CN109219203B - Light equipment adjusting method - Google Patents
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- CN109219203B CN109219203B CN201710516605.XA CN201710516605A CN109219203B CN 109219203 B CN109219203 B CN 109219203B CN 201710516605 A CN201710516605 A CN 201710516605A CN 109219203 B CN109219203 B CN 109219203B
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- H—ELECTRICITY
- H05—ELECTRIC TECHNIQUES NOT OTHERWISE PROVIDED FOR
- H05B—ELECTRIC HEATING; ELECTRIC LIGHT SOURCES NOT OTHERWISE PROVIDED FOR; CIRCUIT ARRANGEMENTS FOR ELECTRIC LIGHT SOURCES, IN GENERAL
- H05B47/00—Circuit arrangements for operating light sources in general, i.e. where the type of light source is not relevant
- H05B47/10—Controlling the light source
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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
- Y02B—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO BUILDINGS, e.g. HOUSING, HOUSE APPLIANCES OR RELATED END-USER APPLICATIONS
- Y02B20/00—Energy efficient lighting technologies, e.g. halogen lamps or gas discharge lamps
- Y02B20/40—Control techniques providing energy savings, e.g. smart controller or presence detection
Abstract
The invention discloses a light equipment adjusting method, which is characterized by comprising the following steps: step 1: receiving the number of statistical days set by a user, and counting the data of the control state change of the lamplight in the set number of statistical days; step 2: predicting the light control state to be generated at the corresponding time in the future according to the statistical data, wherein the predicted result is obtained by integrating the statistical data of the corresponding time and the statistical data of the time adjacent to the corresponding time; and step 3: controlling the operating state of the light according to the predicted light control state; by the technical scheme provided by the invention, automation and intellectualization of light control can be realized, and personalized requirements of users can be met.
Description
[ technical field ] A method for producing a semiconductor device
The invention belongs to the field of intelligent home furnishing, and particularly relates to a method for controlling intelligent home lighting.
[ background of the invention ]
Light control is the indispensable factor of house environment, along with the rise of intelligent house, light intelligent control produces at the same time, and among the prior art, light intelligent control mainly includes following two kinds of forms: 1. through wireless communication methods such as WIFI, ZIGBEE, carry out remote configuration and control to light, 2, through setting up the external conditions that control light relied on in light controller in advance, for example: ambient light, background music, or time, etc., so that the light shows different brightness, effect or color according to the change of the external conditions. Both of the above forms have a same feature, and it is necessary for a professional who designs light control to specify a control rule of light in advance, and then to set a method of light control according to the rule. However, in practical use, it is not easy for ordinary users to obtain the rule, and in addition, the light control rule set by the professional is usually set based on the habits of most users, and is not suitable for users with personalized requirements.
[ summary of the invention ]
In order to solve the technical problems that in the intelligent home, the light control does not need to be carried out according to the habit of using light of a user, personalized setting and the like, the invention provides a home intelligent light control method and a home intelligent light control system for intelligently predicting the control state of the light by counting the habit of using the light of the user.
The invention provides a light equipment adjusting method, which is characterized by comprising the following steps:
a lighting device adjustment method, comprising the steps of:
step 1: receiving the number of statistical days set by a user, and counting the data of the control state change of the lamplight in the set number of statistical days;
step 2: predicting the light control state to be generated at the corresponding time in the future according to the statistical data, wherein the predicted result is obtained by integrating the statistical data of the corresponding time and the statistical data of the time adjacent to the corresponding time;
and step 3: controlling the operating state of the light according to the predicted light control state;
the step 1 further comprises the following steps:
(1.1) numbering the counted days in sequence from 1, setting a time interval of one day, dividing the time of each day into a plurality of time slices according to the time interval, numbering in sequence from 1, and recording the number as (d, n), wherein d is the number of the days, n is the number of the time slices, the maximum number of the days is DMAX, the maximum number of the time slices is NMAX, d is more than or equal to 1 and less than or equal to DMAX, and n is more than or equal to 1 and less than or equal to NMAX;
(1.2) recording data of the change of the light control state of each time slice in one day, wherein in each time slice, the light is changed from on to off, the corresponding change state value is '10', the light is changed from off to on, the corresponding change state value is '01', if the light is kept on all the time, the corresponding change state value is '11', and if the light is kept off all the time, the corresponding change state value is '00'; each change state is recorded as follows: l1(d, n) ═ B, where L1 is a light control state change identifier, d is the number of days, n is the number of time slices, B is a change state value, and the data in which the light control state changes at least includes one piece of data;
(1.3) repeating the step (1.2) until the set statistical days are met;
(1.4) subjecting the recorded value recorded in step (1.3) to the following processing:
(1.4.1) calculating the proportion value of each change state value under the same time slice number, wherein the calculation formula is as follows:
l2(n, B) — (number of pieces of data with time slice number n and change state value B)/(total number of pieces of data with time slice number n);
then sorting all proportional values with the same time slice number according to the size, if a unique maximum value exists, taking the maximum value as a main variable state value of the time slice number, and if a plurality of maximum values exist, randomly selecting one maximum value from the maximum values as the main variable state value of the time slice number, and marking the maximum value as KS (n), wherein n is the number of the same time slice;
(1.4.2) calculating the conversion rate of the change state value of the next time slice for the change state value of each time slice number, the calculation formula is as follows
L3(m, B1, B2) ═ where 1 ≦ m ≦ NMAX-1, B1 is the change state value of time slice number m, and B2 is the change state value of time slice m +1 next to time slice number m (total number of data of time slice number m +1 and change state value B2)/(total number of data of time slice number m and change state value B1);
then sorting the conversion rates with the same time slice number and the corresponding change state values with the same size, if a unique maximum value exists, taking the change state value of the next time slice corresponding to the maximum value as the main conversion state value of the same time slice number, if a plurality of maximum values exist, randomly selecting the change state value of the next time slice corresponding to one maximum value from the maximum values as the main conversion state value of the same time slice number, and recording the change state value as KCS (m), wherein m is the number of the same time slice;
the step 3 further comprises the following steps:
controlling light according to the predicted main change state value of the time slice, specifically comprising the following steps:
if the current time slice is 00 or 10, turning off the light at the beginning of the time slice, and keeping the light-off state in the time slice;
if 11 or 01, the light is turned on at the beginning of the time slice, and the light on state is maintained during the time slice.
[ description of the drawings ]
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this application, and are not to be considered limiting of the invention, in which:
FIG. 1 is a flow chart of a household intelligent light control method provided by the invention;
fig. 2 is a block diagram of a home intelligent lighting control system according to the present invention.
[ detailed description ] embodiments
The present invention will now be described in detail with reference to the drawings and specific embodiments, wherein the exemplary embodiments and descriptions are provided only for the purpose of illustrating the present invention and are not to be construed as unduly limiting the invention.
Referring to fig. 1, which is a flowchart of the household intelligent light control method provided by the present invention, in step S01, a statistical number of days set by a user is received, and in the statistical number of days, behaviors of the user in controlling light are counted, specifically, a sequence of light change states is counted, for example: when the set days input by the user is 3 days, the household intelligent light control system enters a statistical state, the time when the user turns on light and the time when the user turns off light are counted every day within 3 days of statistics, the time when the light brightness is adjusted and the brightness value of the light brightness are adjusted, the statistical values are stored in a memory of the control system, then the operation times of turning on and off the light and adjusting the light brightness are respectively counted based on the same time, and for understanding, a statistical result (the statistical days: 3 days) in practical application can be referred to in the following table.
Counting time | Number of times of turning on light | Number of times of light off | Number of brightness adjustments | Number of times of dimming of brightness |
6:00 | 3 | 0 | 0 | 0 |
7:30 | 0 | 3 | 0 | 0 |
17:00 | 2 | 0 | 0 | 0 |
17:40 | 0 | 1 | 0 | 0 |
19:30 | 0 | 0 | 2 | 1 |
22:30 | 0 | 3 | 0 | 0 |
In step S02, the light control state to be generated at the corresponding future time is predicted based on the data counted in step S01, after the number of counted days is completed, the light control state is predicted based on the statistical table counted in the number of counted days, and in prediction, the main operation at the current time is determined, and then prediction is performed based on the main operation at the current time and the operation at the next time adjacent to the current time, so as to ensure the continuity between the predicted operation and the operation at the previous time, for example, a statistical threshold value of 2 is set, and according to the result counted by the previous table, after three days are counted, for example, on the fourth day, since 6: the number of times of opening at the time of 00 is larger than a set statistical threshold value, so that the main operation at the time of 6:00 is the main operation of opening the light, and the control state of the light at each moment is obtained through statistics in the same way.
In the operation for predicting the future time, not only the main operation at the current time corresponding to the statistical data but also the operation at a time adjacent to the corresponding time are considered, and the operation at the adjacent time may be considered as the operation at a previous time adjacent to the current time or the operation at a subsequent time adjacent to the current time, which may be determined according to the statistical rule of the statistical data of the light control state, for example: if the operation of the next time adjacent to the current time is considered, one comprehensive consideration means can be: if the two operations are the same, the same operation is taken, and if the two operations are different, the former operation is taken. The predicted results are shown in the following table:
in step S03, the control state of the light at the corresponding time is controlled according to the light control state predicted in step S02, for example, according to the predicted light control state table, at 6:00, the light control device sends an on command to the light to turn on the light, and at 7:30, the light control device sends an off command to the light to turn off the light. The prediction of the light operation state is completely based on the historical behavior of the user for operating the light, so the control method can be more suitable for the individual requirements of the user for light control, and the user can customize and change the details of automatic and intelligent control of the light by re-counting the behavior of the user for controlling the light according to the individual requirements of the user at any time.
The change of the light control state is recorded in real time, more hardware resources are needed, and meanwhile, the recorded capacity is wasted due to the fact that the user does not operate the control state caused by misoperation, interference and the like. The step S01 further includes the following steps:
(1.1) numbering the counted days in sequence from 1, setting a time interval of one day, dividing the time of each day into a plurality of time slices according to the time interval, numbering in sequence from 1, and recording the number as (d, n), wherein d is the number of the days, n is the number of the time slices, the maximum number of the days is DMAX, the maximum number of the time slices is NMAX, d is more than or equal to 1 and less than or equal to DMAX, and n is more than or equal to 1 and less than or equal to NMAX;
(1.2) recording data of the change of the light control state of each time slice in one day, wherein in each time slice, the light is changed from on to off, the corresponding change state value is '10', the light is changed from off to on, the corresponding change state value is '01', if the light is kept on all the time, the corresponding change state value is '11', and if the light is kept off all the time, the corresponding change state value is '00'; each change state is recorded as follows: l1(d, n) ═ B, where L1 is a light control state change identifier, d is the number of days, n is the number of time slices, B is a change state value, and the data in which the light control state changes at least includes one piece of data;
(1.3) repeating the step (1.2) until the set statistical days are met;
(1.4) subjecting the recorded value recorded in step (1.3) to the following processing:
(1.4.1) calculating the proportion value of each change state value under the same time slice number, wherein the calculation formula is as follows:
l2(n, B) — (number of pieces of data with time slice number n and change state value B)/(total number of pieces of data with time slice number n);
then sorting all proportional values with the same time slice number according to the size, if a unique maximum value exists, taking the maximum value as a main variable state value of the time slice number, and if a plurality of maximum values exist, randomly selecting one maximum value from the maximum values as the main variable state value of the time slice number, and marking the maximum value as KS (n), wherein n is the time slice number;
(1.4.2) calculating the conversion rate of the change state value of the next time slice for the change state value of each time slice number, wherein the calculation formula is as follows
L3(m, B1, B2) ═ where 1 ≦ m ≦ NMAX-1, B1 is the change state value of time slice number m, and B2 is the change state value of time slice m +1 next to time slice number m (total number of data of time slice number m +1 and change state value B2)/(total number of data of time slice number m and change state value B1);
and then sorting the conversion rates with the same time slice number m and the corresponding change state values with the same size, if a unique maximum value exists, taking the change state value of the next time slice corresponding to the maximum value as the main conversion state value of the same time slice number, and if a plurality of maximum values exist, randomly selecting the change state value of the next time slice corresponding to one maximum value from the maximum values as the main conversion state value of the same time slice number, and recording the change state value as KCS (m), wherein m is the time slice number.
The step S02 further includes the steps of:
(2.1) determining one or more time slice numbers contained in the future corresponding time according to the time slice numbers obtained by dividing in the step (1.1), and sequencing the one or more time slice numbers in ascending order;
(2.2) respectively searching main transformation state values corresponding to the time slice numbers as the main transformation state values of the first time slice and the last time slice in the one or more time slices;
(2.3) for the other time slices except the first time slice and the last time slice in the one or more time slices, the predicted main transformation state value of the time slice is the result of the logical AND operation of the main transformation state value corresponding to the time slice number after the operation of the main transformation state value corresponding to the time slice number and the main transformation state value thereof is carried out, namely: KSP (p2) ((KS (p 2); KCS (p 2))) andU KS (p2), wherein p2 is the number of the other slice, KSP indicates the predicted main transition state value, KS indicates the main transition state value, KCS indicates the main transition state value, N indicates the logical OR operation, and N indicates the logical AND operation.
Step S03 further includes controlling the light according to the predicted main change state value of the time slice, specifically: if the current time slice is 00 or 10, turning off the light at the beginning of the time slice, and keeping the light-off state in the time slice; if 11 or 01, the light is turned on at the beginning of the time slice, and the light on state is maintained during the time slice.
According to the improved technical scheme, the household intelligent light control method is more refined, the link of setting a threshold value by a user is eliminated, all behaviors of the user for controlling light can be basically counted by setting the time interval between 5 minutes and 15 minutes, and the counting precision of the light control state is improved. In each time slice, the change state value of the light control is obtained in a sampling mode, and the defect of high resource consumption caused by real-time monitoring can be effectively reduced.
Based on the control method, the invention also provides a household intelligent light control system, which is shown in fig. 2 and is a structural block diagram of the household intelligent light control system provided by the invention, and the household intelligent light control system comprises a user input device, a light control device, a data statistics device, a light prediction device and a memory, and all the devices can be realized by the FPGA technology. Wherein the content of the first and second substances,
the user input device is connected with the light control device and is used for inputting the control operation of the user on the light;
the data counting device is connected with the control device, when the operation content input by the user through the light control device is the number of counting days, the control system is enabled to enter a counting state, the data of the light change state is counted based on the number of counting days, and the data are stored in the memory;
the light prediction device is connected with the memory and used for enabling the control system to enter a prediction state from a statistics state after statistics is completed, predicting a light control state of a future corresponding time according to the statistical data stored in the memory, and obtaining a prediction result by integrating the statistical data of the corresponding time and the statistical data of the time adjacent to the corresponding time;
the light control device is configured to receive a light control operation of a user and receive a predicted light control operation sent by the light prediction device to control an operation state of light, where a priority of the light control operation sent by the user is higher than a priority of the light control operation sent by the light prediction device, for example: when a user sends an operation command through the light control device, for example, the light is turned on, and at the same time, the light control operation sent by the light prediction device is turned off, the control operation of the user is prioritized, that is, the light control operation sends the operation of turning on the light to the light.
The invention provides a light equipment adjusting method, which is characterized by comprising the following steps:
step 1: receiving the number of statistical days set by a user, and counting the data of the control state change of the lamplight in the set number of statistical days;
step 2: predicting the light control state to be generated at the corresponding time in the future according to the statistical data, wherein the predicted result is obtained by integrating the statistical data of the corresponding time and the statistical data of the time adjacent to the corresponding time;
and step 3: controlling the operating state of the light according to the predicted light control state;
the step 1 further comprises the following steps:
(1.1) numbering the counted days in sequence from 1, setting a time interval of one day, dividing the time of each day into a plurality of time slices according to the time interval, numbering in sequence from 1, and recording the number as (d, n), wherein d is the number of the days, n is the number of the time slices, the maximum number of the days is DMAX, the maximum number of the time slices is NMAX, d is more than or equal to 1 and less than or equal to DMAX, and n is more than or equal to 1 and less than or equal to NMAX;
(1.2) recording data of the change of the light control state of each time slice in one day, wherein in each time slice, the light is changed from on to off, the corresponding change state value is '10', the light is changed from off to on, the corresponding change state value is '01', if the light is kept on all the time, the corresponding change state value is '11', and if the light is kept off all the time, the corresponding change state value is '00'; each change state is recorded as follows: l1(d, n) ═ B, where L1 is a light control state change identifier, d is the number of days, n is the number of time slices, B is a change state value, and the data in which the light control state changes at least includes one piece of data;
(1.3) repeating the step (1.2) until the set statistical days are met;
(1.4) subjecting the recorded value recorded in step (1.3) to the following processing:
(1.4.1) calculating the proportion value of each change state value under the same time slice number, wherein the calculation formula is as follows:
l2(n, B) — (number of pieces of data with time slice number n and change state value B)/(total number of pieces of data with time slice number n);
then sorting all proportional values with the same time slice number according to the size, if a unique maximum value exists, taking the maximum value as a main variable state value of the time slice number, and if a plurality of maximum values exist, randomly selecting one maximum value from the maximum values as the main variable state value of the time slice number, and marking the maximum value as KS (n), wherein n is the number of the same time slice;
(1.4.2) calculating the conversion rate of the change state value of the next time slice for the change state value of each time slice number, the calculation formula is as follows
L3(m, B1, B2) ═ where 1 ≦ m ≦ NMAX-1, B1 is the change state value of time slice number m, and B2 is the change state value of time slice m +1 next to time slice number m (total number of data of time slice number m +1 and change state value B2)/(total number of data of time slice number m and change state value B1);
then sorting the conversion rates with the same time slice number and the corresponding change state values with the same size, if a unique maximum value exists, taking the change state value of the next time slice corresponding to the maximum value as the main conversion state value of the same time slice number, if a plurality of maximum values exist, randomly selecting the change state value of the next time slice corresponding to one maximum value from the maximum values as the main conversion state value of the same time slice number, and recording the change state value as KCS (m), wherein m is the number of the same time slice;
the step 3 further comprises the following steps:
controlling light according to the predicted main change state value of the time slice, specifically comprising the following steps:
if the current time slice is 00 or 10, turning off the light at the beginning of the time slice, and keeping the light-off state in the time slice;
if 11 or 01, the light is turned on at the beginning of the time slice, and the light on state is maintained during the time slice.
It will be understood by those of ordinary skill in the art that all or part of the steps of the above embodiments may be implemented using a computer program flow, which may be stored in a computer readable storage medium and executed on a corresponding hardware platform (e.g., system, apparatus, device, etc.), and when executed, includes one or a combination of the steps of the method embodiments. Alternatively, all or part of the steps of the above embodiments may be implemented by using an integrated circuit, and the steps may be respectively manufactured as an integrated circuit module, or a plurality of the blocks or steps may be manufactured as a single integrated circuit module. The devices/functional modules/functional units in the above embodiments may be implemented by general-purpose computing devices, and they may be centralized on a single computing device or distributed on a network formed by a plurality of computing devices. The means/function modules/function units in the above embodiments are implemented in the form of software function modules and may be stored in a computer-readable storage medium when they are sold or used as separate products. The computer readable storage medium mentioned above may be a read-only memory, a magnetic disk or an optical disk, etc.
Claims (1)
1. A lighting device adjustment method, comprising the steps of:
step 1: receiving the number of statistical days set by a user, and counting the data of the control state change of the lamplight in the set number of statistical days;
step 2: predicting the light control state to be generated at the corresponding time in the future according to the statistical data, wherein the predicted result is obtained by integrating the statistical data of the corresponding time and the statistical data of the time adjacent to the corresponding time;
and step 3: controlling the operating state of the light according to the predicted light control state;
the step 1 further comprises the following steps:
(1.1) numbering the counted days in sequence from 1, setting a time interval of one day, dividing the time of each day into a plurality of time slices according to the time interval, numbering in sequence from 1, and recording the number as (d, n), wherein d is the number of the days, n is the number of the time slices, the maximum number of the days is DMAX, the maximum number of the time slices is NMAX, d is more than or equal to 1 and less than or equal to DMAX, and n is more than or equal to 1 and less than or equal to NMAX;
(1.2) recording data of the change of the light control state of each time slice in one day, wherein in each time slice, the light is changed from on to off, the corresponding change state value is '10', the light is changed from off to on, the corresponding change state value is '01', if the light is kept on all the time, the corresponding change state value is '11', and if the light is kept off all the time, the corresponding change state value is '00'; each change state is recorded as follows: l1(d, n) ═ B, where L1 is a light control state change identifier, d is the number of days, n is the number of time slices, B is a change state value, and the data in which the light control state changes at least includes one piece of data;
(1.3) repeating the step (1.2) until the set statistical days are met;
(1.4) subjecting the recorded value recorded in step (1.3) to the following processing:
(1.4.1) calculating the proportion value of each change state value under the same time slice number, wherein the calculation formula is as follows:
l2(n, B) — (number of pieces of data with time slice number n and change state value B)/(total number of pieces of data with time slice number n);
then, all proportional values with the same time slice number are sorted according to the size, if a unique maximum value exists, the main variable state value of the time slice number corresponding to the maximum value is taken as the main variable state value of the current time slice number, if a plurality of maximum values exist, the main variable state value of the time slice number corresponding to the maximum value is randomly selected from the main variable state values as the main variable state value of the current time slice number, and is marked as KS (n), wherein n is the number of the time slice;
(1.4.2) calculating the conversion rate of the change state value of the next time slice for the change state value of each time slice number, the calculation formula is as follows
L3(m, B1, B2) ═ total number of pieces of data whose slot number is m +1 and whose change state value is B2)/(total number of pieces of data whose same slot number is m and whose change state value is B1), where m is 1 or more and NMAX-1, B1 is the change state value of the same slot number m, and B2 is the change state value of the next slot m +1 of the same slot number m;
then sorting the conversion rates with the same time slice number and the corresponding change state values with the same size, if a unique maximum value exists, taking the change state value of the next time slice corresponding to the maximum value as the main conversion state value of the same time slice number, if a plurality of maximum values exist, randomly selecting the change state value of the next time slice corresponding to one maximum value from the maximum values as the main conversion state value of the same time slice number, and recording the change state value as KCS (m), wherein m is the number of the same time slice;
the step 3 further comprises the following steps:
controlling light according to the predicted main change state value of the time slice, specifically comprising the following steps:
if the current time slice is 00 or 10, turning off the light at the beginning of the time slice, and keeping the light-off state in the time slice;
if 11 or 01, the light is turned on at the beginning of the time slice, and the light on state is maintained during the time slice.
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