Intelligent campus power utilization energy-saving management system based on Internet of Things

Abstract

The invention relates to the technical field of campus energy saving, and particularly discloses an intelligent campus power utilization energy-saving management system based on the Internet of Things, and the system comprises an environment data collection module which is used for collecting environment information at different time points in different street lamp illumination regions; the image acquisition module comprises a camera shooting unit and an identification unit, initial illumination demands in different street lamp illumination areas can be calculated by combining the road image information acquired by the image acquisition module, initial illumination brightness of different areas can be adjusted according to the data, and due to the fact that the data is combined with the road information of different areas, the brightness of the street lamp can be adjusted. Therefore, the adjusted illumination brightness can better adapt to the road conditions of different areas, and students can see the damaged road surface clearly even if the number of people is small, so that the situation that the students fall down or sprain when stepping on the damaged road surface area due to low light brightness is avoided. Energy saving is achieved, and meanwhile potential safety hazards caused by energy saving can be eliminated.

Description

Technical Field

[0001] The present invention relates to the technical field of campus energy conservation, and in particular to an intelligent campus electricity energy conservation management system based on the Internet of Things. Background Art

[0002] The campus electricity energy-saving management system conducts centralized dynamic monitoring of the electricity transmission, distribution and consumption links within the school through real-time monitoring, data analysis, intelligent control and other means to improve and optimize the monitoring and management of electricity balance, while achieving the goal of energy conservation and consumption reduction.

[0003] In the campus electricity energy-saving management system, campus street lamp energy saving is an important issue. It is not only related to energy conservation, but also to the comfort and safety of the campus environment. In order to improve the efficiency of street lamps and save energy, it is usually installed by installing light sensors and infrared sensors. The brightness of street lamps is automatically adjusted according to the surrounding light and traffic conditions to achieve energy saving effects.

[0004] Traditional street lamp energy-saving measures will set the brightness of street lamps to the lowest level to achieve energy saving when there are fewer people. However, if the road in the illuminated section is damaged or there are special circumstances, when a small number of students pass through the area, the brightness of the street lamps will be set to the lowest level due to the low number of people. The low brightness of the light may cause students to step on the damaged area of ​​the road and fall or sprain their feet. In this case, although energy saving can be effectively achieved, there are safety hazards. Summary of the invention

[0005] The purpose of the present invention is to provide an intelligent campus electricity energy-saving management system based on the Internet of Things to solve the following technical problems: How to achieve energy conservation on campus and eliminate the safety hazards caused by energy conservation.

[0006] The purpose of the present invention can be achieved through the following technical solutions: An intelligent campus electricity energy-saving management system based on the Internet of Things, the system comprising: Environmental data collection module, used to collect environmental information at different time points in different street lighting areas; An image acquisition module, comprising a camera unit and a recognition unit, wherein the camera unit is used to capture road images and pedestrian flow images in different street lamp lighting areas; The recognition unit is used to recognize the image taken by the camera unit and extract the required road information and pedestrian flow information; The brightness adjustment module includes a data processing unit, an initial brightness adjustment unit and a dynamic adjustment unit, wherein 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 a preset initial lighting demand threshold; The initial brightness adjustment unit is used to adjust the initial brightness of the street lamp in combination with the initial lighting demand and environmental information in different street lamp lighting areas when it is determined that the initial brightness of the street lamp needs to be adjusted; The dynamic adjustment unit is used to dynamically adjust the light brightness of the street lamp at different time points in combination with the pedestrian flow image information and environmental information collected by the image collection module.

[0007] Furthermore, the adjustment process of the brightness adjustment module includes: S1: First, environmental information, road information and pedestrian flow information are collected through the environmental data collection module and the image collection module respectively; S2: Calculate the initial lighting demand in different street lamp lighting areas by combining the road image information collected by the data processing unit with the image acquisition module; S3: Analyze the preset initial lighting demand threshold value through the data processing unit, and determine whether it is necessary to adjust the initial brightness of different street lamps according to the analysis result; S4: When it is determined that the initial brightness of the street lamp needs to be adjusted, the initial brightness of different street lamps is adjusted by the initial brightness adjustment unit according to the initial lighting demand and environmental information in the lighting areas of different street lamps; S5: Dynamically adjust the light brightness of different street lamps at various time points by combining the pedestrian flow image information, environmental information and initial brightness of different street lamps collected by the image collection module through the dynamic adjustment module.

[0008] Furthermore, the information collected in S1 includes: Environmental information, including rainfall and snowfall amounts; Road information, including damaged areas, potholes, waterlogged areas, and snow accumulation areas in different lighting zones; Crowd flow information, including the number of passers-by and crowd density at different lighting areas at different times.

[0009] Furthermore, the processing process of the data processing unit includes: By formula Calculate the initial lighting demand in the i-th street lighting area ; in, is the damaged area within the lighting area of ​​the ith street lamp, is the pothole area within the i-th street lamp lighting area, is the influence function of the road obstacle area and position, which is set according to empirical fitting. is the total lighting area of ​​the ith street lamp lighting area, is the water accumulation area in the ith street lamp lighting area, is the snow area in the ith street lamp lighting area, is the judgment function, when season ,when season , is the influence coefficient of road material, which is set based on empirical fitting. and 2 is the first weight coefficient.

[0010] Furthermore, the processing process of the data processing unit also includes: By allocating the initial lighting demand in the lighting area of ​​the street lamp The preset initial lighting demand threshold Make a comparison; like , the system determines that the initial lighting demand in the area is high and needs to adjust the initial lighting brightness of the street lamps in the lighting area; like The system determines that the initial lighting demand in the area is low, and there is no need to adjust the initial lighting brightness of the street lamps in the lighting area. The lighting is performed according to the lowest power consumption.

[0011] Furthermore, the adjustment process of the initial brightness adjustment unit includes: Mark the street lamp lighting area that requires the initial lighting brightness of the street lamp; And through the formula Calculate the initial lighting brightness of the i-th street lighting area after adjustment ; in, The preset low power initial lighting brightness, is the first adjustment coefficient comparison table function, because according to the empirical data The influence of the range of values ​​on the initial lighting brightness is based on the test data. is the external light intensity when the street light is turned on, is the preset external light intensity, is the error influence coefficient, which is set according to empirical fitting.

[0012] Furthermore, the adjustment process of the dynamic adjustment module includes: By formula Calculate the lighting brightness at the ath time point in the i-th lighting area ; Among them, a is the data collection at a fixed time interval after the street light is turned on. is the number of passers-by at the ath time point in the i-th lighting area, For the preset number of people, is the crowd density at the ath time point in the ith lighting area, is the preset density, is the rainfall at the ath time point, for The standard value of is the amount of snowfall at the ath time point, for The standard value of and 2 is the second weight coefficient, is the second adjustment coefficient comparison table function, because according to the empirical data The influence of the range of values ​​on the lighting brightness at different time points is obtained based on test data.

[0013] Furthermore, the adjustment process of the dynamic adjustment module also includes: 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 street lamp lighting brightness is changed at each time point.

[0014] Beneficial effects of the present invention: (1) The present invention can calculate the initial lighting demand in different street lamp lighting areas by combining the road image information collected by the image acquisition module, and adjust the initial lighting brightness of different areas according to the data. Since the data is combined with the road information of different areas, the adjusted lighting brightness can be more suitable for the road conditions in different areas, ensuring that trainees can see the damaged road surface clearly even when there are few people, thereby avoiding the situation where trainees step on the damaged road surface area and fall or sprain due to low light brightness. Energy saving can be achieved while eliminating the safety hazards caused by energy saving.

[0015] (2) The present invention 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 lighting brightness for different road conditions. Then, by analyzing the data, it can be judged whether the initial lighting brightness in different areas needs to be adjusted, and the initial brightness adjustment unit can be used to adjust it in time, which can not only save electricity, but also eliminate the safety hazards caused by energy saving.

[0016] (3) The present invention calculates the initial lighting demand in all street lamp lighting areas. The preset initial lighting demand threshold Based on the analysis and comparison results, an accurate judgment can be made on the initial lighting demand in the ith street lamp lighting area. When it is judged that the initial lighting demand in a certain street lamp lighting area is high, it means that the road conditions in this area are poor, and it is necessary to adjust the initial lighting brightness of this area in time to avoid the situation where trainees step on damaged areas of the road due to low light brightness and fall or sprain, thereby ensuring energy saving in electricity use and providing protection for the personal safety of trainees.

[0017] (4) The present invention combines 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 lights are turned on can improve the accuracy and reliability of the adjusted initial lighting brightness, thereby ensuring that while reducing energy consumption, students can also accurately observe the road conditions in different lighting areas to eliminate safety hazards. By adjusting the initial lighting brightness in different areas, students can judge which lighting areas may have poor road conditions based on the different lighting brightness, thereby serving as a warning and further ensuring the personal safety of students.

[0018] (5) The present invention can improve the accuracy of the calculation result of the lighting brightness at the a-th time point in the ith lighting area by combining diversified data such as the number of passers-by and the crowd density at the a-th time point in the ith lighting area, as well as unconventional weather conditions such as rain and snow, thereby improving the accuracy of brightness adjustment. Moreover, since the data is calculated based on the initial lighting brightness after adjustment of the ith street lamp lighting area, the accuracy and reliability of the lighting brightness can be further improved. It can not only adapt to different environmental conditions, but also adapt to road conditions in different lighting areas, thereby improving the utilization efficiency of street lamps and achieving the effect of saving energy. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] The present invention will be further described below in conjunction with the accompanying drawings.

[0020] Figure 1 It is a schematic block diagram of the intelligent campus electricity energy-saving management system based on the Internet of Things in the present invention; Figure 2 It is a flow chart of the adjustment process of the brightness adjustment module in the present invention. DETAILED DESCRIPTION

[0021] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0022] See also Figure 1 As shown, in one embodiment, the present application provides an intelligent campus electricity energy-saving management system based on the Internet of Things, the system comprising: Environmental data collection module, used to collect environmental information at different time points in different street lighting areas; An image acquisition module, comprising a camera unit and a recognition unit, wherein the camera unit is used to capture road images and pedestrian flow images in different street lamp lighting areas; The recognition unit is used to recognize the image taken by the camera unit and extract the required road information and pedestrian flow information; The brightness adjustment module includes a data processing unit, an initial brightness adjustment unit and a dynamic adjustment unit, wherein 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 a preset initial lighting demand threshold; The initial brightness adjustment unit is used to adjust the initial brightness of the street lamp in combination with the initial lighting demand and environmental information in different street lamp lighting areas when it is determined that the initial brightness of the street lamp needs to be adjusted; The dynamic adjustment unit is used to dynamically adjust the light brightness of the street lamp at different time points in combination with the pedestrian flow image information and environmental information collected by the image acquisition module; Through the above technical scheme, this embodiment provides an environmental data acquisition module for collecting environmental information at different time points in different street lamp lighting areas, and provides a camera unit for capturing road images and pedestrian flow images in different street lamp lighting areas, and an identification unit for identifying the images captured by the camera unit, which can extract the required road information and pedestrian flow information. When the system determines that the street lamp needs to be turned on, the data processing unit will first calculate the initial lighting demand in different street lamp lighting areas in combination with the road image information collected by the image acquisition module, and determine whether it is necessary to adjust the initial brightness of different street lamps based on 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 of the street lamp is adjusted by the initial brightness adjustment unit in combination with the initial lighting demand and environmental information in different street lamp lighting areas, thereby achieving control of the minimum brightness. After that, the street lamp brightness at different time points can be dynamically adjusted by relying on the dynamic adjustment unit in combination with the pedestrian flow image information and environmental information collected by the image acquisition module to achieve energy saving effects. By combining 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 is combined with the road information of different areas, the adjusted lighting brightness can be more suitable for the road conditions in different areas, ensuring that trainees can see the damaged road surface clearly even when there are few people, thereby avoiding the situation where trainees step on the damaged road area due to low light brightness and fall or sprain, achieving energy saving and eliminating the safety hazards caused by energy saving; It should be noted that the recognition module is a trained neural network model, which is a prior art and will not be described in detail here.

[0023] See also Figure 2 As shown, the adjustment process of the brightness adjustment module includes: S1: First, environmental information, road information and pedestrian flow information are collected through the environmental data collection module and the image collection module respectively; S2: Calculate the initial lighting demand in different street lamp lighting areas by combining the road image information collected by the data processing unit with the image acquisition module; S3: Analyze the preset initial lighting demand threshold value through the data processing unit, and determine whether it is necessary to adjust the initial brightness of different street lamps according to the analysis result; S4: When it is determined that the initial brightness of the street lamp needs to be adjusted, the initial brightness of different street lamps is adjusted by the initial brightness adjustment unit according to the initial lighting demand and environmental information in the lighting areas of different street lamps; S5: dynamically adjusting the light brightness of different street lamps at various time points by combining the pedestrian flow image information, environmental information and initial brightness of different street lamps collected by the image acquisition module through the dynamic adjustment module; Through the above technical scheme, this embodiment provides an adjustment process of the brightness adjustment module, firstly, the environmental information, road information and pedestrian flow information are respectively collected by the environmental data acquisition module and the image acquisition module, and then 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 acquisition module, and then the data processing unit is analyzed in combination with the preset initial lighting demand threshold, and it is judged whether the initial brightness of different street lamps needs to be adjusted according to the analysis result. When it is judged that the initial brightness of the street lamp needs to be adjusted, the initial brightness of different street lamps is adjusted by the initial brightness adjustment unit based on the initial lighting demand and environmental information in different street lamp lighting areas. After the initial brightness adjustment is completed, the light brightness of different street lamps at various time points can be dynamically adjusted by the dynamic adjustment module in combination with the pedestrian flow image information, environmental information and the initial brightness of different street lamps collected by the image acquisition module; By such a setting, by combining the road image information in different lighting areas, the initial lighting demand in the street lamp lighting area can be calculated, and the data can reflect the demand value of lighting brightness for different road conditions. After that, by analyzing the data, it can be judged whether the initial lighting brightness in different areas needs to be adjusted, and the initial brightness adjustment unit can be adjusted in time, which can not only achieve energy saving in electricity consumption, but also eliminate the safety hazards caused by energy saving; Afterwards, the dynamic adjustment module is combined with the pedestrian flow image information, environmental information and initial brightness of different street lamps collected by the image acquisition module to dynamically adjust the light brightness of different street lamps at various time points, which can improve the efficiency of street lamp use and save energy, thereby ensuring sufficient lighting and achieving energy saving.

[0024] The information collected in S1 includes: Environmental information, including rainfall and snowfall amounts; Road information, including damaged areas, potholes, waterlogged areas, and snow accumulation areas in different lighting zones; Crowd flow information, including the number of people passing by at different times in different lighting areas and crowd density; Through the above technical scheme, this embodiment provides the information collected in S1, including environmental information such as rainfall and snowfall, and road information such as damaged area, pothole area, water accumulation area and snow accumulation area in different lighting areas. The data can provide diversified data support for the adjustment of street lamp lighting brightness under unconventional circumstances, so that the initial lighting brightness of the street lamp can have sufficient lighting effect under unconventional circumstances, thereby improving the safety of students, and the flow of people information can provide accurate data for the subsequent dynamic adjustment of the street lamp lighting brightness, thereby ensuring the normal progress of the dynamic adjustment, thereby improving the utilization efficiency of the street lamp and saving energy.

[0025] The processing process of the data processing unit includes: By formula Calculate the initial lighting demand in the i-th street lighting area ; in, is the damaged area within the lighting area of ​​the ith street lamp, is the pothole area within the i-th street lamp lighting area, is the influence function of the road obstacle area and position, which is set according to empirical fitting. is the total lighting area of ​​the ith street lamp lighting area, is the water accumulation area in the ith street lamp lighting area, is the snow area in the ith street lamp lighting area, is the judgment function, when season ,when season , is the influence coefficient of road material, which is set based on empirical fitting. and 2 is the first weight coefficient, which is set according to empirical fitting; Through the above technical solution, this embodiment provides the initial lighting demand in the i-th street lamp lighting area , can be obtained by formula It is calculated that, obviously, when there is water accumulation area and snow accumulation area in the i-th street lamp lighting area, and the larger the damaged area, pothole area, water accumulation area and snow accumulation area in the i-th street lamp lighting area, the worse the road condition in the i-th street lamp lighting area is. In order to ensure the safety of trainees when passing through the area, the initial lighting demand in the i-th street lamp lighting area is greater. On the contrary, there is no water accumulation area and snow accumulation area in the i-th street lamp lighting area, and the smaller or no damaged area and pothole area in the i-th street lamp lighting area are, the better the road condition in the i-th street lamp lighting area is, and the smaller the initial lighting demand in the i-th street lamp lighting area is. Through this calculation method, the initial lighting demand in the i-th street lamp lighting area calculated can reflect the road condition in the i-th street lamp lighting area, thereby providing accurate data for subsequent judgment of whether the initial lighting brightness needs to be adjusted, thereby improving the accuracy and reliability of the judgment result.

[0026] The processing process of the data processing unit also includes: By allocating the initial lighting demand in the lighting area of ​​the street lamp The preset initial lighting demand threshold Make a comparison; like , the system determines that the initial lighting demand in the area is high and needs to adjust the initial lighting brightness of the street lamps in the lighting area; like , the system determines that the initial lighting demand in the area is low, and there is no need to adjust the initial lighting brightness of the street lamps in the lighting area, and lighting is performed according to the lowest power consumption; Through the above technical solution, this embodiment calculates the initial lighting demand in all street lamp lighting areas. The preset initial lighting demand threshold Based on the analysis and comparison results, an accurate judgment can be made on the initial lighting demand in the i-th street lamp lighting area. When it is judged that the initial lighting demand in a street lamp lighting area is high, it means that the road condition in the area is poor, and it is necessary to adjust the initial lighting brightness of the area in time, so as to avoid the situation where the trainees step on the damaged road area due to low light brightness and fall or sprain, thereby ensuring energy saving and personal safety of the trainees. It should be noted that the above preset initial lighting demand threshold The setting can be fitted according to empirical data.

[0027] The adjustment process of the initial brightness adjustment unit includes: Mark the street lamp lighting area that requires the initial lighting brightness of the street lamp; And through the formula Calculate the initial lighting brightness of the ith street lighting area after adjustment ; in, The preset low-power initial lighting brightness, is the first adjustment coefficient comparison table function, because according to the empirical data The influence of the range of values ​​on the initial lighting brightness is based on the test data. is the external light intensity when the street light is turned on, is the preset external light intensity, is the error influence coefficient, which is set according to empirical fitting; Through the above technical solution, this embodiment provides the initial lighting brightness of the i-th street lamp lighting area after adjustment. , by combining the initial lighting demand in the i-th street lighting area , the preset low-power initial lighting brightness and the external light intensity when the street lights are turned on can improve the accuracy and reliability of the adjusted initial lighting brightness, thereby ensuring that while reducing energy consumption, students can also accurately observe the road conditions in different lighting areas to eliminate safety hazards. By adjusting the initial lighting brightness in different areas, students can judge which lighting areas may have poor road conditions based on the different lighting brightness, thereby serving as a warning and further ensuring the personal safety of students.

[0028] The adjustment process of the dynamic adjustment module includes: By formula Calculate the lighting brightness at the ath time point in the i-th lighting area ; Among them, a is the data collection at a fixed time interval after the street light is turned on. is the number of passers-by at the ath time point in the i-th lighting area, For the preset number of people, is the crowd density at the ath time point in the ith lighting area, is the preset density, is the rainfall at the ath time point, for The standard value can be selected and set according to the allowable error in the empirical data. is the amount of snowfall at the ath time point, for The standard value can be selected and 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 comparison table function, because according to the empirical data The influence of the range of values ​​on the lighting brightness at different time points is obtained based on test data; Through the above technical solution, this embodiment provides the lighting brightness at the ath time point in the i-th lighting area , can be obtained by formula It is calculated that by combining diversified data such as the number of passers-by and crowd density at the a-th time point in the ith lighting area, as well as unconventional weather conditions such as rain and snowfall, the accuracy of the lighting brightness calculation result at the a-th time point in the ith lighting area can be improved, thereby improving the accuracy of the brightness adjustment. Moreover, since the data is calculated based on the initial lighting brightness after adjustment of the ith 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 road conditions in different lighting areas, thereby improving the utilization efficiency of street lamps and saving energy.

[0029] The adjustment process of the dynamic adjustment module also includes: The fixed time interval of a data collection is less than the duration after the street lamp lighting brightness adjustment is completed, and the duration is reset after the street lamp lighting brightness is changed at each time point; By setting it in this way, it can be ensured that the street lamp will not flicker frequently, thereby increasing its service life.

[0030] The above is a detailed description of an embodiment of the present invention, but the content is only a preferred embodiment of the present invention and cannot be considered to limit the scope of implementation of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. The intelligent campus electricity energy-saving management system based on the Internet of Things is characterized by: The system comprises: Environmental data collection module, used to collect environmental information at different time points in different street lighting areas; An image acquisition module, comprising a camera unit and a recognition unit, wherein the camera unit is used to capture road images and pedestrian flow images in different street lamp lighting areas; The recognition unit is used to recognize the image taken by the camera unit and extract the required road information and pedestrian flow information; The brightness adjustment module includes a data processing unit, an initial brightness adjustment unit and a dynamic adjustment unit, wherein 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 a preset initial lighting demand threshold; The initial brightness adjustment unit is used to adjust the initial brightness of the street lamp in combination with the initial lighting demand and environmental information in different street lamp lighting areas when it is determined that the initial brightness of the street lamp needs to be adjusted; The dynamic adjustment unit is used to dynamically adjust the light brightness of the street lamp at different time points in combination with the pedestrian flow image information and environmental information collected by the image collection module.

2. According to the Internet of Things-based intelligent campus electricity energy-saving management system of claim 1, it is characterized in that: The adjustment process of the brightness adjustment module includes: S1: First, environmental information, road information and pedestrian flow information are collected through the environmental data collection module and the image collection module respectively; S2: Calculate the initial lighting demand in different street lamp lighting areas by combining the road image information collected by the data processing unit with the image acquisition module; S3: Analyze the preset initial lighting demand threshold value through the data processing unit, and determine whether it is necessary to adjust the initial brightness of different street lamps according to the analysis result; S4: When it is determined that the initial brightness of the street lamp needs to be adjusted, the initial brightness of different street lamps is adjusted by the initial brightness adjustment unit according to the initial lighting demand and environmental information in the lighting areas of different street lamps; S5: Dynamically adjust the light brightness of different street lamps at various time points by combining the pedestrian flow image information, environmental information and initial brightness of different street lamps collected by the image collection module through the dynamic adjustment module.

3. The intelligent campus electricity energy-saving management system based on the Internet of Things according to claim 2 is characterized in that: The information collected in S1 includes: Environmental information, including rainfall and snowfall amounts; Road information, including damaged areas, potholes, waterlogged areas, and snow accumulation areas in different lighting zones; Crowd flow information, including the number of passers-by and crowd density at different lighting areas at different times.

4. The intelligent campus electricity energy-saving management system based on the Internet of Things according to claim 2 is characterized in that: The processing process of the data processing unit includes: By formula Calculate the initial lighting demand in the i-th street lighting area ; in, is the damaged area within the lighting area of ​​the ith street lamp, is the pothole area within the i-th street lamp lighting area, is the influence function of the road obstacle area and position, which is set according to empirical fitting. is the total lighting area of ​​the ith street lamp lighting area, is the water accumulation area in the ith street lamp lighting area, is the snow area in the ith street lamp lighting area, is the judgment function, when season ,when season , is the road material influence coefficient, which is set based on empirical fitting. and 2 is the first weight coefficient.

5. The intelligent campus electricity energy-saving management system based on the Internet of Things according to claim 4 is characterized in that: The processing process of the data processing unit also includes: By allocating the initial lighting demand in the lighting area of ​​the street lamp The preset initial lighting demand threshold Make a comparison; like , the system determines that the initial lighting demand in the area is high and needs to adjust the initial lighting brightness of the street lamps in the lighting area; like The system determines that the initial lighting demand in the area is low, and there is no need to adjust the initial lighting brightness of the street lamps in the lighting area. The lighting is performed according to the lowest power consumption.

6. The intelligent campus electricity energy-saving management system based on the Internet of Things according to claim 5 is characterized in that: The adjustment process of the initial brightness adjustment unit includes: Mark the street lamp lighting area that requires the initial lighting brightness of the street lamp; And through the formula Calculate the initial lighting brightness of the ith street lighting area after adjustment ; in, The preset low power initial lighting brightness, is the first adjustment coefficient comparison table function, because according to the empirical data The influence of the range of values ​​on the initial lighting brightness is based on the test data. is the external light intensity when the street light is turned on, is the preset external light intensity, is the error influence coefficient, which is set according to empirical fitting.

7. The intelligent campus electricity energy-saving management system based on the Internet of Things according to claim 6 is characterized in that: The adjustment process of the dynamic adjustment module includes: By formula Calculate the lighting brightness at the ath time point in the i-th lighting area ; Among them, a is the data collection at a fixed time interval after the street light is turned on. is the number of passers-by at the ath time point in the i-th lighting area, For the preset number of people, is the crowd density at the ath time point in the ith lighting area, is the preset density, is the rainfall at the ath time point, for The standard value of is the amount of snowfall at the ath time point, for The standard value of and 2 is the second weight coefficient, is the second adjustment coefficient comparison table function, because according to the empirical data The influence of the range of values ​​on the lighting brightness at different time points is obtained based on test data.

8. The intelligent campus electricity energy-saving management system based on the Internet of Things according to claim 7 is characterized in that: The adjustment process of the dynamic adjustment module also includes: 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 street lamp lighting brightness is changed at each time point.

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