CN107438019A - Smart home learning control method, device and system - Google Patents

Abstract

The embodiment of the invention discloses a kind of smart home learning control method, device and system, it is related to Smart Home technical field.Methods described includes：According to the environmental information gathered in real time, and the academic environment regulation rule of setting, the environment adjustment household electrical appliances in intelligent domestic system are manipulated, with the academic environment residing for regularized learning algorithm object；According to the study control rule of the study attribute information of the learning object, and setting, the study control household electrical appliances in the intelligent domestic system are manipulated, to control the learning Content of the learning object.Technical scheme realizes the individualized feature based on learning object, smart home environment is adjusted to the suitable academic environment of learning object, and control the technique effect for playing the learning Content that learning object is adapted to, existing smart home technology is optimized, meets the growing facilitation of people, the personalized learning demand based on smart home.

Description

Smart home learning control method, device and system

Technical Field

The embodiment of the invention relates to an intelligent home technology, in particular to an intelligent home learning control method, device and system.

Background

The coming of the smart home era changes the lives and habits of people, widens the visual field of people, and meanwhile, more intelligently controls the home to become the trend of future development. The smart home technology utilizes advanced computer, embedded system and network communication technology to connect various devices (such as lighting system, environmental control, security system and network household appliances) in the home together through the home network.

At present, the existing home control technology is single, home appliances are poor in cooperative work scheduling and intelligence, and particularly, a realization scheme for comprehensively controlling a specific scene (typical scene, learning scene) is lacked.

Disclosure of Invention

In view of this, embodiments of the present invention provide a method, an apparatus, and a system for controlling smart home learning, so as to optimize an existing smart home technology and meet an increasing demand for convenient, personalized and smart home-based learning of people.

In a first aspect, an embodiment of the present invention provides an intelligent home learning control method, including:

according to the environment information collected in real time and the set learning environment adjustment rule, the environment adjustment household appliances in the intelligent home system are controlled to adjust the learning environment of the learning object;

and controlling the learning control household appliances in the intelligent home system according to the learning attribute information of the learning object and the set learning control rule so as to control the learning content of the learning object.

In a second aspect, an embodiment of the present invention further provides an intelligent home learning control apparatus, including:

the learning environment adjusting module is used for controlling environment adjusting household appliances in the intelligent home system according to the environment information collected in real time and the set learning environment adjusting rule so as to adjust the learning environment of the learning object;

and the learning content adjusting module is used for controlling the learning control household appliances in the intelligent home system according to the learning attribute information of the learning object and the set learning control rule so as to control the learning content of the learning object.

In a third aspect, an embodiment of the present invention further provides an intelligent home learning control system, including:

the first monitoring module is used for recording learning contents of a learning object in a learning environment outside the intelligent home system through the portable monitoring equipment and sending the recorded learning contents to the intelligent home control module;

the second monitoring module is used for acquiring environmental information in the intelligent home system through an information acquisition sensor and sending the environmental information to the intelligent home control module;

the intelligent home control module comprises the intelligent home learning control device provided by the embodiment of the invention;

the learning environment adjusting module is configured in the environment adjusting household appliance and used for adjusting the environment adjusting household appliance according to the control of the intelligent household control module;

and the learning content adjusting module is configured in the learning control household appliance and used for adjusting the learning control household appliance according to the control of the intelligent household control module.

According to the technical scheme of the embodiment of the invention, the environment adjusting household appliances in the intelligent home system are controlled according to the environment information collected in real time and the set learning environment adjusting rule so as to adjust the learning environment of the learning object; according to the learning attribute information of the learning object and the set learning control rule, the learning control household appliances in the intelligent household system are controlled to control the learning content of the learning object, the personalized characteristics based on the learning object are realized, the intelligent household environment is adjusted to the learning environment suitable for the learning object, the technical effect of playing the learning content suitable for the learning object is controlled, the technical problems that the existing household control technology is single, the cooperation scheduling of household appliances and the intelligence degree are poor, particularly, the realization scheme of comprehensively controlling a specific learning scene is lacked are solved, the existing intelligent household technology is optimized, and the increasing convenience and personalized learning requirements based on the intelligent household of people are met.

Drawings

Fig. 1 is a flowchart of a smart home learning control method according to an embodiment of the present invention;

fig. 2 is a flowchart of a smart home learning control method according to a second embodiment of the present invention;

fig. 3 is a flowchart of a smart home learning control method according to a third embodiment of the present invention;

fig. 4 is a flowchart of a smart home learning control method according to a fourth embodiment of the present invention;

FIG. 5 is a flowchart illustrating an implementation of a specific application scenario applicable to the embodiment of the present invention;

fig. 6 is a structural diagram of an intelligent home learning control apparatus according to a fifth embodiment of the present invention;

fig. 7 is a structural diagram of an intelligent home learning control system according to a sixth embodiment of the present invention.

Detailed Description

In order to make the objects, technical solutions and advantages of the present invention more apparent, embodiments of the present invention are described in further detail below with reference to the accompanying drawings. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not limiting of the invention.

It should be further noted that, for the convenience of description, only some but not all of the relevant aspects of the present invention are shown in the drawings. Before discussing exemplary embodiments in more detail, it should be noted that some exemplary embodiments are described as processes or methods depicted as flowcharts. Although a flowchart may describe the operations (or steps) as a sequential process, many of the operations can be performed in parallel, concurrently or simultaneously. In addition, the order of the operations may be re-arranged. The process may be terminated when its operations are completed, but may have additional steps not included in the figure. The processes may correspond to methods, functions, procedures, subroutines, and the like.

For convenience of description, the main components of the smart home system will be briefly described first. Firstly, the smart home system is mainly applied to one or more rooms in the living environment of the user. Typically in a particular study room in a school student's home residence.

The intelligent home system mainly comprises an information acquisition device (typically, a temperature and humidity sensor), a control server and various control household appliances (typically, an air conditioner, a humidifier or a home theater, etc.).

The control server analyzes and processes the information acquired by the information acquisition device to complete the control of various control household appliances.

More specifically, the control server may have a control system built therein, and the control system may specifically include, by way of example and not limitation: the system comprises an acquisition subsystem, an analysis subsystem, an alarm subsystem and a monitoring subsystem. The system comprises an acquisition subsystem, a monitoring subsystem, an analysis subsystem, an alarm subsystem and an analysis subsystem, wherein the acquisition subsystem is used for acquiring external information acquired by each information acquisition device, the monitoring subsystem is used for monitoring environmental changes to acquire latest information, the analysis subsystem is used for comprehensively summarizing the information acquired by the acquisition subsystem and the monitoring subsystem, generating corresponding household appliance control strategies and controlling various control household appliances, and the alarm subsystem is used for carrying out alarm processing on abnormal conditions and the like.

Example one

Fig. 1 is a flowchart of a smart home learning control method according to an embodiment of the present invention, where the method of this embodiment is generally applicable to a learning object (typically, a student) learning through a smart home system. The method of this embodiment may be executed by an intelligent home learning control device, where the device may be implemented by software and/or hardware, and may be generally integrated in a control server in an intelligent home system, and with reference to fig. 1, the intelligent home learning control method provided in this embodiment specifically includes:

and S110, controlling the environment adjusting household appliances in the intelligent home system according to the environment information collected in real time and the set learning environment adjusting rule so as to adjust the learning environment of the learning object.

In this embodiment, the environment information may include indoor environment information, and/or outdoor environment information;

wherein the indoor environment information may include at least one of: temperature information, humidity information, and light information; the outdoor environment information may include at least one of: weather information, wind information, and climate information.

The indoor environment information may be obtained through various sensors configured in the smart home environment, for example: temperature sensors, humidity sensors, or light sensors; the outdoor environment information may be obtained by a user's own input or by searching in the internet (typically, searching for weather forecast or air quality at a geographical location, etc.).

In this embodiment, the environment adjusting appliance may include at least one of: air conditioners, humidifiers, dryers, and fans.

In this embodiment, the learning environment adjustment rule may specifically include: the adjustment threshold value of the environmental information and the adjustment strategy of the environmental adjustment household electrical appliance corresponding to the adjustment threshold value.

In a specific example, the learning environment adjustment rule may include: "humidity value is less than or equal to 20%, turn on humidifier". The learning environment adjustment rule expresses that when the collected humidity value is less than or equal to 20%, the humidifier is started to work.

The learning environment adjustment rule may be set uniquely, or different learning environment adjustment rules may be set according to different physical condition information of the learning object, which is not limited in this embodiment.

Currently, it can be understood that S110 is preferably executed on the premise that the learning object enters the smart home environment. Therefore, in a preferred implementation manner of this embodiment, before S110, the method may further include: and identifying the current position of the learning object, and executing S110 if the learning object is determined to be in the intelligent household environment.

Wherein, can confirm through modes such as intelligent bracelet, fingerprint identification, face identification or infrared scanning whether the study object is in intelligent house environment, this embodiment does not restrict this.

And S120, controlling the learning control household appliances in the intelligent home system according to the learning attribute information of the learning object and the set learning control rule so as to control the learning content of the learning object.

In this embodiment, the learning attribute information may include at least one of: personal likes and dislikes, schools, grades, historical scores, school schedules, learning plans and the classification of the learning subjects;

the learning control appliance may include at least one of: projector, stereo set, computer and playback devices.

The learning attribute information can be input into the intelligent home system in a mode of manual entry when the intelligent home system is initially installed and operated, and can be adjusted, deleted or supplemented in a mode of self-learning or user self-correction in the operation process of the system.

In this embodiment, the set learning control rule may specifically be different learning control strategies that are adopted based on different learning attribute information.

In a specific example, the current learning content can be determined according to the course content in the learning schedule; or determining special learning content corresponding to the examination or competition content according to the examination or competition content recorded in the learning plan; the subject learning sequence and the subject learning time of different learning subjects may also be determined according to the quality classification of the learning subjects, which is not limited in this embodiment.

According to the technical scheme of the embodiment of the invention, the environment adjusting household appliances in the intelligent home system are controlled according to the environment information collected in real time and the set learning environment adjusting rule so as to adjust the learning environment of the learning object; according to the learning attribute information of the learning object and the set learning control rule, the learning control household appliances in the intelligent household system are controlled to control the learning content of the learning object, the personalized characteristics based on the learning object are realized, the intelligent household environment is adjusted to the learning environment suitable for the learning object, the technical effect of playing the learning content suitable for the learning object is controlled, the technical problems that the existing household control technology is single, the cooperation scheduling of household appliances and the intelligence degree are poor, particularly, the realization scheme of comprehensively controlling a specific learning scene is lacked are solved, the existing intelligent household technology is optimized, and the increasing convenience and personalized learning requirements based on the intelligent household of people are met.

Example two

Fig. 2 is a flowchart of a smart home learning control method according to a second embodiment of the present invention, and the second embodiment is optimized based on the foregoing embodiments. In this embodiment, the environmental adjustment household appliances in the smart home system are controlled and specifically optimized according to the environmental information collected in real time and the set learning environment adjustment rule: determining an adjustment rule of the environment adjustment household appliance according to the physical condition information of the learning object; according to the environment information collected in real time and the adjustment rule of the environment adjustment household appliance, the environment adjustment household appliance in the smart home system is controlled, referring to fig. 2, the method of the embodiment specifically includes:

s210, determining an adjustment rule of the environment adjustment household appliance according to the physical condition information of the learning object.

Wherein, the adjustment rule of the environment adjustment appliance may include: the starting condition of the environment adjusting household appliance and/or the operation parameter setting rule of the environment adjusting household appliance.

Considering that the learning objects with different body conditions have different feelings of temperature and humidity or brightness, if the learning objects with different body conditions all adopt the unified adjustment rule of the environment adjustment home appliance, the experience of a part of people on the learning environment will be inevitably poor.

Wherein the physical condition information may include: age, sex, weight, height, eyesight, temperature sensitivity and the like can be used for measuring the parameter information of the environmental experience of the learning object.

In a preferred embodiment of this embodiment, a strategy selection value V may be constructed according to different physical condition information. For example: v-k 1 Age + k2 Weight, where k1 and k2 are set empirical constants, Age is the Age value, and Weight is the Weight value.

Further, the adjustment rules of different environment adjustment home appliances can be determined according to different policy selection values V.

For example, if V <50, adjustment rule 1 is selected; if V >80, adjustment rule 2 is selected. In the adjustment rule 1, there are recorded: the temperature value is more than or equal to 30 ℃, the air conditioner is started, and the temperature of the air conditioner is set to be 28 ℃; the humidity value is less than or equal to 50%, and a humidifier is started; in the adjustment rule 2, there are recorded: the temperature value is more than or equal to 28 ℃, the air conditioner is started, and the temperature of the air conditioner is set to be 26 ℃; and (5) the humidity value is less than or equal to 30%, and the humidifier is started.

Of course, it can be understood by those skilled in the art that the adjustment rule of the environment adjustment appliance corresponding to the physical condition information of the learning object may be determined in other manners, and a specific adjustment method of the environment adjustment appliance, which is specified in the adjustment rule of the environment adjustment appliance, may be determined, which is not limited in this embodiment.

And S220, controlling the environment adjusting household appliances in the intelligent home system according to the environment information acquired in real time and the adjusting rules of the environment adjusting household appliances so as to adjust the learning environment of the learning object.

And S230, controlling the learning control household appliances in the intelligent home system according to the learning attribute information of the learning object and the set learning control rule so as to control the learning content of the learning object.

In a preferred implementation manner of this embodiment, the controlling a learning control home appliance in the smart home system according to the learning attribute information of the learning object and the set learning control rule may include:

acquiring a learning plan in the learning attribute information, wherein the learning plan comprises event types and event times corresponding to examination events and/or competition events; if the arrival of the special learning stage is determined according to the current time and the event time, obtaining special learning content according to the event type; and controlling the learning control household appliance to play the special learning content.

In a specific example, the learning plan includes an end-of-term examination event, the end-of-term examination time is 2016.6.5, a time threshold may be set to 20 days, and then, starting from 20 days away from the end-of-term examination, that is, 2016.5.16, corresponding special learning content is obtained according to the end-of-term examination content, for example, language, mathematics and english, for example, the learning object is preferentially suggested to perform problematic learning, such as: analyzing the latest simulation examination error questions and the like; in another specific example, if a competition event, such as an Olympic Competition, is included in the learning plan, the latest competition simulation questions may be downloaded or the latest competition teaching video may be played in the Internet as the special learning content corresponding to the competition event.

In another preferred implementation manner of this embodiment, the controlling a learning control home appliance in the smart home system according to the learning attribute information of the learning object and the set learning control rule may include:

acquiring the quality classification of the learning subjects in the learning attribute information; determining subject learning sequences and subject learning time of different learning subjects according to the quality classification of the learning subjects; and controlling the learning control household appliance to play corresponding learning contents according to the subject learning sequence and the subject learning time.

Wherein, the classification of goodness and badness of the learning subject specifically comprises: the learning subjects are good at the learning subjects, and the classification labels of the poor learning subjects. For example: excel in English and not excel in mathematics.

In a specific example, the learning content (including the learning order and the learning time) may be selectively set in consideration of the time factor according to the classification of the learning subjects. As in the previous example, if the learning object is not good at mathematics, then the golden learning time at night, e.g., 7: 30-9: 00, as the learning time of mathematics, arranging the learning content of the mathematics; the learning object excels in english, then a later time, such as: 9: 10-10: 00, as the learning time of English, arranging the learning content of English.

The technical scheme of this embodiment is according to the different health information of study object, the adjustment rule of adopting different environment adjustment household electrical appliances carries out the adjustment of learning environment, can be different to the environmental experience of difference based on the people of different constitutions, the study object for different constitutions sets up the learning environment of different grade type, can improve the comfort level of study object in the learning environment that intelligent home systems built greatly, simultaneously, through the good and bad classification to the different course progress condition of study object or study subject, set for the learning content of different grade type, can assist the high-efficient understanding of study object or master the learning content.

EXAMPLE III

Fig. 3 is a flowchart of a smart home learning control method according to a third embodiment of the present invention, and the third embodiment is optimized based on the foregoing embodiments. In this embodiment, it is further preferable to include: if the learning object is determined to be in a learning environment outside the intelligent home system, recording learning content through the portable monitoring equipment; identifying problematic content in the current learning content of the learning object, and labeling the problematic content; acquiring auxiliary understanding information corresponding to the problematic content in the Internet, and providing the auxiliary understanding information to the learning object in a learning environment outside the intelligent home system in real time;

meanwhile, the learning control household appliances in the intelligent home system are controlled and specifically optimized according to the learning attribute information of the learning object and the set learning control rule as follows: if the current date is determined to be the day of class, acquiring the difficult and complicated content in the learning content which corresponds to the current date and is recorded by the portable monitoring equipment; searching auxiliary understanding content corresponding to the difficult content and in a set data format in the Internet according to personal likes and dislikes in the learning attribute information; controlling the learning control household appliance to play the problematic content and the auxiliary understanding content; if the current date is determined to be the rest day, acquiring weak item subjects corresponding to the learning objects according to the quality classification of the learning subjects in the learning attribute information; searching the Internet for auxiliary interest culture content associated with the weak subject; and controlling the learning control household appliance to play the auxiliary interest culture content.

Referring to fig. 3, the method of this embodiment specifically includes:

and S310, identifying the current learning environment of the learning object.

In this embodiment, if it is recognized that the learning object is in a learning environment outside the smart home system, S320 is executed; and if the object to be learned is identified to be in the smart home environment, executing S350.

In the present embodiment, it is considered that the possibility that the learning object performs learning in other environments, such as learning by students in a school classroom or learning by employees in a training classroom, is also present in addition to the smart home environment. In the technical solution of this embodiment, for the case that the learning object is in a learning environment other than the smart home system, all learning contents of the learning object in the learning environment or marked difficult and complicated contents may be recorded, and when the learning object returns to the smart home environment, the learning contents are played; and when the learning object encounters a difficult problem, the associated answering content can be immediately obtained in the Internet so as to meet the real-time answering requirement of the learning object and further improve the learning experience of the learning object.

And S320, recording the learning content through the portable monitoring equipment, and executing S330.

In this embodiment, the on-body monitoring device may include at least one of: cameras, recording pens, smart phones, tablets, and wearable devices.

Wherein, the wearable device can comprise a smart bracelet or a smart watch, etc.

S330, identifying the problematic content in the current learning content of the learning object, and labeling the problematic content.

In a preferred implementation manner of this embodiment, the identifying problematic content in the current learning content of the learning object may specifically include:

acquiring the learning content to be marked in a voice and/or character form in real time through the portable monitoring equipment;

identifying knowledge point keywords in the learning content to be labeled;

searching the knowledge point keywords in the Internet, and if the number of the network questions aiming at the knowledge point keywords is larger than a set difficulty threshold, determining the learning content to be labeled corresponding to the knowledge point keywords as the problematic content.

In another preferred implementation manner of this embodiment, the identifying problematic content in the current learning content of the learning object may specifically include:

acquiring the current learning state of the learning object and/or other learning objects around the learning object in real time through the portable monitoring equipment, wherein the current learning state comprises a question answering state;

and if the current learning state is determined to meet the abnormal learning state condition, determining the learning content corresponding to the current learning state as the problematic content.

In the present preferred embodiment, the abnormal learning state may specifically refer to a state in which the learning object cannot answer a question posed by the teacher.

S340, acquiring auxiliary understanding information corresponding to the problematic content in the Internet, and providing the auxiliary understanding information to the learning object in a learning environment outside the intelligent home system in real time.

And S350, controlling the environment adjusting household appliances in the intelligent home system according to the environment information collected in real time and the set learning environment adjusting rule so as to adjust the learning environment of the learning object.

S360, judging whether the current date is the day of class: if yes, go to S370; otherwise, S3100 is performed.

In the present embodiment, different learning content control methods are adopted for different types of dates such as class days or holidays (typically, including weekends or holidays).

And S370, acquiring problematic content in the learning content recorded by the portable monitoring equipment corresponding to the current date, and executing S380.

And S380, searching the auxiliary understanding content corresponding to the difficult content and in a set data format in the Internet according to the personal likes and dislikes in the learning attribute information, and executing S390.

In this embodiment, considering that different learning objects have different personal likes and dislikes, for example, some learning objects like watching videos, some learning objects like reading texts, or some learning objects like listening to stories, etc., auxiliary understanding contents in different data formats can be selected in the internet according to the likes and dislikes of the learning objects, so as to help a user to understand difficult contents in an easily acceptable manner.

And S390, controlling the learning control household appliance to play the problematic content and the auxiliary understanding content.

In this embodiment, considering that if the user is on a class day, the study at night can mainly aim at subjects of the study in the daytime, the portable monitoring device for recording the study content on the class in the daytime is automatically connected with the environment adjustment household appliance (typically, the portable monitoring device comprises a projector, an influence, a computer, a player and the like), so that the user can perform warm-learning explanation on the difficult content, and the user can repeat recording and video recording in the daytime compared with places difficult to understand, or automatically link the internet to search related videos, pictures, stories and characters for explanation, so as to achieve the purpose of real understanding.

S3100, according to the classification of the learning subjects in the learning attribute information, acquiring weak subjects corresponding to the learning objects, and executing S3110.

S3110, searching auxiliary interest culture contents associated with the weak item subjects in the Internet, and executing S3120.

And S3120, controlling the learning control household appliance to play the auxiliary interest culture content.

In this embodiment, it is considered that if the study is on weekends or holidays, a large period of study time of a study object is long, and meanwhile, a certain rest and relaxation are needed, and the study object can be obtained according to the quality classification of the study subjects to learn, if the study object is poor in physical quality, some short films which promote physical interest can be played, some physical interesting stories can be searched, or some simple experiments or games and the like can be played or downloaded.

The technical scheme of the embodiment of the invention is further expanded aiming at the condition that the learning object is in the learning environment except the intelligent home system, when the learning object is determined to be in other learning environments different from the intelligent home environment, all learning contents of the learning object in the learning environment or marked difficult and complicated contents are recorded, and when the learning object returns to the intelligent home environment, the learning contents are played; the method can also be used for instantly acquiring the associated answering content in the Internet when the learning object encounters a difficult problem so as to meet the real-time answering requirement of the learning object and further improve the learning experience of the learning object, and meanwhile, different learning contents are set through the difference between the class days and the break days, so that the learning object can be further assisted to efficiently understand or master the learning content.

Example four

Fig. 4 is a flowchart of a smart home learning control method according to a fourth embodiment of the present invention, and the present embodiment is optimized based on the foregoing embodiment. In this embodiment, it is further preferable to include: and if an abnormal disturbance event is detected, selecting an abnormal processing strategy corresponding to the event type of the abnormal disturbance event to adjust the environment adjustment household appliance and/or the learning control household appliance.

Referring to fig. 4, the method of this embodiment specifically includes:

and S410, controlling the environment adjusting household appliances in the intelligent home system according to the environment information collected in real time and the set learning environment adjusting rule so as to adjust the learning environment of the learning object.

And S420, controlling the learning control household appliances in the intelligent home system according to the learning attribute information of the learning object and the set learning control rule so as to control the learning content of the learning object.

S430, judging whether an abnormal disturbing event is detected: if yes, go to S440; otherwise, return to S420.

And S440, identifying the type of the abnormal disturbance event.

In this embodiment, the abnormal disturbance event mainly includes a phone access event and a third party visiting event. The telephone access event can be detected in a voice recognition mode or a telephone line monitoring mode, and the third party personnel visiting event can be detected in a voice, fingerprint or face recognition mode and the like.

If the abnormal disturbing event type is a telephone access event, executing S450; if the abnormal disturbing event type is a third party personnel visiting event, executing S470.

And S450, controlling the learning control household appliance to pause the currently played learning content, controlling the learning control household appliance to be connected to a telephone, and executing S460.

And S460, after the telephone is hung up, controlling the learning control household appliance to continuously play the learning content.

In a specific example, if a telephone is accessed, the household appliance can be automatically adjusted through the environment to perform telephone access, a tutorial is paused, the telephone is firstly answered, the telephone is answered, the tutorial is continued, and a good experience is provided for a learning object.

And S470, controlling the learning control household appliance to pause the currently played learning content, and executing S480.

S480, judging whether the third party personnel are long-term resident personnel, and if so, executing S490; otherwise, S4110 is performed.

In this embodiment, the third party personnel can be identified through the smart home monitoring device, and whether the third party personnel are long-term resident personnel is firstly judged, wherein the third party personnel can be judged by identifying keywords. For example. If the identified keywords include: when words such as 'water-checking meter', 'take away' or 'express delivery' are used, it can be determined that the third-party person does not belong to the long-term resident person.

And S490, acquiring the body state information of the third party and executing S4100.

S4100, controlling the environment adjusting household appliance according to the body state information of the third party personnel to correct the current smart home environment, and executing S4110.

In this embodiment, if it is determined that the third party person is a long-term resident person, the current smart home environment may be modified according to the body state information.

Wherein the physical state information of the third party person may include: the body temperature, the speech rate, the height, the age, the body type and other information, preferably, the body state information of the third-party personnel can be acquired through infrared equipment.

In a specific example, if the third-party person is an old person in one year and the current indoor temperature is low, the current indoor temperature may be adaptively increased to improve the experience of the third-party person.

S4110, after the third party person leaves, controlling the learning control household appliance to continuously play the learning content.

In this embodiment, if there is a sudden visit by a third party, the adjustment can be made according to the actual situation, such as: temperature, and brightness value of the home; if the learning object is watching video or listening to lessons, the current playing content can be automatically paused; furthermore, if privacy is involved, the camera equipment can be automatically hidden or closed, and the like.

According to the technical scheme, on the basis of the above embodiments, a processing mechanism for an abnormal disturbance event is added, the smart home learning control method is further improved, when an event disturbing the current learning content of the learning object occurs, the current learning content is paused, and after the abnormal disturbance event disappears, the paused learning content is continuously played, so that the learning experience of the learning object is further optimized.

Fig. 5 is a flowchart illustrating an implementation of a specific application scenario to which the embodiment of the present invention is applicable. As shown in fig. 5, the method of this embodiment includes a plurality of determination processes, and first, if it is determined that a learning object is in a class (in a learning environment outside an intelligent home system), the method may complete labeling of problematic content by controlling portable intelligent devices such as a camera, a recording pen, a mobile phone, and an intelligent wearable device;

if it is determined that the learning object is at home (in a smart home environment), the indoor environment is dynamically adjusted according to the surrounding environment of the day (e.g., hot, cold, moldy rain, etc.) in consideration of environmental factors. For example, according to the hot or cold conditions, the air conditioner is controlled; controlling the humidifier or the dryer according to the drying or the damp condition; according to the intensity or weakness of the light, intelligent light control is carried out;

and then, the current date is further judged, the study days from Monday to Friday can be subjected to environment simulation according to the course arrangement, and the study on weekends can be consolidated according to the advantages and the disadvantages. For example, if the current date is a class day, the personal device will dock to the home device while connecting to a home theater, the internet, and the home player. Completing review and consolidation of the learning content in the daytime; if the current date is weekend, school factors are continuously considered;

when school factors are considered, learning contents can be designed according to factors such as school learning tasks, work and rest time, course arrangement, examination arrangement and the like (post-lesson homework, course planning, city competition and the like). For example, if an end-of-appointment test is about to be met, a targeted recurrence may be made; if the Olympic competition is about to come, special training can be performed; if the weekend operation needs to be completed, various forms of learning content and the like can be provided;

and then, the quality factors are continuously considered, and the learning is carried out in a targeted manner (such as liking mathematics, chemistry, bothersome physics and the like) according to the learning performances of the learning objects and the preference directions of the courses. For example, if the physics are poor, then interest can be fostered and escalated in stages; if the physics is better, the learning can be consolidated, expanded and deeply studied;

and then, continuously considering external factors, and adjusting according to factors such as sudden visits of third-party personnel or external calls. For example, stop the current learning and put into new things; continuing the current learning, adjusting or ignoring the interference appropriately, continuing the learning, etc.

The detailed flow of the specific application scenario can be seen as follows: the technical scheme of this embodiment is on the study mode, and the multiple factor of comprehensive consideration different grade type for intelligent cooperation between the household electrical appliances reaches the technological effect of building high-efficient comfortable learning environment.

Meanwhile, the technical scheme of the embodiment mainly comprises two response modes of different scenes:

1. simple and quick response

In the scene, the instant response is mainly carried out on new things which are contacted at that time in the course and the external learning communication period (not in the intelligent home environment), and a simple help-seeking response mode can be carried out on the internet through a mobile terminal or intelligent wearing, so that the user can understand the new things easily;

2. detailed follow-up response

After the user returns home, the user enters the intelligent home environment, and if the user wants to know new matters outside the day in detail, the intelligent home system can be started to learn in detail.

EXAMPLE five

Fig. 6 is a schematic structural diagram of an intelligent home learning control device according to a fifth embodiment of the present invention. Referring to fig. 6, the smart home learning control apparatus provided in this embodiment may specifically include: a learning environment adjusting module 61 and a learning content adjusting module 62.

The learning environment adjusting module 61 is configured to control the environment adjusting home appliances in the smart home system according to the environment information acquired in real time and the set learning environment adjusting rule, so as to adjust the learning environment of the learning object;

and a learning content adjusting module 62, configured to control a learning control home appliance in the smart home system according to the learning attribute information of the learning object and a set learning control rule, so as to control the learning content of the learning object.

According to the technical scheme of the embodiment of the invention, the environment adjusting household appliances in the intelligent home system are controlled according to the environment information collected in real time and the set learning environment adjusting rule so as to adjust the learning environment of the learning object; according to the learning attribute information of the learning object and the set learning control rule, the learning control household appliances in the intelligent household system are controlled to control the learning content of the learning object, the personalized characteristics based on the learning object are realized, the intelligent household environment is adjusted to the learning environment suitable for the learning object, the technical effect of playing the learning content suitable for the learning object is controlled, the technical problems that the existing household control technology is single, the cooperation scheduling of household appliances and the intelligence degree are poor, particularly, the realization scheme of comprehensively controlling a specific learning scene is lacked are solved, the existing intelligent household technology is optimized, and the increasing convenience and personalized learning requirements based on the intelligent household of people are met.

On the basis of the above embodiments, the environment information may include indoor environment information, and/or outdoor environment information;

wherein the indoor environment information includes at least one of: temperature information, humidity information, and light information;

the outdoor environment information includes at least one of: weather information, wind information, and climate information;

the environment adjusting appliance includes at least one of: air conditioners, humidifiers, dryers, and fans.

On the basis of the foregoing embodiments, the learning environment adjusting module may be configured to:

determining an adjustment rule of the environment adjustment household appliance according to the physical condition information of the learning object;

wherein the adjustment rule of the environment adjustment appliance includes: starting conditions of the environment adjusting household appliance and/or setting rules of running parameters of the environment adjusting household appliance;

and controlling the environment adjusting household appliances in the intelligent household system according to the environment information acquired in real time and the adjusting rules of the environment adjusting household appliances.

On the basis of the foregoing embodiments, the learning attribute information may include at least one of:

personal likes and dislikes, schools, grades, historical scores, school schedules, learning plans and the classification of the learning subjects;

the learning control appliance may include at least one of:

projector, stereo set, computer and playback devices.

On the basis of the foregoing embodiments, the learning content adjusting module may be configured to:

acquiring a learning plan in the learning attribute information, wherein the learning plan comprises event types and event times corresponding to examination events and/or competition events;

if the arrival of the special learning stage is determined according to the current time and the event time, obtaining special learning content according to the event type;

and controlling the learning control household appliance to play the special learning content.

On the basis of the foregoing embodiments, the learning content adjusting module may be configured to:

acquiring the quality classification of the learning subjects in the learning attribute information;

determining subject learning sequences and subject learning time of different learning subjects according to the quality classification of the learning subjects;

and controlling the learning control household appliance to play corresponding learning contents according to the subject learning sequence and the subject learning time.

On the basis of the above embodiments, the apparatus may further include:

the external environment learning content recording module is used for recording learning contents through the portable monitoring equipment if the learning object is determined to be in a learning environment outside the intelligent home system;

the problematic content identification module is used for identifying the problematic content in the current learning content of the learning object and marking the problematic content;

and the understanding information real-time providing module is used for acquiring auxiliary understanding information corresponding to the problematic content in the Internet and providing the auxiliary understanding information to the learning object in a learning environment outside the intelligent home system in real time.

On the basis of the above embodiments, the on-body monitoring device may include at least one of the following: cameras, recording pens, smart phones, tablets, and wearable devices.

On the basis of the foregoing embodiments, the problematic content identification module may be specifically configured to:

learning contents to be marked in voice and/or text forms are acquired in real time through the portable monitoring equipment;

identifying knowledge point keywords in the learning content to be labeled;

searching the knowledge point keywords in the Internet, and if the number of the network questions aiming at the knowledge point keywords is larger than a set difficulty threshold, determining the learning content to be labeled corresponding to the knowledge point keywords as the problematic content.

On the basis of the foregoing embodiments, the problematic content identification module may be specifically configured to:

acquiring the current learning state of the learning object and/or other learning objects around the learning object in real time through the portable monitoring equipment, wherein the current learning state comprises a question answering state;

and if the current learning state is determined to meet the abnormal learning state condition, determining the learning content corresponding to the current learning state as the problematic content.

On the basis of the foregoing embodiments, the learning content adjusting module may be configured to:

if the current date is determined to be the day of class, acquiring the difficult and complicated content in the learning content which corresponds to the current date and is recorded by the portable monitoring equipment;

searching auxiliary understanding content corresponding to the difficult content and in a set data format in the Internet according to personal likes and dislikes in the learning attribute information;

controlling the learning control household appliance to play the problematic content and the auxiliary understanding content;

if the current date is determined to be the rest day, acquiring weak item subjects corresponding to the learning objects according to the quality classification of the learning subjects in the learning attribute information;

searching the Internet for auxiliary interest culture content associated with the weak subject;

and controlling the learning control household appliance to play the auxiliary interest culture content.

On the basis of the above embodiments, the apparatus may further include:

and the abnormal event processing module is used for selecting an abnormal processing strategy corresponding to the event type of the abnormal disturbance event to adjust the environment adjustment household appliance and/or the learning control household appliance if the abnormal disturbance event is detected.

On the basis of the above embodiments, the abnormal disturbance event may be a telephone access event;

the exception handling module may be specifically configured to:

controlling the learning control household appliance to pause the currently played learning content and controlling the learning control household appliance to be connected to a telephone;

and after the telephone is hung up, controlling the learning control household appliance to continuously play the learning content.

On the basis of the above embodiments, the abnormal disturbing event may be a third party visiting event;

the exception handling module may be specifically configured to:

controlling the learning control household appliance to pause the currently played learning content;

identifying the third-party personnel through intelligent home monitoring equipment, and if the third-party personnel is determined to be a long-term resident personnel, acquiring body state information of the third-party personnel;

controlling the environment adjusting household appliance according to the body state information of the third-party personnel so as to correct the current intelligent home environment;

and after the third-party personnel leave, controlling the learning control household appliance to continuously play the learning content.

The intelligent home learning control device provided by the fifth embodiment of the invention belongs to the same inventive concept as the intelligent home learning control method provided by the first to fourth embodiments of the invention, can execute the intelligent home learning control method provided by the first to fourth embodiments of the invention, and has the corresponding functional modules and beneficial effects of executing the intelligent home learning control method. For details of the smart home learning control method, reference may be made to the smart home learning control method provided in the first to fourth embodiments of the present invention.

EXAMPLE six

Fig. 7 is a schematic structural diagram of an intelligent home learning control system according to a sixth embodiment of the present invention. Referring to fig. 7, the smart home learning control system provided in this embodiment specifically includes: the system comprises a first monitoring module 71, a second monitoring module 72, a smart home control module 73, a learning environment adjusting module 74 and a learning content adjusting module 75. Wherein,

the first monitoring module 71 is configured to record, through the portable monitoring device, learning content of a learning object in a learning environment outside the smart home system, and send the recorded learning content to the smart home control module 73.

The second monitoring module 72 is configured to collect the environmental information in the smart home system through an information collection sensor, and send the environmental information to the smart home control module 73.

The smart home control module 73 includes a smart home learning control device according to a fifth embodiment of the present invention.

A learning environment adjusting module 74 disposed inside the environment adjusting appliance 76, configured to adjust the environment adjusting appliance 76 according to the operation and control of the smart home control module 73;

a learning content adjusting module 75 disposed inside the learning control home appliance 77, configured to adjust the learning control home appliance 77 according to the control of the smart home control module 73.

In this embodiment, the smart home control module 73 may preferably include an information summarizing center and an information analyzing center. The learning object will first pass the real-time information to the information summary center via the first monitoring module 71. If simple response is needed, the user can directly acquire simple information from the Internet for understanding; after the second monitoring module 72 sends the information to the information summarizing center, the information of the two parties is finally summarized, the information of the first monitoring module 71 is considered preferentially, the final information is sent to the information analysis center, the priority setting of the household appliance control is carried out, and the household appliance is controlled to obtain external resources and feed the external resources back to the user for processing.

According to the technical scheme of the embodiment of the invention, the environment adjusting household appliances in the intelligent home system are controlled according to the environment information collected in real time and the set learning environment adjusting rule so as to adjust the learning environment of the learning object; according to the learning attribute information of the learning object and the set learning control rule, the learning control household appliances in the intelligent household system are controlled to control the learning content of the learning object, the personalized characteristics based on the learning object are realized, the intelligent household environment is adjusted to the learning environment suitable for the learning object, the technical effect of playing the learning content suitable for the learning object is controlled, the technical problems that the existing household control technology is single, the cooperation scheduling of household appliances and the intelligence degree are poor, particularly, the realization scheme of comprehensively controlling a specific learning scene is lacked are solved, the existing intelligent household technology is optimized, and the increasing convenience and personalized learning requirements based on the intelligent household of people are met.

Obviously, it should be understood by those skilled in the art that the modules or steps of the present invention described above may be implemented by the control server in the smart home system as described above. Alternatively, the embodiments of the present invention may be implemented by programs executable by a computer device, so that they can be stored in a storage device and executed by a processor, where the programs may be stored in a computer-readable storage medium, and the above-mentioned storage medium may be a read-only memory, a magnetic disk or an optical disk, etc.; or separately as individual integrated circuit modules, or as a single integrated circuit module from a plurality of modules or steps within them. Thus, the present invention is not limited to any specific combination of hardware and software.

The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims (14)

1. The intelligent household learning control method is characterized by comprising the following steps:

according to the environment information collected in real time and the set learning environment adjustment rule, the environment adjustment household appliances in the intelligent home system are controlled to adjust the learning environment of the learning object;

and controlling the learning control household appliances in the intelligent home system according to the learning attribute information of the learning object and the set learning control rule so as to control the learning content of the learning object.

2. The method of claim 1, wherein the environmental information comprises indoor environmental information, and/or outdoor environmental information;

wherein the indoor environment information includes at least one of: temperature information, humidity information, and light information;

the outdoor environment information includes at least one of: weather information, wind information, and climate information;

the environment adjusting appliance includes at least one of: air conditioners, humidifiers, dryers, and fans.

3. The method according to claim 1, wherein the controlling of the environment adjustment home appliance in the smart home system according to the environment information collected in real time and the set learning environment adjustment rule comprises:

determining an adjustment rule of the environment adjustment household appliance according to the physical condition information of the learning object;

wherein the adjustment rule of the environment adjustment appliance includes: starting conditions of the environment adjusting household appliance and/or setting rules of running parameters of the environment adjusting household appliance;

and controlling the environment adjusting household appliances in the intelligent household system according to the environment information acquired in real time and the adjusting rules of the environment adjusting household appliances.

4. The method of claim 1, wherein the learning attribute information comprises at least one of:

personal likes and dislikes, schools, grades, historical scores, school schedules, learning plans and the classification of the learning subjects;

the learning control home appliance includes at least one of:

projector, stereo set, computer and playback devices.

5. The method according to any one of claims 1 to 4, wherein the controlling of the learning control household appliance in the smart home system according to the learning attribute information of the learning object and the set learning control rule comprises:

acquiring a learning plan in the learning attribute information, wherein the learning plan comprises event types and event times corresponding to examination events and/or competition events;

if the arrival of the special learning stage is determined according to the current time and the event time, obtaining special learning content according to the event type;

and controlling the learning control household appliance to play the special learning content.

6. The method according to any one of claims 1 to 4, wherein the controlling of the learning control household appliance in the smart home system according to the learning attribute information of the learning object and the set learning control rule comprises:

acquiring the quality classification of the learning subjects in the learning attribute information;

determining subject learning sequences and subject learning time of different learning subjects according to the quality classification of the learning subjects;

and controlling the learning control household appliance to play corresponding learning contents according to the subject learning sequence and the subject learning time.

7. The method according to any one of claims 1-4, further comprising:

if the learning object is determined to be in a learning environment outside the intelligent home system, recording learning content through the portable monitoring equipment;

identifying problematic content in the current learning content of the learning object, and labeling the problematic content;

and acquiring auxiliary understanding information corresponding to the problematic content in the Internet, and providing the auxiliary understanding information to the learning object in a learning environment outside the intelligent home system in real time.

8. The method of claim 1, further comprising:

and if an abnormal disturbance event is detected, selecting an abnormal processing strategy corresponding to the event type of the abnormal disturbance event to adjust the environment adjustment household appliance and/or the learning control household appliance.

9. The utility model provides an intelligence house learning control device which characterized in that includes:

the learning environment adjusting module is used for controlling environment adjusting household appliances in the intelligent home system according to the environment information collected in real time and the set learning environment adjusting rule so as to adjust the learning environment of the learning object;

and the learning content adjusting module is used for controlling the learning control household appliances in the intelligent home system according to the learning attribute information of the learning object and the set learning control rule so as to control the learning content of the learning object.

10. The apparatus of claim 9, wherein the learning environment adjustment module is configured to:

determining an adjustment rule of the environment adjustment household appliance according to the physical condition information of the learning object;

wherein the adjustment rule of the environment adjustment appliance includes: starting conditions of the environment adjusting household appliance and/or setting rules of running parameters of the environment adjusting household appliance;

and controlling the environment adjusting household appliances in the intelligent household system according to the environment information acquired in real time and the adjusting rules of the environment adjusting household appliances.

11. The apparatus of claim 9 or 10, wherein the learning content adjustment module is configured to:

acquiring a learning plan in the learning attribute information, wherein the learning plan comprises event types and event times corresponding to examination events and/or competition events;

if the arrival of the special learning stage is determined according to the current time and the event time, obtaining special learning content according to the event type;

controlling the learning control household appliance to play the special learning content; or

The learning content adjusting module is configured to:

acquiring the quality classification of the learning subjects in the learning attribute information;

determining subject learning sequences and subject learning time of different learning subjects according to the quality classification of the learning subjects;

and controlling the learning control household appliance to play corresponding learning contents according to the subject learning sequence and the subject learning time.

12. The apparatus of claim 9 or 10, further comprising:

the external environment learning content recording module is used for recording learning contents through the portable monitoring equipment if the learning object is determined to be in a learning environment outside the intelligent home system;

the problematic content identification module is used for identifying the problematic content in the current learning content of the learning object and marking the problematic content;

and the understanding information real-time providing module is used for acquiring auxiliary understanding information corresponding to the problematic content in the Internet and providing the auxiliary understanding information to the learning object in a learning environment outside the intelligent home system in real time.

13. The apparatus of claim 9, further comprising:

and the abnormal event processing module is used for selecting an abnormal processing strategy corresponding to the event type of the abnormal disturbance event to adjust the environment adjustment household appliance and/or the learning control household appliance if the abnormal disturbance event is detected.

14. The utility model provides an intelligence house study control system which characterized in that includes:

the first monitoring module is used for recording learning contents of a learning object in a learning environment outside the intelligent home system through the portable monitoring equipment and sending the recorded learning contents to the intelligent home control module;

the second monitoring module is used for acquiring environmental information in the intelligent home system through an information acquisition sensor and sending the environmental information to the intelligent home control module;

the smart home control module comprises the smart home learning control device according to any one of claims 9 to 13;

the learning environment adjusting module is configured in the environment adjusting household appliance and used for adjusting the environment adjusting household appliance according to the control of the intelligent household control module;

and the learning content adjusting module is configured in the learning control household appliance and used for adjusting the learning control household appliance according to the control of the intelligent household control module.