Intelligent campus power saving management system based on internet of things

Abstract

The application relates to the technical field of campus energy-saving, and particularly discloses an intelligent campus power-saving management system based on the Internet of Things, which comprises an environment data acquisition module, which is used for collecting environment information at different time points in different street lamp lighting areas; and an image acquisition module, which comprises a camera unit and an identification unit; through the combination of the road image information collected by the image acquisition module, the initial lighting demand in different street lamp lighting areas can be calculated, and the initial lighting brightness of different areas can be adjusted according to the data; since the data combines the road information of different areas, the adjusted lighting brightness can be more suitable for the road conditions of different areas, and can ensure that students can see the damaged road surface even in the case of few people, so that the situation that students fall or sprain due to stepping on the damaged area of the road surface caused by low light brightness can be avoided, energy-saving is realized, and the safety hidden danger caused by energy-saving can be eliminated.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of campus energy saving, in particular to an intelligent campus power energy saving management system based on the Internet of Things. BACKGROUND

[0002] The campus power energy saving management system improves and optimizes the monitoring and management of power balance through real-time monitoring, data analysis, intelligent control and other means, and realizes the goal of energy saving and consumption reduction.

[0003] In the campus power energy saving management system, campus street lamp energy saving is an important issue, which not only relates to energy saving, but also relates to the comfort and safety of the campus environment. In order to improve the use efficiency of street lamps and achieve the effect of energy saving, light sensors and infrared sensors are usually installed to automatically adjust the brightness of street lamps according to the surrounding light and pedestrian flow, so as to achieve the effect of energy saving.

[0004] The traditional street lamp energy saving measure sets the brightness of the street lamp at the lowest to achieve energy saving in the case of less pedestrian flow. However, if the road of the lighting section is damaged or has special circumstances, a small number of students passing through the area may fall or sprain due to the low light brightness, because the brightness of the street lamp is set at the lowest at this time. In this case, although energy saving can be effectively achieved, there is a safety hazard. SUMMARY

[0005] The purpose of the present application is to provide an intelligent campus power energy saving management system based on the Internet of Things, which solves the following technical problems:

[0006] How to realize campus energy saving and eliminate the safety hazards caused by energy saving.

[0007] The purpose of the present application can be achieved by the following technical solutions:

[0008] The intelligent campus power energy saving management system based on the Internet of Things comprises:

[0009] An environmental data acquisition module for acquiring environmental information at different time points in different street lamp lighting areas;

[0010] An image acquisition module comprising a camera unit and an identification unit, the camera unit being used for shooting road images and pedestrian flow images in different street lamp lighting areas;

[0011] The identification unit is used for identifying the images shot by the camera unit and extracting the required road information and pedestrian flow information;

[0012] The luminance adjustment module comprises a data processing unit, an initial luminance adjustment unit and a dynamic adjustment unit, the data processing unit is used for calculating initial lighting demand in different street lamp lighting areas in combination with road image information collected by the image collection module, and judging whether the initial luminance of different street lamps needs to be adjusted according to a preset initial lighting demand threshold;

[0013] The initial luminance adjustment unit is used for adjusting the initial luminance of the street lamp in combination with the initial lighting demand in different street lamp lighting areas and the environmental information when it is judged that the initial luminance of the street lamp needs to be adjusted;

[0014] The dynamic adjustment unit is used for dynamically adjusting the light luminance of the street lamp at different time points in combination with the crowd image information collected by the image collection module and the environmental information.

[0015] Further, the adjustment process of the luminance adjustment module comprises:

[0016] S1: first, the environmental information, the road information and the crowd information are collected by the environmental data collection module and the image collection module respectively;

[0017] S2: the initial lighting demand in different street lamp lighting areas is calculated by the data processing unit in combination with the road image information collected by the image collection module;

[0018] S3: the data processing unit is combined with the preset initial lighting demand threshold for analysis, and whether the initial luminance of different street lamps needs to be adjusted is judged according to the analysis result;

[0019] S4: when it is judged that the initial luminance of the street lamp needs to be adjusted, the initial luminance of different street lamps is adjusted by the initial luminance adjustment unit in combination with the initial lighting demand in different street lamp lighting areas and the environmental information;

[0020] S5: the light luminance of different street lamps at different time points is dynamically adjusted by the dynamic adjustment module in combination with the crowd image information collected by the image collection module, the environmental information and the initial luminance of different street lamps.

[0021] Further, the information collected in S1 comprises:

[0022] The environmental information comprises rainfall and snowfall;

[0023] The road information comprises damaged area, pothole area, water accumulation area and snow accumulation area in different lighting areas;

[0024] The crowd information comprises the number of people passing by and the crowd density in different lighting areas at different time points.

[0025] Further, the processing procedure of the data processing unit comprises:

[0026] The initial lighting demand in the i-th lighting area is calculated by the formula ;

[0027] Wherein, is the damaged area in the i-th lighting area, is the pothole area in the i-th lighting area, is the position influence function of the road obstacle area, which is set according to empirical fitting, is the total lighting area of the i-th lighting area, is the water accumulation area of the i-th lighting area, is the snow accumulation area of the i-th lighting area, is a judgment function, when , when , , is the road material influence coefficient, which is set according to empirical fitting, and 2 is the first weight coefficient.

[0028] Further, the processing procedure of the data processing unit further comprises:

[0029] The initial lighting demand in all lighting areas is compared with the preset initial lighting demand threshold respectively.

[0030] If , the system judges that the initial lighting demand in the area is high, and the initial lighting brightness of the street lamp in the lighting area needs to be adjusted;

[0031] If , the system judges that the initial lighting demand in the area is low, and the initial lighting brightness of the street lamp in the lighting area does not need to be adjusted, and the lighting is performed according to the minimum power consumption.

[0032] Further, the adjustment procedure of the initial brightness adjustment unit comprises:

[0033] The lighting area of the street lamp requiring initial lighting brightness is marked;

[0034] And the adjusted initial lighting brightness of the i-th lighting area is calculated by the formula ;

[0035] Wherein, ​​The preset low-power initial lighting brightness, This is the first adjustment coefficient lookup table function, based on empirical data. The extent to which the range of numerical values ​​affects the initial lighting brightness is obtained based on test data. The intensity of external light when the streetlights are turned on. The preset external light intensity, The error influence coefficient is set based on empirical fitting.

[0036] Furthermore, the adjustment process of the dynamic adjustment module includes:

[0037] Through formula Calculate the illumination intensity at time point a within the i-th illumination area. ;

[0038] Where 'a' represents a data collection at fixed time intervals after the streetlights are turned on. Let be the number of people passing by in the i-th illuminated area at time a. For the preset number of people, Let be the population density at time point a within the i-th lighting area. For the preset density, Let a be the amount of rainfall at time point a. for The standard value, Let a be the amount of snowfall at time point a. for The standard value, and 2 is the second weighting coefficient. This is the function for the second adjustment coefficient lookup table, based on empirical data. The influence of the range of numerical values ​​on the lighting brightness at different time points was obtained based on test data.

[0039] Furthermore, the adjustment process of the dynamic adjustment module also includes:

[0040] The fixed time interval for each data collection is less than the duration after the street light brightness adjustment is completed, and the duration is reset after the street light brightness is changed at each time point.

[0041] The beneficial effects of this invention are:

[0042] (1) The present application can calculate the initial lighting demand in different street lamp lighting areas by combining the road image information collected by the image collection module, and adjust the initial lighting brightness of different areas according to the data. Since the data combines the road information of different areas, the adjusted lighting brightness can be more suitable for the road conditions of different areas, and can ensure that students can see the damaged road surface even in the case of few people, thereby avoiding the situation that students fall or sprain due to low light brightness, realizing energy saving while eliminating the safety hazards caused by energy saving.

[0043] (2) The present application can calculate the initial lighting demand in the street lamp lighting area by combining the road image information in different lighting areas. The data can reflect the demand value of different road conditions for lighting brightness. After analyzing the data, it can be judged whether the initial lighting brightness in different areas needs to be adjusted, and adjusted in time through the initial brightness adjustment unit. It not only realizes energy saving, but also eliminates the safety hazards caused by energy saving.

[0044] (3) The present application compares the initial lighting demand in all street lamp lighting areas with the preset initial lighting demand threshold Based on the analysis and comparison results, the initial lighting demand in the i-th street lamp lighting area can be accurately judged, and when it is judged that the initial lighting demand in a certain street lamp lighting area is high, it means that the road condition of the area is poor, and the initial lighting brightness of the area needs to be adjusted in time, thereby avoiding the situation that students fall or sprain due to low light brightness, ensuring energy saving while protecting the personal safety of students.

[0045] (4) The present application can improve the accuracy and reliability of the adjusted initial lighting brightness by combining the initial lighting demand in the i-th street lamp lighting area , the preset low-power initial lighting brightness and the external light intensity when the street lamp is turned on, thereby ensuring that students can accurately observe the road conditions in different lighting areas to eliminate safety hazards while reducing energy consumption, and by adjusting the initial lighting brightness in different areas, students can judge which lighting areas may have poor road conditions according to the different lighting brightness, thereby playing a warning role and further protecting the personal safety of students.

[0046] (5) The present application can improve the accuracy of the lighting brightness calculation result of the i-th lighting area at the a-th time point by combining the number of passing people and the crowd density at the a-th time point in the i-th lighting area and diversified data such as irregular weather conditions such as rainfall and snowfall, thereby improving the accuracy of brightness adjustment, and since the data is calculated based on the initial lighting brightness adjusted by the i-th street lamp lighting area, the accuracy and reliability of the lighting brightness can be further improved, which can not only adapt to different environmental conditions, but also adapt to different road conditions of different lighting areas, thereby improving the use efficiency of street lamps and achieving the effect of energy saving. BRIEF DESCRIPTION OF DRAWINGS

[0047] The present application will be further described below with reference to the accompanying drawings.

[0048] Figure 1 is a schematic diagram of the intelligent campus power energy-saving management system based on the Internet of Things in the present application;

[0049] Figure 2 is a flowchart of the adjustment process of the brightness adjustment module. DETAILED DESCRIPTION

[0050] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the present application.

[0051] Please refer to Figure 1 In one embodiment, the present application provides an intelligent campus power energy-saving management system based on the Internet of Things, as shown in the accompanying drawings, the system comprises:

[0052] An environmental data acquisition module is used to acquire environmental information at different time points in different street lamp lighting areas;

[0053] An image acquisition module comprises a camera unit and an identification unit, the camera unit is used to shoot road images and pedestrian flow images in different street lamp lighting areas;

[0054] The identification unit is used to identify the images shot by the camera unit and extract the required road information and pedestrian flow information;

[0055] The brightness adjustment module comprises a data processing unit, an initial brightness adjustment unit and a dynamic adjustment unit. The data processing unit is used to calculate the initial lighting demand in different street lamp lighting areas in combination with the road image information collected by the image collection module, and determine whether the initial brightness of different street lamps needs to be adjusted according to the preset initial lighting demand threshold.

[0056] The initial brightness adjustment unit is used to adjust the initial brightness of the street lamp in combination with the initial lighting demand in different street lamp lighting areas and the environmental information when it is determined that the initial brightness of the street lamp needs to be adjusted.

[0057] The dynamic adjustment unit is used to dynamically adjust the light brightness of the street lamp at different time points in combination with the environmental information and the crowd image information collected by the image collection module.

[0058] Through the above technical solution, the environmental data collection module is provided to collect the environmental information at different time points in different street lamp lighting areas, and the camera unit is provided to shoot the road image and the crowd image in different street lamp lighting areas, and the recognition unit is provided to recognize the image shot by the camera unit, so that the required road information and crowd information can be extracted. When the system determines that the street lamp needs to be turned on, the data processing unit is first used to calculate the initial lighting demand in different street lamp lighting areas in combination with the road image information collected by the image collection module, and determine whether the initial brightness of different street lamps needs to be adjusted according to the preset initial lighting demand threshold. When it is determined that the initial brightness of the street lamp needs to be adjusted, the initial brightness adjustment unit is used to adjust the initial brightness of the street lamp in combination with the initial lighting demand in different street lamp lighting areas and the environmental information, so as to realize the control of the minimum brightness. Then, the dynamic adjustment unit is used to dynamically adjust the light brightness of the street lamp at different time points in combination with the environmental information and the crowd image information collected by the image collection module, so as to realize the energy saving effect.

[0059] By combining the road image information collected by the image collection module, the initial lighting demand in different street lamp lighting areas can be calculated, and the initial lighting brightness of different areas can be adjusted according to the data. Since the data combines the road information of different areas, the adjusted lighting brightness can be more suitable for the road conditions of different areas, so that the students can see the damaged road even in the case of less people, thereby avoiding the situation that the students fall or sprain due to the low light brightness, realizing energy saving while eliminating the safety hidden danger caused by energy saving.

[0060] It should be noted that the recognition module is a trained neural network model, which is prior art and will not be described in detail here.

[0061] Please refer toFigure 2 The adjustment process of the brightness adjustment module includes:

[0062] S1: First, the environmental data acquisition module and the image acquisition module are used to respectively collect environmental information, road information and crowd information;

[0063] S2: The data processing unit is used to calculate the initial lighting demand in different street lamp lighting areas in combination with the road image information collected by the image acquisition module;

[0064] S3: The data processing unit is used to analyze in combination with the preset initial lighting demand threshold, and to determine whether the initial brightness of different street lamps needs to be adjusted according to the analysis result;

[0065] S4: When it is determined that the initial brightness of the street lamp needs to be adjusted, the initial brightness adjustment unit is used to adjust the initial brightness of different street lamps in combination with the initial lighting demand in different street lamp lighting areas and the environmental information;

[0066] S5: The dynamic adjustment module is used to dynamically adjust the light brightness of different street lamps at each time point in combination with the crowd image information collected by the image acquisition module, the environmental information and the initial brightness of different street lamps;

[0067] Through the above technical solution, the adjustment process of the brightness adjustment module is provided. First, the environmental data acquisition module and the image acquisition module are used to respectively collect environmental information, road information and crowd information. Then, the data processing unit is used to calculate the initial lighting demand in different street lamp lighting areas in combination with the road image information collected by the image acquisition module. After that, the data processing unit is used to analyze in combination with the preset initial lighting demand threshold, and to determine whether the initial brightness of different street lamps needs to be adjusted according to the analysis result. When it is determined that the initial brightness of the street lamp needs to be adjusted, the initial brightness adjustment unit is used to adjust the initial brightness of different street lamps in combination with the initial lighting demand in different street lamp lighting areas and the environmental information. After the initial brightness adjustment is completed, the dynamic adjustment module is used to dynamically adjust the light brightness of different street lamps at each time point in combination with the crowd image information collected by the image acquisition module, the environmental information and the initial brightness of different street lamps.

[0068] Through such a setting, the initial lighting demand in the street lamp lighting area can be calculated by combining the road image information in different lighting areas. This data can reflect the demand value of the lighting brightness under different road conditions. Then, whether the initial lighting brightness in different areas needs to be adjusted can be determined by analyzing this data, and the initial brightness adjustment unit is used to adjust in time. This can not only achieve energy saving, but also eliminate the safety hazards caused by energy saving.

[0069] Then, the dynamic adjustment module combines the traffic flow image information, the environmental information and the initial brightness of different street lamps collected by the image acquisition module to dynamically adjust the light brightness of different street lamps at each time point, so as to improve the use efficiency of the street lamps and save energy, thereby ensuring sufficient illumination and realizing energy saving.

[0070] The information collected in S1 includes:

[0071] The environmental information includes the rainfall amount and the snowfall amount.

[0072] The road information includes the damaged area, the pothole area, the water accumulation area and the snow accumulation area in different lighting areas.

[0073] The traffic flow information includes the number of passing people and the crowd density in different lighting areas at different time points.

[0074] Through the above technical solution, the embodiment provides the information collected in S1, which includes the environmental information such as the rainfall amount and the snowfall amount, and the road information such as the damaged area, the pothole area, the water accumulation area and the snow accumulation area in different lighting areas. The data can provide diversified data support for the adjustment of the street lamp illumination brightness in abnormal conditions, so that the initial illumination brightness of the street lamp has sufficient illumination effect in abnormal conditions, thereby improving the safety of the students. The traffic flow information can provide accurate data for the subsequent dynamic adjustment of the street lamp illumination brightness, thereby ensuring the normal operation of the dynamic adjustment, improving the use efficiency of the street lamp and saving energy.

[0075] The processing process of the data processing unit includes:

[0076] The initial illumination demand amount in the i-th street lamp lighting area is calculated by the formula

[0077] wherein, is the damaged area in the i-th street lamp lighting area, is the pothole area in the i-th street lamp lighting area, is the road obstacle area position influence function, which is set according to experience fitting, is the total illumination area of the i-th street lamp lighting area, is the water accumulation area of the i-th street lamp lighting area, is the snow accumulation area of the i-th street lamp lighting area, is a judgment function, when , let , when , let , ​​is a road material influence coefficient, which is set according to experience fitting, and 2 is a first weight coefficient, which is set according to experience fitting;

[0078] Through the technical solution, the embodiment provides an initial lighting demand in the i th road lighting area , which is calculated by the formula Obviously, when there is a water accumulation area and a snow accumulation area in the i th road lighting area, and the damage area, the pothole area, the water accumulation area and the snow accumulation area in the i th road lighting area are larger, it indicates that the road condition of the i th road lighting area is worse, and then in order to ensure the safety of the students when passing through the area, the initial lighting demand in the i th road lighting area is larger, on the contrary, when there is no water accumulation area and snow accumulation area in the i th road lighting area, and the damage area and the pothole area in the i th road lighting area are smaller or non-existent, it indicates that the road condition of the i th road lighting area is better, and then the initial lighting demand in the i th road lighting area is smaller. Through the calculation method, the initial lighting demand in the i th road lighting area calculated can reflect the road condition in the i th road lighting area, thereby providing accurate data for subsequent judgment of whether the initial lighting brightness needs to be adjusted, and thereby improving the accuracy and reliability of the judgment result.

[0079] The processing process of the data processing unit further includes:

[0080] By comparing the initial lighting demand in all road lighting areas with preset initial lighting demand thresholds respectively;

[0081] If , the system judges that the initial lighting demand in the area is high, and needs to adjust the initial lighting brightness of the road lamp in the lighting area;

[0082] If , the system judges that the initial lighting demand in the area is low, and does not need to adjust the initial lighting brightness of the road lamp in the lighting area, and illuminates according to the lowest power consumption;

[0083] Through the technical solution, the embodiment compares the initial lighting demand in all road lighting areas with preset initial lighting demand thresholds respectively.By comparing the results, we can accurately determine the initial lighting demand in the i-th street light illumination area. When the initial lighting demand in a street light illumination area is high, it means that the road conditions in that area are poor. In this case, we need to adjust the initial lighting brightness in that area in time to avoid students falling or spraining their ankles due to low light brightness. This ensures energy conservation while protecting the personal safety of students.

[0084] It should be noted that the above-mentioned preset initial lighting demand threshold The settings can be fitted based on empirical data.

[0085] The adjustment process of the initial brightness adjustment unit includes:

[0086] Mark the areas to be illuminated by the streetlights that require the initial illumination brightness;

[0087] And through the formula Calculate the initial illumination brightness of the i-th street light illumination area after adjustment. ;

[0088] in, The preset low-power initial lighting brightness, This is the first adjustment coefficient lookup table function, based on empirical data. The extent to which the range of numerical values ​​affects the initial lighting brightness is obtained based on test data. The intensity of external light when the streetlights are turned on. The preset external light intensity, The error influence coefficient is set based on empirical fitting.

[0089] Through the above technical solution, this embodiment provides the initial illumination brightness of the i-th street light illumination area after adjustment. By combining the initial lighting demand in the i-th street light illumination area The preset low-power initial lighting brightness and the external light intensity when the streetlights are turned on can improve the accuracy and reliability of the adjusted initial lighting brightness. This ensures that while reducing energy consumption, trainees can also accurately observe the road conditions in different lighting areas to eliminate safety hazards. Furthermore, by adjusting the initial lighting brightness in different areas, trainees can judge which lighting areas may have poor road conditions based on the different lighting brightness, thus serving as a warning and further ensuring the personal safety of trainees.

[0090] The adjustment process of the dynamic adjustment module includes:

[0091] Through formula The lighting brightness of the i-th lighting area at the a-th time point is calculated ;

[0092] Wherein, a is the data collection at a fixed time interval after the street lamp is turned on, is the number of passing people in the i-th lighting area at the a-th time point, is the preset number of people, is the crowd density in the i-th lighting area at the a-th time point, is the preset density, is the rainfall amount at the a-th time point, is the standard value of , which can be set according to the allowable error in the empirical data, is the snowfall amount at the a-th time point, is the standard value of , which can be set according to the allowable error in the empirical data, and 2 is the second weight coefficient, which is set according to empirical fitting, is the second adjustment coefficient table function, which is based on the empirical data The value range of the numerical value affects the degree of influence of the lighting brightness at different time points based on test data;

[0093] Through the above technical solution, the lighting brightness of the i-th lighting area at the a-th time point can be calculated by the formula By combining the number of passing people and the crowd density in the i-th lighting area at the a-th time point, as well as the diversified data such as irregular weather conditions such as rainfall and snowfall, the accuracy of the lighting brightness calculation result at the a-th time point in the i-th lighting area can be improved, thereby improving the accuracy of the brightness adjustment. And since this data is calculated based on the initial lighting brightness adjusted by the i-th street lamp lighting area, the accuracy and reliability of the lighting brightness can be further improved, which not only can adapt to different environmental conditions, but also can adapt to different lighting areas of the road conditions, thereby improving the use efficiency of the street lamp and achieving the effect of energy saving.

[0094] The adjustment process of the dynamic adjustment module further includes:

[0095] The fixed time interval of one data collection is less than the duration after the street lamp lighting brightness adjustment is completed, and the duration is reset after the lighting brightness of the street lamp is changed at each time point;

[0096] By such setting, it can be ensured that the street lamp will not appear frequent flickering, thereby improving its service life.

[0097] The above has been described in detail one embodiment of the present application, but the content is only the preferred embodiment of the present application, cannot be considered for limiting the scope of the present application. Any equivalent changes and improvements made in the scope of the present application, should still belong to the scope of the present application.

Claims

1. The intelligent campus power saving management system based on the Internet of Things, characterized in that, The system comprises: An environmental data acquisition module for acquiring environmental information at different time points in different street light illumination areas; An image acquisition module comprising a camera unit and an identification unit, the camera unit being configured to capture road images and people flow images in different street light illumination areas; The identification unit is configured to identify the images captured by the camera unit and extract the required road information and people flow information; A brightness adjustment module comprising a data processing unit, an initial brightness adjustment unit and a dynamic adjustment unit, the data processing unit being configured to calculate the initial illumination demand in different street light illumination areas in combination with the road image information acquired by the image acquisition module, and determine whether the initial brightness of different street lights needs to be adjusted in combination with the preset initial illumination demand threshold; The initial brightness adjustment unit is configured to adjust the initial brightness of the street lights in combination with the initial illumination demand and environmental information in different street light illumination areas when it is determined that the initial brightness of the street lights needs to be adjusted; The dynamic adjustment unit is configured to dynamically adjust the light brightness of the street lights at different time points in combination with the people flow image information and environmental information acquired by the image acquisition module; The processing process of the data processing unit comprises: The initial lighting demand amount in the i-th streetlight lighting area is calculated by the formula ;​ wherein, is the damaged area within the i-th streetlight lighting area, is the pothole area within the i-th streetlight lighting area, is the road obstacle area position influence function, which is empirically fitted, is the total lighting area of the i-th streetlight lighting area, is the waterlogging area of the i-th streetlight lighting area, is the snow accumulation area of the i-th streetlight lighting area, is the judgment function, when , , , , is the road material influence coefficient, which is empirically fitted, and 2 is the first weight coefficient; The adjustment process of the initial brightness adjustment unit comprises: annotating the street light illumination area requiring the initial illumination brightness of the street light; And through the formula The adjusted initial lighting brightness of the i-th street light lighting area is calculated ; wherein, is a preset low-power initial lighting brightness, is a first adjustment coefficient table function, which is determined according to empirical data in the influence degree of the value range of the numerical value on the initial lighting brightness is obtained based on test data, is an external light intensity when the street lamp is turned on, is a preset external light intensity, is an error influence coefficient, which is determined according to empirical fitting; The adjustment process of the dynamic adjustment unit comprises: The illumination brightness at the a-th time point in the i-th illumination area is calculated by the formula ; and ; Where 'a' represents a data collection at fixed time intervals after the streetlights are turned on. Let be the number of people passing by in the i-th illuminated area at time a. For the preset number of people, Let be the population density at time point a within the i-th lighting area. For the preset density, Let a be the amount of rainfall at time point a. for The standard value, Let a be the amount of snowfall at time point a. for The standard value, and 2 is the second weighting coefficient. This is the function for the second adjustment coefficient lookup table, based on empirical data. The influence of the range of numerical values ​​on the lighting brightness at different time points was obtained based on test data. 2.The smart campus power saving management system based on Internet of Things according to claim 1, characterized in that, The adjustment process of the brightness adjustment module comprises: S1: First, the environmental data acquisition module and the image acquisition module are used to acquire environmental information, road information and people flow information, respectively; S2: The data processing unit calculates the initial illumination demand in different street light illumination areas in combination with the road image information acquired by the image acquisition module; S3: The data processing unit analyzes in combination with the preset initial illumination demand threshold, and determines whether the initial brightness of different street lights needs to be adjusted according to the analysis result; S4: When it is determined that the initial brightness of the street lights needs to be adjusted, the initial brightness of different street lights is adjusted by the initial brightness adjustment unit in combination with the initial illumination demand and environmental information in different street light illumination areas; S5: The dynamic adjustment unit dynamically adjusts the light brightness of different street lights at different time points in combination with the people flow image information, environmental information and initial brightness of different street lights acquired by the image acquisition module. 3.The smart campus power saving management system based on Internet of Things according to claim 2, characterized in that, The information acquired in S1 comprises: The environmental information includes the rainfall amount and the snowfall amount; The road information includes the damaged area, the pothole area, the water accumulation area and the snow accumulation area in different illumination areas; The people flow information includes the number of people passing by and the crowd density in different illumination areas at different time points. 4.The smart campus power saving management system based on Internet of Things according to claim 3, characterized in that, The processing process of the data processing unit further comprises: by comparing the initial lighting demand amount within all the lighting areas of the street light respectively with preset initial lighting demand amount thresholds respectively If , the system judges that the initial lighting demand in the area is high, and needs to adjust the initial lighting brightness of the street lamp in the lighting area; If , the system judges that the initial lighting demand in the area is low, and the initial lighting brightness of the street lamp in the lighting area does not need to be adjusted, and the lighting is performed according to the minimum power consumption. 5.The smart campus power saving management system based on Internet of Things according to claim 4, characterized in that, The adjustment process of the dynamic adjustment unit further comprises: The fixed time interval of one data acquisition is less than the duration after the completion of the street light illumination brightness adjustment, and the duration is reset after the illumination brightness of the street light at each time point is changed.

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