A lighting control method and system based on the Internet of Things

Abstract

The present invention relates to the technical field of intelligent control of lamps, and is a lamp control method and system based on the Internet of Things. The specific method comprises: obtaining real-time environmental data of the environment around the lamp to be controlled, and calculating and obtaining a water droplet scattering factor and a particle absorption factor; obtaining an actual reachable area switching value of the target lamp to be controlled that currently emits light; searching for neighboring lamps of the target lamp to be controlled, and calculating a target reachable area switching value; adjusting the illumination and color temperature of the lamp to be controlled; respectively calculating and obtaining an energy efficiency feedback coefficient and a light efficiency feedback coefficient according to the color temperature adjustment data and the illumination adjustment data, and evaluating the lamp control effectiveness of the lamp to be controlled; the present invention solves the problem in the prior art that many lamp control systems rely on preset schedules or static sensors, and cannot be intelligently adjusted according to real-time environmental changes, resulting in insufficient light, energy waste, and unstable lighting effects.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent lamp control, and is a lamp control method and system based on the Internet of Things. Background Art

[0002] Existing outdoor lighting control solutions generally have problems such as fixed control modes, poor environmental adaptability, lack of coordinated regulation of adjacent lighting, and insufficient feedback mechanisms. For example, many systems rely on preset schedules or static sensors and cannot make intelligent adjustments based on real-time environmental changes, resulting in insufficient lighting or energy waste. In addition, traditional technologies also fail to effectively consider the impact of weather conditions on light propagation, and fail to dynamically adjust the light source of lamps based on changes in water droplets and particles in the air, resulting in unstable lighting effects.

[0003] In the existing disclosed invention technologies, for example, the patent with publication number CN115837876A discloses a vehicle lighting control system, which includes a vehicle current driving information collection module, a lighting required brightness assessment and analysis module, a next road section information extraction module, a vehicle driving vision auxiliary analysis module, a lighting brightness confirmation and evaluation module, a vehicle information library and a vehicle brightness control execution module to control the vehicle lighting.

[0004] The above-mentioned patent lacks coordination between lamps. The system focuses on the control of lamps of a single vehicle and fails to utilize the synergy between multiple lamps, which limits the optimization of the overall lighting effect. Summary of the invention

[0005] The technical problem to be solved by the present invention is that in the prior art, many lighting control systems rely on preset schedules or static sensors and cannot be intelligently adjusted according to real-time environmental changes, resulting in insufficient light, waste of energy and unstable lighting effects. A lighting control method and system based on the Internet of Things are proposed.

[0006] In order to achieve the above object, the technical solution of a lighting control method based on the Internet of Things of the present invention comprises the following steps:

[0007] S1: Acquire real-time environmental data of the environment around the lamp to be controlled, and simultaneously extract factory usage data of the lamp to be controlled to form a standard usage data set of the lamp to be controlled;

[0008] S2: importing the real-time environmental data into the water droplet scattering factor calculation strategy and the particle absorption factor calculation strategy respectively, and calculating and obtaining the water droplet scattering factor and the particle absorption factor;

[0009] S3: The water drop scattering factor and the particle absorption factor are introduced into the actual reachable area evaluation strategy of the light, and the actual reachable area switching value of the light currently emitted by the target lamp to be controlled is obtained;

[0010] S4: Search for neighboring lamps of the target lamp to be controlled and calculate the switching value of the target reachable area;

[0011] S5: adjusting the illumination of the lamp to be controlled according to the switching value of the target reachable area, synchronously obtaining the traffic flow information of the traffic section connected to the section where the lamp is located, and adjusting the color temperature of the lamp to be controlled according to the traffic flow information;

[0012] S6: Calculate and obtain an energy efficiency feedback coefficient and a light efficiency feedback coefficient according to the color temperature adjustment data and the illumination adjustment data;

[0013] S7: According to S6, the lamp control effectiveness of the lamp to be controlled is evaluated.

[0014] Specifically, in S2, the water droplet scattering factor calculation strategy is as follows:

[0015] ;

[0016] in, is the water drop scattering factor;

[0017] The total number of water droplets in the air of the monitoring area where the lamp to be controlled is located; Indicates A water drop, For the The diameter of a water droplet; SD is the baseline diameter of the water droplet; SE is the scattering coefficient of the water droplet;

[0018] Furthermore, the method for obtaining the baseline diameter SD of the water droplets specifically includes: using a laser scattering method, randomly sampling the diameters of water droplets in the air of the monitoring area where the lamps to be controlled are located in the past year, with a sample size of 10,000 groups, wherein the sample size for each quarter is 2,500 groups, and the value of the baseline diameter SD of the water droplets is the average value of the diameters of the 10,000 groups of water droplets;

[0019] In S2, the particle absorption factor calculation strategy is as follows:

[0020] ;

[0021] in, is the particle absorption factor;

[0022] The total number of particles in the air of the monitoring area where the lamps to be controlled are located; Indicates Particles; Indicates The particle size of each particle; KL is the baseline particle size of the particle; is the particle absorption coefficient.

[0023] Furthermore, the method for obtaining the baseline particle size KL of the particulate matter specifically includes: using a particle counter to randomly sample the particle size of the particulate matter in the air of the monitoring area where the lamp to be controlled is located in the past year, the sample size is 10,000 groups, wherein the sample size for each quarter is 2,500 groups, and the value of the baseline particle size KL of the particulate matter is the average value of the particle sizes of the 10,000 groups of particulate matter;

[0024] In S3, the actual reachable area evaluation strategy of the light specifically includes:

[0025] ;

[0026] in, is the actual accessible area of ​​the light; is the baseline reachable area of ​​the ray.

[0027] Specifically, S4 includes the following specific steps:

[0028] S41: In the traffic section where the target lamp to be controlled is located, calculating the straight-line distance between the remaining lamps to be controlled in the traffic section and the target lamp to be controlled;

[0029] S42: Searching for neighboring lamps of the target lamp to be controlled, wherein the neighboring lamps include: lamps to be controlled with the shortest straight-line distance to the target lamp to be controlled in the directions on both sides of the target lamp to be controlled, wherein the straight-line distance between the target lamp to be controlled and the neighboring lamp on one side is a first straight-line distance The straight-line distance between the target lamp to be controlled and the adjacent lamp on the other side is the second straight-line distance ;

[0030] S43: Calculate the target reachable area switching value according to the straight-line distance between the target lamp to be controlled and the adjacent lamps. The calculation formula of the target reachable area switching value is:

[0031] ;

[0032] in, Switching value for the first target reachable area; Switch value for the second target reachable area.

[0033] Specifically, S5 includes the following specific steps:

[0034] S51: extracting a first target reachable area switching value and a second target reachable area switching value;

[0035] S52: adjusting the illumination of the lamp to be controlled according to the first target reachable area switching value and the second target reachable area switching value, wherein the illumination adjustment includes:

[0036] ;

[0037] in, are respectively the first illumination and the second illumination after the lamp to be controlled is adjusted;

[0038] is the baseline illuminance of the luminaire to be controlled.

[0039] Specifically, S5 also includes the following specific steps:

[0040] S53: synchronously obtaining, through the Internet of Things service platform, the traffic flow information of the intersection of the traffic section connected to the section where the lamp is located;

[0041] S54: adjusting the color temperature of the lamp to be controlled according to the traffic flow information, specifically:

[0042] ;

[0043] in, The color temperature of the lamp to be controlled after adjustment;

[0044] is the baseline color temperature; are the traffic flow influence coefficient and the distance influence coefficient respectively;

[0045] C is the maximum traffic density at the intersection in the traffic section connected to the section where the lamp is located; D is the straight-line distance between the lamp to be controlled and the first vehicle in the traffic flow in the traffic section with the maximum traffic density at the intersection.

[0046] Specifically, in S6, the calculation strategy of the energy efficiency feedback coefficient EF is:

[0047] ;

[0048] in, The color temperature of the lamp to be controlled after adjustment The dimensionless color temperature value of

[0049] Baseline color temperature of the lamp to be controlled The dimensionless color temperature value of

[0050] A is the lighting coverage area, ; W is the baseline power of the lamp to be controlled.

[0051] Specifically, in S6, the calculation strategy of the light effect feedback coefficient LF is:

[0052] ;

[0053] in, is the baseline illumination of the lamp to be controlled The dimensionless illuminance value of ;

[0054] are respectively the first dimensionless illuminance value and the second dimensionless illuminance value of the lamp to be controlled after adjustment; is the luminous efficiency of the lamp to be controlled.

[0055] Specifically, in S7, the strategy for evaluating the lamp control effectiveness of the lamp to be controlled is:

[0056] ;

[0057] in, To control the effectiveness of lighting fixtures; They are energy efficiency proportional coefficient and light efficiency proportional coefficient respectively; .

[0058] In addition, the lighting control system based on the Internet of Things of the present invention includes the following modules:

[0059] Environmental data acquisition module, influencing factor calculation module, actual reachable area evaluation module, target reachable area evaluation module, lighting adjustment module, adjustment feedback coefficient calculation module, effectiveness evaluation module;

[0060] The environmental data acquisition module is used to acquire real-time environmental data of the environment around the lamp to be controlled, and simultaneously extract factory usage data of the lamp to be controlled to form a standard usage data set of the lamp to be controlled;

[0061] The influencing factor calculation module is used to import the real-time environmental data into the water droplet scattering factor calculation strategy and the particle absorption factor calculation strategy respectively, and calculate and obtain the water droplet scattering factor and the particle absorption factor;

[0062] The actual reachable area evaluation module is used to introduce the water drop scattering factor and the particle absorption factor into the actual reachable area evaluation strategy of the light, and obtain the actual reachable area switching value of the light currently emitted by the target lamp to be controlled;

[0063] The target reachable area evaluation module is used to search for neighboring lamps of the target lamp to be controlled and calculate the target reachable area switching value;

[0064] The lamp adjustment module adjusts the illumination of the lamp to be controlled according to the target reachable area switching value, synchronously obtains the traffic flow information of the traffic section connected to the section where the lamp is located, and adjusts the color temperature of the lamp to be controlled according to the traffic flow information;

[0065] The adjustment feedback coefficient calculation module calculates and obtains the energy efficiency feedback coefficient and the light efficiency feedback coefficient according to the color temperature adjustment data and the illumination adjustment data;

[0066] The effectiveness evaluation module is used to evaluate the lamp control effectiveness of the lamp to be controlled.

[0067] Specifically, the effectiveness evaluation module includes: a lamp control effectiveness calculation unit, an effectiveness threshold judgment unit, and a lamp control suggestion output unit;

[0068] The lamp control effectiveness calculation unit is used to calculate the lamp control effectiveness in real time;

[0069] The effectiveness threshold judgment unit judges the effectiveness of lamp control according to a preset effectiveness threshold, and screens out lamps that fail to meet the control standards;

[0070] The lamp control suggestion output unit outputs the lamp control suggestion according to the lamp control effectiveness judgment result;

[0071] A storage medium stores instructions, and when a computer reads the instructions, the computer executes the lighting control method based on the Internet of Things.

[0072] An electronic device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the above-mentioned method for controlling a lamp based on the Internet of Things is implemented.

[0073] Compared with the prior art, the technical effects of the present invention are as follows: by acquiring environmental data and factory usage data of lamps in real time, constructing a standard usage data set, and combining intelligent calculation influencing factors such as water droplet scattering factor and particle absorption factor, the optimal adjustment of lamp illumination and color temperature is achieved. In addition, the solution also utilizes the communication capabilities between lamps to achieve collaborative work of adjacent lamps to improve the overall lighting effect, and timely evaluates the control effectiveness of lamps through the calculation of energy efficiency feedback coefficient and light efficiency feedback coefficient. This innovative method aims to significantly improve the control effect of outdoor lamps, reduce energy consumption, and improve the intelligence level of the system, so as to better meet the growing demand for outdoor lighting in modern cities. BRIEF DESCRIPTION OF THE DRAWINGS

[0074] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative labor. Among them:

[0075] Figure 1 A schematic diagram of a flow chart of a lamp control method based on the Internet of Things of the present invention;

[0076] Figure 2 This is a schematic diagram of the structure of a lighting control system based on the Internet of Things of the present invention;

[0077] Figure 3 It is a schematic diagram of the structure of the effectiveness evaluation module of the present invention. DETAILED DESCRIPTION

[0078] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the accompanying drawings.

[0079] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0080] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0081] Example 1

[0082] like Figure 1 As shown, a lighting control method based on the Internet of Things in an embodiment of the present invention is as follows: Figure 1 As shown, the specific steps are as follows:

[0083] S1: Acquire real-time environmental data of the environment around the lamp to be controlled, and simultaneously extract factory usage data of the lamp to be controlled to form a standard usage data set of the lamp to be controlled;

[0084] S2: importing the real-time environmental data into the water droplet scattering factor calculation strategy and the particle absorption factor calculation strategy respectively, and calculating and obtaining the water droplet scattering factor and the particle absorption factor;

[0085] In S2, the water droplet scattering factor calculation strategy is as follows:

[0086] ;

[0087] in, is the water drop scattering factor;

[0088] The total number of water droplets in the air of the monitoring area where the lamp to be controlled is located; Indicates A water drop, For the The diameter of a water droplet; SD is the baseline diameter of the water droplet; SE is the scattering coefficient of the water droplet;

[0089] For example, in this embodiment, a calculation strategy for the water droplet scattering coefficient is provided, specifically: , is the refractive index of the water droplet; is the wavelength of the light to be controlled;

[0090] In S2, the particle absorption factor calculation strategy is as follows:

[0091] ;

[0092] in, is the particle absorption factor;

[0093] The total number of particles in the air of the monitoring area where the lamps to be controlled are located; Indicates Particles; Indicates The particle size of each particle; KL is the baseline particle size of the particle; is the particle absorption coefficient.

[0094] For example, in this embodiment, a calculation strategy for the particle absorption coefficient is provided, specifically: ; are the maximum particle size and the minimum particle size among all particles respectively; The particle size is The effective absorption cross section of particles for light; Indicates that the particle size of all particles is The amount of particulate matter; is the integral symbol, indicating the particle size 's points.

[0095] S3: The water drop scattering factor and the particle absorption factor are introduced into the actual reachable area evaluation strategy of the light, and the actual reachable area switching value of the light currently emitted by the target lamp to be controlled is obtained;

[0096] In S3, the actual reachable area evaluation strategy of the light specifically includes:

[0097] ;

[0098] in, is the actual accessible area of ​​the light; is the baseline reachable area of ​​the ray.

[0099] S4: Search for neighboring lamps of the target lamp to be controlled and calculate the switching value of the target reachable area;

[0100] S4 includes the following specific steps:

[0101] S41: In the traffic section where the target lamp to be controlled is located, calculating the straight-line distance between the remaining lamps to be controlled in the traffic section and the target lamp to be controlled;

[0102] S42: Searching for neighboring lamps of the target lamp to be controlled, wherein the neighboring lamps include: lamps to be controlled with the shortest straight-line distance to the target lamp to be controlled in the directions on both sides of the target lamp to be controlled, wherein the straight-line distance between the target lamp to be controlled and the neighboring lamp on one side is a first straight-line distance The straight-line distance between the target lamp to be controlled and the adjacent lamp on the other side is the second straight-line distance ;

[0103] S43: Calculate the target reachable area switching value according to the straight-line distance between the target lamp to be controlled and the adjacent lamps. The calculation formula of the target reachable area switching value is:

[0104] ;

[0105] in, Switching value for the first target reachable area; Switch value for the second target reachable area.

[0106] S5: adjusting the illumination of the lamp to be controlled according to the switching value of the target reachable area, synchronously obtaining the traffic flow information of the traffic section connected to the section where the lamp is located, and adjusting the color temperature of the lamp to be controlled according to the traffic flow information;

[0107] S5 includes the following specific steps:

[0108] S51: extracting a first target reachable area switching value and a second target reachable area switching value;

[0109] S52: adjusting the illumination of the lamp to be controlled according to the first target reachable area switching value and the second target reachable area switching value, wherein the illumination adjustment includes:

[0110] ;

[0111] in, are respectively the first illumination and the second illumination after the lamp to be controlled is adjusted;

[0112] is the baseline illuminance of the luminaire to be controlled.

[0113] For example, in this embodiment, a specific implementation method of adjusting the illumination of the lamp to be controlled according to the first target reachable area switching value and the second target reachable area switching value is provided, including:

[0114] S521: Start the LED street lamp with a rotatable or tiltable lampshade. In this embodiment, the LED street lamp is embedded with an intelligent controller supporting angle adjustment and a servo motor for controlling the angle of the lampshade;

[0115] S522: according to the calculated first illuminance and second illuminance, setting a target angle of the lampshade, and converting the angle value into a control parameter recognizable by the servo motor, wherein the first illuminance is used to control the illuminance of the lamp module on one side, and the second illuminance is used to control the illuminance of the lamp module on the other side;

[0116] S523: Extract target angle values ​​on both sides of the lampshade through a control panel or a programming interface, and adjust the angle of the lampshade to change the distribution and illumination of the light.

[0117] S5 also includes the following specific steps:

[0118] S53: synchronously obtaining, through the Internet of Things service platform, the traffic flow information of the intersection of the traffic section connected to the section where the lamp is located;

[0119] S54: adjusting the color temperature of the lamp to be controlled according to the traffic flow information, specifically:

[0120] ;

[0121] in, The color temperature of the lamp to be controlled after adjustment;

[0122] is the baseline color temperature; are the traffic flow influence coefficient and the distance influence coefficient respectively;

[0123] C is the maximum traffic density at the intersection in the traffic section connected to the section where the lamp is located; D is the straight-line distance between the lamp to be controlled and the first vehicle in the traffic flow in the traffic section with the maximum traffic density at the intersection.

[0124] S6: Calculate and obtain an energy efficiency feedback coefficient and a light efficiency feedback coefficient according to the color temperature adjustment data and the illumination adjustment data;

[0125] In S6, the calculation strategy of the energy efficiency feedback coefficient EF is:

[0126] ;

[0127] in, The color temperature of the lamp to be controlled after adjustment The dimensionless color temperature value of

[0128] Baseline color temperature of the lamp to be controlled The dimensionless color temperature value of

[0129] A is the lighting coverage area, ; W is the baseline power of the lamp to be controlled.

[0130] In S6, the calculation strategy of the light effect feedback coefficient LF is:

[0131] ;

[0132] in, is the baseline illumination of the lamp to be controlled The dimensionless illuminance value of ;

[0133] are respectively the first dimensionless illuminance value and the second dimensionless illuminance value of the lamp to be controlled after adjustment; is the luminous efficiency of the lamp to be controlled.

[0134] S7: According to S6, the lamp control effectiveness of the lamp to be controlled is evaluated.

[0135] In S7, the strategy for evaluating the lamp control effectiveness of the lamp to be controlled is specifically:

[0136] ;

[0137] in, To control the effectiveness of lighting fixtures; They are energy efficiency proportional coefficient and light efficiency proportional coefficient respectively; .

[0138] Example 2

[0139] like Figure 2 As shown, a lighting control system based on the Internet of Things according to an embodiment of the present invention includes the following modules:

[0140] Environmental data acquisition module, influencing factor calculation module, actual reachable area evaluation module, target reachable area evaluation module, lighting adjustment module, adjustment feedback coefficient calculation module, effectiveness evaluation module;

[0141] The environmental data acquisition module is used to acquire real-time environmental data of the environment around the lamp to be controlled, and simultaneously extract factory usage data of the lamp to be controlled to form a standard usage data set of the lamp to be controlled;

[0142] The influencing factor calculation module is used to import the real-time environmental data into the water droplet scattering factor calculation strategy and the particle absorption factor calculation strategy respectively, and calculate and obtain the water droplet scattering factor and the particle absorption factor;

[0143] The actual reachable area evaluation module is used to introduce the water drop scattering factor and the particle absorption factor into the actual reachable area evaluation strategy of the light, and obtain the actual reachable area switching value of the light currently emitted by the target lamp to be controlled;

[0144] The target reachable area evaluation module is used to search for neighboring lamps of the target lamp to be controlled and calculate the target reachable area switching value;

[0145] The lamp adjustment module adjusts the illumination of the lamp to be controlled according to the target reachable area switching value, synchronously obtains the traffic flow information of the traffic section connected to the section where the lamp is located, and adjusts the color temperature of the lamp to be controlled according to the traffic flow information;

[0146] The adjustment feedback coefficient calculation module calculates and obtains the energy efficiency feedback coefficient and the light efficiency feedback coefficient according to the color temperature adjustment data and the illumination adjustment data;

[0147] The effectiveness evaluation module is used to evaluate the lamp control effectiveness of the lamp to be controlled.

[0148] Specifically, Figure 3 As shown, the effectiveness evaluation module includes: a lamp control effectiveness calculation unit, an effectiveness threshold judgment unit, and a lamp control suggestion output unit;

[0149] The lamp control effectiveness calculation unit is used to calculate the lamp control effectiveness in real time;

[0150] The effectiveness threshold judgment unit judges the effectiveness of lamp control according to a preset effectiveness threshold, and screens out lamps that fail to meet the control standards;

[0151] The lamp control suggestion output unit outputs the lamp control suggestion according to the lamp control effectiveness judgment result.

[0152] Exemplarily, in this embodiment, an example suggestion for lamp control suggestion is given, specifically including: when the judgment result of the lamp control effectiveness is qualified, maintain the current settings and monitor the energy efficiency and light efficiency, and regularly check the lamp lighting effect; when the judgment result of the lamp control effectiveness is unqualified, clean the lamp to ensure that the luminous flux is not obstructed or replace the lamp with a new one or reinstall the lamp.

[0153] Example 3

[0154] This embodiment provides an electronic device, including: a processor and a memory, wherein the memory stores a computer program that can be called by the processor;

[0155] The processor executes the above-mentioned lighting control method based on the Internet of Things by calling the computer program stored in the memory.

[0156] The electronic device may have relatively large differences due to different configurations or performances, and may include one or more processors (Central Processing Units, CPU) and one or more memories, wherein the memory stores at least one computer program, which is loaded and executed by the processor to implement a lighting control method based on the Internet of Things provided by the above method embodiment. The electronic device may also include other components for implementing the functions of the device, for example, the electronic device may also have components such as a wired or wireless network interface and an input and output interface to input and output data. This embodiment will not be described in detail here.

[0157] Example 4

[0158] This embodiment provides a storage medium on which erasable instructions are stored;

[0159] When the instruction is executed on the computer device, the computer device executes the above-mentioned lighting control method based on the Internet of Things.

[0160] For example, the storage medium can be a read-only memory (ROM), a random access memory (RAM), a compact disc (CD-ROM), a magnetic tape, a floppy disk, an optical data storage device, etc.

[0161] It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0162] It should be understood that determining B based on A does not mean determining B only based on A. B can also be determined based on A and / or other information.

[0163] The above embodiments can be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented by software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When a computer instruction or computer program is loaded or executed on a computer, a process or function according to an embodiment of the present invention is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. Computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, computer instructions can be transmitted from one website site, computer, server or data center to another website site, computer, server or data center through a wired network or / and a wireless network. The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or data center that contains one or more available media sets. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state hard disk.

[0164] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed in the present invention can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0165] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0166] In the several embodiments provided by the present invention, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic, for example, the division of units is only one, and there may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0167] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0168] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0169] In the description of this specification, the description with reference to the terms "one embodiment", "example", "specific example", etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0170] In summary, compared with the prior art, the technical effects of the present invention are as follows: by acquiring environmental data and factory usage data of lamps in real time, constructing a standard usage data set, and combining intelligent calculation influencing factors such as water droplet scattering factor and particle absorption factor, the optimal adjustment of lamp illumination and color temperature is achieved. In addition, the solution also utilizes the communication capabilities between lamps to achieve collaborative work of adjacent lamps to improve the overall lighting effect, and timely evaluates the control effectiveness of lamps through the calculation of energy efficiency feedback coefficient and light efficiency feedback coefficient. This innovative method aims to significantly improve the control effect of outdoor lamps, reduce energy consumption, and improve the intelligence level of the system, so as to better meet the growing demand for outdoor lighting in modern cities.

[0171] The above shows and describes the basic principles and main features of the present invention and the advantages of the present invention. It should be understood by those skilled in the art that the present invention is not limited to the above embodiments. The above embodiments and descriptions are only for explaining the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention to be protected. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. A lighting control method based on the Internet of Things, characterized in that: The method comprises the following specific steps: S1: Acquire real-time environmental data of the environment around the lamp to be controlled, and simultaneously extract factory usage data of the lamp to be controlled to form a standard usage data set of the lamp to be controlled; S2: importing the real-time environmental data into the water droplet scattering factor calculation strategy and the particle absorption factor calculation strategy respectively, and calculating and obtaining the water droplet scattering factor and the particle absorption factor; In S2, the water droplet scattering factor calculation strategy is as follows: ； in, is the water drop scattering factor; The total number of water droplets in the air of the monitoring area where the lamp to be controlled is located; Indicates A water drop, For the The diameter of a water droplet; SD is the baseline diameter of the water droplet; SE is the scattering coefficient of the water droplet; In S2, the particle absorption factor calculation strategy is as follows: ； in, is the particle absorption factor; The total number of particles in the air of the monitoring area where the lamps to be controlled are located; Indicates Particles; Indicates The particle size of each particle; KL is the baseline particle size of the particle; is the particle absorption coefficient; S3: The water drop scattering factor and the particle absorption factor are introduced into the actual reachable area evaluation strategy of the light, and the actual reachable area switching value of the light currently emitted by the target lamp to be controlled is obtained; In S3, the actual reachable area evaluation strategy of the light specifically includes: ； in, is the actual accessible area of ​​the light; is the baseline reachable area of ​​the light; S4: Search for neighboring lamps of the target lamp to be controlled and calculate the switching value of the target reachable area; S5: adjusting the illumination of the lamp to be controlled according to the switching value of the target reachable area, synchronously obtaining the traffic flow information of the traffic section connected to the section where the lamp is located, and adjusting the color temperature of the lamp to be controlled according to the traffic flow information; S6: Calculate and obtain an energy efficiency feedback coefficient and a light efficiency feedback coefficient according to the color temperature adjustment data and the illumination adjustment data; S7: According to S6, the lamp control effectiveness of the lamp to be controlled is evaluated.

2. The lighting control method based on the Internet of Things according to claim 1, characterized in that: S4 includes the following specific steps: S41: In the traffic section where the target lamp to be controlled is located, calculating the straight-line distance between the remaining lamps to be controlled in the traffic section and the target lamp to be controlled; S42: Searching for neighboring lamps of the target lamp to be controlled, wherein the neighboring lamps include: lamps to be controlled with the shortest straight-line distance to the target lamp to be controlled in the directions on both sides of the target lamp to be controlled, wherein the straight-line distance between the target lamp to be controlled and the neighboring lamp on one side is a first straight-line distance The straight-line distance between the target lamp to be controlled and the adjacent lamp on the other side is the second straight-line distance ; S43: Calculate the target reachable area switching value according to the straight-line distance between the target lamp to be controlled and the adjacent lamps. The calculation formula of the target reachable area switching value is: ； in, Switching value for the first target reachable area; Switch value for the second target reachable area.

3. The lighting control method based on the Internet of Things according to claim 2, characterized in that: S5 includes the following specific steps: S51: extracting a first target reachable area switching value and a second target reachable area switching value; S52: adjusting the illumination of the lamp to be controlled according to the first target reachable area switching value and the second target reachable area switching value, wherein the illumination adjustment includes: ； in, are respectively the first illumination and the second illumination after the lamp to be controlled is adjusted; is the baseline illuminance of the luminaire to be controlled.

4. The lighting control method based on the Internet of Things according to claim 3 is characterized in that: S5 also includes the following specific steps: S53: synchronously obtaining, through the Internet of Things service platform, the traffic flow information of the intersection of the traffic section connected to the section where the lamp is located; S54: adjusting the color temperature of the lamp to be controlled according to the traffic flow information, specifically: ； in, The color temperature of the lamp to be controlled after adjustment; is the baseline color temperature; are the traffic flow influence coefficient and the distance influence coefficient respectively; C is the maximum traffic density at the intersection in the traffic section connected to the section where the lamp is located; D is the straight-line distance between the lamp to be controlled and the first vehicle in the traffic flow in the traffic section with the maximum traffic density at the intersection.

5. The lighting control method based on the Internet of Things according to claim 4 is characterized in that: In S6, the calculation strategy of the energy efficiency feedback coefficient EF is: ； in, The color temperature of the lamp to be controlled after adjustment The dimensionless color temperature value of Baseline color temperature of the lamp to be controlled The dimensionless color temperature value of A is the lighting coverage area, ; W is the baseline power of the lamp to be controlled.

6. The lighting control method based on the Internet of Things according to claim 5, characterized in that: In S6, the calculation strategy of the light effect feedback coefficient LF is: ； in, is the baseline illumination of the lamp to be controlled The dimensionless illuminance value of ; are respectively the first dimensionless illuminance value and the second dimensionless illuminance value of the lamp to be controlled after adjustment; is the luminous efficiency of the lamp to be controlled.

7. The lighting control method based on the Internet of Things according to claim 6, characterized in that: In S7, the strategy for evaluating the lamp control effectiveness of the lamp to be controlled is specifically: ； in, To control the effectiveness of lighting fixtures; They are energy efficiency proportional coefficient and light efficiency proportional coefficient respectively; .

8. A lighting control system based on the Internet of Things, which is used to implement a lighting control method based on the Internet of Things as claimed in any one of claims 1 to 7, characterized in that: The system includes the following modules: Environmental data acquisition module, influencing factor calculation module, actual reachable area evaluation module, target reachable area evaluation module, lighting adjustment module, adjustment feedback coefficient calculation module, effectiveness evaluation module; The environmental data acquisition module is used to acquire real-time environmental data of the environment around the lamp to be controlled, and simultaneously extract factory usage data of the lamp to be controlled to form a standard usage data set of the lamp to be controlled; The influencing factor calculation module is used to import the real-time environmental data into the water droplet scattering factor calculation strategy and the particle absorption factor calculation strategy respectively, and calculate and obtain the water droplet scattering factor and the particle absorption factor; The actual reachable area evaluation module is used to introduce the water drop scattering factor and the particle absorption factor into the actual reachable area evaluation strategy of the light, and obtain the actual reachable area switching value of the light currently emitted by the target lamp to be controlled; The target reachable area evaluation module is used to search for neighboring lamps of the target lamp to be controlled and calculate the target reachable area switching value; The lamp adjustment module adjusts the illumination of the lamp to be controlled according to the target reachable area switching value, synchronously obtains the traffic flow information of the traffic section connected to the section where the lamp is located, and adjusts the color temperature of the lamp to be controlled according to the traffic flow information; The adjustment feedback coefficient calculation module calculates and obtains the energy efficiency feedback coefficient and the light efficiency feedback coefficient according to the color temperature adjustment data and the illumination adjustment data; The effectiveness evaluation module is used to evaluate the lamp control effectiveness of the lamp to be controlled.

Images