Intelligent green illumination control method for weakening urban light pollution

Abstract

The invention discloses an intelligent green illumination control method for weakening urban light pollution, and relates to the field of illumination control, and the method comprises the steps: determining a weakening coefficient of a light pollution weakening factor to illumination intensity, and determining a reflection coefficient of a light reflection object to the illumination intensity; calculating a direct illumination effect at the illumination point, and calculating a reflected illumination effect at the illumination point; a direct light pollution identification standard is formed, and a reflected light pollution identification standard is formed; taking the lighting point with light pollution as a lighting point to be regulated and controlled; classifying the lighting points to be regulated and controlled into necessary lighting points and unnecessary lighting points; and adjusting the actual illumination intensity of the necessary illumination point to an illumination intensity allowable value. According to the method, the light reflection object and the light pollution weakening factor are determined, the corresponding weakening coefficient and reflection coefficient are determined, and different adjustments are carried out at the necessary illumination point and the unnecessary illumination point, so that the actual illumination requirement can be met, and the influence of light pollution can be weakened to the greatest extent.

Description

Technical Field

[0001] The present invention relates to the field of lighting control, and in particular to an intelligent green lighting control method for reducing urban light pollution. Background Art

[0002] Light pollution is a new source of environmental pollution after waste gas, waste water, waste residue and noise pollution. Light pollution is threatening people's health. In daily life, the most common light pollution conditions are the dizziness of pedestrians and drivers caused by the reflection of mirror buildings, and the discomfort caused by unreasonable light intensity at night.

[0003] However, since light pollution is affected by a variety of factors in the environment, it is difficult to accurately control the intensity of lighting when making adjustments to reduce light pollution, resulting in the inability to meet lighting needs while reducing light pollution. Summary of the invention

[0004] In order to solve the above technical problems, an intelligent green lighting control method for weakening urban light pollution is provided. This technical solution solves the problem raised in the above background technology that light pollution is affected by the comprehensive influence of environmental factors. When adjusting the light pollution reduction, it is difficult to accurately control the lighting intensity, resulting in the inability to meet lighting needs and reduce light pollution at the same time.

[0005] In order to achieve the above purpose, the technical solution adopted by the present invention is:

[0006] An intelligent green lighting control method for reducing urban light pollution, comprising:

[0007] Obtain at least one lighting point in the city, and obtain the actual light intensity of the lighting point;

[0008] Identify reflective objects in the environment where the lighting point is located to obtain at least one light reflecting object;

[0009] Obtaining at least one light pollution weakening factor in the environment where the lighting point is located;

[0010] Determine the attenuation coefficient of light pollution attenuation factors on light intensity, and determine the reflection coefficient of light reflecting objects on light intensity;

[0011] Calculate the direct lighting effect at the lighting point, and calculate the reflected lighting effect at the lighting point;

[0012] Forming identification standards for direct light pollution and reflected light pollution;

[0013] Based on the direct light pollution identification standard and the reflected light pollution identification standard, at least one lighting point with light pollution is obtained, and the lighting point with light pollution is used as the lighting point to be regulated;

[0014] Perform lighting necessity detection on the lighting points to be regulated, and classify the lighting points to be regulated into necessary lighting points and non-essential lighting points based on the lighting necessity;

[0015] Turn off lights at non-essential lighting points;

[0016] At the necessary lighting point, the allowable value of the light intensity at the necessary lighting point is calculated, and the actual light intensity at the necessary lighting point is adjusted to the allowable value of the light intensity.

[0017] Preferably, the identifying of reflective objects in the environment where the lighting point is located to obtain at least one light reflecting object comprises the following steps:

[0018] Based on big data, the maximum light intensity that does not cause dizziness in human eyes is obtained as the characteristic light intensity;

[0019] Based on big data, the value range of the illumination distance of urban lighting is obtained, and the value range of the illumination distance is divided into equal intervals to obtain at least one distance point;

[0020] Using the sample light intensity to illuminate the sample point, obtaining the sample actual light intensity of the sample light intensity at a position where the distance from the sample point is equal to the value at the distance point;

[0021] The actual light intensity of the sample is divided by the sample light intensity to obtain the action ratio;

[0022] Pair and fit the action ratio with the value at the distance point to obtain the action fitting function, where the action ratio is the independent variable and the value at the distance point is the dependent variable;

[0023] The characteristic light intensity is divided by the actual light intensity to obtain the actual ratio, and the actual ratio is substituted into the fitting function to obtain the recognition distance;

[0024] The area whose distance from the lighting point does not exceed the recognition distance is regarded as the lighting recognition range;

[0025] In the lighting recognition range, the distance from the object to the lighting point is obtained as the lighting distance;

[0026] Substitute the lighting distance into the action fitting function and inversely solve the lighting ratio. Multiply the lighting ratio by the actual light intensity to get the effective light intensity acting on the object.

[0027] Get the reflection intensity of the light reflected by the object, divide the light reflection intensity by the effective light intensity to get the reflection coefficient of the object;

[0028] An object whose reflection coefficient is greater than a first preset value is regarded as a light reflecting object, and the first preset value is set based on empirical data.

[0029] Preferably, obtaining at least one light pollution weakening factor in the environment where the lighting point is located comprises the following steps:

[0030] In the lighting recognition range, the absorbed light intensity is obtained by subtracting the reflected light intensity of the object from the effective light intensity of the object.

[0031] The absorbed light intensity is divided by the effective light intensity to obtain the absorption coefficient of the object;

[0032] An object with an absorption coefficient greater than a second preset value is used as a light pollution weakening factor, and the second preset value is set based on empirical data.

[0033] Preferably, the determining of the attenuation coefficient of the light pollution attenuation factor to the light intensity and the determining of the reflection coefficient of the light reflecting object to the light intensity comprises the following steps:

[0034] The absorption coefficient of the object that serves as a light pollution weakening factor is used as the weakening coefficient of the light pollution weakening factor;

[0035] The reflection coefficient of the object that is a light reflecting object is taken as the reflection coefficient of the light reflecting object.

[0036] Preferably, the calculating of the direct lighting effect at the lighting point and the calculating of the reflected lighting effect at the lighting point include the following steps:

[0037] Use the comprehensive lighting formula to calculate the direct lighting effect at the lighting point;

[0038] Use the reflection comprehensive formula to calculate the reflected lighting effect at the lighting point;

[0039] The comprehensive formula for illumination is as follows:

[0040]

[0041] Among them, A is the direct lighting effect, a is the actual light intensity, i is the subscript, n is the total number of light pollution weakening factors, and a i is the weakening coefficient of the i-th light pollution weakening factor;

[0042] The reflection synthesis formula is as follows:

[0043]

[0044] Among them, B is the reflected lighting effect, a is the actual lighting intensity, j is the subscript, m is the total number of light reflecting objects, and b j is the reflection coefficient of the jth light reflecting object.

[0045] Preferably, the forming of the direct light pollution identification standard and the forming of the reflected light pollution identification standard comprises the following steps:

[0046] Based on the historical data, obtaining at least one historical light intensity of the lighting point;

[0047] Based on the historical light intensity, the historical direct light effect at the lighting point is calculated, and the historical reflected light effect at the lighting point is calculated;

[0048] Obtain the effect of historical direct lighting effects on people within the lighting recognition range of the lighting point, and use the historical direct lighting effects with dizziness effects as target direct lighting effects;

[0049] The maximum value of the target's direct illumination effect is used as the direct light pollution identification standard;

[0050] Obtain the effect of historical reflected lighting effects on people within the lighting recognition range of the lighting point, and use the historical reflected lighting effects with dizziness effects as target reflected lighting effects;

[0051] The maximum value of the target's reflected lighting effect is used as the identification standard for reflected light pollution.

[0052] Preferably, obtaining at least one lighting point with light pollution based on the direct light pollution identification standard and the reflected light pollution identification standard comprises the following steps:

[0053] Lighting points whose direct lighting effects exceed the direct light pollution identification standard or whose reflected lighting effects exceed the reflected light pollution identification standard are regarded as lighting points with light pollution.

[0054] Preferably, the lighting necessity detection for the lighting point to be regulated comprises the following steps:

[0055] Treat lighting points that are not lighting points to be regulated as non-regulated lighting points;

[0056] Perform road surface recognition, obstacle recognition and traffic recognition at the lighting point to be controlled;

[0057] When the road surface at the lighting point to be regulated is uneven, or there are obstacles at the lighting point to be regulated, or there are vehicles passing by the lighting point to be regulated, then the lighting point to be regulated may be necessary for lighting, otherwise, the lighting point to be regulated is not necessary for lighting;

[0058] When the lighting point to be regulated is a lighting point that may be necessary, a non-regulated lighting point in the lighting identification range of the lighting point to be regulated is used as a characteristic lighting point;

[0059] Obtain the distance from the characteristic lighting point to the lighting point to be controlled as the characteristic distance;

[0060] Substitute the characteristic distance into the fitting function and inversely solve for the characteristic ratio;

[0061] Use the light intensity estimation formula to calculate the comprehensive lighting intensity of the characteristic lighting point at the lighting point to be regulated;

[0062] Based on historical data, obtain the minimum light intensity that can be recognized by the human eye;

[0063] When the comprehensive lighting intensity is less than the minimum lighting intensity, the lighting point to be regulated and the lighting may be necessary is considered necessary for lighting; otherwise, the lighting point to be regulated and the lighting may be necessary is considered unnecessary for lighting;

[0064] The light intensity estimation formula is as follows:

[0065]

[0066] Where C is the comprehensive lighting intensity, k is the subscript, p is the total number of characteristic lighting points, c k is the actual illumination intensity of the kth characteristic lighting point, d k is the characteristic ratio of the kth characteristic lighting point.

[0067] Preferably, the step of classifying the lighting points to be regulated into necessary lighting points and non-necessary lighting points based on lighting necessity comprises the following steps:

[0068] The lighting points that are necessary for lighting to be controlled are regarded as necessary lighting points, and the lighting points that are not necessary for lighting to be controlled are regarded as non-essential lighting points.

[0069] Preferably, the calculation of the allowable value of the illumination intensity of the necessary illumination point comprises the following steps:

[0070] A control interval is formed, the endpoints of the control interval are 0 and the actual light intensity of the necessary lighting point, and the control interval is divided at equal intervals to obtain at least one control point;

[0071] Under the condition that the lighting intensity at the necessary lighting point is equal to the value at the control point, the direct lighting effect at the necessary lighting point is calculated as the conditional direct lighting effect, and the reflected lighting effect at the necessary lighting point is calculated as the conditional reflected lighting effect;

[0072] The control point where the conditional direct lighting effect does not exceed the direct light pollution identification standard and the conditional reflected lighting effect does not exceed the reflected light pollution identification standard is taken as the target control point;

[0073] The maximum value of at least one target control point is used as the allowable value of light intensity.

[0074] Compared with the prior art, the present invention has the following beneficial effects:

[0075] By determining the light reflecting objects and light pollution weakening factors, and determining their corresponding weakening coefficients and reflection coefficients, and at the same time, performing lighting necessity detection, the lighting points to be controlled are identified and classified into necessary lighting points and non-essential lighting points, and different adjustments are made to the necessary lighting points and non-essential lighting points. In the entire control process, various factors in the lighting environment are taken into consideration, and the control is more precise. When controlling, it can not only meet the actual lighting needs, but also minimize the impact of light pollution. BRIEF DESCRIPTION OF THE DRAWINGS

[0076] Figure 1 It is a flow chart of the intelligent green lighting control method for reducing urban light pollution of the present invention;

[0077] Figure 2 A schematic diagram of a process of identifying a reflective object in an environment where a lighting point is located to obtain at least one light reflecting object according to the present invention;

[0078] Figure 3 A schematic diagram of a process of obtaining at least one light pollution weakening factor in an environment where a lighting point is located according to the present invention;

[0079] Figure 4 A schematic diagram of a process for determining a weakening coefficient of a light pollution weakening factor to light intensity and a reflection coefficient of a light reflecting object to light intensity according to the present invention;

[0080] Figure 5 A schematic diagram of a flow chart of calculating the direct lighting effect at a lighting point and calculating the reflected lighting effect at a lighting point according to the present invention;

[0081] Figure 6 A schematic diagram of the process of forming a direct light pollution identification standard and a reflected light pollution identification standard of the present invention;

[0082] Figure 7 A schematic diagram of a process of performing lighting necessity detection on a lighting point to be regulated according to the present invention;

[0083] Figure 8 The figure is a flow chart of the method for calculating the allowable value of the illumination intensity at the necessary illumination point according to the present invention. DETAILED DESCRIPTION

[0084] The following description is used to disclose the present invention so that those skilled in the art can implement the present invention. The preferred embodiments described below are only examples, and those skilled in the art may think of other obvious variations.

[0085] Reference Figure 1 As shown, an intelligent green lighting control method for reducing urban light pollution includes:

[0086] Obtain at least one lighting point in the city, and obtain the actual light intensity of the lighting point;

[0087] Identify reflective objects in the environment where the lighting point is located to obtain at least one light reflecting object;

[0088] Obtaining at least one light pollution weakening factor in the environment where the lighting point is located;

[0089] Determine the attenuation coefficient of light pollution attenuation factors on light intensity, and determine the reflection coefficient of light reflecting objects on light intensity;

[0090] Calculate the direct lighting effect at the lighting point, and calculate the reflected lighting effect at the lighting point;

[0091] Forming identification standards for direct light pollution and reflected light pollution;

[0092] Based on the direct light pollution identification standard and the reflected light pollution identification standard, at least one lighting point with light pollution is obtained, and the lighting point with light pollution is used as the lighting point to be regulated;

[0093] Perform lighting necessity detection on the lighting points to be regulated, and classify the lighting points to be regulated into necessary lighting points and non-essential lighting points based on the lighting necessity;

[0094] Turn off lights at non-essential lighting points;

[0095] At the necessary lighting point, the allowable value of the light intensity at the necessary lighting point is calculated, and the actual light intensity at the necessary lighting point is adjusted to the allowable value of the light intensity.

[0096] In actual lighting, there are two situations: one is the direct effect, and the other is the specular reflection. These two situations are different and need to be distinguished. Both of them will produce light pollution, which is specifically manifested as a dizzy effect on people;

[0097] In order to analyze the direct effect, it is necessary to comprehensively consider the situation in the environment and the actual light intensity of the lighting point. There are some objects in the environment that will weaken the lighting, such as green plants, so it is necessary to determine their weakening coefficients;

[0098] In order to analyze the specular reflection, it is necessary to comprehensively consider the reflection situation in the environment and the actual light intensity of the lighting point. Different light-reflecting objects have different degrees of reflection, so it is necessary to distinguish them and obtain a comprehensive reflection result.

[0099] On the other hand, when the lighting points to be regulated are determined, it is also necessary to conduct lighting necessity detection, because some places need lighting and some places do not need lighting. Therefore, it is necessary to distinguish between the two during regulation.

[0100] In this solution, corresponding algorithms are set to solve the above-mentioned problems.

[0101] Reference Figure 2 As shown, identifying a reflective object in an environment where a lighting point is located to obtain at least one light reflecting object includes the following steps:

[0102] Based on big data, the maximum light intensity that does not cause dizziness in human eyes is obtained as the characteristic light intensity;

[0103] Based on big data, the value range of the illumination distance of urban lighting is obtained, and the value range of the illumination distance is divided into equal intervals to obtain at least one distance point;

[0104] Using the sample light intensity to illuminate the sample point, obtaining the sample actual light intensity of the sample light intensity at a position where the distance from the sample point is equal to the value at the distance point;

[0105] The actual light intensity of the sample is divided by the sample light intensity to obtain the action ratio;

[0106] Pair and fit the action ratio with the value at the distance point to obtain the action fitting function, where the action ratio is the independent variable and the value at the distance point is the dependent variable;

[0107] The characteristic light intensity is divided by the actual light intensity to obtain the actual ratio, and the actual ratio is substituted into the fitting function to obtain the recognition distance;

[0108] The area whose distance from the lighting point does not exceed the recognition distance is regarded as the lighting recognition range;

[0109] In the lighting recognition range, the distance from the object to the lighting point is obtained as the lighting distance;

[0110] Substitute the lighting distance into the action fitting function and inversely solve the lighting ratio. Multiply the lighting ratio by the actual light intensity to get the effective light intensity acting on the object.

[0111] Get the reflection intensity of the light reflected by the object, divide the light reflection intensity by the effective light intensity to get the reflection coefficient of the object;

[0112] An object whose reflection coefficient is greater than a first preset value is regarded as a light reflecting object, and the first preset value is set based on empirical data.

[0113] When identifying a light-reflecting object, it is necessary to calculate the reflection coefficient of the object. Based on empirical data, it is easy to obtain a critical value for determining whether an object is a light-reflecting object. Thus, the first preset value is obtained, which is mainly used to identify objects that are easy to cause reflection, such as mirrors and glass.

[0114] When calculating the reflection coefficient, it is necessary to obtain the light intensity before and after reflection. However, due to the distance between the lighting point and the object, the actual light intensity of the lighting point will be weakened after propagation. Therefore, in order to calculate accurately, it is necessary to consider the weakening situation. For this purpose, an action fitting function is formed.

[0115] During identification, in order to reduce the workload, the identification area is divided to obtain the lighting identification range. For the part outside the lighting identification range, the intensity of the lighting point is greatly weakened after propagation, so it is not considered.

[0116] Reference Figure 3 As shown, obtaining at least one light pollution weakening factor in the environment where the lighting point is located includes the following steps:

[0117] In the lighting recognition range, the absorbed light intensity is obtained by subtracting the reflected light intensity of the object from the effective light intensity of the object.

[0118] The absorbed light intensity is divided by the effective light intensity to obtain the absorption coefficient of the object;

[0119] An object with an absorption coefficient greater than a second preset value is used as a light pollution weakening factor, and the second preset value is set based on empirical data.

[0120] When identifying light pollution weakening factors, it is necessary to calculate the absorption coefficient of the object. Based on empirical data, it is easy to obtain the critical value of light pollution weakening factor identification, that is, objects that have good light absorption, such as trees and black objects.

[0121] When calculating the absorption coefficient, it is necessary to obtain the light intensity before absorption and the light intensity absorbed. The light intensity before absorption is consistent with the light intensity before reflection, but due to the distance between the illumination point and the object, the actual light intensity of the illumination point will be weakened after propagation. Therefore, in order to accurately calculate, it is necessary to consider the attenuation situation. For this purpose, an action fitting function is formed for subsequent calculations.

[0122] Reference Figure 4 As shown, determining the attenuation coefficient of the light pollution attenuation factor on the light intensity and determining the reflection coefficient of the light reflecting object on the light intensity include the following steps:

[0123] The absorption coefficient of the object that serves as a light pollution weakening factor is used as the weakening coefficient of the light pollution weakening factor;

[0124] The reflection coefficient of the object that is a light reflecting object is taken as the reflection coefficient of the light reflecting object.

[0125] Reference Figure 5 As shown, calculating the direct lighting effect at the lighting point and calculating the reflected lighting effect at the lighting point include the following steps:

[0126] Use the comprehensive lighting formula to calculate the direct lighting effect at the lighting point;

[0127] Use the reflection comprehensive formula to calculate the reflected lighting effect at the lighting point;

[0128] The comprehensive formula for illumination is as follows:

[0129]

[0130] Among them, A is the direct lighting effect, a is the actual light intensity, i is the subscript, n is the total number of light pollution weakening factors, and a i is the weakening coefficient of the i-th light pollution weakening factor;

[0131] The reflection synthesis formula is as follows:

[0132]

[0133] Among them, B is the reflected lighting effect, a is the actual lighting intensity, j is the subscript, m is the total number of light reflecting objects, and b j is the reflection coefficient of the jth light reflecting object.

[0134] There is more than one light pollution weakening factor at the lighting point, and the influence of all light pollution weakening factors needs to be integrated. Since the light pollution weakening factors are randomly distributed, all situations are averaged in the comprehensive lighting formula, and the average result is used as the direct lighting effect at the lighting point;

[0135] There is more than one light reflecting object at the lighting point, and the influence of all the light reflecting objects needs to be combined. Since the light reflecting objects are randomly distributed, all situations are averaged in the reflection synthesis formula, and the average result is used as the reflected lighting effect at the lighting point.

[0136] Reference Figure 6 As shown, forming the direct light pollution identification standard and forming the reflected light pollution identification standard include the following steps:

[0137] Based on the historical data, obtaining at least one historical light intensity of the lighting point;

[0138] Based on the historical light intensity, the historical direct light effect at the lighting point is calculated, and the historical reflected light effect at the lighting point is calculated;

[0139] Obtain the effect of historical direct lighting effects on people within the lighting recognition range of the lighting point, and use the historical direct lighting effects with dizziness effects as target direct lighting effects;

[0140] The maximum value of the target's direct illumination effect is used as the direct light pollution identification standard;

[0141] Obtain the effect of historical reflected lighting effects on people within the lighting recognition range of the lighting point, and use the historical reflected lighting effects with dizziness effects as target reflected lighting effects;

[0142] The maximum value of the target's reflected lighting effect is used as the identification standard for reflected light pollution.

[0143] The critical value is determined according to the effect on personnel, thereby enabling the two light pollution situations to be identified separately according to the direct light pollution identification standard and the reflected light pollution identification standard.

[0144] Based on the direct light pollution identification standard and the reflected light pollution identification standard, obtaining at least one lighting point with light pollution includes the following steps:

[0145] Lighting points whose direct lighting effects exceed the direct light pollution identification standard or whose reflected lighting effects exceed the reflected light pollution identification standard are regarded as lighting points with light pollution.

[0146] Reference Figure 7 As shown, the lighting necessity detection for the lighting point to be regulated includes the following steps:

[0147] Treat lighting points that are not lighting points to be regulated as non-regulated lighting points;

[0148] Perform road surface recognition, obstacle recognition and traffic recognition at the lighting point to be controlled;

[0149] When the road surface at the lighting point to be regulated is uneven, or there are obstacles at the lighting point to be regulated, or there are vehicles passing by the lighting point to be regulated, then the lighting point to be regulated may be necessary for lighting, otherwise, the lighting point to be regulated is not necessary for lighting;

[0150] When the lighting point to be regulated is a lighting point that may be necessary, a non-regulated lighting point in the lighting identification range of the lighting point to be regulated is used as a characteristic lighting point;

[0151] Obtain the distance from the characteristic lighting point to the lighting point to be controlled as the characteristic distance;

[0152] Substitute the characteristic distance into the fitting function and inversely solve for the characteristic ratio;

[0153] Use the light intensity estimation formula to calculate the comprehensive lighting intensity of the characteristic lighting point at the lighting point to be regulated;

[0154] Based on historical data, obtain the minimum light intensity that can be recognized by the human eye;

[0155] When the comprehensive lighting intensity is less than the minimum lighting intensity, the lighting point to be regulated and the lighting may be necessary is considered necessary for lighting; otherwise, the lighting point to be regulated and the lighting may be necessary is considered unnecessary for lighting;

[0156] The light intensity estimation formula is as follows:

[0157]

[0158] Where C is the comprehensive lighting intensity, k is the subscript, p is the total number of characteristic lighting points, c k is the actual illumination intensity of the kth characteristic lighting point, d k is the characteristic ratio of the kth characteristic lighting point.

[0159] The lighting point to be regulated is a lighting point where light pollution exists, but lighting may be necessary or unnecessary at the lighting point to be regulated. The reason why lighting is not necessary is that there is no potential risk here or the non-regulated lighting point near the lighting point to be regulated can provide sufficient lighting brightness. Therefore, lighting is not required. The situation where lighting is not required is easy to solve, and it can be turned off directly. However, in the situation where lighting is required, the actual light intensity of the necessary lighting point needs to be adjusted, because there is light pollution there, but the brightness provided by the nearby sub-lighting points is insufficient. Therefore, it cannot be turned off directly, and the brightness can only be reduced, so as to meet the lighting needs and reduce light pollution at the same time.

[0160] Based on the lighting necessity, the lighting points to be regulated are classified into necessary lighting points and non-essential lighting points, including the following steps:

[0161] The lighting points that are necessary for lighting to be controlled are regarded as necessary lighting points, and the lighting points that are not necessary for lighting to be controlled are regarded as non-essential lighting points.

[0162] Reference Figure 8 As shown, calculating the allowable value of the illumination intensity at the necessary lighting point includes the following steps:

[0163] A control interval is formed, the endpoints of the control interval are 0 and the actual light intensity of the necessary lighting point, and the control interval is divided at equal intervals to obtain at least one control point;

[0164] Under the condition that the lighting intensity at the necessary lighting point is equal to the value at the control point, the direct lighting effect at the necessary lighting point is calculated as the conditional direct lighting effect, and the reflected lighting effect at the necessary lighting point is calculated as the conditional reflected lighting effect;

[0165] The control point where the conditional direct lighting effect does not exceed the direct light pollution identification standard and the conditional reflected lighting effect does not exceed the reflected light pollution identification standard is taken as the target control point;

[0166] The maximum value of at least one target control point is used as the allowable value of light intensity.

[0167] Furthermore, the present solution also proposes a storage medium on which a computer-readable program is stored. When the computer-readable program is called, the above-mentioned intelligent green lighting control method for reducing urban light pollution is executed.

[0168] It is understandable that the storage medium may be a magnetic medium, such as a floppy disk, a hard disk, or a magnetic tape; an optical medium, such as a DVD; or a semiconductor medium, such as a solid state drive (SSD).

[0169] To sum up, the advantages of the present invention are: by determining the light reflecting objects and light pollution weakening factors, and determining their corresponding weakening coefficients and reflection coefficients, and at the same time, performing lighting necessity detection, thereby identifying the lighting points to be controlled and classified into necessary lighting points and non-essential lighting points, and making different adjustments at the necessary lighting points and non-essential lighting points, so that in the entire control process, various factors in the lighting environment are taken into consideration, and the control is more precise. When controlling, it can not only meet the actual lighting needs, but also minimize the impact of light pollution.

[0170] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The above embodiments and descriptions only describe the principles of the present invention. The present invention may be subject to various changes and improvements without departing from the spirit and scope of the present invention. These changes and improvements fall within the scope of the present invention. The scope of protection claimed by the present invention is defined by the attached claims and their equivalents.

Claims

1. An intelligent green lighting control method for reducing urban light pollution, characterized in that: include: Obtain at least one lighting point in the city, and obtain the actual light intensity of the lighting point; Identify reflective objects in the environment where the lighting point is located to obtain at least one light reflecting object; Obtaining at least one light pollution weakening factor in the environment where the lighting point is located; Determine the attenuation coefficient of light pollution attenuation factors on light intensity, and determine the reflection coefficient of light reflecting objects on light intensity; Calculate the direct lighting effect at the lighting point, and calculate the reflected lighting effect at the lighting point; Forming identification standards for direct light pollution and reflected light pollution; Based on the direct light pollution identification standard and the reflected light pollution identification standard, at least one lighting point with light pollution is obtained, and the lighting point with light pollution is used as the lighting point to be regulated; Perform lighting necessity detection on the lighting points to be regulated, and classify the lighting points to be regulated into necessary lighting points and non-essential lighting points based on the lighting necessity; Turn off lights at non-essential lighting points; At the necessary lighting point, the allowable value of the light intensity at the necessary lighting point is calculated, and the actual light intensity at the necessary lighting point is adjusted to the allowable value of the light intensity.

2. The intelligent green lighting control method for reducing urban light pollution according to claim 1, characterized in that: The identification of reflective objects in the environment where the lighting point is located to obtain at least one light reflecting object comprises the following steps: Based on big data, the maximum light intensity that does not cause dizziness in human eyes is obtained as the characteristic light intensity; Based on big data, the value range of the illumination distance of urban lighting is obtained, and the value range of the illumination distance is divided into equal intervals to obtain at least one distance point; Using the sample light intensity to illuminate the sample point, obtaining the sample actual light intensity of the sample light intensity at a position where the distance from the sample point is equal to the value at the distance point; The actual light intensity of the sample is divided by the sample light intensity to obtain the action ratio; Pair and fit the action ratio with the value at the distance point to obtain the action fitting function, where the action ratio is the independent variable and the value at the distance point is the dependent variable; The characteristic light intensity is divided by the actual light intensity to obtain the actual ratio, and the actual ratio is substituted into the fitting function to obtain the recognition distance; The area whose distance from the lighting point does not exceed the recognition distance is regarded as the lighting recognition range; In the lighting recognition range, the distance from the object to the lighting point is obtained as the lighting distance; Substitute the lighting distance into the action fitting function and inversely solve the lighting ratio. Multiply the lighting ratio by the actual light intensity to get the effective light intensity acting on the object. Get the reflection intensity of the light reflected by the object, divide the light reflection intensity by the effective light intensity to get the reflection coefficient of the object; An object whose reflection coefficient is greater than a first preset value is regarded as a light reflecting object, and the first preset value is set based on empirical data.

3. The intelligent green lighting control method for reducing urban light pollution according to claim 2, characterized in that: The step of obtaining at least one light pollution weakening factor in the environment where the lighting point is located comprises the following steps: In the lighting recognition range, the absorbed light intensity is obtained by subtracting the reflected light intensity of the object from the effective light intensity of the object. The absorbed light intensity is divided by the effective light intensity to obtain the absorption coefficient of the object; An object with an absorption coefficient greater than a second preset value is used as a light pollution weakening factor, and the second preset value is set based on empirical data.

4. The intelligent green lighting control method for reducing urban light pollution according to claim 3, characterized in that: Determining the attenuation coefficient of the light pollution attenuation factor to the light intensity and determining the reflection coefficient of the light reflecting object to the light intensity comprises the following steps: The absorption coefficient of the object that serves as a light pollution weakening factor is used as the weakening coefficient of the light pollution weakening factor; The reflection coefficient of the object that is a light reflecting object is taken as the reflection coefficient of the light reflecting object.

5. The intelligent green lighting control method for reducing urban light pollution according to claim 4, characterized in that: The calculation of the direct lighting effect at the lighting point and the calculation of the reflected lighting effect at the lighting point include the following steps: Use the comprehensive lighting formula to calculate the direct lighting effect at the lighting point; Use the reflection comprehensive formula to calculate the reflected lighting effect at the lighting point; The comprehensive formula for illumination is as follows: Among them, A is the direct lighting effect, a is the actual light intensity, i is the subscript, n is the total number of light pollution weakening factors, and a i is the weakening coefficient of the i-th light pollution weakening factor; The reflection synthesis formula is as follows: Among them, B is the reflected lighting effect, a is the actual lighting intensity, j is the subscript, m is the total number of light reflecting objects, and b j is the reflection coefficient of the jth light reflecting object.

6. The intelligent green lighting control method for reducing urban light pollution according to claim 5, characterized in that: The forming of the direct light pollution identification standard and the forming of the reflected light pollution identification standard comprises the following steps: Based on the historical data, obtaining at least one historical light intensity of the lighting point; Based on the historical light intensity, the historical direct light effect at the lighting point is calculated, and the historical reflected light effect at the lighting point is calculated; Obtain the effect of historical direct lighting effects on people within the lighting recognition range of the lighting point, and use the historical direct lighting effects with dizziness effects as target direct lighting effects; The maximum value of the target's direct illumination effect is used as the direct light pollution identification standard; Obtain the effect of historical reflected lighting effects on people within the lighting recognition range of the lighting point, and use the historical reflected lighting effects with dizziness effects as target reflected lighting effects; The maximum value of the target's reflected lighting effect is used as the reflected light pollution identification standard.

7. The intelligent green lighting control method for reducing urban light pollution according to claim 6, characterized in that: The step of obtaining at least one lighting point with light pollution based on the direct light pollution identification standard and the reflected light pollution identification standard comprises the following steps: Lighting points whose direct lighting effects exceed the direct light pollution identification standard or whose reflected lighting effects exceed the reflected light pollution identification standard are regarded as lighting points with light pollution.

8. The intelligent green lighting control method for reducing urban light pollution according to claim 7, characterized in that: The lighting necessity detection of the lighting point to be regulated comprises the following steps: Treat lighting points that are not lighting points to be regulated as non-regulated lighting points; Perform road surface recognition, obstacle recognition and traffic recognition at the lighting point to be controlled; When the road surface at the lighting point to be regulated is uneven, or there are obstacles at the lighting point to be regulated, or there are vehicles passing by the lighting point to be regulated, then the lighting point to be regulated may be necessary for lighting, otherwise, the lighting point to be regulated is not necessary for lighting; When the lighting point to be regulated is a lighting point that may be necessary, a non-regulated lighting point in the lighting identification range of the lighting point to be regulated is used as a characteristic lighting point; Obtain the distance from the characteristic lighting point to the lighting point to be controlled as the characteristic distance; Substitute the characteristic distance into the fitting function and inversely solve for the characteristic ratio; Use the light intensity estimation formula to calculate the comprehensive lighting intensity of the characteristic lighting point at the lighting point to be regulated; Based on historical data, obtain the minimum light intensity that can be recognized by the human eye; When the comprehensive lighting intensity is less than the minimum lighting intensity, the lighting point to be regulated and the lighting may be necessary is considered necessary for lighting; otherwise, the lighting point to be regulated and the lighting may be necessary is considered unnecessary for lighting; The light intensity estimation formula is as follows: Where C is the comprehensive lighting intensity, k is the subscript, p is the total number of characteristic lighting points, c k is the actual illumination intensity of the kth characteristic lighting point, d k is the characteristic ratio of the kth characteristic lighting point.

9. The intelligent green lighting control method for reducing urban light pollution according to claim 8, characterized in that: The method of classifying the lighting points to be regulated into necessary lighting points and non-necessary lighting points based on lighting necessity comprises the following steps: The lighting points that are necessary for lighting to be controlled are regarded as necessary lighting points, and the lighting points that are not necessary for lighting to be controlled are regarded as non-essential lighting points.

10. The intelligent green lighting control method for reducing urban light pollution according to claim 9, characterized in that: The calculation to obtain the allowable value of the illumination intensity of the necessary illumination point comprises the following steps: A control interval is formed, the endpoints of the control interval are 0 and the actual light intensity of the necessary lighting point, and the control interval is divided at equal intervals to obtain at least one control point; Under the condition that the lighting intensity at the necessary lighting point is equal to the value at the control point, the direct lighting effect at the necessary lighting point is calculated as the conditional direct lighting effect, and the reflected lighting effect at the necessary lighting point is calculated as the conditional reflected lighting effect; The control point where the conditional direct lighting effect does not exceed the direct light pollution identification standard and the conditional reflected lighting effect does not exceed the reflected light pollution identification standard is taken as the target control point; The maximum value of at least one target control point is used as the allowable value of light intensity.

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