CN117008487B - Intelligent home control system and method based on Internet of things - Google Patents

Intelligent home control system and method based on Internet of things Download PDF

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Publication number
CN117008487B
CN117008487B CN202310842543.7A CN202310842543A CN117008487B CN 117008487 B CN117008487 B CN 117008487B CN 202310842543 A CN202310842543 A CN 202310842543A CN 117008487 B CN117008487 B CN 117008487B
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equipment
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target user
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CN117008487A (en
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陈增荣
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Hans Shanghai Smart Home Technology Co ltd
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    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B15/00—Systems controlled by a computer
    • G05B15/02—Systems controlled by a computer electric
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B19/00—Programme-control systems
    • G05B19/02—Programme-control systems electric
    • G05B19/418—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM]
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B2219/00—Program-control systems
    • G05B2219/20—Pc systems
    • G05B2219/26—Pc applications
    • G05B2219/2642—Domotique, domestic, home control, automation, smart house
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
    • Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
    • Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]

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  • General Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Automation & Control Theory (AREA)
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  • Quality & Reliability (AREA)
  • Selective Calling Equipment (AREA)

Abstract

The invention relates to the technical field of intelligent home, in particular to an intelligent home control system and method based on the Internet of things, comprising the following steps: collecting the position information of all areas and the equipment information of all intelligent households, and calling the position information of a target user recorded in a period of time before any use; encrypting and storing all acquired data; analyzing the relevance of each area, and dividing the primary equipment and the secondary equipment; dividing n x n blocks, obtaining the position range of any block, analyzing the position rule of any secondary equipment before use, and further constructing a personalized block set of any secondary equipment; predicting all areas which a target user enters, and intelligently controlling the opening of the main equipment and the secondary equipment; when the using time length of the user is not detected to be larger than the set threshold value, the equipment is closed for real-time display, and the intelligence of the intelligent home is effectively improved.

Description

Intelligent home control system and method based on Internet of things
Technical Field
The invention relates to the technical field of intelligent home, in particular to an intelligent home control system and method based on the Internet of things.
Background
The intelligent home is to fully use a network security communication technology, an automatic control technology and a computer network technology in an intelligent home control system, so that furniture has certain intelligent characteristics. Along with the rapid development of economy, smart home gradually becomes an important trend of modern architecture in the informatization process, and meets the actual requirement of consumers for pursuing higher life quality. Along with the rapid development of the current internet of things technology, cloud computing technology and the like, a plurality of new technologies play a very important role in an intelligent home control system, and provide more comfortable and safer service for the home life of people.
In the prior art, the intelligent home is controlled by voice, when a user enters a residence, the intelligent home almost responds to the residence, a host controls a lighting system to be started, controls a temperature module and other intelligent modules to be started, however, when the user has low functional requirements on certain intelligent modules, the user is not only influenced to use after the intelligent modules are started, but also a lot of resources are wasted; therefore, how to intelligently control the smart home according to the user needs becomes a problem to be solved.
Disclosure of Invention
The invention aims to provide an intelligent home control system and method based on the Internet of things, so as to solve the problems in the background technology.
In order to solve the technical problems, the invention provides the following technical scheme: an intelligent home control method based on the Internet of things comprises the following steps:
Step S100: constructing a two-dimensional plane coordinate system by using a plane design diagram of a living place of a target user, and collecting position information of all areas divided in the plane design diagram to form an area range set; collecting equipment information of all intelligent home, setting the equipment information as target equipment, and forming an equipment information set, wherein the equipment information set comprises intelligent home names and corresponding position information; based on the device information set, collecting historical use records of any target device to form a use record set; based on the usage record set, the human body sensor is utilized to call the position information of the target user, which is recorded by any usage in a period of time before the usage, so as to form a position information set; encrypting and storing all acquired data;
Step S200: analyzing the relevance of each region in the regional scope set according to the regional scope set and the position information set; analyzing the use regularity of the target user to any target device according to the use record set, and further dividing the primary device and the secondary device of any target device;
Step S300: dividing any region in the region range set into n x n blocks, respectively obtaining the position range of any block, and forming a block set; matching the position range of any block in the block set with any secondary equipment information in the equipment information set to form a block equipment set; analyzing the position rule of the target user in the block set before any secondary equipment is used according to the block set and the position information set recorded by any use, and further constructing a personalized block set of any secondary equipment according to the position rule and the block equipment set;
Step S400: setting a human body sensor in any area, acquiring the position information of a current target user in real time by using the human body sensor, predicting all areas which the target user enters according to the relevance of the current position information and the areas, and setting the areas as areas to be used, and intelligently controlling the main equipment of all the areas to be used to be started at the moment; when a target user enters any area to be used, matching the real-time position of the target user with the block set, analyzing the probability that the user accords with the personalized block set of any secondary equipment, and starting the secondary equipment with the intelligent control probability exceeding a threshold value;
step S500: when the human body sensor in any area does not detect that the using time of the target user is longer than the set threshold, closing the primary equipment and the secondary equipment in the area to be used, and displaying the working states of all the target equipment in real time
Further, step S100 includes:
Step S110: acquiring a planar design diagram of a living place of a target user, constructing a two-dimensional planar coordinate system by taking a certain vertex angle of a horizontal plane of the living place as a coordinate origin, and acquiring position information of all areas divided in the planar design diagram to form an area range set A;
Step S120: collecting equipment information of all intelligent home, and setting the intelligent home as target equipment to form an equipment information set B; further collecting information of historical usage records of any target device bi in the device information set B to form a usage record information set Ci= { c1, c2, …, cm }, wherein c1, c2, …, cm respectively represent time points and usage time periods in the 1 st, 2 nd, … th and m th historical usage records of the corresponding any target device bi;
Step S130: installing a human body sensor on any region in the region range set A, and calling the position information of the target user in the t time period before using any use record cj by using the human body sensor to form a position information set
Dj= { (x 1, y 1), (x 2, y 2), …, (xt, yt) }, wherein (x 1, y 1), (x 2, y 2), …, (xt, yt) represent the location information of the target user at t time points of the target user 1,2, … in the period t before use of the arbitrary use record cj, wherein the purpose of the period t is to preserve the integrity of the data so that the user habit determination is more accurate;
Step S140: and acquiring the acquired regional scope set A, the equipment information set B, the usage record information set Ci and the position information set Dj, and carrying out encryption storage processing by utilizing an asymmetric algorithm.
Further, step S200 includes:
Step S210: acquiring all areas in the area range set A entered by the target user in the position information set Dj to form an area sequence set Ej= { e j1,ej2,…,ej k }, wherein e j1,ej2,…,ej k represents the area with sequence numbers of 1,2, …, k entered by the target user in a t period before any use record cj, Traversing the usage record information set Ci of any target device bi at the moment to form a sequence set E consisting of m region sequence sets Ej; acquiring the duty ratio p (E j f) of any region E j f in the sequence set E, when p (E j f) is larger than the probability threshold alpha/m, representing the region r as any region E j f, extracting all region sequence sets Ej of the region r in the sequence set E to form a screening set E= { E1, E2, …, ew }, wherein E1, E2, …, ew represent the 1st, 2 nd, … th and w region sequence sets of the region r;
Step S220: confirming the position fj of the region r in the arbitrary region sequence set Ej according to the screening set E to form a sequence label set: * Ef= { f1, f2, …, fw }, where f1, f2, …, fw represent position index information in which the w regions r1, 2, … are sequentially concentrated; according to the adjacent label fj+1 of any label fj in the sequential label set, confirming that any adjacent area of the area r is e j (fj+1); further, the association degree β (λ) = | between any adjacent region e j (fj+1) and other adjacent regions is obtained! { e λ[f(λ)+1]-ej (fj+1) }, wherein λ=1, 2, …, w, obtaining the association between any adjacent region e j (fj+1) and region r according to the association degree β (λ) = [ Σ w λ＝1 β (λ) ]/w, traversing the sequential index set to perform descending of the w association values ρj by using an bubbling sequencing method, and confirming that the adjacent region corresponding to ρ1 is e q (fq+1); if ρ1 is greater than the association threshold σ, the adjacent region e q (fq+1) is confirmed as a connected region of the region r, otherwise, if it is smaller than the association threshold, it is determined that the region r has no connected region; wherein, the bubbling sequencing method belongs to the conventional technical means of the technicians in the field, so that excessive redundant description is not made in the application; at this time, the connection area of any area E j f in the sequence set E is E q (fq+1), and it is confirmed whether the connection area E q (fq+1) still exists according to step S210 and step S220; by traversing the regional scope set a, the associated regions are aggregated according to the connection regions of any region e j f, and the descending order is carried out according to the number and the size of any region types after aggregation, so as to form a regional scope set a' = { R1, R2, …, rz }, wherein R1, R2, …, rz represent the 1 st, 2 nd, … th and z-type regional sets after the associated regions are aggregated in the regional scope set a;
The acquired region sequence is screened according to the region r, the position marks of the region r are concentrated in all the screened region sequences, the connection similarity of the region sequence sets is analyzed according to each mark sequence, and the connection region of the region r is confirmed, so that the region range sets are classified and aggregated, the analysis of the region relevance is facilitated, the analysis capability of the working state of main equipment is confirmed according to the region relevance in the follow-up process is improved;
Step S230: matching the position information of all target devices acquired according to the device information set B with the region range set A, and confirming that the region set corresponding to any region au where any target device bi is positioned is Rg; according to the usage record information set Ci of any target device bi, confirming that the usage frequency of any target device bi is hi= (c1+c2+ … +cm)/m, and when the usage frequency hi > gamma 1, rejecting any target device bi, such as a refrigerator, which needs to be started for a long time, and cannot be used as a target device to divide a primary device and a secondary device; when the frequency γ2< hi < γ1 is used, an arbitrary target device bi is divided into primary devices; conversely, if the frequency hi < γ2 is used, any target device bi is divided into secondary devices, where γ1, γ2 both represent frequency thresholds.
Further, step S300 includes:
step S310: dividing any area au in the area range set a into n x n blocks according to the area of the area, respectively obtaining the position range of any block, and forming a block set u= { U1, U2, …, U (n x n) }; where u1, u2, …, u (n×n) represents the 1,2, …, n×n block position information after halving the arbitrary region au; according to step S230, any secondary device information in any area au is acquired, the any secondary device information is matched with the block set U, and the block position ua corresponding to any secondary device ba is confirmed;
Step S320: acquiring a use record set of any secondary equipment ba as Ca, acquiring the position information of a target user in any area au based on a position information set Dj formed by any use record cj in the use record set Ca, and further matching all the position information of the target user in any area au with a block set to form any block change Uj; obtaining the block change of the target user in any area au in m usage records by traversing the usage record set Ca, and forming a block change set of = { U1,/U2, …,/Um }; based on the block change set U, integrating all the block changes into a new block change set U0 by using an integration algorithm, and taking the new block change set U0 as a personalized block set of any secondary equipment ba; the integration algorithm belongs to a conventional technical means of a person skilled in the art, so that excessive details are not made in the application;
By dividing any area into a plurality of blocks, the position change of the equipment and the position change of the target user are summarized into the change of block information, the block change rule of the target user when any equipment is used is further analyzed according to the change of the block, a personalized block set of any secondary equipment is constructed, the accuracy of data is improved, the personalized blocks constructed by different users are different, the diversity of system analysis is improved, and the follow-up confirmation of the working states of all the equipment according to the real-time position of the user is facilitated.
Further, step S400 includes:
Step S410: acquiring the position information (x 0, y 0) of the current target user in real time by utilizing a human body sensor, and determining that the area where the target user is positioned is au, taking the area set Rg as an area to be used according to the relevance of the areas, and intelligently controlling the main equipment of all the areas Rg to be used to be started at the moment;
Step S420: the position change when the target user enters the area au is detected in real time by utilizing a human body sensor, and the position change acquired in real time is matched with the block set U to form real-time block change um+1; at this time, matching the real-time block change um+1 with the new block change U0 to obtain a matching similarity y= |um+1 n U0|/|um+1U 0|; and when the matching similarity is larger than the matching threshold value phi, the intelligent starting is carried out on any secondary equipment ba, and otherwise, the secondary equipment ba is in a closed state.
Analyzing the user position in real time by utilizing a human body sensor, confirming the associated area of the user according to the user position, and intelligently starting main equipment of the area; and further, according to the block change of the user position and the similarity of the personalized block set, the working state of the secondary equipment is intelligently matched, and the control performance of the intelligent home is improved.
Further, the intelligent home control system, the system includes: the system comprises a data acquisition module, a database, a region analysis module, a personalized construction module, an intelligent control module and a data feedback module;
Constructing a two-dimensional plane coordinate system by a data acquisition module according to a plane design diagram of a target user residence, and acquiring position information of all areas divided in the plane design diagram to form an area range set; collecting equipment information of all intelligent home, setting the equipment information as target equipment, and forming an equipment information set, wherein the equipment information set comprises intelligent home names and corresponding position information; ; based on the device information set, collecting historical use records of any target device to form a use record set; based on the usage record set, the human body sensor is utilized to call the position information of the target user, which is recorded by any usage in a period of time before the usage, so as to form a position information set;
Encrypting and storing all acquired data through a database;
Analyzing the relevance of each region in the regional scope set according to the regional scope set and the position information set by a regional analysis module; analyzing the use regularity of the target user to any target device according to the use record set, and further dividing the primary device and the secondary device of any target device;
Dividing any region in the region range set into n x n blocks through a personalized construction module, and respectively acquiring the position range of any block to form a block set; matching the position range of any block in the block set with any secondary equipment information in the equipment information set to form a block equipment set; analyzing the position rule of the target user in the block set before any secondary equipment is used according to the block set and the position information set recorded by any use, and further constructing a personalized block set of any secondary equipment according to the position rule and the block equipment set;
Setting human body sensors in all areas through an intelligent control module, acquiring the position information of a current target user in real time by utilizing the human body sensors, predicting all areas which the target user enters according to the relevance of the current position information and the areas, and setting the areas as areas to be used, and intelligently controlling main equipment of all the areas to be used to be started at the moment; when a target user enters any area to be used, matching the real-time position of the target user with the block set, analyzing the probability that the user accords with the personalized block set of any secondary equipment, and starting the secondary equipment with the intelligent control probability exceeding a threshold value;
And when the human body sensor in any area does not detect that the using time length of the target user is larger than the set threshold value, closing the primary equipment and the secondary equipment of the area to be used by the data feedback module, and displaying the working states of all the target equipment in real time.
Further, the data acquisition module comprises a regional range acquisition unit, an equipment information acquisition unit and a position information acquisition unit;
The regional range acquisition unit is used for acquiring the position information of all regions divided in the plane design drawing; the device information acquisition unit is used for acquiring historical use records of any target device; the position information acquisition unit is used for calling the position information of the target user, which is recorded in a period of time before the use, by utilizing the human body sensor.
Further, the area analysis module comprises a correlation analysis unit and a device dividing unit;
the association analysis unit is used for analyzing the association of each region in the regional scope set according to the regional scope set and the position information set; the device dividing unit is used for analyzing the use regularity of the target user on any target device according to the use record set and further dividing the primary device and the secondary device on any target device.
Further, the personalized construction module comprises a block matching unit and a personalized analysis unit;
the block matching unit is used for dividing any area into n x n blocks to form a block set, and matching the position range of any block in the block set with any piece of secondary equipment information in the equipment information set to form a block equipment set; the personalized analysis unit is used for analyzing the position rule of the target user in the block set before any secondary equipment is used, and further constructing a personalized block set of any secondary equipment according to the position rule and the block equipment set.
Further, the intelligent control module comprises a real-time acquisition unit, a main equipment control unit and a secondary equipment control unit;
The real-time acquisition unit is used for acquiring the position information of the current target user in real time; the main equipment control unit is used for predicting all areas entered by the target user according to the relevance of the current position information and the areas, setting the areas as areas to be used, and intelligently controlling the main equipment of all the areas to be used to be started at the moment; the secondary equipment control unit is used for matching the real-time position of the target user with the block set when the target user enters any area to be used, analyzing the probability that the user accords with the personalized block set of any secondary equipment, and intelligently controlling the secondary equipment with the probability exceeding a threshold to be started.
Compared with the prior art, the invention has the following beneficial effects:
Through analyzing the relevance among all the areas, the analysis capability of confirming the working state of the main equipment according to the relevance of the areas is improved; dividing any area into n x n blocks, classifying the position change of a target user into block change, further analyzing the block change rule of the target user when any equipment is used according to the block change, constructing a personalized block set of any secondary equipment, improving the accuracy of data, and improving the diversity of system analysis because the personalized blocks constructed by different users are different; analyzing the user position in real time by utilizing a human body sensor, confirming the associated area of the user according to the user position, and intelligently starting main equipment of the area; and further, according to the block change of the user position and the similarity of the personalized block set, the working state of the secondary equipment is intelligently matched, and the control performance of the intelligent home is improved.
Drawings
The accompanying drawings are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate the invention and together with the embodiments of the invention, serve to explain the invention. In the drawings:
FIG. 1 is a block diagram of an intelligent home control system based on the Internet of things;
fig. 2 is a flowchart of an intelligent home control method based on the internet of things.
Detailed Description
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 be within the scope of the invention.
Referring to fig. 1, the present invention provides the following technical solutions: an intelligent home control system, the system comprising: the system comprises a data acquisition module, a database, a region analysis module, a personalized construction module, an intelligent control module and a data feedback module;
Constructing a two-dimensional plane coordinate system by a data acquisition module according to a plane design diagram of a target user residence, and acquiring position information of all areas divided in the plane design diagram to form an area range set; collecting equipment information of all intelligent home, setting the equipment information as target equipment, and forming an equipment information set, wherein the equipment information set comprises intelligent home names and corresponding position information; ; based on the device information set, collecting historical use records of any target device to form a use record set; based on the usage record set, the human body sensor is utilized to call the position information of the target user, which is recorded by any usage in a period of time before the usage, so as to form a position information set;
the data acquisition module comprises an area range acquisition unit, an equipment information acquisition unit and a position information acquisition unit;
The regional range acquisition unit is used for acquiring the position information of all regions divided in the plane design drawing; the device information acquisition unit is used for acquiring historical use records of any target device; the position information acquisition unit is used for calling the position information of the target user, which is recorded in a period of time before the use, by utilizing the human body sensor.
Encrypting and storing all acquired data through a database;
the database is used for collecting a regional scope set, a device information set, a usage record set and a position information set, and encrypting and storing the collected data by utilizing an asymmetric algorithm.
Analyzing the relevance of each region in the regional scope set according to the regional scope set and the position information set by a regional analysis module; analyzing the use regularity of the target user to any target device according to the use record set, and further dividing the primary device and the secondary device of any target device;
the area analysis module comprises a correlation analysis unit and a device division unit;
the association analysis unit is used for analyzing the association of each region in the regional scope set according to the regional scope set and the position information set; the device dividing unit is used for analyzing the use regularity of the target user on any target device according to the use record set and further dividing the primary device and the secondary device on any target device.
Dividing any region in the region range set into n x n blocks through a personalized construction module, and respectively acquiring the position range of any block to form a block set; matching the position range of any block in the block set with any secondary equipment information in the equipment information set to form a block equipment set; analyzing the position rule of the target user in the block set before any secondary equipment is used according to the block set and the position information set recorded by any use, and further constructing a personalized block set of any secondary equipment according to the position rule and the block equipment set;
the individuation construction module comprises a block matching unit and an individuation analysis unit;
the block matching unit is used for dividing any area into n x n blocks to form a block set, and matching the position range of any block in the block set with any piece of secondary equipment information in the equipment information set to form a block equipment set; the personalized analysis unit is used for analyzing the position rule of the target user in the block set before any secondary equipment is used, and further constructing a personalized block set of any secondary equipment according to the position rule and the block equipment set.
Setting human body sensors in all areas through an intelligent control module, acquiring the position information of a current target user in real time by utilizing the human body sensors, predicting all areas which the target user enters according to the relevance of the current position information and the areas, and setting the areas as areas to be used, and intelligently controlling main equipment of all the areas to be used to be started at the moment; when a target user enters any area to be used, matching the real-time position of the target user with the block set, analyzing the probability that the user accords with the personalized block set of any secondary equipment, and starting the secondary equipment with the intelligent control probability exceeding a threshold value;
The intelligent control module comprises a real-time acquisition unit, a main equipment control unit and a secondary equipment control unit;
The real-time acquisition unit is used for acquiring the position information of the current target user in real time; the main equipment control unit is used for predicting all areas entered by the target user according to the relevance of the current position information and the areas, setting the areas as areas to be used, and intelligently controlling the main equipment of all the areas to be used to be started at the moment; the secondary equipment control unit is used for matching the real-time position of the target user with the block set when the target user enters any area to be used, analyzing the probability that the user accords with the personalized block set of any secondary equipment, and intelligently controlling the secondary equipment with the probability exceeding a threshold to be started.
And when the human body sensor in any area does not detect that the using time length of the target user is larger than the set threshold value, closing the primary equipment and the secondary equipment of the area to be used by the data feedback module, and displaying the working states of all the target equipment in real time.
Referring to fig. 2, the present invention provides the following technical solutions: an intelligent home control method based on the Internet of things comprises the following steps:
Step S100: constructing a two-dimensional plane coordinate system by using a plane design diagram of a living place of a target user, and collecting position information of all areas divided in the plane design diagram to form an area range set; collecting equipment information of all intelligent home, setting the equipment information as target equipment, and forming an equipment information set, wherein the equipment information set comprises intelligent home names and corresponding position information; based on the device information set, collecting historical use records of any target device to form a use record set; based on the usage record set, the human body sensor is utilized to call the position information of the target user, which is recorded by any usage in a period of time before the usage, so as to form a position information set; encrypting and storing all acquired data;
The step S100 includes:
Step S110: acquiring a planar design diagram of a living place of a target user, constructing a two-dimensional planar coordinate system by taking a certain vertex angle of a horizontal plane of the living place as a coordinate origin, and acquiring position information of all areas divided in the planar design diagram to form an area range set A;
Step S120: collecting equipment information of all intelligent home, and setting the intelligent home as target equipment to form an equipment information set B; further collecting information of historical usage records of any target device bi in the device information set B to form a usage record information set Ci= { c1, c2, …, cm }, wherein c1, c2, …, cm respectively represent time points and usage time periods in the 1 st, 2 nd, … th and m th historical usage records of the corresponding any target device bi;
Step S130: installing a human body sensor on any region in the region range set A, and calling the position information of the target user in the t time period before using any use record cj by using the human body sensor to form a position information set
Dj= { (x 1, y 1), (x 2, y 2), …, (xt, yt) }, wherein (x 1, y 1), (x 2, y 2), …, (xt, yt) represent the location information of the target user at t time points of the target user 1,2, … in the period t before use of the arbitrary use record cj, wherein the purpose of the period t is to preserve the integrity of the data so that the user habit determination is more accurate;
Step S140: and acquiring the acquired regional scope set A, the equipment information set B, the usage record information set Ci and the position information set Dj, and carrying out encryption storage processing by utilizing an asymmetric algorithm.
Step S200: analyzing the relevance of each region in the regional scope set according to the regional scope set and the position information set; analyzing the use regularity of the target user to any target device according to the use record set, and further dividing the primary device and the secondary device of any target device;
step S200 includes:
Step S210: acquiring all areas in the area range set A entered by the target user in the position information set Dj to form an area sequence set Ej= { e j1,ej2,…,ej k }, wherein e j1,ej2,…,ej k represents the area with sequence numbers of 1,2, …, k entered by the target user in a t period before any use record cj, Traversing the usage record information set Ci of any target device bi at the moment to form a sequence set E consisting of m region sequence sets Ej; acquiring the duty ratio p (E j f) of any region E j f in the sequence set E, when p (E j f) is larger than the probability threshold alpha/m, representing the region r as any region E j f, extracting all region sequence sets Ej of the region r in the sequence set E to form a screening set E= { E1, E2, …, ew }, wherein E1, E2, …, ew represent the 1st, 2 nd, … th and w region sequence sets of the region r;
Step S220: confirming the position fj of the region r in the arbitrary region sequence set Ej according to the screening set E to form a sequence label set: * Ef= { f1, f2, …, fw }, where f1, f2, …, fw represent position index information in which the w regions r1, 2, … are sequentially concentrated; according to the adjacent label fj+1 of any label fj in the sequential label set, confirming that any adjacent area of the area r is e j (fj+1); further, the association degree β (λ) = | between any adjacent region e j (fj+1) and other adjacent regions is obtained! { e λ[f(λ)+1]-ej (fj+1) }, wherein λ=1, 2, …, w, obtaining the association between any adjacent region e j (fj+1) and region r according to the association degree β (λ) = [ Σ w λ＝1 β (λ) ]/w, traversing the sequential index set to perform descending of the w association values ρj by using an bubbling sequencing method, and confirming that the adjacent region corresponding to ρ1 is e q (fq+1); if ρ1 is greater than the association threshold σ, the adjacent region e q (fq+1) is confirmed as a connected region of the region r, otherwise, if it is smaller than the association threshold, it is determined that the region r has no connected region; wherein, the bubbling sequencing method belongs to the conventional technical means of the technicians in the field, so that excessive redundant description is not made in the application; at this time, the connection area of any area E j f in the sequence set E is E q (fq+1), and it is confirmed whether the connection area E q (fq+1) still exists according to step S210 and step S220; by traversing the regional scope set a, the associated regions are aggregated according to the connection regions of any region e j f, and the descending order is carried out according to the number and the size of any region types after aggregation, so as to form a regional scope set a' = { R1, R2, …, rz }, wherein R1, R2, …, rz represent the 1 st, 2 nd, … th and z-type regional sets after the associated regions are aggregated in the regional scope set a;
Step S230: matching the position information of all target devices acquired according to the device information set B with the region range set A, and confirming that the region set corresponding to any region au where any target device bi is positioned is Rg; according to the usage record information set Ci of any target device bi, confirming that the usage frequency of any target device bi is hi= (c1+c2+ … +cm)/m, and when the usage frequency hi > gamma 1, rejecting any target device bi, such as a refrigerator, which needs to be started for a long time, and cannot be used as a target device to divide a primary device and a secondary device; when the frequency γ2< hi < γ1 is used, an arbitrary target device bi is divided into primary devices; conversely, if the frequency hi < γ2 is used, any target device bi is divided into secondary devices, where γ1, γ2 both represent frequency thresholds.
Step S300: dividing any region in the region range set into n x n blocks, respectively obtaining the position range of any block, and forming a block set; matching the position range of any block in the block set with any secondary equipment information in the equipment information set to form a block equipment set; analyzing the position rule of the target user in the block set before any secondary equipment is used according to the block set and the position information set recorded by any use, and further constructing a personalized block set of any secondary equipment according to the position rule and the block equipment set;
step S300 includes:
step S310: dividing any area au in the area range set a into n x n blocks according to the area of the area, respectively obtaining the position range of any block, and forming a block set u= { U1, U2, …, U (n x n) }; where u1, u2, …, u (n×n) represents the 1,2, …, n×n block position information after halving the arbitrary region au; according to step S230, any secondary device information in any area au is acquired, the any secondary device information is matched with the block set U, and the block position ua corresponding to any secondary device ba is confirmed;
Step S320: acquiring a use record set of any secondary equipment ba as Ca, acquiring the position information of a target user in any area au based on a position information set Dj formed by any use record cj in the use record set Ca, and further matching all the position information of the target user in any area au with a block set to form any block change Uj; obtaining the block change of the target user in any area au in m usage records by traversing the usage record set Ca, and forming a block change set of = { U1,/U2, …,/Um }; based on the block change set U, integrating all the block changes into a new block change set U0 by using an integration algorithm, and taking the new block change set U0 as a personalized block set of any secondary equipment ba; the integration algorithm belongs to a conventional technical means of a person skilled in the art, so that redundant description is not made in the present application.
Step S400: setting a human body sensor in any area, acquiring the position information of a current target user in real time by using the human body sensor, predicting all areas which the target user enters according to the relevance of the current position information and the areas, and setting the areas as areas to be used, and intelligently controlling the main equipment of all the areas to be used to be started at the moment; when a target user enters any area to be used, matching the real-time position of the target user with the block set, analyzing the probability that the user accords with the personalized block set of any secondary equipment, and starting the secondary equipment with the intelligent control probability exceeding a threshold value;
Step S400 includes:
Step S410: acquiring the position information (x 0, y 0) of the current target user in real time by utilizing a human body sensor, and determining that the area where the target user is positioned is au, taking the area set Rg as an area to be used according to the relevance of the areas, and intelligently controlling the main equipment of all the areas Rg to be used to be started at the moment;
Step S420: the position change when the target user enters the area au is detected in real time by utilizing a human body sensor, and the position change acquired in real time is matched with the block set U to form real-time block change um+1; at this time, matching the real-time block change um+1 with the new block change U0 to obtain a matching similarity y= |um+1 n U0|/|um+1U 0|; and when the matching similarity is larger than the matching threshold value phi, the intelligent starting is carried out on any secondary equipment ba, and otherwise, the secondary equipment ba is in a closed state.
Step S500: when the human body sensor in any area does not detect that the using time of the target user is longer than the set threshold, closing the primary equipment and the secondary equipment in the area to be used, and displaying the working states of all the target equipment in real time.
For example:
The step S100 includes:
Step S110: acquiring a planar design diagram of a living place of a target user, constructing a two-dimensional planar coordinate system by taking a certain vertex angle of a horizontal plane of the living place as a coordinate origin, and acquiring position information of all areas divided in the planar design diagram to form an area range set A;
Step S120: collecting equipment information of all intelligent home, and setting the intelligent home as target equipment to form an equipment information set B; further collecting information of historical usage records of any target device B10 in the device information set B to form a usage record information set Ci= { c1, c2, …, c500}, wherein c1, c2, …, c500 respectively represent time points and usage time periods in 1 st, 2 nd, … th and 500 th historical usage records of the corresponding any target device B10;
Step S130: installing a human body sensor on any area in the area range set A, calling the position information of the target user in the 1-minute time period before the use of the optional use record c50 by utilizing the human body sensor to form a position information set D50= { (x 1, y 1), (x 2, y 2), …, (x 60, y 60) }, wherein (x 1, y 1), (x 2, y 2), …, (x 60, y 60) represents the position information of the target user when the optional use record c50 is at the 1-minute time period before the use of the target user, 1,2, … and 60 time points;
Step S140: and acquiring the acquired regional scope set A, the equipment information set B, the use record set C10 and the position information set D50, and carrying out encryption storage processing by utilizing an asymmetric algorithm.
Step S200 includes:
Step S210: acquiring all areas in the area range set A entered by the target user in the position information set D50 to form an area sequence set E50= { E 501,e502,…,e50 }, wherein E 501,e502,…,e50 represents the areas with sequence marks of 1,2, … and 20 entered by the target user in a 1-min time period before the optional use record c50 is used; traversing the usage record set C10 of any target device b10 at this time to form a sequence set E composed of 500 region sequence sets E50; acquiring the duty ratio p (E 50 f) of any region E 50 f in the sequence set E50, when p (E 50 f) is greater than the probability threshold value 100/500=1/5, representing the region r as any region E 50 f, extracting all region sequence sets E50 with the region r in the sequence set E to form a screening set = { E1, E2, …, E200}, wherein E1, E2, …, E200 represents the 1 st, 2 nd, … th and 200 th region sequence sets with the region r;
step S220: confirming the position f50 of the region r in a certain region sequence set E50 according to the screening set, and forming a sequence label set: * Ef= { f1, f2, …, f200}, where f1, f2, …, f200 represent the position index information in which the areas r1, 2, …,200 are sequentially concentrated; according to the adjacent label f20+1 of any label f20 in the sequential label set, confirm that any adjacent area of the area r is e j (f20+1); further, the association degree β (λ) = of any adjacent region e 50 (f20+1) and other adjacent regions is obtained! { e λ[f(λ)+1]-e50 (f50+1) }, wherein λ=1, 2, …,200, obtaining the association between any adjacent region e 50 (f20+1) and region r as ρ20= [ Σ 200 λ＝1 β (λ) ]/200 according to the association degree β (λ), traversing the sequential index set to perform descending of 200 association values ρ50 by using an bubbling ordering method, and confirming that the adjacent region corresponding to ρ1 is e q(fq+1)＝e3 (f3+1); when ρ1 is greater than the association threshold σ=0.6, the adjacent region e 3 (f3+1) is confirmed as the connected region of the region r; at this time, the connection area of any area E 50 f in the sequence set E is E 3 (f3+1), and it is confirmed whether the connection area E 3 (f3+1) still exists according to step S210 and step S220; by traversing the regional scope set a, the associated regions are aggregated according to the connection regions of any region e j f, and the regional scope set a' = { R1, R2, …, R5} is formed by descending order according to the number of the aggregated arbitrary region types, wherein R1, R2, …, R5 represent the 1 st, 2 nd, … th and 5 th regional scope sets after the associated regions are aggregated in the regional scope set a;
Step S230: matching the position information of all target devices acquired according to the device information set B with the region range set A, and confirming that the region set corresponding to any region au where any target device B10 is positioned is R2; according to the usage record set C10 of any target device b10, confirming that the usage frequency of any target device b10 is h10= (c1+c2+ … +c500)/500, and eliminating any target device bi when the usage frequency h10> γ1=5 times/day; when the frequency of use 2< h10<5 times/day, dividing any target device b10 into primary devices; conversely, if the frequency h10 is used <2 times/day, any target device b10 is divided into secondary devices.
Step S300 includes:
Step S310: dividing an arbitrary region au in the region range set a into 20 x 20 blocks according to the region area, respectively obtaining the position range of the arbitrary block, and forming a block set u= { U1, U2, …, U (20 x 20) }; according to step S230, any secondary device information in any area au is acquired, the any secondary device information is matched with the block set U, and the block position U120 corresponding to any secondary device b13 is confirmed;
Step S320: acquiring a usage record set of any secondary device b13 as C120, acquiring the position information of the target user in any area au based on a position information set D50 formed by any usage record C50 in the usage record set C120, and further matching all the position information of the target user in any area au with a block set to form any block change U50; by traversing the usage record set C120, the block change of the target user in any area au in the 500 usage records is obtained, so as to form a block change set of = { U1,/U2, …,/U500 }; based on the set of block changes U, the new block change U0 is integrated for all the block changes by using the integration algorithm, and then the new block change U0 is used as the personalized set of blocks of any secondary device ba.
Step S400 includes:
Step S410: acquiring the position information (x 0, y 0) of the current target user in real time by utilizing a human body sensor, and determining that the area where the target user is positioned is au, taking the area set Rg as an area to be used according to the relevance of the areas, and intelligently controlling the main equipment of all the areas Rg to be used to be started at the moment;
Step S420: the position change when the target user enters the area au is detected in real time by utilizing a human body sensor, and the position change acquired in real time is matched with the block set U to form real-time block change um+1; at this time, matching the real-time block change um+1 with the new block change U0 to obtain a matching similarity y= |um+1 n U0|/|um+1U 0|; and when the matching similarity is larger than the matching threshold phi, the intelligent starting is performed on any secondary equipment ba.
Step S500: when the human body sensor does not detect that the using time of the target user is longer than the set threshold, closing the primary equipment and the secondary equipment of the to-be-used area, and displaying the working states of all the target equipment in real time.
Finally, it should be noted that: the foregoing description is only a preferred embodiment of the present invention, and the present invention is not limited thereto, but it is to be understood that modifications and equivalents of some of the technical features described in the foregoing embodiments may be made by those skilled in the art, although the present invention has been described in detail with reference to the foregoing embodiments. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims (8)

1. An intelligent home control method based on the Internet of things is characterized by comprising the following steps of: the method comprises the following steps:
step S100: constructing a two-dimensional plane coordinate system by using a plane design diagram of a living place of a target user, and collecting position information of all areas divided in the plane design diagram to form an area range set; collecting equipment information of all intelligent home, setting the equipment information as target equipment, and forming an equipment information set; based on the device information set, collecting historical use records of any target device to form a use record set; based on the usage record set, the human body sensor is utilized to call the position information of the target user, which is recorded by any usage in a period of time before the usage, so as to form a position information set; encrypting and storing all acquired data;
Step S200: analyzing the relevance of each region in the regional scope set according to the regional scope set and the position information set; analyzing the use regularity of the target user to any target device according to the use record set, and further dividing the primary device and the secondary device of any target device;
Step S300: dividing any region in the region range set into n x n blocks, respectively obtaining the position range of any block, and forming a block set; matching the position range of any block in the block set with any secondary equipment information in the equipment information set to form a block equipment set; analyzing the position rule of the target user in the block set before any secondary equipment is used according to the block set and the position information set recorded by any use, and further constructing a personalized block set of any secondary equipment according to the position rule and the block equipment set;
Step S400: acquiring the position information of a current target user in real time by utilizing a human body sensor, predicting all areas which the target user enters according to the relevance of the current position information and the areas, and setting the areas as areas to be used, and intelligently controlling main equipment of all the areas to be used to be started at the moment; when a target user enters any area to be used, matching the real-time position of the target user with the block set, analyzing the probability that the user accords with the personalized block set of any secondary equipment, and starting the secondary equipment with the intelligent control probability exceeding a threshold value;
Step S500: when the human body sensor does not detect that the using time length of the target user is greater than a set threshold value, closing the primary equipment and the secondary equipment of the area to be used, and displaying the working states of all the target equipment in real time;
The step S100 includes:
Step S110: acquiring a planar design diagram of a living place of a target user, constructing a two-dimensional planar coordinate system by taking a certain vertex angle of a horizontal plane of the living place as a coordinate origin, and acquiring position information of all areas divided in the planar design diagram to form an area range set A;
Step S120: collecting equipment information of all intelligent home, and setting the intelligent home as target equipment to form an equipment information set B; further collecting information of historical usage records of any target device bi in the device information set B to form a usage record information set Ci= { c1, c2, …, cm }, wherein c1, c2, …, cm respectively represent time points and usage time periods in the 1 st, 2 nd, … th and m th historical usage records of the corresponding any target device bi;
Step S130: installing a human body sensor on any area in the area range set A, calling the position information of the target user in the t time period before the use of the optional use record cj by utilizing the human body sensor, and forming a position information set Dj= { (x 1, y 1), (x 2, y 2), …, (xt, yt) }, wherein (x 1, y 1), (x 2, y 2) …, (xt, yt) represents the position information of the target user when the optional use record cj is in the 1 st, 2, … and t time points of the target user in the t time period before the use;
Step S140: collecting the collected regional scope set A, the equipment information set B, the usage record information set Ci and the location information set Dj, and carrying out encryption storage processing by using an asymmetric algorithm;
The step S200 includes:
Step S210: acquiring all areas in the area range set A entered by the target user in the position information set Dj to form an area sequence set Ej= { e j1,ej2,…,ej k }, wherein e j1,ej2,…,ej k represents the area with sequence numbers of 1,2, …, k entered by the target user in a t period before any use record cj, Traversing the usage record information set Ci of any target device bi at the moment to form a sequence set E consisting of m region sequence sets Ej; acquiring the duty ratio p (E j f) of any region E j f in the sequence set E, when p (E j f) is larger than the probability threshold alpha/m, representing the region r as any region E j f, extracting all region sequence sets Ej of the region r in the sequence set E to form a screening set E= { E1, E2, …, ew }, wherein E1, E2, …, ew represent the 1st, 2 nd, … th and w region sequence sets of the region r;
Step S220: confirming the position fj of the region r in the arbitrary region sequence set Ej according to the screening set E to form a sequence label set: * Ef= { f1, f2, …, fw }, where f1, f2, …, fw represent position index information in which the w regions r1, 2, … are sequentially concentrated; according to the adjacent label fj+1 of any label fj in the sequential label set, confirming that any adjacent area of the area r is e j (fj+1); further, the association degree β (λ) = | between any adjacent region e j (fj+1) and other adjacent regions is obtained! { e λ[f(λ)+1]-ej (fj+1) }, wherein λ=1, 2, …, w, obtaining the association between any adjacent region e j (fj+1) and region r according to the association degree β (λ) = [ Σ w λ＝1 β (λ) ]/w, traversing the sequential index set to perform descending of the w association values ρj by using an bubbling sequencing method, and confirming that the adjacent region corresponding to ρ1 is e q (fq+1); when ρ1 is greater than the association threshold σ, the adjacent region e q (fq+1) is confirmed as the connected region of the region r; at this time, the connection area of any area E j f in the sequence set E is E q (fq+1), and it is confirmed whether the connection area E q (fq+1) still exists according to step S210 and step S220; by traversing the regional scope set a, the associated regions are aggregated according to the connection regions of any region e j f, and the descending order is carried out according to the number and the size of any region types after aggregation, so as to form a regional scope set a' = { R1, R2, …, rz }, wherein R1, R2, …, rz represent the 1 st, 2 nd, … th and z-type regional sets after the associated regions are aggregated in the regional scope set a;
Step S230: matching the position information of all target devices acquired according to the device information set B with the region range set A, and confirming that the region set corresponding to any region au where any target device bi is positioned is Rg; according to the usage record information set Ci of any target device bi, confirming that the usage frequency of any target device bi is hi= (c1+c2+ … +cm)/m, and eliminating any target device bi when the usage frequency hi > gamma 1; when the frequency γ2< hi < γ1 is used, an arbitrary target device bi is divided into primary devices; conversely, if the frequency hi < γ2 is used, any target device bi is divided into secondary devices, where γ1, γ2 both represent frequency thresholds.
2. The intelligent home control method based on the internet of things according to claim 1, wherein the method comprises the following steps: the step S300 includes:
step S310: dividing any area au in the area range set a into n x n blocks according to the area of the area, respectively obtaining the position range of any block, and forming a block set u= { U1, U2, …, U (n x n) }; where u1, u2, …, u (n×n) represents the 1,2, …, n×n block position information after halving the arbitrary region au; according to step S230, any secondary device information in any area au is acquired, the any secondary device information is matched with the block set U, and the block position ua corresponding to any secondary device ba is confirmed;
Step S320: acquiring a use record set of any secondary equipment ba as Ca, acquiring the position information of a target user in any area au based on a position information set Dj formed by any use record cj in the use record set Ca, and further matching all the position information of the target user in any area au with a block set to form any block change Uj; obtaining the block change of the target user in any area au in m usage records by traversing the usage record set Ca, and forming a block change set of = { U1,/U2, …,/Um }; based on the set of block changes U, the new block change U0 is integrated for all the block changes by using the integration algorithm, and then the new block change U0 is used as the personalized set of blocks of any secondary device ba.
3. The intelligent home control method based on the internet of things according to claim 2, wherein the method comprises the following steps: the step S400 includes:
Step S410: acquiring the position information (x 0, y 0) of the current target user in real time by utilizing a human body sensor, and determining that the area where the target user is positioned is au, taking the area set Rg as an area to be used according to the relevance of the areas, and intelligently controlling the main equipment of all the areas Rg to be used to be started at the moment;
Step S420: the position change when the target user enters the area au is detected in real time by utilizing a human body sensor, and the position change acquired in real time is matched with the block set U to form real-time block change um+1; at this time, matching the real-time block change um+1 with the new block change U0 to obtain a matching similarity y= |um+1 n U0|/|um+1U 0|; and when the matching similarity is larger than the matching threshold phi, the intelligent starting is performed on any secondary equipment ba.
4. An intelligent home control system for implementing an intelligent home control method based on the internet of things as set forth in any one of claims 1 to 3, wherein: the system comprises: the system comprises a data acquisition module, a database, a region analysis module, a personalized construction module, an intelligent control module and a data feedback module;
Constructing a two-dimensional plane coordinate system by using a plane design diagram of a target user residence through the data acquisition module, and acquiring the position information of all areas divided in the plane design diagram to form an area range set; collecting equipment information of all intelligent home, setting the equipment information as target equipment, and forming an equipment information set; based on the device information set, collecting historical use records of any target device to form a use record set; based on the usage record set, the human body sensor is utilized to call the position information of the target user, which is recorded by any usage in a period of time before the usage, so as to form a position information set;
encrypting and storing all acquired data through the database;
Analyzing the relevance of each region in the regional scope set according to the regional scope set and the position information set by the regional analysis module; analyzing the use regularity of the target user to any target device according to the use record set, and further dividing the primary device and the secondary device of any target device;
Dividing any region in the region range set into n x n blocks through the personalized construction module, and respectively acquiring the position range of any block to form a block set; matching the position range of any block in the block set with any secondary equipment information in the equipment information set to form a block equipment set; analyzing the position rule of the target user in the block set before any secondary equipment is used according to the block set and the position information set recorded by any use, and further constructing a personalized block set of any secondary equipment according to the position rule and the block equipment set;
the intelligent control module is used for acquiring the position information of the current target user in real time by utilizing the human body sensor, predicting all areas which the target user enters according to the relevance of the current position information and the areas, and setting the areas as areas to be used, and intelligently controlling the main equipment of all the areas to be used to be started at the moment; when a target user enters any area to be used, matching the real-time position of the target user with the block set, analyzing the probability that the user accords with the personalized block set of any secondary equipment, and starting the secondary equipment with the intelligent control probability exceeding a threshold value;
And when the human body sensor does not detect that the using time of the target user is longer than the set threshold value, the data feedback module closes the primary equipment and the secondary equipment of the area to be used, and displays the working states of all the target equipment in real time.
5. The smart home control system of claim 4, wherein: the data acquisition module comprises a regional range acquisition unit, an equipment information acquisition unit and a position information acquisition unit;
The regional range acquisition unit is used for acquiring the position information of all regions divided in the plane design drawing; the device information acquisition unit is used for acquiring historical use records of any target device; the position information acquisition unit is used for utilizing the human body sensor to call the position information of the target user, which is recorded in a period of time before being used, for arbitrary use.
6. The smart home control system of claim 4, wherein: the area analysis module comprises a correlation analysis unit and an equipment dividing unit;
The association analysis unit is used for analyzing the association of each area in the area range set according to the area range set and the position information set; the device dividing unit is used for analyzing the use regularity of the target user on any target device according to the use record set and further dividing the primary device and the secondary device on any target device.
7. The smart home control system of claim 4, wherein: the personalized construction module comprises a block matching unit and a personalized analysis unit;
The block matching unit is used for dividing any area into n-n blocks to form a block set, and matching the position range of any block in the block set with any secondary equipment information in the equipment information set to form a block equipment set; the personalized analysis unit is used for analyzing the position rule of the target user in the block set before any secondary equipment is used, and further constructing a personalized block set of any secondary equipment according to the position rule and the block equipment set.
8. The smart home control system of claim 4, wherein: the intelligent control module comprises a real-time acquisition unit, a main equipment control unit and a secondary equipment control unit;
The real-time acquisition unit is used for acquiring the position information of the current target user in real time; the main equipment control unit is used for predicting all areas entered by the target user according to the relevance between the current position information and the areas, setting the areas as areas to be used, and intelligently controlling the main equipment of all the areas to be used to be started at the moment; the secondary equipment control unit is used for matching the real-time position of the target user with the block set when the target user enters any area to be used, analyzing the probability that the user accords with the personalized block set of any secondary equipment, and intelligently controlling the secondary equipment with the probability exceeding a threshold to be started.
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Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110620948A (en) * 2019-09-16 2019-12-27 深圳创维－Rgb电子有限公司 Display method, display terminal and readable storage medium
CN112035139A (en) * 2020-08-21 2020-12-04 深圳Tcl新技术有限公司 Data updating method, device, system and storage medium for intelligent household equipment
CN113110094A (en) * 2021-05-18 2021-07-13 珠海瑞杰电子科技有限公司 Intelligent home control system based on Internet of things
CN113569965A (en) * 2021-07-30 2021-10-29 杨世斌 User behavior analysis method and system based on Internet of things
CN114114947A (en) * 2021-12-24 2022-03-01 珠海格力电器股份有限公司 Control method and device of intelligent household equipment
CN115278275A (en) * 2022-06-21 2022-11-01 北京字跳网络技术有限公司 Information presentation method, device, equipment, storage medium and program product
CN115599260A (en) * 2022-10-11 2023-01-13 杭州华橙软件技术有限公司（Cn） Intelligent scene generation method, device and system, storage medium and electronic device

Family Cites Families (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP5714783B2 (en) * 2013-03-29 2015-05-07 パナソニック インテレクチュアル プロパティ コーポレーション オブアメリカＰａｎａｓｏｎｉｃ Ｉｎｔｅｌｌｅｃｔｕａｌ Ｐｒｏｐｅｒｔｙ Ｃｏｒｐｏｒａｔｉｏｎ ｏｆ Ａｍｅｒｉｃａ Control method and program for portable information terminal

Patent Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110620948A (en) * 2019-09-16 2019-12-27 深圳创维－Rgb电子有限公司 Display method, display terminal and readable storage medium
CN112035139A (en) * 2020-08-21 2020-12-04 深圳Tcl新技术有限公司 Data updating method, device, system and storage medium for intelligent household equipment
CN113110094A (en) * 2021-05-18 2021-07-13 珠海瑞杰电子科技有限公司 Intelligent home control system based on Internet of things
CN113569965A (en) * 2021-07-30 2021-10-29 杨世斌 User behavior analysis method and system based on Internet of things
CN114114947A (en) * 2021-12-24 2022-03-01 珠海格力电器股份有限公司 Control method and device of intelligent household equipment
CN115278275A (en) * 2022-06-21 2022-11-01 北京字跳网络技术有限公司 Information presentation method, device, equipment, storage medium and program product
CN115599260A (en) * 2022-10-11 2023-01-13 杭州华橙软件技术有限公司（Cn） Intelligent scene generation method, device and system, storage medium and electronic device

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