Intelligent lighting lamp based on Internet of Things and intelligent control method thereof

Abstract

The invention discloses an intelligent lighting lamp based on the Internet of Things and an intelligent control method thereof, and relates to the technical field of lighting, the intelligent lighting lamp comprises a data acquisition module, a data processing module, a data analysis module, an execution module and a control center; the data acquisition module is used for acquiring indoor related data, the data processing module is used for processing and calculating to obtain a comprehensive indoor illumination coefficient, and the data analysis module is used for carrying out grade judgment on indoor illumination intensity in a threshold setting mode. And then the execution module determines how to adjust the illumination intensity to adapt to the indoor environment according to the grade judgment result, and the control center can record and determine the peak day and the valley day of the illumination intensity per week, so that a user can perform evaluation and determination conveniently, and the function of automatically adjusting the illumination intensity according to the indoor condition is realized.

Description

Technical Field

[0001] The present invention relates to the technical field of lighting, and specifically to an intelligent lighting fixture based on the Internet of Things and its intelligent control method. Background Art

[0002] Lighting fixtures are devices used to provide artificial light for illuminating indoor or outdoor environments. They can adopt different technologies and light sources, such as incandescent lamps, fluorescent lamps, LED lamps, etc., to generate appropriate light intensity and color. However, traditional lighting control schemes usually use physical switches or remote controls to manually control the on / off state of lighting fixtures. This method requires manual intervention and is not intelligent and automated enough. Specifically, this control scheme requires users to manually turn on or off the fixtures when entering or leaving the room or according to needs, which is easy to be forgotten or waste energy. Summary of the Invention

[0003] To solve the deficiencies mentioned in the above background art, the purpose of the present invention is to provide an intelligent lighting fixture based on the Internet of Things and its intelligent control method, which can automatically adjust the lighting intensity according to the indoor situation.

[0004] In a first aspect, the purpose of the present invention can be achieved by the following technical solutions: An intelligent lighting fixture based on the Internet of Things, comprising:

[0005] A data acquisition module: used to collect indoor relevant data and send it to the data processing module, where the indoor relevant data includes initial ambient brightness, indoor light intensity, and walking decibel data;

[0006] A data processing module: used to perform data marking on the indoor relevant data, perform comprehensive indoor lighting evaluation calculation using the marked indoor relevant data, obtain a comprehensive indoor lighting coefficient, and send the comprehensive indoor lighting coefficient to the data analysis module;

[0007] A data analysis module: used to set an indoor lighting coefficient threshold, perform a ratio calculation on the comprehensive indoor lighting coefficient and the indoor lighting coefficient threshold, determine the indoor lighting intensity according to the ratio size, and send different levels of intensity signals to the execution module;

[0008] An execution module: used to change the lighting intensity according to different levels of intensity signals;

[0009] A control center: used to determine the peak days and valley days of each week based on the weekly indoor lighting intensity data and feedback them to the execution module.

[0010] Combined with the first aspect, in some implementation manners of the first aspect, the system further includes: The marking process of the data processing module:

[0011] Data mark the relevant indoor data. Among them, mark the initial environmental brightness as Li, mark the indoor light intensity as Gi, and mark the walking decibel data as Fi, where i is the label of the data acquisition times of the data acquisition module, and i = 1, 2, 3,..., n, and n is the total number of data acquisition times of the data acquisition module.

[0012] Combined with the first aspect, in some implementation manners of the first aspect, the system further includes: the calculation process of the data processing module:

[0013] Using the formula

[0014] In the formula, Zpi is the comprehensive indoor lighting coefficient, L0 is the preset standard environmental brightness coefficient, G0 is the preset standard light intensity coefficient, a is the environmental brightness influence coefficient, b is the light intensity influence coefficient, and c is the walking acquisition influence coefficient.

[0015] Combined with the first aspect, in some implementation manners of the first aspect, the system further includes: the calculation process of the data analysis module:

[0016] Set the indoor lighting coefficient threshold Zp0, and the ratio calculation formula by the comprehensive indoor lighting coefficient Zpi and the indoor lighting coefficient threshold Zp0 is as follows:

[0017] Using the formula Calculate the ratio result Bli, where both k1 and k2 are preset proportionality coefficients.

[0018] Combined with the first aspect, in some implementation manners of the first aspect, the system further includes: the analysis process of the data analysis module:

[0019] Set the ratio threshold Bl0, and compare the ratio result Bli with the ratio threshold Bl0: Send different levels of intensity signals to the execution module according to the comparison result:

[0020] If Bli ≤ Bl0, send a low-level intensity signal to the execution module;

[0021] If Bl0 < Bli ≤ 2Bl0, send a medium-level intensity signal to the execution module;

[0022] If Bli > 2Bl0, send a high-level intensity signal to the execution module.

[0023] In combination with the first aspect, in some implementations of the first aspect, the system further includes: the control center collects daily indoor lighting intensity data in real time, integrates the collected daily indoor lighting intensity data and performs mean processing to obtain the mean data of indoor lighting intensity, then sorts the data, marks the day with the maximum mean indoor lighting intensity as the peak day, and marks the day with the minimum mean indoor lighting intensity as the underestimated day.

[0024] In a second aspect, to achieve the above object, the present invention discloses an intelligent control method for an intelligent lighting fixture based on the Internet of Things. The method includes the following steps:

[0025] Obtain indoor relevant data, perform data marking on the indoor relevant data, and use the marked indoor relevant data to perform comprehensive indoor lighting evaluation calculation to obtain a comprehensive indoor lighting coefficient. Among them, the indoor relevant data includes initial ambient brightness, indoor light intensity, and walking decibel data;

[0026] Set an indoor lighting coefficient threshold, perform ratio calculation based on the comprehensive indoor lighting coefficient and the indoor lighting coefficient threshold, determine the level of indoor lighting intensity according to the ratio size, and change the lighting intensity based on the level of indoor lighting intensity. Among them, the indoor lighting intensity includes low level, medium level, and high level.

[0027] Advantages of the present invention:

[0028] The present invention collects indoor relevant data through a data collection module, then processes and calculates to obtain a comprehensive indoor lighting coefficient through a data processing module, and then determines the level of indoor lighting intensity by setting a threshold through a data analysis module. Then, the execution module determines how to adjust the lighting intensity to adapt to the indoor environment according to the level determination result, and the control center can record and determine the peak day and trough day of the weekly lighting intensity, which is convenient for users to evaluate and determine, realizing the function of automatically adjusting the lighting intensity according to the indoor situation. Description of the Drawings

[0029] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, for those of ordinary skill in the art, other drawings can also be obtained based on these drawings without creative efforts;

[0030] Figure 1 is a schematic structural diagram of the system of the present invention;

[0031] Figure 2 is a schematic flowchart of the method of the present invention. Detailed Embodiments

[0032] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0033] Embodiment 1:

[0034] As Figure 1 shown, the intelligent lighting fixture based on the Internet of Things includes:

[0035] a data acquisition module, a data processing module, a data analysis module, an execution module, and a control center;

[0036] The data acquisition module is used to collect indoor related data and send the collected indoor related data to the data processing module for processing. After receiving the indoor related data sent by the data acquisition module, the data processing module performs data processing. Among them, the indoor related data includes the initial ambient brightness, indoor light intensity, and walking decibel data;

[0037] Specifically, the processing process of the data processing module includes the following steps:

[0038] Perform data marking on the indoor related data. Among them, mark the initial ambient brightness as Li, mark the indoor light intensity as Gi, and mark the walking decibel data as Fi, where i is the serial number of the data acquisition times of the data acquisition module, and i = 1, 2, 3,..., n, and n is the total number of data acquisition times of the data acquisition module;

[0039] Use the marked indoor related data to perform comprehensive indoor lighting evaluation calculation to obtain the comprehensive indoor lighting coefficient. The calculation formula is as follows:

[0040]

[0041] In the formula, Zpi is the comprehensive indoor lighting coefficient, L0 is the preset standard ambient brightness coefficient, G0 is the preset standard light intensity coefficient, a is the ambient brightness influence coefficient, b is the light intensity influence coefficient, and c is the walking acquisition influence coefficient;

[0042] Furthermore, in the specific implementation process, the preset standard ambient brightness coefficient and the preset standard light intensity coefficient are obtained by collecting the initial ambient brightness and indoor light intensity daily, and then through multiple simulation calculations and taking the data average value;

[0043] Among them, within this embodiment, the ambient brightness influence coefficient, the light intensity influence coefficient, and the walking acquisition influence coefficient are obtained by the present application through comprehensive evaluation and calculation based on external factor influences when initially obtaining the ambient brightness, indoor light intensity, and walking decibel data on a daily basis, including human factors, machine detection, environmental factors, etc.; human factors are those caused by human operations or improper scanning;

[0044] Send the calculated comprehensive indoor lighting coefficient Zpi to the data analysis module for analysis;

[0045] After receiving the comprehensive indoor lighting coefficient Zpi sent by the data processing module, the data analysis module performs data analysis. Specifically, the analysis process of the data analysis module includes the following steps:

[0046] Set the indoor lighting coefficient threshold Zp0, calculate the ratio of the received comprehensive indoor lighting coefficient Zpi to the indoor lighting coefficient threshold Zp0, and determine the indoor lighting intensity according to the ratio size;

[0047] Among them, the ratio calculation formula of the comprehensive indoor lighting coefficient Zpi and the indoor lighting coefficient threshold Zp0 is as follows:

[0048] Using the formula Calculate the ratio result Bli, where k1 and k2 are both preset proportional coefficients;

[0049] Set the ratio threshold Bl0, compare the ratio result Bli with the ratio threshold Bl0: Send different-level intensity signals to the execution module according to the comparison result;

[0050] If Bli ≤ Bl0, it is determined that the indoor lighting intensity is low at this time, and the data analysis module sends a low-level intensity signal to the execution module;

[0051] If Bl0 < Bli ≤ 2Bl0, it is determined that the indoor lighting intensity is medium at this time, and the data analysis module sends a medium-level intensity signal to the execution module;

[0052] If Bli > 2Bl0, it is determined that the indoor lighting intensity is high at this time, and the data analysis module sends a high-level intensity signal to the execution module;

[0053] The execution module is used to perform lighting execution after receiving different-level intensity signals sent by the data analysis module. Specifically:

[0054] After receiving the low-level intensity signal sent by the data analysis module, the execution module controls the lighting device to increase the lighting intensity to solve the problem of dimness caused by low indoor intensity;

[0055] After receiving the medium-intensity signal sent by the data analysis module, the execution module does not need to control the lighting device to change the lighting intensity;

[0056] After receiving the low-intensity signal sent by the data analysis module, the execution module controls the lighting device to reduce the lighting intensity to solve the problem of over-brightness caused by high indoor intensity;

[0057] The control center is used to determine the peak days and trough days of each week based on the weekly indoor lighting intensity data and feedback them to the execution module. Specifically: it collects the daily indoor lighting intensity data in real time, integrates and averages the collected daily indoor lighting intensity data to obtain the average indoor lighting intensity data, stores the average indoor lighting intensity data to determine the daily change of the indoor lighting intensity, marks the day with the maximum average indoor lighting intensity as the peak day, and marks the day with the minimum average indoor lighting intensity as the underestimated day.

[0058] Embodiment 2: As Figure 2 shown, the intelligent control method of the intelligent lighting fixture based on the Internet of Things includes the following steps:

[0059] Obtain indoor relevant data, perform data marking on the indoor relevant data, and use the marked indoor relevant data to perform comprehensive indoor lighting evaluation calculation to obtain the comprehensive indoor lighting coefficient. Among them, the indoor relevant data includes the initial environmental brightness, indoor light intensity, and walking decibel data;

[0060] Set the indoor lighting coefficient threshold, perform ratio calculation based on the comprehensive indoor lighting coefficient and the indoor lighting coefficient threshold, determine the level of the indoor lighting intensity according to the ratio size, and change the lighting intensity based on the level of the indoor lighting intensity. Among them, the indoor lighting intensity includes low, medium, and high levels.

[0061] Based on the same inventive concept, the present invention further provides a computer device, which includes: one or more processors, and a memory for storing one or more computer programs; the program includes program instructions, and the processor is configured to execute the program instructions stored in the memory. The processor may be a Central Processing Unit (CPU), or may also be other general-purpose processors, Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field-Programmable Gate Arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. It is the computing core and control core of the terminal, and is used to implement one or more instructions. Specifically, it is used to load and execute one or more instructions in the computer storage medium to implement the above method.

[0062] It should be further noted that, based on the same inventive concept, the present invention further provides a computer storage medium, on which a computer program is stored, and the computer program, when run by a processor, executes the above method. The storage medium may adopt any combination of one or more computer-readable media. The computer-readable medium may be a computer-readable signal medium or a computer-readable storage medium. The computer-readable storage medium may, for example, but not be limited to, an electrical, magnetic, optical, electrical, magnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the above. More specific examples (non-exhaustive list) of the computer-readable storage medium include: an electrical connection having one or more wires, a portable computer disk, a hard disk, a Random Access Memory (RAM), a Read Only Memory (ROM), an Erasable Programmable Read Only Memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present invention, the computer-readable storage medium may be any tangible medium that contains or stores a program, and the program may be used by or in combination with an instruction execution system, apparatus, or device.

[0063] The above formulas are all calculated by removing the dimension and taking their numerical values. The formula is obtained by collecting a large amount of data for software simulation to obtain a formula that is closest to the actual situation. The preset parameters and preset thresholds in the formula are set by those skilled in the art according to the actual situation or obtained by simulating a large amount of data.

[0064] In the description of this specification, the descriptions referring to the terms "one embodiment", "example", "specific example", etc. mean that the specific features, structures, materials or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present disclosure. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0065] The above has shown and described the basic principles, main features and advantages of the present disclosure. Those skilled in the art of this industry should understand that the present disclosure is not limited by the above embodiments. The above embodiments and the descriptions in the specification only illustrate the principles of the present disclosure. Without departing from the spirit and scope of the present disclosure, the present disclosure will have various changes and improvements, and these changes and improvements all fall within the scope of the present disclosure claimed.

Claims

1. The intelligent lighting fixture based on the Internet of Things is characterized in that Including: Data acquisition module: used to collect indoor relevant data and send it to the data processing module. Among them, the indoor relevant data includes initial ambient brightness, indoor light intensity, and walking decibel data; Data processing module: used to mark the indoor relevant data, and use the marked indoor relevant data to perform comprehensive indoor lighting evaluation calculation to obtain the comprehensive indoor lighting coefficient, and send the comprehensive indoor lighting coefficient to the data analysis module; Data analysis module: used to set the indoor lighting coefficient threshold, calculate the ratio of the comprehensive indoor lighting coefficient to the indoor lighting coefficient threshold, determine the indoor lighting intensity according to the ratio size, and send different levels of intensity signals to the execution module; Execution module: used to change the lighting intensity according to different levels of intensity signals; Control center: used to determine the peak day and trough day of each week based on the weekly indoor lighting intensity data and feedback to the execution module.

2. The intelligent lighting fixture based on the Internet of Things according to claim 1, wherein The marking process of the data processing module: Mark the indoor relevant data. Among them, mark the initial ambient brightness as Li, mark the indoor light intensity as Gi, and mark the walking decibel data as Fi. Among them, i is the label of the data acquisition times of the data acquisition module, and i = 1, 2, 3,..., n, where n is the total number of data acquisition times of the data acquisition module.

3. The intelligent lighting fixture based on the Internet of Things according to claim 2, characterized in that The calculation process of the data processing module: Using the formula In the formula, Zpi is the comprehensive indoor lighting coefficient, L0 is the preset standard ambient brightness coefficient, G0 is the preset standard light intensity coefficient, a is the ambient brightness influence coefficient, b is the light intensity influence coefficient, and c is the walking acquisition influence coefficient.

4. The intelligent lighting fixture based on the Internet of Things according to claim 1, characterized in that, The calculation process of the data analysis module: Set the indoor lighting coefficient threshold Zp0, and the ratio calculation formula of the comprehensive indoor lighting coefficient Zpi and the indoor lighting coefficient threshold Zp0 is as follows: Using the formula the ratio result Bli is calculated, where both k1 and k2 are preset proportionality coefficients.

5. The intelligent lighting fixture based on the Internet of Things according to claim 4, wherein The analysis process of the data analysis module: Set the ratio threshold Bl0, and compare the ratio result Bli with the ratio threshold Bl0: send different levels of intensity signals to the execution module according to the comparison result: If Bli ≤ Bl0, then send a low-level intensity signal to the execution module; If Bl0 < Bli ≤ 2Bl0, then send a medium-level intensity signal to the execution module; If Bli > 2Bl0, then send a high-level intensity signal to the execution module.

6. The intelligent lighting fixture based on the Internet of Things according to claim 1, characterized in that, The control center collects the daily indoor lighting intensity data in real time, integrates and averages the collected daily indoor lighting intensity data to obtain the average indoor lighting intensity data, and then sorts it. Mark the day with the maximum average indoor lighting intensity as the peak day, and mark the day with the minimum average indoor lighting intensity as the underestimated day.

7. The intelligent control method of an intelligent lighting fixture based on the Internet of Things, characterized in that The method includes the following steps: Obtain indoor relevant data, mark the indoor relevant data, and use the marked indoor relevant data to perform comprehensive indoor lighting evaluation calculation to obtain the comprehensive indoor lighting coefficient. Among them, the indoor relevant data includes initial ambient brightness, indoor light intensity, and walking decibel data; Set the indoor lighting coefficient threshold, perform ratio calculation based on the comprehensive indoor lighting coefficient and the indoor lighting coefficient threshold, determine the level of indoor lighting intensity according to the ratio size, and change the lighting intensity based on the level of indoor lighting intensity, where the indoor lighting intensity includes low level, medium level, and high level.

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