CN117215209A - Cloud home control method and system based on Internet of things - Google Patents
Cloud home control method and system based on Internet of things Download PDFInfo
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Abstract
The invention relates to the technical field of intelligent home, in particular to a cloud home control method and system based on the Internet of things. The method comprises the steps of setting an Internet of things module to collect intelligent home data in an online self-adaptive manner, collecting the intelligent home data in a cloud data center, storing the intelligent home data in a database, extracting real-time monitoring data in the database in the cloud data center, carrying out online identification, storing the real-time monitoring data in a standard data set, carrying out microexpressive judgment according to the standard data set to form real-time fine-tuning data, quickly matching comfort identification information of a user according to current user information to be used as optimal data recommendation, and carrying out online broadcasting and recommendation of the user according to the optimal data recommendation. According to the scheme, through on-line judgment of the micro-expression of the person, the optimal cloud home state configuration scheme under the corresponding preset micro-expression number is carried out, the quick prompt of the person is realized by combining the internet of things technology, the home state is automatically controlled, and intelligent feedback of the person demand is achieved.
Description
Technical Field
The invention relates to the technical field of intelligent home, in particular to a cloud home control method and system based on the Internet of things.
Background
The intelligent control technology mainly solves the problems that: and how each control object (such as light, television, air conditioner, curtain and the like) in the home system performs effective information interaction, so that information sharing and intelligent linkage are realized. Typical application of intelligent control technology: a home light control system; a home intelligent lighting system; a home environment control system; a home security system; a home security alarm system; home theater control systems, etc. Development trend of intelligent control technology: with the continuous maturity and perfection of the internet of things technology, various intelligent terminal devices gradually replace traditional household appliances, so that household intellectualization is realized. In this process, smart home technology will be better developed. The intelligent home control technology is a necessary means for realizing intelligent life, and is a thinking and going way for people to 'future life'.
Before the technology of the invention, an intelligent home system starts to walk into the life of people, but a specific home control method is not clear, and the preset actions are controlled according to the settings of the people, so that the needs of the people at different moments are adaptively matched with the needs of the people along with the development of the technology of the Internet of things and the continuous enrichment of a cloud database.
Disclosure of Invention
In view of the above problems, the invention provides a cloud home control method and a system based on the Internet of things, which are used for carrying out an optimal cloud home state configuration scheme under a corresponding preset micro expression number through on-line judgment of a person, realizing rapid prompt of the person by combining the Internet of things technology, automatically controlling the home state and achieving intelligent feedback of the person's needs.
According to a first aspect of the embodiment of the invention, a cloud home control method based on the Internet of things is provided.
In one or more embodiments, preferably, the cloud home control method based on the internet of things includes:
an internet of things module is arranged for online self-adaptive intelligent home data acquisition;
collecting intelligent home data in a cloud data center and storing the intelligent home data in a database;
extracting real-time monitoring data in a database from a cloud data center, carrying out online identification, and storing the real-time monitoring data into a standard data set;
performing microexpressive judgment according to the standard data set to further form real-time fine adjustment data;
performing user habit learning on line, and rapidly matching comfort degree identification information of a user according to current user information to be used as optimal data recommendation;
and carrying out online broadcasting and recommendation of the user according to the optimal data recommendation.
In one or more embodiments, preferably, the setting the internet of things module to perform online adaptive smart home data collection specifically includes:
the method comprises the steps that an Internet of things module and an Internet of things control module are arranged on all camera equipment and infrared detection equipment;
all infrared detection devices are in a normally open state;
when the infrared detection equipment monitors that people enter the corresponding area, judging the total number of people in the corresponding area, and further forming a people number list of each area;
and starting cameras associated with the Internet of things according to the people number list, and performing automatic household data acquisition.
In one or more embodiments, preferably, the collecting the smart home data at the cloud data center and storing the smart home data in a database specifically includes:
acquiring face data of all people obtained by the camera equipment in a cloud data center;
acquiring the running state of each household device on line through the intelligent household device in real time;
and storing the face data and the running state together into a database.
In one or more embodiments, preferably, the extracting, at the cloud data center, real-time monitoring data in a database, performing online identification, and storing the real-time monitoring data in a standard data set specifically includes:
the facial data in the database is obtained from the cloud data center, and facial information point location identification is carried out to form micro expression point locations;
acquiring online identification data in real time, and acquiring current time and weather through a network of a cloud data center;
on-line collection of air temperature and air humidity in different areas is performed by a sensor.
In one or more embodiments, preferably, the performing microexpressive judgment according to the standard data set, so as to form real-time fine tuning data specifically includes:
presetting a micro expression database;
judging the classification of each expression in the micro-expression database by using a first calculation formula according to the historical data, wherein the classification of each expression comprises a better state and a worse state;
the interval is preset, automatic adjustment operation is carried out according to the user requirement, the second calculation formula is utilized in the automatic adjustment operation process to calculate an adjustment index, when the adjustment index is a non-negative number, whether the current adjustment direction is correct or not is judged, and otherwise, the current adjustment direction is wrong;
the first calculation formula is as follows:
A= B(C)
wherein A is the classification of expressions, B () is the extraction function of the maximum 5 digital average value in unit time, and C is the emotion score of micro expressions;
the second calculation formula is as follows:
，
wherein D is the adjustment index, T0 is the start point of the adjustment time, and T1 is the end point of the adjustment time. .
In one or more embodiments, preferably, the online learning of user habits, according to current user information, quickly matches comfort identifying information of a user, and the method specifically includes:
calculating a common matching state by using a third calculation formula according to the current time and weather of the standard data set;
obtaining all user data with scores, and obtaining an optimal matching coefficient by using a fourth calculation formula;
according to the optimal matching coefficient, combining the air temperature and the air humidity of the standard data set, and forming on-line adjustment curve data by using a fifth calculation formula;
according to the air temperature and the air humidity when the online adjustment curve data takes the maximum value, the air humidity is set to be the most common set humidity of a user, and the air temperature and the air humidity are recommended as optimal data in combination with a common matching state;
the third calculation formula is as follows:
J=H(F,G)
wherein F is air temperature, G is time at the current moment, H () is a matching state function, and J is a common matching state;
the fourth calculation formula is as follows:
{K1,K2}=ARGMIN∑{J+L×K1+M×K2-N}
wherein, K1 is a first coefficient, K2 is a second coefficient, { K1, K2} is an optimal matching coefficient, ARGMIN is an optimal coefficient learning function, L is air temperature, M is air humidity, N is scored user data, and Sigma is a summation function for obtaining corresponding data in all historical data;
the fifth calculation formula is:
S=L×K1+M×K2
wherein S is online adjustment curve data.
In one or more embodiments, preferably, the performing online broadcasting and recommending of the user according to the optimal data recommendation specifically includes:
firstly, recommending to a current user according to the optimal data recommendation line, and transmitting the recommended data recommendation line to a remote control device screen;
and when the feedback of the optimal data recommendation is not performed at preset time intervals, broadcasting recommendation is performed through the intelligent home sound equipment, and the user performs self judgment and setting.
According to a second aspect of the embodiment of the invention, a cloud home control system based on the Internet of things is provided.
In one or more embodiments, preferably, the cloud home control system based on the internet of things includes:
the camera shooting management and control module is used for setting the Internet of things module to perform online self-adaptive intelligent home data acquisition;
the cloud collection module is used for collecting intelligent home data in the cloud data center and storing the intelligent home data in the database;
the cloud rapid processing module is used for extracting real-time monitoring data in the database from the cloud data center, carrying out online identification and storing the real-time monitoring data into the standard data set;
the demand grouping module is used for carrying out microexpressive judgment according to the standard data set so as to form real-time fine tuning data;
the automatic on-site control module is used for carrying out user habit learning on line, and rapidly matching comfort degree identification information of a user according to current user information to be used as optimal data recommendation;
and the fine tuning control module is used for carrying out online broadcasting and recommendation of the user according to the optimal data recommendation.
According to a third aspect of embodiments of the present invention, there is provided a computer readable storage medium having stored thereon computer program instructions which, when executed by a processor, implement a method according to any of the first aspect of embodiments of the present invention.
According to a fourth aspect of embodiments of the present invention there is provided an electronic device comprising a memory and a processor, the memory being for storing one or more computer program instructions, wherein the one or more computer program instructions are executable by the processor to implement the method of any of the first aspects of embodiments of the present invention.
The technical scheme provided by the embodiment of the invention can comprise the following beneficial effects:
according to the scheme, the cloud home equipment is efficiently, quickly and reliably controlled by quickly collecting cloud information and combining the collected information to quickly learn.
According to the scheme, the camera shooting information at different positions is acquired through the Internet of things, so that the state of a person is mastered, efficient and low-energy-consumption monitoring based on the Internet of things equipment is further formed, and the adaptability of cloud home control is improved.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims thereof as well as the appended drawings.
The technical scheme of the invention is further described in detail through the drawings and the embodiments.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are needed in the description of the embodiments will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a flowchart of a cloud home control method based on the internet of things according to an embodiment of the invention.
Fig. 2 is a flowchart of online self-adaptive intelligent home data acquisition by setting an internet of things module in a cloud home control method based on the internet of things according to an embodiment of the invention.
Fig. 3 is a flowchart of collecting intelligent home data in a cloud data center and storing the intelligent home data in a database in a cloud home control method based on the internet of things according to an embodiment of the invention.
Fig. 4 is a flowchart of extracting real-time monitoring data in a database from a cloud data center, performing online identification, and storing the real-time monitoring data in a standard data set in a cloud home control method based on the internet of things according to an embodiment of the present invention.
Fig. 5 is a flowchart of performing microexpressive judgment according to the standard data set in the cloud home control method based on the internet of things according to an embodiment of the present invention, so as to form real-time fine tuning data.
Fig. 6 is a flowchart of performing online user habit learning in a cloud home control method based on the internet of things according to an embodiment of the present invention, and quickly matching comfort identification information of a user according to current user information, as optimal data recommendation.
Fig. 7 is a flowchart of performing online broadcasting and recommendation of a user according to the optimal data recommendation in the cloud home control method based on the internet of things according to an embodiment of the present invention.
Fig. 8 is a block diagram of a cloud home control system based on the internet of things according to an embodiment of the present invention.
Fig. 9 is a block diagram of an electronic device in one embodiment of the invention.
Detailed Description
In some of the flows described in the specification and claims of the present invention and in the foregoing figures, a plurality of operations occurring in a particular order are included, but it should be understood that the operations may be performed out of order or performed in parallel, with the order of operations such as 101, 102, etc., being merely used to distinguish between the various operations, the order of the operations themselves not representing any order of execution. In addition, the flows may include more or fewer operations, and the operations may be performed sequentially or in parallel. It should be noted that, the descriptions of "first" and "second" herein are used to distinguish different messages, devices, modules, etc., and do not represent a sequence, and are not limited to the "first" and the "second" being different types.
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to fall within the scope of the invention.
The intelligent control technology mainly solves the problems that: and how each control object (such as light, television, air conditioner, curtain and the like) in the home system performs effective information interaction, so that information sharing and intelligent linkage are realized. Typical application of intelligent control technology: a home light control system; a home intelligent lighting system; a home environment control system; a home security system; a home security alarm system; home theater control systems, etc. Development trend of intelligent control technology: with the continuous maturity and perfection of the internet of things technology, various intelligent terminal devices gradually replace traditional household appliances, so that household intellectualization is realized. In this process, smart home technology will be better developed. The intelligent home control technology is a necessary means for realizing intelligent life, and is a thinking and going way for people to 'future life'.
Before the technology of the invention, an intelligent home system starts to walk into the life of people, but a specific home control method is not clear, and the preset actions are controlled according to the settings of the people, so that the needs of the people at different moments are adaptively matched with the needs of the people along with the development of the technology of the Internet of things and the continuous enrichment of a cloud database.
The embodiment of the invention provides a cloud home control method and system based on the Internet of things. According to the scheme, through on-line judgment of the micro-expression of the person, the optimal cloud home state configuration scheme under the corresponding preset micro-expression number is carried out, the quick prompt of the person is realized by combining the internet of things technology, the home state is automatically controlled, and intelligent feedback of the person demand is achieved.
According to a first aspect of the embodiment of the invention, a cloud home control method based on the Internet of things is provided.
Fig. 1 is a flowchart of a cloud home control method based on the internet of things according to an embodiment of the invention.
In one or more embodiments, preferably, the cloud home control method based on the internet of things includes:
s101, setting an Internet of things module for online self-adaptive intelligent home data acquisition;
s102, collecting intelligent home data in a cloud data center and storing the intelligent home data in a database;
s103, extracting real-time monitoring data in a database from a cloud data center, carrying out online identification, and storing the real-time monitoring data into a standard data set;
s104, performing microexpressive judgment according to the standard data set so as to form real-time fine adjustment data;
s105, carrying out user habit learning online, and quickly matching comfort degree identification information of a user according to current user information to be used as optimal data recommendation;
and S106, performing online broadcasting and recommendation of the user according to the optimal data recommendation.
In the embodiment of the invention, the control of the camera equipment is performed through the Internet of things, so that the collection of cloud data is completed, the rapid processing of the cloud data is performed, the online judgment based on the micro expression is realized, a free demand data set is further formed, the automatic control recommendation based on the optimal data is completed, and the online fine adjustment control based on the optimal data is finally performed.
Fig. 2 is a flowchart of online self-adaptive intelligent home data acquisition by setting an internet of things module in a cloud home control method based on the internet of things according to an embodiment of the invention.
As shown in fig. 2, in one or more embodiments, preferably, the setting the internet of things module to perform online adaptive smart home data collection specifically includes:
s201, setting an Internet of things module and an Internet of things control module on all camera equipment and infrared detection equipment;
s202, all infrared detection devices are in a normally open state;
s203, when the infrared detection equipment monitors that people enter the corresponding area, judging the total number of people in the corresponding area, and further forming a people number list of each area;
s204, starting cameras associated with the animal networking according to the people number list, and performing automatic household data acquisition.
In the embodiment of the invention, all the camera equipment is configured with an Internet of things management sub-module and an Internet of things communication sub-module to carry out uploading and management of data, on the basis, decision making can be tried according to information perceived at different moments, at present, the decision making scheme comprises whether two first types are human perception or not, and information acquisition is carried out through infrared equipment at a normally open entrance position; the second class of perception information of whether the second class is in the corresponding active area is mainly based on monitoring of normally open infrared equipment in different areas, and finally a camera system based on internet of things management is formed, so that self-adaptive intelligent home data acquisition is realized.
Fig. 3 is a flowchart of collecting intelligent home data in a cloud data center and storing the intelligent home data in a database in a cloud home control method based on the internet of things according to an embodiment of the invention.
As shown in fig. 3, in one or more embodiments, preferably, the collecting, at the cloud data center, the smart home data and storing the smart home data in a database specifically includes:
s301, acquiring face data of all people obtained by the camera equipment in a cloud data center;
s302, acquiring the running state of each household device on line through the intelligent household device in real time;
and S303, storing the face data and the running state together into a database.
In the embodiment of the invention, the cloud data collection process comprises two types: one type is information acquired by the image pickup apparatus; the other type is state information of the intelligent home equipment obtained in real time.
Fig. 4 is a flowchart of extracting real-time monitoring data in a database from a cloud data center, performing online identification, and storing the real-time monitoring data in a standard data set in a cloud home control method based on the internet of things according to an embodiment of the present invention.
As shown in fig. 4, in one or more embodiments, preferably, the extracting, at the cloud data center, real-time monitoring data in a database, performing online identification, and storing the real-time monitoring data in a standard data set specifically includes:
s401, obtaining the face data in a database in a cloud data center, and identifying facial information point positions to form micro expression point positions;
s402, acquiring online identification data in real time, and acquiring current time and weather through a network of a cloud data center;
s403, carrying out on-line acquisition of air temperature and air humidity of different areas through a sensor.
In the embodiment of the invention, the rapid processing process mainly comprises the steps of collecting micro-expression data in image data, firstly identifying human face contours, identifying human face information points to form a data set, and finally, based on the micro-expression points of the data set; secondly, carrying out on-line identification on the current time, weather, air temperature and air humidity to form a standard data set in a preset time period.
Fig. 5 is a flowchart of performing microexpressive judgment according to the standard data set in the cloud home control method based on the internet of things according to an embodiment of the present invention, so as to form real-time fine tuning data.
In one or more embodiments, as shown in fig. 5, preferably, the performing the microexpressive judgment according to the standard data set further forms real-time fine tuning data specifically includes:
s501, presetting a micro-expression database;
s502, judging classification of each expression in the micro-expression database by using a first calculation formula according to historical data, wherein the classification of each expression comprises a better state and a worse state;
s503, performing automatic adjustment operation according to the user requirement at intervals of a preset period, wherein the automatic adjustment operation process calculates an adjustment index by using a second calculation formula, and if the adjustment index is a non-negative number, the current adjustment direction is correct, otherwise, the current adjustment direction is wrong;
the first calculation formula is as follows:
A= B(C)
wherein A is the classification of expressions, B () is the extraction function of the maximum 5 digital average value in unit time, and C is the emotion score of micro expressions;
the second calculation formula is as follows:
，
wherein D is the adjustment index, T0 is the start point of the adjustment time, and T1 is the end point of the adjustment time.
In the embodiment of the invention, on-line comparison is performed based on the preset micro-expression database, so that a key feature of the micro-expression is formed; the matching of the current state is carried out according to the key characteristics, generally, the matching is carried out according to the historical data, the matching result is divided into two types, one type is that the original state is better, the other type is that the original state is worse, whether the current state is increased by the corresponding micro expression proportion is judged through simple adjustment, and if the current state is increased, the direction is considered to be correct, otherwise, the direction is considered to be incorrect, and reverse adjustment is needed.
Fig. 6 is a flowchart of performing online user habit learning in a cloud home control method based on the internet of things according to an embodiment of the present invention, and quickly matching comfort identification information of a user according to current user information, as optimal data recommendation.
As shown in fig. 6, in one or more embodiments, preferably, the online learning of user habits, according to current user information, quickly matches comfort identifying information of a user, and the method specifically includes:
s601, calculating a common matching state by using a third calculation formula according to the current time and weather of the standard data set;
s602, obtaining all user data with scores, and obtaining an optimal matching coefficient by using a fourth calculation formula;
s603, forming on-line adjustment curve data by utilizing a fifth calculation formula according to the optimal matching coefficient and combining the air temperature and the air humidity of the standard data set;
s604, according to the air temperature and the air humidity when the online adjustment curve data takes the maximum value, setting the air humidity as the most common setting humidity of a user, and recommending the most common setting humidity as optimal data by combining with a common matching state;
the third calculation formula is as follows:
J=H(F,G)
wherein F is air temperature, G is time at the current moment, H () is a matching state function, and J is a common matching state;
the fourth calculation formula is as follows:
{K1,K2}=ARGMIN∑{J+L×K1+M×K2-N}
wherein, K1 is a first coefficient, K2 is a second coefficient, { K1, K2} is an optimal matching coefficient, ARGMIN is an optimal coefficient learning function, L is air temperature, M is air humidity, N is scored user data, and Sigma is a summation function for obtaining corresponding data in all historical data;
the fifth calculation formula is:
S=L×K1+M×K2
wherein S is online adjustment curve data.
In the embodiment of the invention, the optimal state is adjusted according to the demand data set, so that online habit learning is performed, the historical data of the corresponding user is learned, the online recommendation of the most habit data of the user is selected according to the historical data under the corresponding time, temperature and humidity, and the comfort degree identification information of the user is rapidly matched.
Fig. 7 is a flowchart of performing online broadcasting and recommendation of a user according to the optimal data recommendation in the cloud home control method based on the internet of things according to an embodiment of the present invention.
As shown in fig. 7, in one or more embodiments, preferably, the performing online broadcasting and recommending of the user according to the optimal data recommendation specifically includes:
s701, recommending the current user according to the optimal data recommendation line, and firstly sending the recommendation line to a remote control device screen;
s702, when feedback of the optimal data recommendation is not performed at preset time intervals, broadcasting recommendation is performed through the intelligent home sound equipment, and self judgment and setting are performed by a user.
In the embodiment of the invention, after the optimal data recommendation is finished, the recommendation is carried out on line to the current user, the recommendation process is firstly sent to a remote control device screen, then the broadcasting recommendation is carried out through the intelligent home sound equipment, and the interval for noticing the recommendation is generally set by the user.
According to a second aspect of the embodiment of the invention, a cloud home control system based on the Internet of things is provided.
Fig. 8 is a block diagram of a cloud home control system based on the internet of things according to an embodiment of the present invention.
In one or more embodiments, preferably, the cloud home control system based on the internet of things includes:
the camera control module 801 is used for setting an internet of things module to perform online self-adaptive intelligent home data acquisition;
the cloud collection module 802 is configured to collect intelligent home data in a cloud data center and store the intelligent home data in a database;
the cloud rapid processing module 803 is used for extracting real-time monitoring data in a database in a cloud data center, carrying out online identification and storing the real-time monitoring data in a standard data set;
the requirement grouping module 804 is configured to perform microexpressive judgment according to the standard data set, so as to form real-time fine tuning data;
the automatic on-site control module 805 is configured to perform user habit learning online, and quickly match comfort identification information of a user according to current user information, as optimal data recommendation;
and the fine tuning control module 806 is configured to perform online broadcasting and recommendation of the user according to the optimal data recommendation.
In the embodiment of the invention, a system suitable for different structures is realized through a series of modularized designs, and the system can realize closed-loop, reliable and efficient execution through acquisition, analysis and control.
According to a third aspect of embodiments of the present invention, there is provided a computer readable storage medium having stored thereon computer program instructions which, when executed by a processor, implement a method according to any of the first aspect of embodiments of the present invention.
According to a fourth aspect of an embodiment of the present invention, there is provided an electronic device. Fig. 9 is a block diagram of an electronic device in one embodiment of the invention. The electronic device shown in fig. 9 is a general cloud home control device based on the internet of things. Referring to fig. 9, the electronic device includes a plurality of acquisition devices 901 and a processing device 902; wherein different acquisition devices 901 monitor different areas of a target scene, and the monitoring areas of a plurality of acquisition devices cover the target scene;
each acquisition device 901 is configured to acquire an image of a target scene and identify position information of a moving target in the acquired image;
the processing device 902 comprises a processor 903, a communication interface 904, a memory 905 and a communication bus 906, wherein the processor 903, the communication interface 904, the memory 905 communicate with each other via the communication bus 906,
a memory 905 for storing a computer program;
the processor 903 is configured to implement any of the above cloud home control method steps based on the internet of things provided in the embodiments of the present invention when executing the computer program stored in the memory 905.
The communication bus 906 referred to by the processing device may be a peripheral component interconnect standard (Peripheral Component Interconnect, PCI) bus, or an extended industry standard architecture (Extended Industry Standard Architecture, EISA) bus, or the like. Communication bus 906 may be divided into an address bus, a data bus, a control bus, and the like. For ease of illustration, the figures are shown with only one line, but not with only one bus or one type of bus.
The communication interface 904 is used for communication between the processing device and other devices described above.
The Memory 905 may include random access Memory (Random Access Memory, RAM) or may include Non-Volatile Memory (NVM), such as at least one magnetic disk Memory. Optionally, the memory 905 may also be at least one storage device located remotely from the aforementioned processor 903.
The processor 903 may be a general-purpose processor, including a central processing unit (Central Processing Unit, CPU), a network processor (Network Processor, NP), and the like; but also digital signal processors (Digital Signal Processing, DSP), application specific integrated circuits (Application Specific Integrated Circuit, ASIC), field programmable gate arrays (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components.
The technical scheme provided by the embodiment of the invention can comprise the following beneficial effects:
according to the scheme, the cloud home equipment is efficiently, quickly and reliably controlled by quickly collecting cloud information and combining the collected information to quickly learn.
According to the scheme, the camera shooting information at different positions is acquired through the Internet of things, so that the state of a person is mastered, efficient and low-energy-consumption monitoring based on the Internet of things equipment is further formed, and the adaptability of cloud home control is improved.
It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, magnetic disk storage, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
It will be apparent to those skilled in the art that various modifications and variations can be made to the present invention without departing from the spirit or scope of the invention. Thus, it is intended that the present invention also include such modifications and alterations insofar as they come within the scope of the appended claims or the equivalents thereof.
Claims (9)
1. The cloud home control method based on the Internet of things is characterized by comprising the following steps:
an internet of things module is arranged for online self-adaptive intelligent home data acquisition;
collecting intelligent home data in a cloud data center and storing the intelligent home data in a database;
extracting real-time monitoring data in a database from a cloud data center, carrying out online identification, and storing the real-time monitoring data into a standard data set;
performing user habit learning on line, and rapidly matching comfort degree identification information of a user according to current user information to be used as optimal data recommendation;
and carrying out online broadcasting and recommendation of the user according to the optimal data recommendation.
2. The cloud home control method based on the internet of things of claim 1, wherein the setting the internet of things module performs online self-adaptive intelligent home data acquisition, and specifically comprises:
the method comprises the steps that an Internet of things module and an Internet of things control module are arranged on all camera equipment and infrared detection equipment;
all infrared detection devices are in a normally open state;
when the infrared detection equipment monitors that people enter the corresponding area, judging the total number of people in the corresponding area, and further forming a people number list of each area;
and starting cameras associated with the Internet of things according to the people number list, and performing automatic household data acquisition.
3. The cloud home control method based on the internet of things of claim 1, wherein the collecting intelligent home data in the cloud data center and storing the intelligent home data in the database specifically comprises:
acquiring face data of all people obtained by the camera equipment in a cloud data center;
acquiring the running state of each household device on line through the intelligent household device in real time;
and storing the face data and the running state together into a database.
4. The cloud home control method based on the internet of things of claim 3, wherein the extracting real-time monitoring data in a database at a cloud data center, performing online identification, and storing the real-time monitoring data in a standard data set, specifically comprises:
acquiring online identification data in real time, and acquiring current time and weather through a network of a cloud data center;
on-line collection of air temperature and air humidity in different areas is performed by a sensor.
5. The cloud home control method based on the internet of things of claim 1, wherein the online user habit learning is performed, and comfort level identification information of a user is quickly matched according to current user information to be used as optimal data recommendation, and the method specifically comprises the following steps:
calculating a common matching state by using a third calculation formula according to the current time and weather of the standard data set;
obtaining all user data with scores, and obtaining an optimal matching coefficient by using a fourth calculation formula;
according to the optimal matching coefficient, combining the air temperature and the air humidity of the standard data set, and forming on-line adjustment curve data by using a fifth calculation formula;
according to the air temperature and the air humidity when the online adjustment curve data takes the maximum value, the air humidity is set to be the most common set humidity of a user, and the air temperature and the air humidity are recommended as optimal data in combination with a common matching state;
the third calculation formula is as follows:
；
wherein F is air temperature, G is time at the current moment, H () is a matching state function, and J is a common matching state;
the fourth calculation formula is as follows:
；
wherein, K1 is a first coefficient, K2 is a second coefficient, { K1, K2} is an optimal matching coefficient, ARGMIN is an optimal coefficient learning function, L is air temperature, M is air humidity, N is scored user data, and Sigma is a summation function for obtaining corresponding data in all historical data;
the fifth calculation formula is:
；
wherein S is online adjustment curve data.
6. The cloud home control method based on the internet of things of claim 1, wherein the online broadcasting and recommending of the user according to the optimal data recommendation comprises the following steps:
firstly, recommending to a current user according to the optimal data recommendation line, and transmitting the recommended data recommendation line to a remote control device screen;
and when the feedback of the optimal data recommendation is not performed at preset time intervals, broadcasting recommendation is performed through the intelligent home sound equipment, and the user performs self judgment and setting.
7. A cloud home control system based on the internet of things, wherein the system is configured to implement the method according to any one of claims 1 to 6, the system comprising:
the camera shooting management and control module is used for setting the Internet of things module to perform online self-adaptive intelligent home data acquisition;
the cloud collection module is used for collecting intelligent home data in the cloud data center and storing the intelligent home data in the database;
the cloud rapid processing module is used for extracting real-time monitoring data in the database from the cloud data center, carrying out online identification and storing the real-time monitoring data into the standard data set;
the automatic on-site control module is used for carrying out user habit learning on line, and rapidly matching comfort degree identification information of a user according to current user information to be used as optimal data recommendation;
and the fine tuning control module is used for carrying out online broadcasting and recommendation of the user according to the optimal data recommendation.
8. A computer readable storage medium, on which computer program instructions are stored, which computer program instructions, when executed by a processor, implement the method of any of claims 1-6.
9. An electronic device comprising a memory and a processor, wherein the memory is configured to store one or more computer program instructions, wherein the one or more computer program instructions are executed by the processor to implement the method of any of claims 1-6.
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