CN114137848A - Household noise intelligent control system and method based on 5G platform - Google Patents
Household noise intelligent control system and method based on 5G platform Download PDFInfo
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- CN114137848A CN114137848A CN202111443227.XA CN202111443227A CN114137848A CN 114137848 A CN114137848 A CN 114137848A CN 202111443227 A CN202111443227 A CN 202111443227A CN 114137848 A CN114137848 A CN 114137848A
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- 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
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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
- 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], computer integrated manufacturing [CIM]
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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
- G05B2219/00—Program-control systems
- G05B2219/20—Pc systems
- G05B2219/26—Pc applications
- G05B2219/2642—Domotique, domestic, home control, automation, smart house
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- 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]
Abstract
The invention relates to the technical field of intelligent home furnishing, in particular to a household noise intelligent control system and a household noise intelligent control method based on a 5G platform, wherein the system comprises: the data acquisition module is used for acquiring environmental data of an environment where the intelligent window is located in real time and recording acquisition time corresponding to the environmental data; the action acquisition module is used for acquiring action data of the user in a preset time period before the acquisition time; the habit correcting module is used for analyzing the environmental preference of the user according to the action data to obtain a correction coefficient representing the environmental preference; the central control module is used for generating a control instruction according to the environmental data and the correction coefficient; and the switch execution module is used for executing window opening or window closing operation according to the control instruction. The correction coefficient obtained by the invention can reflect the recent environmental preference of the user, improves the freshness and the dynamic property of the correction coefficient, enables the window opening or closing to be adaptive to the recent personal habits of the user, and solves the technical problem that the window opening or closing cannot be adaptive to the personal habits of the user.
Description
Technical Field
The invention relates to the technical field of intelligent home furnishing, in particular to a household noise intelligent control system and method based on a 5G platform.
Background
With the technological progress and economic development, the living standard of people is continuously improved, so that the requirements of people on home life are higher and higher, and smart home is also a popular industry. Especially, intelligent door and window occupies very big proportion in intelligent house trade, and intelligent door and window is the biggest characteristics in not needing user manual operation, just can realize opening and closing of door and window's ventilation function.
In order to improve the remote control requirement of a user, a smart window capable of realizing remote control appears in the market, so as to overcome the defect that the smart window cannot be opened or closed in time due to the fact that the user and the smart window are located in different places. For example, there are related technologies disclosed in the prior chinese patents, and the disclosed smart window capable of implementing remote control includes a window body, an electric driving system for driving a window on the window body to open, close or rotate, a monitoring device for monitoring environmental data of an environment where the window body is located, a wireless signal transceiver for receiving and transmitting a control command for controlling the window to open or close, and a controller for controlling the electric driving system to operate and control the window according to the control command.
In the above technical solution, by monitoring the environmental data where the window body is located, for example, temperature, humidity, air quality, wind speed, etc., it is determined whether the window needs to be opened or closed according to the environmental data, and the window is directly controlled to be opened or closed by the controller, so that the window can be opened or closed even if the user is not at home. However, whether the window needs to be opened or closed is determined according to the environmental data, for example, the temperature is higher for opening the window and lower for closing the window, so that the determination ignores the individual difference of the user and the personal habits of the user, for example, the user prefers higher temperature and also prefers lower temperature, which makes the window opening or closing not well adapted to the personal habits of the user, and the user needs to modify the control result of opening or closing the window by himself, resulting in poor experience of the user.
Disclosure of Invention
The invention provides a household noise intelligent control system and method based on a 5G platform, and solves the technical problem that the prior art cannot be adapted to personal habits of users.
The basic scheme provided by the invention is as follows: family's noise intelligence control system based on 5G platform includes:
the data acquisition module is used for acquiring environmental data of an environment where the intelligent window is located in real time and recording acquisition time corresponding to the environmental data;
the action acquisition module is used for acquiring action data of the user in a preset time period before the acquisition time;
the habit correcting module is used for analyzing the environmental preference of the user according to the action data to obtain a correction coefficient representing the environmental preference;
the central control module is used for generating a control instruction according to the environmental data and the correction coefficient;
and the switch execution module is used for executing window opening or window closing operation on the intelligent window according to the control instruction.
The working principle and the advantages of the invention are as follows: in the technical scheme, the core of the technical scheme of intelligent control of the family noise lies in that the window opening or closing of the intelligent window is controlled according to the environment preference of a user. After the environmental data of the environment where the smart window is located are collected, whether the window needs to be opened or closed is not directly judged according to the environmental data, but the difference of the environmental preference of the user is considered, the environmental preference is embodied by a correction coefficient, for example, most people can open the window when the temperature is higher than 25 ℃, but a certain user likes a relatively hot environment, and only when the temperature is higher than 27 ℃, the window is opened; the correction coefficient for representing the environment preference is obtained according to the action data of the user, such as the time point, duration, environment data and the like of window opening and window closing, the rules of the motion data can reflect the environmental preference of the user, so the obtained correction coefficient can also reflect the environmental preference of the user, besides, the motion data for analyzing the correction coefficient is in a specific time period (a preset time period before the acquisition time), this particular time period is the time period closest to the moment of collecting the environmental data of the environment in which the smart window is located, therefore, the action data of the specific time period is also the embodiment of the latest environment preference of the user, the obtained correction coefficient can also embody the latest environment preference of the user, the update and the dynamic of the correction coefficient are improved, so that the entire process of controlling the opening or closing of the window can be adapted to the user's recent personal habits.
The correction coefficient obtained by the invention can reflect the recent environmental preference of the user, improves the freshness and the dynamic property of the correction coefficient, enables the window opening or closing to be adaptive to the recent personal habits of the user, and solves the technical problem that the prior art cannot be adaptive to the personal habits of the user.
Further, the action acquisition module is used for acquiring action data of the user in a preset time period before the acquisition time, wherein the action data comprises a plurality of window closing time points, window opening time points and noise decibels; the habit modification module is used for analyzing the environmental preference of the user according to the action data to obtain a modification coefficient representing the environmental preference, and further comprises:
acquiring noise decibels corresponding to a plurality of window closing time points, and calculating an average value of the noise decibels corresponding to the window closing time points, and recording the average value as a reference noise decibel;
obtaining a plurality of window closing durations according to the plurality of window closing time points and the plurality of window opening time points;
and fitting the plurality of noise decibels and the plurality of window closing durations to obtain a noise correction coefficient and a noise correction constant representing noise preference.
Has the advantages that: the reference noise decibel is calculated according to the average value of the noise decibels corresponding to a plurality of window closing time points, can reflect the lowest noise decibel enabling a user to close a window, can reflect the static individual difference of the preference of the user on noise, and is a static characteristic; the noise correction coefficient representing the noise preference obtained by fitting reflects the change characteristic between the window closing time length and the noise decibel number, can reflect the dynamic individual difference of the user to the noise preference, and is a dynamic characteristic.
Further, the action acquisition module is used for acquiring action data of the user in a preset time period before the acquisition time, wherein the action data comprises a plurality of window opening time points, window closing time points and air quality indexes; the habit modification module is used for analyzing the environmental preference of the user according to the action data to obtain a modification coefficient representing the environmental preference, and further comprises:
acquiring air quality indexes corresponding to a plurality of windowing time points, calculating an average value of the air quality indexes corresponding to the windowing time points, and recording the average value as a reference air quality index;
obtaining a plurality of windowing time lengths according to the plurality of windowing time points and the plurality of window closing time points;
and fitting the plurality of air quality indexes and the plurality of windowing time lengths to obtain an air correction coefficient and an air correction constant representing air quality preference.
Has the advantages that: the reference air quality index is calculated according to the average value of the air quality indexes corresponding to a plurality of windowing time points, can represent the lowest air quality index for windowing a user, and can reflect the static individual difference of the preference of the user to the air quality, which is a static characteristic; the air correction coefficient representing the air quality preference obtained by fitting reflects the change characteristic between the windowing time length and the air quality index, can reflect the dynamic individual difference of the user on the air quality preference, and is a dynamic characteristic.
Further, the central control module is used for generating a control instruction according to the environmental data and the correction coefficient representing the environmental preference, wherein the control instruction comprises a trigger instruction and a continuous instruction;
generating the trigger instruction includes: judging the noise decibel number and the standard noise decibel number, and if the noise decibel number is higher than the standard noise decibel number, generating a window-closing trigger instruction; or judging the sizes of the air quality index and the reference air quality index, and if the air quality index is higher than the reference air quality index, generating a window opening trigger instruction;
generating the persistence instruction includes: calculating the window closing duration, wherein the window closing duration is a noise correction coefficient x (noise decibel number-reference noise decibel number) + a noise correction constant, and a window closing duration instruction is generated according to the window closing duration; alternatively, the window duration is calculated as an air correction coefficient x (air quality index-reference air quality index) + air correction constant, and a window duration command is generated from the window duration.
Has the advantages that: the window closing/opening triggering instruction is obtained according to the average value, so that the minimum preference of a user for noise/air quality can be reflected relatively stably, and the triggering accuracy is improved; the window closing/opening continuous instruction is obtained according to the noise correction coefficient/air correction coefficient, the preference of the user on the change of noise or air quality can be reflected, and the accuracy of the window closing duration/opening duration is improved.
Further, the switch execution module further comprises a motor, and the motor is used for driving the intelligent window to open or close the window.
Has the advantages that: can open or close with the pivoted mode through motor drive smart window to realize windowing or close window operation, the technology is mature, the fault rate is low.
Further, the switch execution module further comprises a timer, and the timer is used for recording the window closing duration/the window opening duration.
Has the advantages that: and the window closing duration/window opening duration is recorded, so that subsequent checking is facilitated.
Based on the above intelligent control system for household noise based on 5G platform, the invention also provides an intelligent control method for household noise based on 5G platform, comprising the following steps:
s1, collecting environmental data of the environment where the intelligent window is located in real time, and recording collection time corresponding to the environmental data;
s2, acquiring action data of the user in a preset time period before the acquisition time;
s3, analyzing the environmental preference of the user according to the action data to obtain a correction coefficient representing the environmental preference;
s4, generating a control command according to the environmental data and the correction coefficient;
and S5, performing window opening or window closing operation on the smart window according to the control command.
The working principle and the advantages of the invention are as follows: the difference of the environmental preference of the user is considered, the environmental preference is reflected by correction coefficients, the correction coefficients are obtained according to the action data of the user, the law of the action data can reflect the environmental preference of the user, and therefore the obtained correction coefficients can also reflect the environmental preference of the user; the action data used for analyzing the correction coefficient is a specific time period of a preset time period before the collection time, the specific time period is a time period which is the latest time period of the moment of collecting the environment data of the environment where the intelligent window is located, so that the action data of the specific time period is the embodiment of the latest environment preference of the user, the obtained correction coefficient can also embody the latest environment preference of the user, the freshness and the dynamic property of the correction coefficient are improved, and the window opening or closing can be adapted to the latest personal habits of the user.
Further, in S2, acquiring motion data of the user in a preset time period before the acquisition time, where the motion data includes a plurality of window closing time points, window opening time points, and noise decibels; in S3, analyzing the environmental preference of the user according to the motion data to obtain a correction coefficient representing the environmental preference, including:
acquiring noise decibels corresponding to a plurality of window closing time points, and calculating an average value of the noise decibels corresponding to the window closing time points, and recording the average value as a reference noise decibel;
obtaining a plurality of window closing durations according to the plurality of window closing time points and the plurality of window opening time points;
and fitting the plurality of noise decibels and the plurality of window closing durations to obtain a noise correction coefficient and a noise correction constant representing noise preference.
Has the advantages that: the reference noise decibel is calculated according to the average value, so that the lowest noise decibel which enables a user to close a window can be reflected, and the static individual difference of the user on the noise preference can be reflected; the noise correction coefficient representing the noise preference obtained by fitting reflects the change characteristic between the window closing time and the noise decibel number, and can reflect the dynamic individual difference of the user to the noise preference.
Further, in S2, acquiring motion data of the user in a preset time period before the acquisition time, where the motion data includes a plurality of window opening time points, window closing time points, and an air quality index; in S3, analyzing the environmental preference of the user according to the motion data to obtain a correction coefficient representing the environmental preference, including:
acquiring air quality indexes corresponding to a plurality of windowing time points, calculating an average value of the air quality indexes corresponding to the windowing time points, and recording the average value as a reference air quality index;
obtaining a plurality of windowing time lengths according to the plurality of windowing time points and the plurality of window closing time points;
and fitting the plurality of air quality indexes and the plurality of windowing time lengths to obtain an air correction coefficient and an air correction constant representing air quality preference.
Has the advantages that: the reference air quality index is obtained by calculation according to the average value, can represent the lowest air quality index for windowing the user, and can reflect the static individual difference of the user on the preference of the air quality; the air correction coefficient representing the air quality preference obtained through fitting reflects the change characteristics between the windowing time length and the air quality index, and can reflect the dynamic individual difference of the user on the air quality preference.
Further, in S4, forming a control command according to the environmental data and the correction coefficient representing the environmental preference, where the control command includes a trigger command and a persistence command;
generating the trigger instruction includes: judging the noise decibel number and the standard noise decibel number, and if the noise decibel number is higher than the standard noise decibel number, generating a window-closing trigger instruction; or judging the sizes of the air quality index and the reference air quality index, and if the air quality index is higher than the reference air quality index, generating a window opening trigger instruction;
generating the persistence instruction includes: calculating the window closing duration, wherein the window closing duration is a noise correction coefficient x (noise decibel number-reference noise decibel number) + a noise correction constant, and a window closing duration instruction is generated according to the window closing duration; alternatively, the window duration is calculated as an air correction coefficient x (air quality index-reference air quality index) + air correction constant, and a window duration command is generated from the window duration.
Has the advantages that: the window closing/opening triggering instruction is obtained according to the average value, so that the minimum preference of a user for noise/air quality can be reflected relatively stably, and the triggering accuracy is improved; the window closing/opening continuous instruction is obtained according to the noise correction coefficient/air correction coefficient, the preference of the user on the change of noise or air quality can be reflected, and the accuracy of the window closing duration/opening duration is improved.
Drawings
Fig. 1 is a system structure block diagram of an embodiment of the intelligent household noise control system based on a 5G platform.
Detailed Description
The following is further detailed by the specific embodiments:
example 1
An embodiment is substantially as shown in figure 1, comprising:
the data acquisition module is used for acquiring environmental data of an environment where the intelligent window is located in real time and recording acquisition time corresponding to the environmental data;
the action acquisition module is used for acquiring action data of the user in a preset time period before the acquisition time;
the habit correcting module is used for analyzing the environmental preference of the user according to the action data to obtain a correction coefficient representing the environmental preference;
the central control module is used for generating a control instruction according to the environmental data and the correction coefficient;
and the switch execution module is used for executing window opening or window closing operation according to the control instruction.
In this embodiment, the data acquisition module includes a noise detector and an air quality detector, the action acquisition module, the habit modification module and the central control module are all integrated on the server, the functions thereof are realized by software/program/code/computer instructions, and the switch control module includes a motor and a timer.
The specific implementation process is as follows:
and S1, the data acquisition module acquires the environmental data of the environment where the intelligent window is located in real time and records the acquisition time corresponding to the environmental data. For example, adopt noise detector real-time detection smart window to be located the noise decibel of environment, record corresponding acquisition time simultaneously, for example: 52 decibels, 52 minutes at 11 months, 5 days, and 10 days in 2021.
And S2, the action acquisition module acquires action data of the user in a preset time period before the acquisition time. In this embodiment, the manner of acquiring the motion data is as follows: install camera and noise detection appearance at the smart window department in the family, whether 24 hours control has the operation of closing the window, and a plurality of action data of user are according to fixed format prestore in the server, for example, close the window: the window closing time point is 50 decibels at 11 months, 5 days and 10 days in 2021, the noise decibel number is 55 decibels, and the window is opened: the windowing time point is 50 minutes at 2021 year, 11 months, 5 days and 14 days, and the noise decibel number is 50 decibels. The preset time period can be manually set to be 7 days, most people work for 5 days and rest for 2 days every week according to the current working time regulation of China, and a complete 'working' and 'resting' cycle is just formed in one week, so that the action data of 7 days can accurately reflect the latest living state, work and rest rule and personal habits of the user, and the correction accuracy is improved.
And S3, analyzing the environmental preference of the user according to the action data by the habit correction module to obtain a correction coefficient representing the environmental preference. In this embodiment, the specific process is as follows:
first, obtaining noise decibels corresponding to a plurality of window closing time points, for example: acquiring data of 10 window closing time points, wherein the 10 window closing time points are marked as tc1, tc2, tc3.. tc9 and tc 10; and calculating an average value of noise decibels corresponding to a plurality of window closing time points, and recording the average value as a reference noise decibel, namely calculating an average value of the noise decibels corresponding to10 window closing time points tc1, tc2, tc3.. tc9 and tc10, so that the reference noise decibel can reflect the lowest noise decibel of a user closing window, can reflect the static individual difference of the user on noise preference, and is a static characteristic, namely a starting threshold value of the closing window.
Then, a plurality of closed window durations are obtained according to the plurality of closed window time points and the plurality of open window time points, for example: obtaining windowing time points corresponding to10 window closing time points, wherein 10 window closing time points are marked as to1, to2, to3.. to9 and to10, obtaining 10 window closing time lengths according to the 10 window closing time points and the 10 window opening time points, wherein the 10 window closing time lengths are marked as delta tc1 to1 to tc1, the delta tc2 to2 to tc2, the delta tc3 to3 to tc3.. the delta tc9 to9 to tc9, and the delta tc10 to10 to tc 10.
And finally, fitting a plurality of noise decibels and a plurality of window closing durations, namely fitting the noise decibels corresponding to10 window closing time points and the 10 window closing durations by adopting a least square method to obtain a fitting relational expression, wherein the coefficient in the fitting relational expression is a noise correction coefficient, and the constant in the fitting relational expression is a noise correction constant, so that the noise correction coefficient reflects the change characteristic between the window closing durations and the noise decibels, can reflect the dynamic individual difference of the preference of the user on the noise, and reflects the dynamic characteristic of the user on the window closing.
And S4, the central control module generates a control command according to the environmental data and the correction coefficient.
In this embodiment, the generated control instruction includes a trigger instruction and a persistent instruction, which are described as follows:
firstly, generating a trigger instruction: judging the noise decibel number and the reference noise decibel number, and if the noise decibel number is higher than the reference noise decibel number, generating a window-closing trigger instruction, so that the window-closing trigger instruction can reflect the minimum preference of a user to noise relatively stably (the preference essentially means aversion), and the triggering accuracy is improved.
Secondly, generating a continuous instruction: the window closing duration is calculated, the window closing duration is equal to a noise correction coefficient x (noise decibel-reference noise decibel) + a noise correction constant, a window closing duration instruction is generated according to the window closing duration, the noise decibel refers to the noise decibel of the environment where the intelligent window is located, and therefore the window closing duration instruction is obtained according to the noise correction coefficient, the preference of a user on the change of noise in relative change can be reflected, and the accuracy of the window closing duration is improved.
S5, the switch execution module executes window closing operation according to the control instruction: controlling a motor to drive the intelligent window to be closed in a rotating mode according to a window closing triggering instruction so as to realize window closing operation; and controlling the intelligent window to keep a closed state within the window closing duration according to the window closing duration instruction.
Example 2
The only difference from embodiment 1 is that,
and S1, detecting the air quality index of the environment where the intelligent window is located in real time by adopting an air quality detector, and simultaneously recording corresponding acquisition time.
S2, the manner of acquiring the motion data is as follows: a camera and an air quality detector are installed at a home intelligent window, and whether windowing operation exists or not is monitored in 24 hours.
And S3, analyzing the environmental preference of the user according to the action data by the habit correction module to obtain a correction coefficient representing the environmental preference. In this embodiment, the specific process is as follows:
first, obtaining air quality indexes corresponding to a plurality of windowing time points, for example: acquiring data of 10 windowing time points, wherein the 10 windowing time points are still recorded as to1, to2, to3.. to9 and to 10; and calculating the average value of the air quality indexes corresponding to the windowing time points, and recording the average value as a reference air quality index, namely calculating the average value of the air quality indexes corresponding to the 10 windowing time points of to1, to2, to3.. to9 and to10, so that the reference air quality index can represent the lowest air quality index of the user windowing and can reflect the static individual difference of the preference of the user on the air quality, and the reference air quality index is a static characteristic, namely a starting threshold value of the windowing.
Then, a plurality of windowing durations are obtained according to the plurality of windowing time points and the plurality of closing time points, for example: obtaining the closing window time points corresponding to10 windowing time points, wherein 10 closing window time points are also denoted as tc1, tc2, tc3.. tc9 and tc10, obtaining 10 windowing time lengths according to the 10 windowing time points and the 10 closing window time points, and the 10 windowing time lengths are denoted as Δ to1 ═ tc1-to1, Δ to2 ═ tc2-to2, Δ to3 ═ tc3-to3.. Δ to9 ═ tc9-to9, and Δ to10 ═ tc10-to 10.
And finally, fitting a plurality of air quality indexes and a plurality of windowing time lengths, namely fitting the air quality indexes corresponding to10 windowing time points and the 10 windowing time lengths by adopting a least square method to obtain a fitting relational expression, wherein the coefficient in the fitting relational expression is an air correction coefficient, and the constant in the fitting relational expression is an air correction constant, so that the air correction coefficient reflects the change characteristic between the windowing time length and the air quality index, can reflect the dynamic individual difference of the preference of the user to the air quality, and reflects the dynamic characteristic of windowing of the user.
And S4, the central control module generates a control command according to the environmental data and the correction coefficient.
In this embodiment, the generated control instruction includes a trigger instruction and a persistent instruction, which are described as follows:
firstly, generating a trigger instruction: and judging the sizes of the air quality index and the reference air quality index, and if the air quality index is higher than the reference air quality index, generating a windowing trigger instruction, so that the windowing trigger instruction can reflect the minimum preference of a user to the air quality relatively stably, and the triggering accuracy is improved.
Secondly, generating a continuous instruction: the windowing duration time is calculated, the windowing duration time is equal to an air correction coefficient x (air quality index-reference air quality index) + an air correction constant, and a windowing duration instruction is generated according to the windowing duration time, wherein the air quality index refers to the air quality index of the environment where the acquired intelligent window is located.
S5, the switch execution module executes windowing operation according to the control instruction: controlling a motor to drive an intelligent window to be opened in a rotating mode according to a window opening triggering instruction so as to realize window opening operation; and controlling the intelligent window to keep an open state within the window opening duration according to the window opening duration instruction.
The foregoing is merely an example of the present invention, and common general knowledge in the field of known specific structures and characteristics is not described herein in any greater extent than that known in the art at the filing date or prior to the priority date of the application, so that those skilled in the art can now appreciate that all of the above-described techniques in this field and have the ability to apply routine experimentation before this date can be combined with one or more of the present teachings to complete and implement the present invention, and that certain typical known structures or known methods do not pose any impediments to the implementation of the present invention by those skilled in the art. It should be noted that, for those skilled in the art, without departing from the structure of the present invention, several changes and modifications can be made, which should also be regarded as the protection scope of the present invention, and these will not affect the effect of the implementation of the present invention and the practicability of the patent. The scope of the claims of the present application shall be determined by the contents of the claims, and the description of the embodiments and the like in the specification shall be used to explain the contents of the claims.
Claims (10)
1. Noise intelligence control system of family based on 5G platform, its characterized in that includes:
the data acquisition module is used for acquiring environmental data of an environment where the intelligent window is located in real time and recording acquisition time corresponding to the environmental data;
the action acquisition module is used for acquiring action data of the user in a preset time period before the acquisition time;
the habit correcting module is used for analyzing the environmental preference of the user according to the action data to obtain a correction coefficient representing the environmental preference;
the central control module is used for generating a control instruction according to the environmental data and the correction coefficient;
and the switch execution module is used for executing window opening or window closing operation on the intelligent window according to the control instruction.
2. The intelligent home noise control system based on the 5G platform according to claim 1, wherein the action obtaining module is configured to obtain action data of the user in a preset time period before the collection time, and the action data includes a plurality of window closing time points, window opening time points and noise decibels; the habit modification module is used for analyzing the environmental preference of the user according to the action data to obtain a modification coefficient representing the environmental preference, and further comprises:
acquiring noise decibels corresponding to a plurality of window closing time points, and calculating an average value of the noise decibels corresponding to the window closing time points, and recording the average value as a reference noise decibel;
obtaining a plurality of window closing durations according to the plurality of window closing time points and the plurality of window opening time points;
and fitting the plurality of noise decibels and the plurality of window closing durations to obtain a noise correction coefficient and a noise correction constant representing noise preference.
3. The intelligent home noise control system based on the 5G platform as claimed in claim 1, wherein the action obtaining module is configured to obtain action data of the user in a preset time period before the collection time, and the action data includes a plurality of window opening time points, window closing time points and air quality indexes; the habit modification module is used for analyzing the environmental preference of the user according to the action data to obtain a modification coefficient representing the environmental preference, and further comprises:
acquiring air quality indexes corresponding to a plurality of windowing time points, calculating an average value of the air quality indexes corresponding to the windowing time points, and recording the average value as a reference air quality index;
obtaining a plurality of windowing time lengths according to the plurality of windowing time points and the plurality of window closing time points;
and fitting the plurality of air quality indexes and the plurality of windowing time lengths to obtain an air correction coefficient and an air correction constant representing air quality preference.
4. The intelligent household noise control system based on the 5G platform as claimed in claim 2 or 3, wherein the central control module is used for generating control instructions according to the environmental data and the correction coefficient representing the environmental preference, and the control instructions comprise a trigger instruction and a continuous instruction;
generating the trigger instruction includes: judging the noise decibel number and the standard noise decibel number, and if the noise decibel number is higher than the standard noise decibel number, generating a window-closing trigger instruction; or judging the sizes of the air quality index and the reference air quality index, and if the air quality index is higher than the reference air quality index, generating a window opening trigger instruction;
generating the persistence instruction includes: calculating the window closing duration, wherein the window closing duration is a noise correction coefficient x (noise decibel number-reference noise decibel number) + a noise correction constant, and a window closing duration instruction is generated according to the window closing duration; alternatively, the window duration is calculated as an air correction coefficient x (air quality index-reference air quality index) + air correction constant, and a window duration command is generated from the window duration.
5. The intelligent control system for household noise based on 5G platform is characterized in that the switch execution module further comprises a motor, and the motor is used for driving the intelligent window to open or close the window.
6. The intelligent control system for household noise based on 5G platform is characterized in that the switch execution module further comprises a timer, and the timer is used for recording the window closing duration/the window opening duration.
7. The intelligent household noise control method based on the 5G platform is characterized by comprising the following steps:
s1, collecting environmental data of the environment where the intelligent window is located in real time, and recording collection time corresponding to the environmental data;
s2, acquiring action data of the user in a preset time period before the acquisition time;
s3, analyzing the environmental preference of the user according to the action data to obtain a correction coefficient representing the environmental preference;
s4, generating a control command according to the environmental data and the correction coefficient;
and S5, performing window opening or window closing operation on the smart window according to the control command.
8. The intelligent home noise control method based on the 5G platform according to claim 7, wherein in S2, motion data of the user in a preset time period before the collection time is obtained, the motion data including a plurality of window closing time points, window opening time points and noise decibels; in S3, analyzing the environmental preference of the user according to the motion data to obtain a correction coefficient representing the environmental preference, including:
acquiring noise decibels corresponding to a plurality of window closing time points, and calculating an average value of the noise decibels corresponding to the window closing time points, and recording the average value as a reference noise decibel;
obtaining a plurality of window closing durations according to the plurality of window closing time points and the plurality of window opening time points;
and fitting the plurality of noise decibels and the plurality of window closing durations to obtain a noise correction coefficient and a noise correction constant representing noise preference.
9. The intelligent control method for household noise based on 5G platform as claimed in claim 7, wherein in S2, the action data of the user in a preset time period before the collection time is obtained, the action data includes a plurality of window opening time points, window closing time points and air quality indexes; in S3, analyzing the environmental preference of the user according to the motion data to obtain a correction coefficient representing the environmental preference, including:
acquiring air quality indexes corresponding to a plurality of windowing time points, calculating an average value of the air quality indexes corresponding to the windowing time points, and recording the average value as a reference air quality index;
obtaining a plurality of windowing time lengths according to the plurality of windowing time points and the plurality of window closing time points;
and fitting the plurality of air quality indexes and the plurality of windowing time lengths to obtain an air correction coefficient and an air correction constant representing air quality preference.
10. The intelligent household noise control method based on the 5G platform as claimed in claim 8 or 9, wherein in S4, a control command is generated according to the environmental data and the correction coefficient representing the environmental preference, and the control command comprises a trigger command and a continuous command;
generating the trigger instruction includes: judging the noise decibel number and the standard noise decibel number, and if the noise decibel number is higher than the standard noise decibel number, generating a window-closing trigger instruction; or judging the sizes of the air quality index and the reference air quality index, and if the air quality index is higher than the reference air quality index, generating a window opening trigger instruction;
generating the persistence instruction includes: calculating the window closing duration, wherein the window closing duration is a noise correction coefficient x (noise decibel number-reference noise decibel number) + a noise correction constant, and a window closing duration instruction is generated according to the window closing duration; alternatively, the window duration is calculated as an air correction coefficient x (air quality index-reference air quality index) + air correction constant, and a window duration command is generated from the window duration.
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