching and identifying the dynamic face information through a cloud deep learning cyclic neural network model, identifying the body state information of the air conditioner user and generating a corresponding control instruction;
s3, feeding back the body state information of the air conditioner user and the corresponding control instruction to an air conditioner main controller;
s4, the air conditioner master controller sends the corresponding control instruction to the air conditioner user to request the air conditioner user to confirm whether to execute the corresponding control instruction;
and S5, the air conditioner main controller performs intelligent automatic adjustment according to the feedback information of the air conditioner user.
As a further improvement of the present invention, S1 includes:
s11, configuring a binocular camera by the air conditioner, and controlling the binocular camera to rotate in an air conditioning area;
s12, when the air conditioner user is monitored to move into an air conditioning area, acquiring a real-time dynamic image of the face of the air conditioner user;
and S13, extracting face dynamic information from the collected real-time dynamic image and uploading the face dynamic information to a cloud.
As a further improvement of the present invention, in S2, the body state information of the air conditioner user is identified according to a classification model between the human face dynamic information and the body state information, which is established in advance, and a corresponding control command is generated.
As a further improvement of the present invention, S2 includes:
s21, collecting video data containing a plurality of face images in advance, extracting face dynamic information at each moment respectively, and uploading all face dynamic information to a cloud end;
s22, sending all face dynamic information and body state information into a deep learning cyclic neural network model at the cloud end, and training to obtain a classification model;
s23, forming a mapping relation between the body state information and the control instruction at the cloud end;
and S24, inputting the face dynamic information corresponding to the current moment into the trained classification model at the cloud, identifying the body state information corresponding to the face dynamic information, and generating a corresponding control instruction according to the mapping relation between the body state information and the control instruction.
As a further improvement of the invention, the dynamic information of the human face is uploaded to the cloud through a built-in WIFI module of the air conditioner.
As a further improvement of the present invention, the air conditioner master controller performs logic processing on the feedback body state information and control instruction, communicates with the air conditioner user, and transmits information to the air conditioner user to confirm whether to execute the corresponding control instruction.
As a further improvement of the present invention, when the air conditioner master controller performs logic processing, the method adopted is as follows: the air conditioner collects the dynamic human face image of the air conditioner user at the current moment, the human face expression of the air conditioner user is identified, and the air conditioner main controller determines whether to execute the control instruction according to the human face expression fed back by the air conditioner user.
As a further improvement of the present invention, when the air conditioner master controller performs logic processing, the method adopted is as follows: the air conditioner main controller controls a loudspeaker built in the air conditioner to broadcast body state information of the air conditioner user through a voice module built in the air conditioner and broadcast whether the corresponding control instruction is executed or not to the air conditioner user, and the air conditioner user determines whether the control instruction is executed or not through voice.
As a further improvement of the present invention, when the air conditioner master controller performs logic processing, the method adopted is as follows: the air conditioner master controller sends the body state information of the air conditioner user and the control instruction to the APP client side, and the air conditioner user operates the APP client side to determine whether to execute the control instruction.
The invention also provides a system for controlling the air conditioner based on the dynamic information of the human face, which comprises the following components:
the data acquisition module is used for acquiring a real-time dynamic image of the face of the air conditioner user, acquiring face dynamic information and uploading the face dynamic information to the cloud;
the data matching module is used for matching and identifying the human face dynamic information through a cloud deep learning cyclic neural network model, identifying the body state information of the air conditioner user and generating a corresponding control instruction;
the data feedback module is used for feeding back the body state information of the identified air conditioner user and the corresponding control instruction to the air conditioner main controller;
the instruction confirming module is used for sending the corresponding control instruction to the air conditioner user by the air conditioner main controller to request the air conditioner user to confirm whether to execute the corresponding control instruction or not;
and the intelligent adjusting module is used for carrying out intelligent automatic adjustment on the air conditioner main controller according to the feedback information of the air conditioner user.
The invention has the beneficial effects that:
the air conditioner can detect out human face periodic variation through configuring the binocular camera, discerns human action state etc. to the demand of environment through face's change, and the air conditioner carries out automatic travelling comfort according to user's demand intelligently and adjusts. The air conditioner does not need to be set by a user, the required ambient temperature of the current physical condition of the user can be met, and more humanized intelligent air conditioner adjustment is realized.
Drawings
The above and other objects, features and advantages of the present disclosure will become more apparent by describing in detail exemplary embodiments thereof with reference to the attached drawings. The drawings described below are merely some embodiments of the present disclosure, and other drawings may be derived from those drawings by those of ordinary skill in the art without inventive effort.
Fig. 1 is a schematic flow chart of a method for controlling an air conditioner based on face dynamic information in an embodiment of the present invention.
Detailed Description
Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings.
While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art so that they can be readily implemented by those skilled in the art. As can be readily understood by those skilled in the art to which the present invention pertains, the embodiments to be described later may be modified into various forms without departing from the concept and scope of the present invention. Wherever possible, the same reference numbers will be used throughout the drawings to refer to the same or like parts.
The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used herein, the singular forms "a", "an" and "the" include plural forms as well, unless the contrary is expressly stated. The term "comprising" as used in the specification embodies particular features, regions, constants, steps, actions, elements and/or components and does not exclude the presence or addition of other particular features, regions, constants, steps, actions, elements, components and/or groups.
All terms including technical and scientific terms used hereinafter have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. Terms defined in dictionaries are to be interpreted as meanings complied with in the relevant technical documents and the present disclosure, and cannot be interpreted as having a very formal meaning without definition.
The invention discloses a method for controlling an air conditioner based on face dynamic information, which comprises the following steps:
and S1, acquiring a real-time dynamic image of the face of the air conditioner user, acquiring face dynamic information and uploading the face dynamic information to a cloud. Specifically, S1 includes:
and S11, configuring the binocular camera by the air conditioner, and controlling the binocular camera to rotate in the air conditioning area.
And S12, when the air conditioner user is monitored to move into the air conditioning area, acquiring a real-time dynamic image of the face of the air conditioner user. When the real-time dynamic image acquisition fails, the binocular camera can continue to rotate until the real-time dynamic image of the face is successfully acquired.
And S13, extracting face dynamic information from the collected real-time dynamic image and uploading the face dynamic information to a cloud. Optionally, the face dynamic information is extracted by using a mobilenet v 3.
And S2, matching and identifying the dynamic information of the human face through the cloud deep learning cyclic neural network model, identifying the body state information of the air conditioner user and generating a corresponding control instruction. In the step, the body state information of the air conditioner user is identified according to a classification model between the human face dynamic information and the body state information which are established in advance, and a corresponding control instruction is generated. Specifically, S2 includes:
and S21, collecting video data containing a plurality of face images in advance, extracting face dynamic information at each moment respectively, and uploading all face dynamic information to a cloud. Optionally, the dynamic information of the human face is uploaded to the cloud through a built-in WIFI module of the air conditioner.
And S22, sending all the face dynamic information and the body state information into a deep learning cyclic neural network model at the cloud end, and training to obtain a classification model.
The body state information is, for example, information on fine blood vessels, complexion, and heartbeat of the human face. For example, information such as heartbeats can be measured through the relationship between the front frame and the back frame of the video sequence of the human face.
The deep learning cyclic neural network model is a better model after a large amount of sample training, and can accurately identify body state information corresponding to the dynamic information of the human face.
And S23, forming a mapping relation between the body state information and the control command at the cloud.
The control instruction is stored in the cloud end in advance and can be directly called in the subsequent identification process. For example, a mapping relation can be formed between human heartbeat and a control instruction for adjusting the refrigerating capacity, and the proper temperature and wind direction can be adjusted according to the heartbeat, such as fast heartbeat and large amount of movement, so that the refrigerating capacity of the air conditioner is improved. For another example, the human face capillary vessels may form a mapping relationship with the control commands for temperature adjustment, the human face color may form a mapping relationship with the control commands for temperature adjustment, and the like.
And S24, inputting the face dynamic information corresponding to the current moment into the trained classification model at the cloud, identifying the body state information corresponding to the face dynamic information, and generating a corresponding control instruction according to the mapping relation between the body state information and the control instruction.
And S3, feeding back the body state information of the air conditioner user and the corresponding control instruction to the air conditioner main controller.
And S4, the air conditioner main controller sends the corresponding control command to the air conditioner user to request the air conditioner user to confirm whether to execute the corresponding control command.
And S5, the air conditioner main controller performs intelligent automatic adjustment according to the feedback information of the air conditioner user.
Further, the air conditioner main controller performs logic processing on the fed back body state information and the control instruction, communicates with an air conditioner user, and transmits the information to the air conditioner user to confirm whether to execute the corresponding control instruction.
Optionally, when the air conditioner master controller performs the logic processing, the method adopted is as follows: the air conditioner collects the face dynamic image of the air conditioner user at the current moment, the face expression of the air conditioner user is identified, and the air conditioner main controller determines whether to execute a control instruction according to the face expression fed back by the air conditioner user.
Optionally, when the air conditioner master controller performs the logic processing, the method adopted is as follows: the air conditioner main controller controls a loudspeaker built in the air conditioner to broadcast body state information of an air conditioner user through a voice module built in the air conditioner, and broadcasts whether the air conditioner user executes a corresponding control instruction or not, and the air conditioner user determines whether the control instruction is executed or not through voice.
Optionally, when the air conditioner master controller performs the logic processing, the method adopted is as follows: the air conditioner main controller sends the body state information and the control instruction of the air conditioner user to the APP client side, and the air conditioner user operates the APP client side to determine whether to execute the control instruction.
And under the condition of network disconnection, the binocular camera controls the air conditioner service to be closed.
The invention discloses a system for controlling an air conditioner based on face dynamic information, which comprises: the intelligent control system comprises a data acquisition module, a data matching module, a data feedback module, an instruction confirmation module and an intelligent regulation module.
The data acquisition module is used for acquiring a real-time dynamic image of the face of the air conditioner user, acquiring face dynamic information and uploading the face dynamic information to the cloud. Specifically, the data acquisition module executes the flow of S1 in the method for controlling the air conditioner based on the dynamic human face information.
The data matching module is used for matching and recognizing the dynamic information of the human face through a deep learning cyclic neural network model at the cloud end, recognizing the body state information of the air conditioner user and generating a corresponding control instruction. Specifically, the data acquisition module executes the flow of S2 in the method for controlling the air conditioner based on the dynamic human face information.
And the data feedback module is used for feeding back the body state information of the identified air conditioner user and the corresponding control instruction to the air conditioner main controller. Specifically, the data acquisition module executes the flow of S3 in the method for controlling the air conditioner based on the dynamic human face information.
The instruction confirmation module is used for sending the corresponding control instruction to the air conditioner user by the air conditioner main controller to request the air conditioner user to confirm whether to execute the corresponding control instruction. Specifically, the instruction confirmation module executes the flow of S4 in the method for controlling the air conditioner based on the dynamic human face information.
The intelligent adjusting module is used for the air conditioner main controller to carry out intelligent automatic adjustment according to the feedback information of the air conditioner user. Specifically, the intelligent adjusting module executes the flow of S5 in the method for controlling the air conditioner based on the dynamic human face information.
The invention will be further illustrated by means of two specific examples.
The embodiment 1, the air conditioner disposes the binocular camera, the user uses the air conditioner at home, when the user is faced with the binocular camera, the binocular camera obtains the real-time dynamic image of user's face, the people's face dynamic information of every moment is drawed and the high in the clouds is uploaded with data through image recognition technology, match the discernment through degree of depth learning circulation neural network model to people's face dynamic information in the high in the clouds, discern user's health state information and generate corresponding control command, feed back the result to the air conditioner master controller, the air conditioner master controller carries out intelligent air supply regulation according to user's feedback information. For example, after the user moves indoors in summer, the air conditioner detects that the heartbeat of the user is fast and the body of the user sweats, and at the moment, the air conditioner adjusts the environment requirement to be the optimum air conditioner cooling mode according to the body state of the user, and the cooling capacity is increased.
Embodiment 2, the air conditioner is provided with a binocular camera, the user uses the air conditioner at home, when facing the binocular camera, the binocular camera obtains a real-time dynamic image of the face of the user, the dynamic information of the face at each moment is extracted through an image recognition technology and data is uploaded to a cloud, the dynamic information of the face is matched and recognized through a deep learning cyclic neural network model at the cloud, the body state information of the user is recognized and corresponding control instructions are generated, the result is fed back to an air conditioner main controller, the air conditioner main controller performs logic processing on the fed-back body state information and the control instructions and feeds back the information to a voice module through communication of a serial port communication protocol and a voice module in the air conditioner, the voice module controls a loudspeaker to broadcast the body state information of the user and broadcast whether the corresponding control instructions are executed for the user, and the execution of the control instructions is determined by the voice of the user, at this time, the air conditioner adjusts the comfortable environment temperature. For example, the air conditioner detects that the body of the user is cooled, the air conditioner performs voice broadcast to 'feel cool feeling of silk through the body, and whether the refrigerating capacity (or the air supply direction or the air supply size) of the air conditioner is adjusted', and the user can execute the voice broadcast according to the judgment of the user.
Thus, it should be appreciated by those skilled in the art that while a number of exemplary embodiments of the invention have been illustrated and described in detail herein, many other variations or modifications consistent with the principles of the invention may be directly determined or derived from the disclosure of the present invention without departing from the spirit and scope of the invention. Accordingly, the scope of the invention should be understood and interpreted to cover all such other variations or modifications.
In the description provided herein, numerous specific details are set forth. It is understood, however, that embodiments of the invention may be practiced without these specific details. In some instances, well-known methods, structures and techniques have not been shown in detail in order not to obscure an understanding of this description.
Similarly, it should be appreciated that in the foregoing description of exemplary embodiments of the invention, various features of the invention are sometimes grouped together in a single embodiment, figure, or description thereof for the purpose of streamlining the disclosure and aiding in the understanding of one or more of the various inventive aspects. However, the disclosed method should not be interpreted as reflecting an intention that: that the invention as claimed requires more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive aspects lie in less than all features of a single foregoing disclosed embodiment. Thus, the claims following the detailed description are hereby expressly incorporated into this detailed description, with each claim standing on its own as a separate embodiment of this invention.
Furthermore, those skilled in the art will appreciate that while some embodiments described herein include some features included in other embodiments, rather than other features, combinations of features of different embodiments are meant to be within the scope of the invention and form different embodiments. For example, in the claims, any of the claimed embodiments may be used in any combination.
Thus, it should be appreciated by those skilled in the art that while a number of exemplary embodiments of the invention have been illustrated and described in detail herein, many other variations or modifications consistent with the principles of the invention may be directly determined or derived from the disclosure of the present invention without departing from the spirit and scope of the invention. Accordingly, the scope of the invention should be understood and interpreted to cover all such other variations or modifications.
Claims (6)
1. A method for controlling an air conditioner based on face dynamic information is characterized by comprising the following steps:
s1, acquiring a real-time dynamic image of the face of the air conditioner user, acquiring face dynamic information and uploading the face dynamic information to a cloud;
s2, matching and identifying the dynamic face information through a cloud deep learning cyclic neural network model, identifying the body state information of the air conditioner user and generating a corresponding control instruction;
s3, feeding back the body state information of the identified air conditioner user and the corresponding control instruction to an air conditioner main controller;
s4, the air conditioner master controller sends the corresponding control instruction to the air conditioner user to request the air conditioner user to confirm whether to execute the corresponding control instruction;
s5, the air conditioner main controller carries out intelligent automatic adjustment according to the feedback information of the air conditioner user;
wherein the step S2 includes:
s21, collecting video data containing a plurality of face images in advance, extracting face dynamic information at each moment respectively, and uploading all face dynamic information to a cloud end;
s22, sending all face dynamic information and body state information into a deep learning cyclic neural network model at the cloud end, and training to obtain a classification model;
s23, forming a mapping relation between the body state information and the control instruction at the cloud end;
s24, inputting the face dynamic information corresponding to the current moment into the trained classification model at the cloud end, identifying the body state information corresponding to the face dynamic information, and generating a corresponding control instruction according to the mapping relation between the body state information and the control instruction;
wherein the step S4 includes: the air conditioner main controller carries out logic processing on the fed back body state information and the control instruction, communicates with the air conditioner user, and transmits information to the air conditioner user to confirm whether to execute the corresponding control instruction or not; when the air conditioner main controller performs logic processing, the adopted method comprises the following steps: the air conditioner collects a dynamic human face image of the air conditioner user at the current moment, the human face expression of the air conditioner user is identified, and the air conditioner main controller determines whether to execute the control instruction according to the human face expression fed back by the air conditioner user; the air conditioner main controller controls a loudspeaker built in the air conditioner to broadcast body state information of the air conditioner user through a voice module built in the air conditioner and broadcast whether the corresponding control instruction is executed or not to the air conditioner user, and the air conditioner user determines whether the control instruction is executed or not through voice.
2. The method for controlling an air conditioner based on human face dynamic information as claimed in claim 1, wherein the S1 includes:
s11, configuring a binocular camera by the air conditioner, and controlling the binocular camera to rotate in an air conditioning area;
s12, when the air conditioner user is monitored to move into an air conditioning area, acquiring a real-time dynamic image of the face of the air conditioner user;
and S13, extracting face dynamic information from the collected real-time dynamic image and uploading the face dynamic information to a cloud.
3. The method as claimed in claim 1, wherein in S2, the body state information of the air conditioner user is identified according to a pre-established classification model between the human face dynamic information and the body state information, and a corresponding control command is generated.
4. The method of claim 3, wherein the dynamic human face information is uploaded to the cloud through a WIFI module built in the air conditioner.
5. The method for controlling the air conditioner based on the dynamic human face information as claimed in claim 1, wherein the air conditioner master controller adopts a method when performing logic processing, which is as follows: the air conditioner master controller sends the body state information of the air conditioner user and the control instruction to the APP client side, and the air conditioner user operates the APP client side to determine whether to execute the control instruction.
6. A system for realizing the control of the air conditioner based on the dynamic human face information, which is characterized by comprising the following components:
the data acquisition module is used for acquiring a real-time dynamic image of the face of the air conditioner user, acquiring face dynamic information and uploading the face dynamic information to the cloud;
the data matching module is used for matching and identifying the human face dynamic information through a cloud deep learning cyclic neural network model, identifying the body state information of the air conditioner user and generating a corresponding control instruction;
the data feedback module is used for feeding back the body state information of the identified air conditioner user and the corresponding control instruction to the air conditioner main controller;
the instruction confirming module is used for sending the corresponding control instruction to the air conditioner user by the air conditioner main controller to request the air conditioner user to confirm whether to execute the corresponding control instruction or not;
and the intelligent adjusting module is used for carrying out intelligent automatic adjustment on the air conditioner main controller according to the feedback information of the air conditioner user.
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| CN112303861A (en) * | 2020-09-28 | 2021-02-02 | 山东师范大学 | Air conditioner temperature adjusting method and system based on human body thermal adaptability behavior |
| CN112650072A (en) * | 2020-12-21 | 2021-04-13 | 三六零视觉(北京)科技有限公司 | Equipment control method, device, equipment and storage medium based on face recognition |
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