LED bulb regulation and control system based on time

Abstract

The invention belongs to the technical field of bulb regulation and control, and particularly discloses and provides a time-based LED bulb regulation and control system, which comprises an environment information acquisition module, a lighting information import module, a lighting mode confirmation module, a lighting instruction analysis module, a database and a regional lighting control terminal. According to the method, the illumination mode switching demand degree is analyzed by setting the mode adjustment factor and the vehicle aggregation compensation factor, and then the illumination mode is confirmed, so that the problem that scene adaptability analysis is not carried out on the current regulation and control mode is effectively solved, design optimization can be carried out around a specific application scene, and subsequent bulb regulation and control can be carried out; compared with the prior art, the lamp bulb regulation and control scene is expanded, energy waste caused by premature lighting starting can be avoided by confirming the lighting starting time point and the appropriate lighting brightness in the target area, adjusting the starting number of the lamp beads and confirming all the lamp beads adjusted to be started, and meanwhile it is ensured that lighting is started at the appropriate time.

Description

Technical Field

[0001] The present invention belongs to the technical field of bulb regulation. Specifically, it relates to a time-based LED bulb regulation system. Background Art

[0002] In urban public lighting, such as street lights and park lighting, in the past, relying on manual regular inspections, manual control of switches and brightness adjustment not only consumed a lot of manpower, but also it was very difficult to make accurate and timely adjustments according to the actual lighting conditions. In this context, the importance of dynamic regulation based on time is self-evident.

[0003] Existing technologies such as the Chinese patent application with the application number 202410936515.6, which discloses a dynamic control method and system for LED lights based on the Internet of Things. It collects environmental data inside and outside the factory in real time through photosensitive sensors and cameras, uses edge computing technology for real-time data processing and dynamic adaptive control, combines deep learning algorithms to analyze and optimize historical data, generates an efficient lighting control strategy, and the integrated management module predicts lighting requirements and makes advance adjustments based on the optimized control model and real-time data to achieve the overall regulation and optimization of the system. The blockchain storage module encrypts the integrated data to ensure the security and immutability of the data. Through the above technical means, the efficient and intelligent control of LED lights in the factory is realized, significantly improving the response speed, control accuracy and overall performance of the system, optimizing the resource utilization efficiency, and ensuring the security and transparency of the data.

[0004] Another existing technology is the Chinese patent application with the application number 202311756539.5, which discloses a multi-purpose intelligent LED scene light control system and method. It retrieves existing application cases of LED scene lights through the Internet, classifies them based on the application scenarios and application subjects and enters them into the database as the source of reference cases for the lighting design of LED scene lights. After receiving customer order information, it matches the received customer order information with the application cases in the database to determine the design mode and then designs a lighting plan. It modifies the lighting plan based on the feedback information received by the customer after receiving the designed LED scene light lighting plan, calculates the lighting plan design efficiency index based on the total design duration and the number of modifications of the LED scene light lighting plan, and thus realizes the rapid design of lighting plans for different application scenarios, meeting the lighting requirements of multiple scenarios and multiple purposes while reducing the lighting plan design time and improving the lighting plan design efficiency.

[0005] Regarding the above technical solutions, obviously, there are still the following deficiencies in current bulb regulation: 1. Currently, it is designed and optimized around specific application scenarios for bulb regulation. The scenarios are relatively single, not suitable for relatively complex lighting usage scenarios, with large limitations and insufficient adaptability.

[0006] 2. Although some technologies use historical data for analysis and optimization, their data utilization mainly focuses on the realization of their own specific functions, lacking continuous monitoring of the long-term energy consumption data of urban public lighting and an adaptive control mechanism based on this. It is difficult to automatically and continuously optimize the bulb control strategy according to the energy consumption changes caused by long-term factors such as the aging of lighting facilities, and thus it is impossible to continuously improve the energy utilization efficiency while ensuring the lighting effect.

[0007] 3. The current control mode does not conduct scene adaptability analysis, resulting in insufficient flexibility and pertinence in bulb control and unable to guarantee the bulb control efficiency. Summary of the Invention

[0008] In view of this, to solve the problems raised in the above background technology, a time-based LED bulb control system is proposed.

[0009] The object of the present invention can be achieved through the following technical solutions: In the first aspect of the present invention, a time-based LED bulb control system is provided. The system includes: an environmental information acquisition module, which is used to acquire the illumination brightness information and the area of the target area, start the camera in the target area for video acquisition at the same time, and import the current time point.

[0010] A lighting information import module, which is used to import the lighting instructions for today in the target area.

[0011] A lighting mode confirmation module, which is used to confirm the lighting mode based on the video of the target area collected and the lighting instructions for today, and obtain the lighting mode started today.

[0012] A lighting instruction analysis module, which is used to confirm the current adjusted lighting instruction based on the illumination brightness information, energy consumption monitoring data, and lighting instructions for today.

[0013] A database, which is used to store the lighting instructions, energy consumption monitoring data, and status monitoring data corresponding to each monitoring day of the target area, store the power consumption of each illumination brightness per unit time, store the set number of lamp beads and the luminous flux of a single lamp bead of the lamps in the target area, and store the associated lamp bead positions corresponding to each luminous flux monitoring point in the target area.

[0014] A regional lighting control terminal, which is used to perform corresponding lighting control based on the lighting mode started today and the current adjusted lighting instruction.

[0015] Compared with the prior art, the beneficial effects of the present invention are as follows: (1) By setting a mode adjustment factor and a vehicle aggregation compensation factor to analyze the demand degree for switching lighting modes, and then confirming the lighting mode, the present invention effectively solves the problem that the current regulation mode does not conduct scene adaptability analysis, can be designed and optimized around specific application scenarios and then adjust the bulbs subsequently, expands the bulb regulation scenarios, and increases the adaptability and practicability in relatively complex lighting usage scenarios.

[0016] (2) By setting the mode adjustment factor from two dimensions of the total planned power consumption and the lighting task, the present invention can accurately understand the degree to which the current power consumption plan deviates from the normal level, and then it is convenient to subsequently adjust the lighting mode targeted, can flexibly respond to different power consumption plan scenarios, thereby improving the adaptability and flexibility of the lighting mode.

[0017] (3) When confirming the current adjusted lighting instruction, by confirming the lighting start time point, the appropriate lighting brightness in the target area, adjusting the number of turned-on lamp beads, and confirming each adjusted turned-on lamp bead, the present invention can avoid the energy waste caused by premature lighting start, and at the same time ensure that the lighting starts at the appropriate time, so as to timely meet the actual usage needs of different lighting areas, and can better adapt to environmental changes.

[0018] (4) By combining the energy consumption data and the luminous flux of each monitoring point to confirm the number of turned-on lamp beads to be adjusted, the present invention solves the problems existing in the current data utilization mainly focusing on the realization of its own specific functions, improves the depth of data integration and mining at the urban lighting management level, realizes the continuous monitoring of the long-term energy consumption data of urban public lighting, and sets up an adaptive regulation mechanism, which can automatically, continuously and finely optimize the bulb regulation strategy according to the energy consumption changes brought by long-term factors such as the aging of lighting facilities, and then while ensuring the lighting effect, can continuously improve the energy utilization efficiency, avoid energy waste, and ensure the efficient operation of lighting equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the drawings in the following description are only some embodiments of the present invention, and for those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0020] Figure 1 It is a schematic diagram of the processes of each module of the system of the present invention.

[0021] Figure 2 It is a schematic diagram of the overall process of the present invention.

[0022] Figure 3 It is a schematic diagram of the lighting mode confirmation process of the present invention. Detailed implementation manners

[0023] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0024] Please refer to Figures 1 to 2 As shown, the present invention provides a time-based LED bulb control system, which includes: an environmental information collection module, a lighting information import module, a lighting mode confirmation module, a lighting instruction analysis module, a database, and a regional lighting control terminal.

[0025] Among the above, the lighting mode confirmation module is respectively connected to the environmental information collection module, the lighting information import module, the lighting instruction analysis module, and the database, and the lighting instruction analysis module is also respectively connected to the database and the regional lighting control terminal.

[0026] The environmental information collection module is used to collect the light brightness information and the target area of the target area, start the camera of the target area for video collection at the same time, and import the current time point.

[0027] Specifically, the light brightness information includes the light brightness at each monitoring time point, which is monitored by a light sensor.

[0028] The lighting information import module is used to import the lighting instructions for today in the target area.

[0029] Specifically, the lighting instructions for today record, including but not limited to, the total planned power consumption for today and the lighting tasks. Among them, the lighting tasks record the lighting types, such as traffic lighting and maintenance lighting, etc.

[0030] It should be added that the purpose of importing the total planned power consumption for today and the lighting tasks in this step is to clarify the total planned power consumption for lighting on that day and the specific lighting task content to be executed. The total planned power consumption can directly reflect the scale of the power consumption expected for lighting on that day, while the lighting tasks cover the specific arrangements of different types of lighting such as traffic lighting, landscape lighting, and indoor lighting, providing basic data for further analysis and decision-making in the future. By parsing the lighting instructions for today to obtain these key information, it is convenient to compare with past data and reasonably confirm and adjust the lighting mode according to the actual situation.

[0031] The lighting mode confirmation module is used to confirm the lighting mode based on the collected video of the target area and the lighting instructions for today, and obtain the lighting mode started today.

[0032] Specifically, please refer to Figure 3 shown below. The illumination mode confirmation includes: A1. Based on the illumination instruction for today, set a mode adjustment factor, denoted as .

[0033] A2. Segment the video of the target area collected into each video frame, and record the acquisition time point of each video frame.

[0034] A3. Identify each video frame through a target detection algorithm, and statistically obtain the number of vehicles existing in each video frame.

[0035] A4. Statistically obtain the number of video frames in which the number of vehicles is greater than the set reference number of vehicles, denoted as the number of concerned video frames, and divide it by the number of video frames to obtain the traffic flow aggregation ratio .

[0036] A5. Based on the acquisition time points of each concerned video frame, set a vehicle aggregation compensation factor , and statistically obtain the demand degree for illumination mode switching , , is the set reference traffic flow aggregation ratio.

[0037] A6. Determine whether the demand degree for illumination mode switching is greater than the set value. If so, use the adaptive mode as the illumination mode started today. If not, use the pre-set initial default illumination mode as the illumination mode started today.

[0038] It should be added that in a specific embodiment, the set reference number of vehicles is mainly set according to the vehicle capacity of the target area. Exemplarily, if the target area is a two-lane road, the set reference number of vehicles can take a value of 4, and exemparily, the reference traffic flow aggregation ratio can take a value of 0.6.

[0039] In a specific embodiment, the target detection algorithm includes classic target detection algorithms such as Haar feature + Adaboost algorithm, HOG feature + SVM algorithm, etc., which extract the features of vehicles in the video frame and separate the vehicles as targets from the background. These methods train a classifier to learn the feature patterns such as the shape and texture of vehicles, so as to identify the position, size, etc. of vehicles in new video frames.

[0040] In the embodiment of the present invention, by setting a mode adjustment factor and a vehicle aggregation compensation factor to analyze the demand degree for illumination mode switching, and then performing illumination mode confirmation, the problem that the current regulation mode does not perform scene adaptability analysis is effectively solved. It can be designed and optimized around a specific application scenario and then perform subsequent bulb regulation, expanding the bulb regulation scenario and increasing the adaptability and practicality in a more complex illumination usage scenario.

[0041] Further, a mode adjustment factor is set in step A1, including: A11. Extract the total planned power consumption and lighting tasks for today from the lighting instruction for today.

[0042] A12. If there is only traffic lighting in the lighting tasks, extract the lighting instructions for each monitoring day corresponding to the target area from the database, and then extract the total planned power consumption of the target area on each monitoring day, select the maximum total power consumption therefrom, and at the same time obtain the average planned power consumption through average calculation.

[0043] A13. Compare the total planned power consumption for today with the average planned power consumption. If the total planned power consumption for today is lower than or equal to the average planned power consumption, take 0 as the mode adjustment factor.

[0044] A14. If the total planned power consumption for today is higher than the average planned power consumption, record the total planned power consumption for today and the maximum total power consumption as and respectively, and take as the mode adjustment factor , where e is the natural constant.

[0045] A15. If there is not only traffic lighting in the lighting tasks, take 1 as the mode adjustment factor, and thus obtain the mode adjustment factor , whose value is 0 or or 1.

[0046] In the embodiment of the present invention, by setting the mode adjustment factor from two dimensions of the total planned power consumption and lighting tasks, it is possible to accurately understand the degree to which the current power consumption plan deviates from the normal level, and then it is convenient to subsequently adjust the lighting mode targeted, and can flexibly respond to different power consumption plan scenarios, thereby improving the adaptability and flexibility of the lighting mode.

[0047] It can be understood that when there is only traffic lighting in the lighting tasks, searching for the lighting instructions for each monitoring day corresponding to the target area in the database is to obtain a more comprehensive historical lighting planning situation. On this basis, further extracting the total planned power consumption for each monitoring day can understand the range of past power consumption levels for the traffic lighting in this area on different monitoring days.

[0048] It can be understood that selecting the maximum total power consumption can determine the situation where the traffic lighting consumes the most power in the past monitoring days, and it can be used as an upper limit reference value to measure the gap between the current power consumption plan and the historical extreme value. Calculating the average planned power consumption is to obtain a relatively normal power consumption level reference value, comprehensively reflecting the general situation of past traffic lighting power consumption, and helping to subsequently judge whether the power consumption plan for the day is within a reasonable range.

[0049] Understandably, when the total planned electricity consumption today is higher than the average total planned electricity consumption, the total planned electricity consumption today and the maximum total electricity consumption are respectively recorded as relevant variables, and the pattern adjustment factor is calculated. The purpose of doing this is to quantify the degree to which the daily electricity consumption plan exceeds the average level, and to comprehensively consider how serious its deviation from the normal situation is in combination with the maximum electricity consumption. The pattern adjustment factor can be used to indicate the amplitude or direction of the corresponding adjustment that the subsequent lighting pattern needs to make, so that the lighting pattern can be dynamically optimized according to the comparison between the actual electricity consumption plan and historical data, while ensuring lighting requirements and reasonably controlling energy consumption as much as possible.

[0050] It should be added that the purpose of determining the pattern adjustment factor through the above different situations is to establish a unified judgment basis based on data comparison and analysis in lighting management, which is convenient for confirming the lighting pattern. Extracting the daily target electricity consumption plan from today's lighting instruction and combining it with the determination process of the entire pattern adjustment factor is to comprehensively consider the lighting electricity consumption expectation of the day and the past electricity consumption history, and realize the intelligent and dynamic adjustment of the lighting pattern, which can not only meet the actual lighting requirements, but also reasonably control energy consumption and improve the overall operation efficiency and economy of the lighting system.

[0051] Further, the setting of the vehicle aggregation compensation factor described in step A5 includes: A51. Compare the acquisition time points of each concerned video frame to obtain the acquisition interval duration of each concerned video frame. If the acquisition interval duration corresponding to a certain adjacent concerned video frame is within the set reference time window, then the adjacent concerned video frames are formed into a continuous video frame pair, and the number of continuous video frame pairs is counted and recorded as 。

[0052] A52. If the acquisition interval duration corresponding to a certain adjacent concerned video frame exceeds the set reference time window, then this adjacent concerned video frame is recorded as an intermittent adjacent video frame. Then, the maximum acquisition interval duration is screened out from the acquisition interval durations of each intermittent adjacent video frame and recorded as 。

[0053] A53. Count the number of concerned video frames and record it as , set the vehicle aggregation compensation factor , , is the set reference acquisition interruption duration, and respectively represent the weight coefficients corresponding to the number of continuous video frame pairs and the maximum acquisition interval duration.

[0054] In a specific embodiment, and both reflect the persistence and coherence of vehicle round trips, Value and The larger the value, the more continuous the vehicle movement is and the shorter the interval time is. It conducts vehicle aggregation compensation analysis from the proportion dimension of consecutive video frames. It conducts vehicle aggregation compensation analysis from the dimension of interval duration. Obviously, the proportion of consecutive video frames intuitively reflects the aggregation situation, while the interval duration belongs to a supplementary factor. Therefore, the weight coefficient corresponding to the number of pairs of consecutive video frames is set to be greater than the weight coefficient corresponding to the maximum acquisition interval duration. Specifically, and They can be respectively set to 0.6 and 0.4. At the same time, the reference acquisition interruption duration can be set according to the total video duration of the target area. For example, the reference acquisition interruption duration can be one-third of the total video duration of the target area.

[0055] The lighting instruction analysis module is used to confirm the current adjusted lighting instruction based on the above-mentioned light brightness information and today's lighting instruction.

[0056] Specifically, confirming the current adjusted lighting instruction includes: J1. Based on the light brightness information, the current time point, and the lighting mode started today, confirm the lighting start time point in the target area and confirm the appropriate lighting brightness in the target area.

[0057] J2. Extract the lighting instruction, energy consumption monitoring data, and status monitoring data corresponding to each monitoring day of the target area from the database, confirm the number of turned-on beads to be adjusted and confirm each adjusted turned-on bead, and record the positions of each adjusted turned-on bead.

[0058] J3. Use the appropriate lighting brightness in the target area as the light brightness of each adjusted turned-on bead, and form the current adjusted lighting instruction with the light brightness and positions of each adjusted turned-on bead.

[0059] Further, in step J1, confirming the lighting start time point in the target area includes: H1. Extract the light brightness of each monitoring time point from the light brightness information.

[0060] H2. If the light brightness at the current monitoring time point is less than or equal to the pre-set lighting start trigger light brightness, then use the current monitoring time point as the lighting start time point in the target area.

[0061] H3. If the light brightness at the current monitoring time point is greater than the pre-set lighting start trigger light brightness, extract the light brightness of each monitoring time point from the light brightness information.

[0062] H4. Taking the monitoring time points as the abscissa and the illumination brightness as the ordinate, construct an illumination brightness change curve, fit the illumination brightness change curve to obtain a fitting function, and import the preset illumination start trigger brightness into the fitting function to obtain the predicted start trigger time point.

[0063] H5. Determine whether the illumination mode started today is the adaptive mode. If it is not the adaptive mode, use the preset illumination start time point as the reference start trigger time point.

[0064] H6. If the predicted start trigger time point is before the reference start trigger time point, use the predicted start trigger time point as the illumination start time point in the target area. If the predicted start trigger time point is the same as the reference start trigger time point, or the predicted start trigger time point is after the reference start trigger time point, use the reference start trigger time point as the illumination start time point in the target area.

[0065] H7. If it is the adaptive mode, analyze the degree of early start demand, and take the product of the degree of early start demand and the preset appropriate early start duration as the early start trigger duration.

[0066] H8. Take the time point with an interval duration equal to the early start trigger duration from the predicted start trigger time point as the illumination start time point in the target area.

[0067] In a specific embodiment, comprehensively considering the predicted start trigger time point and the reference start trigger time point helps to optimize the energy utilization efficiency while ensuring the illumination effect. Starting the illumination too early will cause energy waste, while starting too late may not meet the illumination demand and affect the use safety, etc. By reasonably comparing the two, find an optimal start time point that can not only turn on the illumination in a timely manner according to the actual light conditions but also avoid unnecessary energy consumption, so that the illumination system can achieve the goal of energy conservation and consumption reduction on the basis of meeting the regional function requirements, and achieve a good balance between energy utilization and illumination effect. And this setting can improve the scientificity, rationality of determining the illumination start time and the overall efficiency of illumination management in many aspects compared with directly using the predicted start trigger time point as the illumination start time point.

[0068] Regarding the construction of the illumination brightness change curve in step H4, professional drawing software such as the chart function of Excel, Origin and other professional drawing tools can be used, or a self-developed data analysis and visualization program can be used to complete the drawing work, so that the change trend of the illumination brightness over time can be intuitively presented, which is convenient for subsequent analysis and prediction.

[0069] Regarding the fitting of the constructed light intensity change curve in step H4. The purpose of fitting is to find a fitting function that can accurately describe the law of light intensity changing with time, including various methods such as linear fitting, polynomial fitting, and non-linear fitting.

[0070] Exemplarily, when the change of light intensity shows an approximately linear trend, a linear fitting method can be adopted. Generally, the least squares method is used to determine the slope and intercept of the fitting line, and the linear equation is used as the fitting function, with the independent variable being the monitoring time point and the dependent variable being the light intensity. When the change of light intensity is not a simple linear relationship but shows a certain curve form, polynomial fitting is more appropriate, such as a quadratic polynomial. Similarly, optimization algorithms such as the least squares method are used to determine the coefficients of each term of the polynomial according to the collected data to obtain the corresponding polynomial fitting function. When the change of light intensity conforms to non-linear laws such as exponential growth or decay, logarithmic change, etc., corresponding non-linear functions need to be used for fitting. For example, in the form of exponential function fitting, the coefficients are determined according to the data through non-linear fitting algorithms to obtain the fitting function.

[0071] Regarding step H5, it should be supplemented that the pre-set lighting start time point is determined based on comprehensive factors such as past experience, lighting area function requirements, and conventional environment. For example, for a certain park, according to its daily opening and visitor activity rules, it is stipulated that the lighting is started at 18:30 in the evening. This time point is a standard arrangement set after long-term consideration. Directly adopting the predicted start trigger time point may deviate significantly from the original reasonable pre-designed plan due to factors such as accidental fluctuations in light intensity changes or prediction errors. By setting a reference start trigger time point and comparing it, while considering the actual light changes, the initial lighting plan is still respected, ensuring that the lighting start generally conforms to the expected time rhythm, and avoiding changing the lighting start time too frequently or randomly, which may affect the normal lighting order and usage experience of the area.

[0072] Regarding step H5, it should be supplemented that judging whether the lighting mode started today is the adaptive mode reflects the consideration of the flexibility of lighting management. In the non-adaptive mode, more reliance is placed on the pre-set lighting start time point as an important reference, which meets the requirements of some scenarios with relatively fixed time requirements and does not want the lighting start time to change frequently, such as the lighting of some unit parks with strict work and rest time arrangements. In the adaptive mode, more emphasis can be placed on adjusting the lighting start according to the start trigger time point predicted by the real-time light change to better cope with scenarios such as outdoor public places with changeable weather, meeting the diverse lighting management strategy requirements in different lighting areas and different usage scenarios. Through this comparison and judgment mechanism, flexible switching and precise control of the lighting start time are achieved.

[0073] Regarding what needs to be supplemented in step H6, by comparing with the reference start trigger time point, if the predicted time point is significantly advanced, it indicates that there may be errors caused by such abnormal fluctuations. At this time, referring to the relatively stable preset start time point to finally determine the lighting start time can avoid the situation of premature lighting start due to prediction errors, improve the accuracy of determining the lighting start time, and ensure that the lighting start decision is more reliable.

[0074] Regarding the analysis of the early start demand degree in step H7, it includes: dividing the light intensity change curve into two equal parts to obtain the two divided curve segments, extracting the slopes of the two curve segments, and screening out the minimum slope from them as the target light intensity change rate, denoted as , and at the same time calculating the difference between the slopes of the two curve segments, taking the absolute value of the difference, and denoting it as .

[0075] Set the early start demand degree , , is the set reference light intensity change rate, is the set reference light intensity change rate difference.

[0076] In a specific embodiment, can take the value of 0.1, can take the value of 0.2.

[0077] Furthermore, in step J1, confirming the appropriate lighting intensity in the target area includes: importing the lighting start time point in the target area into the fitting function, and taking the output result as the light intensity when triggering the lighting.

[0078] Matching and comparing the light intensity when triggering the lighting with the corresponding light intensity intervals of the set start lighting intensities to obtain the matching start lighting intensity, denoted as , and taking as the appropriate lighting intensity in the target area.

[0079] Furthermore, in step J2, confirming the number of turned-on lamp beads includes: extracting the power consumption per unit time of each lighting intensity from the database, and at the same time extracting the lighting intensity of each lighting time period from the lighting instructions corresponding to each monitoring day in the target area, and then statistically calculating the power consumption of each lighting time period and summing to obtain the total power consumption of each monitoring day.

[0080] Extracting the monitored power consumption from the energy consumption monitoring data of each monitoring day, taking the difference between the monitored power consumption and the total power consumption to obtain the power consumption difference, using the monitoring day as the abscissa and the power consumption difference as the ordinate to construct a power consumption difference curve, and extracting the slope of the power consumption difference curve as the power consumption difference growth rate, denoted as .

[0081] Extract the light fluxes monitored by each light flux monitoring point from the state data, calculate the standard deviation, and record the calculation result as the light flux difference degree. Calculate the mean value of the light flux difference degrees for each monitoring day to obtain the average light flux difference degree, denoted as .

[0082] Extract the set number of lamp beads and the light flux of a single lamp bead of the lamps in the target area from the database, denoted as and respectively. At the same time, denote the area of the target area and the appropriate illumination brightness as and respectively, and calculate the number of lamp beads to be turned on , , and are the growth rate of power consumption difference and the light flux difference degree for setting reference respectively.

[0083] In a specific embodiment, can take the value of 0.1, and the reference value of the light flux difference degree can generally be set at 10%-20% of the light flux of the lamp beads. Exemplarily, .

[0084] It should be added that This part represents the product of the square of the appropriate illumination brightness and the area of the target area. It reflects the total light flux requirement to achieve the appropriate illumination brightness, represents dividing the total light flux requirement by the light flux of a single lamp bead to obtain the theoretically required number of lamp beads to meet the appropriate illumination brightness. Composed of , represents the correction factor corresponding to the growth rate of power consumption difference, represents the correction factor corresponding to the light flux difference degree.

[0085] Understandably, when the power consumption growth rate is large, it may mean that there are problems with the efficiency of the existing lighting system. For example, some lamp beads are aging, resulting in increased power consumption but reduced luminous efficiency. However, to ensure that the brightness of the illuminated area can reach the minimum safety and usage standards (road lighting should ensure the safe passage of pedestrians and vehicles), it is necessary to appropriately increase the number of lamp beads. At the same time, when the light flux is uneven, it means that there are brighter and darker areas in the illuminated area. If the light flux difference is too large, the darker areas may form lighting blind spots, affecting people's activities in this area. To eliminate these lighting blind spots and make the light evenly distributed, it is necessary to turn on more lamp beads to supplement the light.

[0086] Understandably, to achieve the required illumination brightness in a specific area, it is often necessary to turn on a certain number of light bulbs to provide sufficient luminous flux. Usually, when other conditions such as the luminous flux specifications of the lamp beads and the lighting environment are relatively fixed, the more light bulbs are turned on, the greater the total luminous flux obtained in this area, and the easier it is to achieve the desired illumination brightness.

[0087] In the embodiments of the present invention, by combining the energy consumption data and the luminous flux of each monitoring point, the number of turned-on lamp beads is confirmed and adjusted, solving the problems existing in the current data utilization mainly focusing on the realization of its own specific functions, improving the depth of data integration and mining at the urban lighting management level, realizing the continuous monitoring of the long-term energy consumption data of urban public lighting, and setting up an adaptive regulation mechanism, which can automatically, continuously and finely optimize the lamp regulation strategy according to the energy consumption changes caused by long-term factors such as the aging of lighting facilities, so as to continuously improve the energy utilization efficiency while ensuring the lighting effect, avoid energy waste, and ensure the efficient operation of lighting equipment.

[0088] Furthermore, in step J2, confirming each adjusted and turned-on lamp bead includes: calculating the average value of the luminous fluxes monitored by each luminous flux monitoring point on different monitoring days to obtain the average monitored luminous flux of each luminous flux monitoring point.

[0089] Extract the associated lamp bead positions corresponding to each luminous flux monitoring point in the target area from the database, and then, according to the corresponding relationship between the luminous flux monitoring point and the lamp bead position, sort each set lamp bead in descending order of the average monitored luminous flux of its corresponding luminous flux monitoring point, and screen out the first ranked set lamp beads as each adjusted and turned-on lamp bead.

[0090] It should be added that the luminous flux monitoring can be carried out by arranging multiple optical sensor nodes in the target area according to a certain rule, such as grid-like or concentric circle-like, and determining the layout method according to specific monitoring requirements, the shape of the area, and the corresponding irradiation projection positions of the lamp beads in the lamp. These optical sensors can be small devices with a certain illuminance measurement function, such as silicon photocell type optical sensors, etc., which can sense the illumination intensity of the surrounding environment in real time.

[0091] When confirming the current adjusted lighting instruction in the embodiments of the present invention, by confirming the lighting start time point, the appropriate lighting brightness in the target area, the number of turned-on lamp beads to be adjusted, and confirming each adjusted and turned-on lamp bead, it is possible to avoid energy waste caused by premature lighting, and at the same time ensure that the lighting starts at the appropriate time, so as to timely meet the actual use needs of different lighting areas and better adapt to environmental changes.

[0092] The database is used to store the lighting instructions, energy consumption monitoring data, and status monitoring data corresponding to each monitoring day of the target area, store the power consumption of each lighting brightness per unit time, store the set number of lamp beads and the luminous flux of a single lamp bead of the lamps in the target area, and store the associated lamp bead positions corresponding to each luminous flux monitoring point in the target area.

[0093] The area lighting control terminal is used to perform corresponding lighting regulation based on the lighting mode started today and the current adjusted lighting instructions.

[0094] The above content is only an example and illustration of the concept of the present invention. Those skilled in the art of this technology can make various modifications, supplements, or use similar methods to replace the specific embodiments described. As long as they do not deviate from the concept of the invention or exceed the scope defined by the present invention, they should fall within the protection scope of the present invention.

Claims

1. A time-based LED bulb control system, characterized in that, The system includes: An environmental information collection module, which is used to collect the illumination brightness information and the area of the target area, start the camera in the target area for video collection at the same time, and import the current time point; A lighting information import module, which is used to import the lighting instructions for today in the target area; A lighting mode confirmation module, which is used to confirm the lighting mode based on the collected video of the target area and the lighting instructions for today, and obtain the lighting mode started today; A lighting instruction analysis module, which is used to confirm the current adjusted lighting instruction based on the illumination brightness information and the lighting instructions for today; A database, which is used to store the lighting instructions, energy consumption monitoring data and status monitoring data for each monitoring day corresponding to the target area, store the power consumption of each illumination brightness per unit time, store the set number of lamp beads and the luminous flux of a single lamp bead in the lamps in the target area, and store the associated lamp bead positions corresponding to each luminous flux monitoring point in the target area; A regional lighting control terminal, which is used to perform corresponding lighting regulation based on the lighting mode started today and the current adjusted lighting instruction.

2. The time-based LED bulb control system according to claim 1, wherein: The confirmation of the lighting mode includes: Based on today's lighting instructions, set the mode adjustment factor, denoted as ; Segmenting the collected video of the target area into each video frame, and recording the collection time point of each video frame; Identifying each video frame through a target detection algorithm, and statistically obtaining the number of vehicles existing in each video frame; Count the number of video frames in which the number of vehicles is greater than the set reference number of vehicles, record it as the number of concerned video frames, and divide it by the number of video frames to obtain the traffic flow aggregation ratio ; Set a vehicle aggregation compensation factor based on the acquisition time points of each concerned video frame and count the demand degree of lighting mode switching , , is the traffic flow aggregation ratio set as a reference Judging whether the demand degree of lighting mode switching is greater than the set value. If so, taking the adaptive mode as the lighting mode started today. If not, taking the preset initial default lighting mode as the lighting mode started today.

3. The time-based LED bulb control system according to claim 2, wherein: The setting of the mode adjustment factor includes: Extracting the total planned power consumption and lighting tasks for today from the lighting instructions for today; If there is only traffic lighting in the lighting tasks, extracting the lighting instructions for each monitoring day corresponding to the target area from the database, and then extracting the total planned power consumption of the target area on each monitoring day, screening out the maximum total power consumption therefrom, and calculating the average planned total power consumption through averaging; Comparing the total planned power consumption for today with the average planned total power consumption. If the total planned power consumption for today is lower than or equal to the average planned total power consumption, taking 0 as the mode adjustment factor; If the total planned power consumption today is higher than the average total planned power consumption, record the total planned power consumption today and the maximum total power consumption as and respectively, and use as the pattern adjustment factor , where is the natural constant; If there is more than just traffic lighting in the lighting task, take 1 as the mode adjustment factor to obtain the mode adjustment factor , which takes a value of 0 or or 1.

4. The time-based LED bulb control system according to claim 2, wherein: The setting of the vehicle aggregation compensation factor includes: By comparing the acquisition time points of each video frame of interest, the acquisition interval duration of each video frame of interest is obtained. If the acquisition interval duration corresponding to a certain adjacent pair of video frames of interest is within the set reference time window, the adjacent video frames of interest are combined into a pair of consecutive video frames, and the number of pairs of consecutive video frames is counted, denoted as ; If the acquisition interval duration corresponding to a certain adjacent video frame of interest exceeds the set reference time window, then mark this adjacent video frame of interest as a discontinuous adjacent video frame. Furthermore, screen out the maximum acquisition interval duration from the acquisition interval durations of each discontinuous adjacent video frame, and denote it as ; Count the number of video frames of interest, denoted as , and set the vehicle aggregation compensation factor , , is the set reference acquisition interruption duration, and represent the weight coefficients corresponding to the number of consecutive video frame pairs and the maximum acquisition interval duration, respectively.

5. The time-based LED bulb control system according to claim 2, wherein: The confirmation of the current adjusted lighting instruction includes: Based on the illumination brightness information, the current time point and the lighting mode started today, confirming the lighting start time point in the target area and the appropriate illumination brightness in the target area; Extracting the lighting instructions, energy consumption monitoring data and status monitoring data for each monitoring day corresponding to the target area from the database, confirming the number of turned-on lamp beads to be adjusted and confirming each adjusted turned-on lamp bead, and recording the positions of each adjusted turned-on lamp bead; Taking the appropriate illumination brightness in the target area as the illumination brightness of each adjusted turned-on lamp bead, and forming the current adjusted lighting instruction with the illumination brightness and position of each adjusted turned-on lamp bead.

6. The time-based LED bulb control system according to claim 5, wherein: The confirmation of the lighting start time point in the target area includes: Extracting the illumination brightness at each monitoring time point from the illumination brightness information; If the illumination brightness at the current monitored time point is less than or equal to the preset lighting start trigger illumination brightness, taking the current monitored time point as the lighting start time point in the target area; If the illumination brightness at the current monitored time point is greater than the preset illumination start trigger brightness, extract the illumination brightness at each monitored time point from the illumination brightness information; Taking the monitored time point as the abscissa and the illumination brightness as the ordinate, construct an illumination brightness change curve, fit the illumination brightness change curve to obtain a fitting function, and import the preset illumination start trigger brightness into the fitting function to obtain a predicted start trigger time point; Determine whether the illumination mode started today is the adaptive mode. If it is not the adaptive mode, use the preset illumination start time point as the reference start trigger time point; If the predicted start trigger time point is before the reference start trigger time point, use the predicted start trigger time point as the illumination start time point in the target area. If the predicted start trigger time point is the same as the reference start trigger time point, or the predicted start trigger time point is after the reference start trigger time point, use the reference start trigger time point as the illumination start time point in the target area; If it is the adaptive mode, analyze the degree of early start demand, and take the product of the degree of early start demand and the preset appropriate early start duration as the early start trigger duration; Use the time point with an interval duration equal to the early start trigger duration from the predicted start trigger time point as the illumination start time point in the target area.

7. The time-based LED bulb control system according to claim 6, wherein: The analysis of the degree of early start demand includes: Divide the light intensity change curve into two equal parts to obtain two divided curve segments, extract the slopes of the two curve segments, and select the minimum slope from them as the target light intensity change rate, denoted as , and at the same time calculate the difference between the slopes of the two curve segments, take the absolute value of the difference, and denote it as ; Set the advanced startup demand degree , , is the set reference illumination brightness change rate, is the set reference light brightness change rate difference.

8. The time-based LED bulb control system according to claim 5, wherein: The confirmation of the appropriate illumination brightness in the target area includes: Import the illumination start time point in the target area into the fitting function, and use the output result as the illumination brightness when triggering the illumination; Match and compare the light intensity at which lighting is triggered with the corresponding light intensity intervals of the set start lighting intensities to obtain the matched start lighting intensity, denoted as , and use as the appropriate lighting intensity within the target area.

9. The time-based LED bulb control system according to claim 5, wherein: The confirmation of adjusting the number of turned-on lamp beads includes: Extract the power consumption per unit time at each illumination brightness from the database, and at the same time extract the illumination brightness of each illumination time period from the illumination instructions of each monitored day in the target area, and then calculate the power consumption of each illumination time period and sum to obtain the total power consumption of each monitored day; Extract the monitored power consumption from the energy consumption monitoring data of each monitoring day, subtract the monitored power consumption from the total power consumption to obtain the power consumption difference. Use the monitoring day as the abscissa and the power consumption difference as the ordinate to construct a power consumption difference curve, and extract the slope of the power consumption difference curve as the power consumption difference growth rate, denoted as ; Extract the light fluxes corresponding to each light flux monitoring point from the state data, calculate the standard deviation, record the calculation result as the light flux difference degree, calculate the mean value of the light flux difference degrees for each monitoring day, and obtain the average light flux difference degree, denoted as ; Extract the set number of lamp beads and the luminous flux of a single lamp bead within the target area from the database, denoted as and respectively. At the same time, denote the area of the target area and the appropriate illumination brightness as and respectively, and calculate the number of turned-on lamp beads to be adjusted , , and are the growth rate of power consumption difference and the luminous flux difference degree set as references respectively.

10. A time-based LED bulb control system according to claim 5, characterized in that: The confirmation of each adjusted turned-on lamp bead includes: Calculate the average value of the monitored light fluxes corresponding to each light flux monitoring point on different monitored days to obtain the average monitored light flux of each light flux monitoring point; Extract the associated bead positions corresponding to each luminous flux monitoring point within the target area from the database, and then, according to the correspondence between the luminous flux monitoring points and the bead positions, sort each set bead in descending order of the average monitored luminous flux of its corresponding luminous flux monitoring point, and screen out each set bead ranked in the top positions as each adjusted and turned-on bead.

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