Intelligent control method and system adopting direct current lighting in smart city

Abstract

The invention relates to the technical field of smart city lighting, solves the problem that the balance between energy saving and lighting effects cannot be realized in the prior art, and provides an intelligent control method and system adopting direct current lighting for a smart city. The method comprises the following steps: obtaining a target strategy according to lighting facility position information and real-time ambient illuminance in a target area under an urban direct current lighting scene in combination with a timing strategy; according to the target strategy, controlling the illumination facility to illuminate, and obtaining an initial operation state parameter and a quality evaluation parameter; acquiring a preset operation state parameter template of the lighting facility in the target area under the control of the target strategy; adjusting the initial operation state parameter according to a preset operation state parameter template in combination with the quality evaluation parameter to obtain a target operation state parameter; and according to the target strategy and the target operation state parameter, controlling the illumination facilities in the target area to illuminate. On the premise of saving energy, the urban lighting effect can be improved.

Description

Technical Field

[0001] The present invention relates to the technical field of smart city lighting, and particularly to an intelligent control method and system for direct current lighting in a smart city. Background Art

[0002] Smart city lighting is an important part of modern city development. It aims to optimize the management and operation of urban lighting facilities by integrating advanced sensors, data communication networks, and intelligent control systems. The smart city lighting system not only provides efficient street lighting but also enables precise lighting adjustment to improve energy utilization efficiency, reduce energy consumption, and meet the lighting needs of urban residents. With the advancement of urbanization and the continuous development of intelligent technologies, smart city lighting has become an important way to enhance urban sustainable development, improve residents' quality of life, and promote the concept of green energy conservation.

[0003] Existing smart city lighting control technologies mainly rely on induction-based automatic adjustment and time-sequence-based lighting control strategies. For example, ambient light sensors can monitor the external illuminance in real time and automatically adjust the brightness of street lights according to the real-time lighting data; or intelligent algorithms can be used to dynamically adjust the light intensity based on preset time periods or weather conditions. In addition, existing technologies have also introduced intelligent scheduling systems, which can optimize the lighting effect according to different urban scenarios, such as road traffic, public areas, or commercial areas, through remote control and data analysis. However, although these technologies have made progress in energy conservation and improving management efficiency, they still face the problem of balancing energy consumption and lighting effect.

[0004] Although existing smart city lighting control technologies can improve energy utilization efficiency to a certain extent, they usually have difficulty achieving an accurate balance between lighting effect and energy consumption. In many cases, induction-based lighting adjustment methods may not fully consider lighting uniformity and the passing rate of lit lamps, resulting in poor lighting effects in some areas and even affecting urban safety. And time-sequence-based control strategies are prone to over-illumination during certain time periods, causing unnecessary energy consumption. Although some advanced control strategies attempt to solve this problem by subdividing areas and precisely adjusting brightness, due to the lack of close integration with real-time ambient illuminance, operating state parameters, and quality evaluation parameters of lighting facilities, existing technologies still fail to effectively achieve precise adjustment.

[0005] Therefore, how to improve the urban lighting effect on the premise of energy conservation is an urgent problem to be solved in the current smart city lighting control technology. Summary of the Invention

[0006] In view of this, the present invention provides an intelligent control method and system for DC lighting in a smart city, aiming to solve the problem in the existing lighting control technology of smart cities that it is impossible to achieve a balance between energy conservation and lighting effects.

[0007] The technical solution adopted by the present invention is as follows: In a first aspect, the present invention provides an intelligent control method for DC lighting in a smart city, and the method includes: Based on the position information of lighting facilities and the real-time ambient light intensity in a target area under the DC lighting scenario of the city, and in combination with a preset timing strategy for DC lighting control, obtain a target strategy for DC lighting control; According to the target strategy, control the lighting facilities to perform lighting, and obtain the initial operating state parameters of the lighting facilities and the quality evaluation parameters of the lighting in the target area. Among them, the initial operating state parameters include the initial current value, the initial voltage value, and the initial power value, and the quality evaluation parameters include the qualified rate of lighting and the lighting uniformity; Obtain a preset operating state parameter template of the lighting facilities in the target area under the control of the target strategy, where the preset operating state parameter template is the operating state parameters collected when the basic lighting requirements of the target area are met and the energy consumption is minimized; According to the preset operating state parameter template, in combination with the quality evaluation parameters, adjust the initial operating state parameters to obtain target operating state parameters; According to the target strategy and the target operating state parameters, control the lighting facilities in the target area to perform lighting.

[0008] In a second aspect, the present invention provides an intelligent control system for DC lighting in a smart city. The control system includes an intelligent lighting management platform, and the intelligent lighting management platform is communicatively connected to the control unit. The intelligent lighting management platform includes at least one processor, at least one memory, and computer program instructions stored in the memory. When the computer program instructions are executed by the processor 401, the method as described above is implemented.

[0009] In summary, the beneficial effects of the present invention are as follows: The intelligent control method and system for DC lighting in the smart city provided by the present invention effectively achieves the balance between energy conservation and lighting effects by precisely combining the location information of lighting facilities, the real-time ambient illuminance, and the preset DC lighting control timing strategy. First, based on the ambient illuminance in the target area and the location information of lighting facilities, combined with the preset timing control strategy, an accurate lighting control target strategy is generated; by obtaining the initial operating state parameters of lighting facilities and the quality evaluation parameters of the target area, the change of lighting effects can be monitored in real time and compared with the preset operating state template, which is the parameter setting with the optimal energy efficiency and meeting the basic lighting requirements, enabling the lighting facilities to be adjusted to the lowest energy consumption state on the premise of ensuring lighting quality; finally, by precisely adjusting the initial operating state parameters of lighting facilities, the target operating state parameters are obtained, so that under real-time control, both the lighting uniformity and the qualified rate of lighting in the lighting area can be ensured, and unnecessary energy consumption can be significantly reduced, successfully achieving the best balance between energy conservation and lighting effects. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required to be used in the embodiments of the present invention will be briefly introduced below. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained according to these drawings, and all of these are within the protection scope of the present invention.

[0011] Figure 1 It is a schematic flow chart of the overall work of the intelligent control method for DC lighting in the smart city in Embodiment 1 of the present invention; Figure 2 It is a schematic flow chart of obtaining the target strategy for DC lighting control in Embodiment 1 of the present invention; Figure 3 It is a schematic flow chart of adjusting the lighting strategy during the period and the lighting strategy within the period in Embodiment 1 of the present invention; Figure 4 It is a schematic flow chart of calculating the illuminance correction coefficient in Embodiment 1 of the present invention; Figure 5 It is a schematic flow chart of correcting the lighting turn-on time point and / or the lighting turn-off time point in Embodiment 1 of the present invention; Figure 6 It is a schematic flow chart of obtaining the initial operating state parameters of lighting facilities and the quality evaluation parameters of target area lighting in Embodiment 1 of the present invention; Figure 7 It is a schematic flow chart of obtaining the preset operating state parameter template of lighting facilities in the target area under the control of the target strategy in Embodiment 1 of the present invention; Figure 8Schematic flowchart of adjusting the initial operating state parameters to obtain the target operating state parameters in Embodiment 1 of the present invention; Figure 9 Schematic flowchart of weighted fusion calculation of the deviation value between the qualified rate of lighting and the preset qualified rate threshold and the deviation value between the lighting uniformity and the preset uniformity threshold in Embodiment 1 of the present invention; Figure 10 Schematic diagram of the management interface of the national-level intelligent lighting management platform in Embodiment 3 of the present invention; Figure 11 Schematic diagram of the management interface of the regional-level intelligent lighting management platform in Embodiment 3 of the present invention; Figure 12 Schematic diagram of the structure of the intelligent lighting management platform in Embodiment 3 of the present invention. Detailed implementation manners

[0012] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. It should be noted that in this document, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or sequence between these entities or operations. In the description of the present invention, it should be understood that the terms "center", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc. indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings, and are only for the convenience of describing the present application and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and thus cannot be understood as a limitation to the present invention. Moreover, the term "comprising", "including" or any other variant thereof is intended to cover a non-exclusive inclusion, such that a process, method, article or device including a series of elements not only includes those elements but also includes other elements not expressly listed, or further includes elements inherent to such process, method, article or device. Without further limitation, the elements defined by the statement "comprising..." do not exclude the existence of additional identical elements in the process, method, article or device including the said elements. If there is no conflict, the embodiments of the present invention and the various features in the embodiments may be combined with each other, and all are within the protection scope of the present invention.

[0013] Embodiment 1

[0014] Please refer to Figure 1 , Embodiment 1 of the present invention discloses an intelligent control method for direct current lighting in a smart city, and the method includes: According to the position information of lighting facilities and the real-time ambient illuminance in a target area under the urban DC lighting scenario, combined with the preset time-series strategy for DC lighting control, obtain the target strategy for DC lighting control; Specifically, first collect the position data of all lighting facilities and the real-time ambient illuminance information in the target area. The specific positions of the lighting facilities can ensure that the system accurately calculates the lighting range and its impact on the illuminance at different positions in the area. The real-time ambient illuminance data is used to understand the current natural lighting conditions in real time, avoiding providing excessive artificial lighting when the light is sufficient. Next, by combining the preset DC lighting control time-series strategy (such as adjusting the lighting intensity according to factors such as time period and weather), the system will generate an optimal lighting control target strategy. This strategy not only considers energy efficiency but also ensures the quality of the lighting effect in the area, ensuring that the lighting needs of the target area are met at different time periods.

[0015] According to the target strategy, control the lighting facilities to perform lighting, and obtain the initial operating state parameters of the lighting facilities and the quality evaluation parameters of the lighting in the target area. Among them, the initial operating state parameters include the initial current value, the initial voltage value, and the initial power value, and the quality evaluation parameters include the qualified lighting rate and the lighting uniformity; Specifically, according to the aforementioned target strategy, the system controls the lighting facilities to start working and adjusts their brightness and other parameters. At this time, the system will obtain the initial operating state parameters of each lighting facility in real time, including current, voltage, and power, etc. These parameters reflect the energy consumption status and operating performance of the lighting facilities. At the same time, the system will also evaluate the lighting quality of the target area according to the lighting requirements of the target area, obtain relevant quality evaluation parameters, mainly including the qualified lighting rate (i.e., the proportion of each lamp working normally and meeting the requirements) and the lighting uniformity (i.e., the degree of balance of the light distribution in the lighting area). These evaluation parameters can help the system evaluate the preliminary lighting effect and provide data support for subsequent optimization.

[0016] Obtain the preset operating state parameter template of the lighting facilities in the target area under the control of the target strategy, where the preset operating state parameter template is the operating state parameters collected when the basic lighting requirements of the target area are met and the energy consumption is minimized; Specifically, according to the requirements of the target strategy, obtain the preset operating state parameter template of the lighting facilities in the target area. This template is based on the principle of minimizing energy consumption and ensures that the target area can meet the basic lighting requirements. The parameters in the template (such as current, voltage, power, etc.) are obtained through historical data analysis and optimization algorithms, representing the working state of the lighting facilities in the optimal energy efficiency operating state. These parameters can not only ensure energy conservation but also ensure that the lighting facilities provide qualified lighting effects when working normally. This template provides a reference benchmark for subsequent adjustment and optimization, ensuring that each lighting facility can achieve the lowest energy consumption on the premise of meeting the area requirements.

[0017] Adjust the initial operating state parameters according to the preset operating state parameter template and in combination with the quality evaluation parameters to obtain the target operating state parameters; Specifically, adjust in combination with the initial operating state parameters according to the preset operating state parameter template and the quality evaluation parameters collected in real time. Quality evaluation parameters (such as the qualified rate of lit lamps and illumination uniformity) provide feedback on the lighting effect, helping the system judge whether the current lighting meets the standards. When it is found that the lighting effect is not good (such as uneven illumination or insufficient illumination in some areas), the system will optimize and adjust by adjusting the operating parameters such as the current and power of the lighting facilities, so as to achieve the expected lighting quality. This process can be carried out dynamically to ensure excellent lighting effects are maintained at all times in different environments and to minimize energy consumption to the greatest extent.

[0018] Control the lighting facilities in the target area to provide lighting according to the target strategy and the target operating state parameters.

[0019] Specifically, based on the adjusted target operating state parameters, the system controls the working state of the lighting facilities again. The target operating state parameters are obtained through the adjustment and optimization of the initial operating state, ensuring the lighting quality and energy efficiency requirements of the target area. The system will implement dynamic control according to the target strategy to ensure that the lighting facilities can achieve the best operating effects at different times and under different lighting environments. At this time, parameters such as the brightness and power of the lighting facilities are at optimal values to achieve a balance between energy conservation and lighting effects. This control process has a high degree of automation and adaptability, and can respond to external environmental changes in real time to ensure that the lighting system is always in the best operating state.

[0020] In one embodiment, please refer to Figure 2 , the obtaining of the target strategy for DC lighting control according to the lighting facility location information and the real-time environmental illuminance in the target area under the urban DC lighting scenario in combination with the preset time-sequencing strategy for DC lighting control includes: Obtain the target area attribute category according to the lighting facility location information; Specifically, by obtaining the specific location information of the lighting facilities and combining the regional characteristics such as the urban planning, road type, commercial area or residential area where the location is located, determine the attribute category of the target area. These attribute categories can include road lighting, public area lighting, commercial area lighting, residential area lighting, etc. Different areas have different lighting requirements and standards. By clarifying the attribute category of the target area, the system can formulate corresponding lighting strategies according to the special needs of different areas. For example, commercial areas may require higher brightness and longer lighting periods, while residential areas may pay more attention to energy conservation and a comfortable lighting environment.

[0021] Obtain the inter - period lighting strategy and intra - period lighting strategy according to the timing strategy and the target area attribute category, where the lighting strategy includes the lighting turn - on time point, the lighting turn - off time point, and the lighting brightness level; Specifically, according to the attribute category of the target area and the preset timing lighting control strategy, formulate the corresponding inter - period lighting strategy and intra - period lighting strategy. The inter - period lighting strategy includes the lighting plan information for weekdays and holidays, while the intra - period lighting strategy focuses on all - day lighting adjustment, including the intra - day lighting plan information for each day. Each strategy includes the setting of the lighting turn - on time point, the lighting turn - off time point, and the brightness level. For example, commercial areas may quickly turn on the lighting at dusk and maintain a high brightness level, while residential areas may adjust the turn - on and turn - off times, as well as the brightness level, according to the change of natural light intensity, ensuring that the lighting needs are met while saving energy.

[0022] Compare the real - time ambient light intensity with the preset light intensity threshold, and judge whether it is necessary to adjust the inter - period lighting strategy and the intra - period lighting strategy according to the comparison result; Specifically, the ambient light intensity of the target area is monitored in real time and compared with the preset light intensity threshold. If the real - time light intensity is lower than the set threshold, it means that lighting facilities need to be turned on to supplement the insufficient light; if the light intensity is higher than the threshold, it may be necessary to delay the turn - on or turn off the lighting facilities in advance to avoid over - lighting and wasting energy. The goal of this step is to ensure that lighting equipment is always accurately adjusted according to the actual light conditions, avoiding turning on or continuously lighting under unnecessary circumstances, thus achieving the purpose of energy conservation.

[0023] When it is necessary to adjust the inter - period lighting strategy and the intra - period lighting strategy, obtain the target area level and the target reference light intensity according to the target area attribute category; Specifically, after comparing the real - time light intensity with the threshold and finding that it is necessary to adjust the inter - period lighting strategy and the intra - period lighting strategy, further obtain the level of this area (such as the first - level lighting area, the second - level lighting area, etc.) and the target reference light intensity according to the attribute category of the target area; the target area level is set according to the importance of the area, lighting requirements, and safety requirements. For example, main traffic arteries may be given a higher level, requiring stronger lighting intensity and longer lighting periods; while residential areas may be at a lower level, focusing on energy conservation and comfort. The target reference light intensity is the ideal lighting intensity value set according to the area function and lighting standards, helping the system ensure that the lighting effect meets the actual needs when adjusting the strategy.

[0024] Adjust the inter - period lighting strategy and the intra - period lighting strategy according to the target area level and the target reference light intensity to obtain the target strategy.

[0025] Specifically, according to the target area level and the target reference illuminance, adjust the inter-cycle lighting strategy and the intra-cycle lighting strategy. By adjusting the lighting on-time, off-time, and brightness level, ensure that while meeting the lighting requirements of the target area, the optimal energy efficiency is also maintained. For example, if the target area is divided into high-level areas, higher brightness and longer lighting periods may be required; while for low-level areas, the lighting strategy will tend to be in an energy-saving mode, reducing the lighting duration and appropriately lowering the brightness. Ultimately, the adjusted lighting strategy will form the target strategy, ensuring that the lighting effect in the target area can meet both the functional requirements and the energy-saving goal.

[0026] In one embodiment, please refer to Figure 3 , the adjusting of the inter-cycle lighting strategy and the intra-cycle lighting strategy according to the target area level and the target reference illuminance to obtain the target strategy includes: Obtain the illuminance adjustment weight according to the target area level; Specifically, determine the weight of illuminance adjustment based on the level information of the target area (such as high-level or low-level lighting areas); the level of the target area determines the demand for lighting quality in that area; high-level areas (such as important commercial areas or traffic arteries) have a higher demand for illuminance and require a larger adjustment weight; while low-level areas (such as residential areas or less active areas) have a lower demand for lighting and a smaller adjustment weight. In this way, the system can carry out refined management of the adjustment of illuminance according to the functional requirements of different areas, ensuring that the lighting effect matches the importance of the area.

[0027] Calculate the illuminance deviation value according to the target reference illuminance and the real-time ambient illuminance; Specifically, calculate the illuminance deviation value between the two by comparing the real-time ambient illuminance with the target reference illuminance. If the actual illuminance is lower than the target illuminance, it means that the lighting brightness needs to be increased; conversely, the lighting brightness may need to be reduced. The illuminance deviation value provides a quantified difference as the basis for subsequent adjustment of the lighting strategy, ensuring that the lighting equipment can meet the lighting requirements while avoiding unnecessary energy waste.

[0028] Calculate the illuminance correction coefficient according to the illuminance deviation value and the illuminance adjustment weight; Specifically, once the illuminance deviation value is calculated, an illuminance correction coefficient is calculated in combination with the illuminance adjustment weight of the target area. This coefficient is used to adjust the actual brightness and switching time of the lighting so that the illuminance can better meet the actual needs of the target area. The correction coefficient is dynamic and is flexibly adjusted according to factors such as the real-time illuminance and the target area level, so as to ensure that the system always maintains the best lighting effect and energy efficiency balance under different environmental conditions.

[0029] According to the illuminance correction coefficient, the original brightness value corresponding to the illumination brightness level is corrected to obtain a corrected brightness value; Specifically, the original brightness value of the lighting facilities is adjusted according to the previously calculated illuminance correction coefficient. The corrected brightness value takes into account the illuminance deviation and the target area level, thereby providing more accurate brightness adjustment for the lighting equipment in the area. For example, when the ambient illuminance is low, the illuminance correction coefficient will increase the brightness value to ensure that the illumination in the target area meets the standard; when the ambient illuminance is high, the correction coefficient will appropriately reduce the brightness value to achieve energy-saving effects.

[0030] According to the preset lighting time adjustment step and the illuminance deviation value, the lighting start time point and / or the lighting end time point are corrected to obtain a corrected start time point and / or a corrected end time point; Specifically, the lighting start and end time points are corrected according to the illuminance deviation value and the preset lighting time adjustment step. The time adjustment step refers to the minimum step for the system to adjust the lighting time each time, usually to ensure a smooth transition of the lighting strategy and avoid disturbing the user due to frequent switching. When the ambient illuminance is insufficient, the start time point may be advanced and the end time point is correspondingly delayed; conversely, if the ambient illuminance is sufficient, the start time is postponed or the end time is advanced. In this way, the lighting time can be dynamically adjusted according to the real-time lighting conditions, further optimizing energy use.

[0031] According to the corrected brightness value, the corrected start time point and / or the corrected end time point, the target strategy is determined.

[0032] In one embodiment, please refer to Figure 4 , the calculation of the illuminance correction coefficient according to the illuminance deviation value and the illuminance adjustment weight includes: According to the target area attribute category, an illuminance correction mathematical model corresponding to the scenario is selected, where the mathematical model is used to describe the non-linear relationship between the illuminance deviation value and the illuminance correction coefficient, and the mathematical model includes an exponential function model and a piecewise linear function model; Specifically, the most suitable mathematical model for illuminance correction is selected according to the attribute category of the target area (e.g., residential area, commercial area, transportation hub, etc.). Each area has different lighting requirements and environmental characteristics, so different mathematical models are used to describe the non-linear relationship between illuminance deviation and correction coefficient. Commonly used mathematical models include the exponential function model and the piecewise linear function model. The exponential function model is suitable for scenarios with large illuminance changes and can more accurately describe the rapid response of illuminance to environmental changes; while the piecewise linear function model is suitable for environments with stable changes, and through piecewise linear fitting, it can better meet the gentle lighting adjustment requirements. For example, according to the attribute category of the target area, the obtained exponential function model is as follows: Where, ΔL represents the illuminance deviation value; a represents the regional adjustment sensitivity coefficient that determines the correction speed; K represents the illuminance correction coefficient, and its range is between 0 and 1; Another example, according to the attribute category of the target area, the obtained piecewise linear function model is as follows: Where, L1 represents the preset first illuminance deviation threshold; L2 represents the second illuminance deviation threshold; L1 is less than L2; A1 represents the linear slope in the first segment (i.e., when ΔL ∈ [0, L1)), that is, the correction increment corresponding to each unit of ΔL; A2 represents the linear slope in the second segment (ΔL ∈ [L1, L2)); where, A2 is greater than A1; B1 represents the intercept term of the second segment to ensure the continuity of the second segment and the first segment at L1; B2 represents the constant value of the third segment, indicating that when ΔL exceeds L2, the maximum or saturation value maintained by the illuminance correction coefficient, B2 is greater than B1, A1, A2, B1, B2, 、 The specific values of can be set differently according to different requirements of the scenario and are not limited here; This selection process enables the correction algorithm to adapt to different urban lighting scenarios and make corresponding optimization adjustments according to regional characteristics: by adopting the corresponding illuminance correction function model according to the attribute category of different target areas, it can more accurately meet the actual lighting adjustment needs of various scenarios. Residential areas are usually more sensitive to lighting changes and pursue a gentle and comfortable lighting experience. Therefore, it is suitable to adopt the piecewise linear function model. By setting different linear response slopes in different illuminance deviation intervals, stable and controllable adjustment can be achieved, avoiding over-compensation caused by small deviations; while in commercial areas or transportation hubs where lighting requirements fluctuate violently and change rapidly, the exponential function model is more suitable because it has a stronger response ability to large-range illuminance changes and can quickly increase or decrease the illuminance to adapt to complex environmental requirements. By selecting the correction function model according to local conditions, not only the accuracy and sensitivity of lighting adjustment are improved, but also the adaptability of the system to environmental changes and the overall energy efficiency control level are enhanced.

[0033] Substitute the illuminance deviation value and the illuminance adjustment weight as input variables into the illuminance correction mathematical model to obtain the initial illuminance correction coefficient; Specifically, substitute the calculated illuminance deviation value and illuminance adjustment weight as input variables into the selected illuminance correction mathematical model. The illuminance deviation value reflects the difference between the actual environmental illuminance and the target illuminance, while the illuminance adjustment weight affects the magnitude of the correction coefficient according to the importance and function of the target area. After substituting into the model, the system will obtain a preliminary illuminance correction coefficient, which reflects the gap between the current environmental illuminance and the predetermined target and provides a basis for the next lighting adjustment. In this way, the model can take into account the needs of different areas and environmental changes and generate a reasonable preliminary correction coefficient.

[0034] Normalize the initial illuminance correction coefficient according to a preset correction coefficient interval to obtain the illuminance correction coefficient.

[0035] Specifically, normalize the initial illuminance correction coefficient. The purpose of normalization is to ensure that the correction coefficient is within a certain preset interval to avoid excessive adjustment causing energy waste or uneven lighting. The preset correction coefficient interval is usually determined according to the needs of different scenarios and energy efficiency standards during the system design stage. For example, the correction coefficient may be limited within the range of [0, 1]. Through normalization, the value of the correction coefficient will be mapped into this interval, thus ensuring that the corrected brightness and time adjustment can be carried out within a reasonable range. This processing step ensures that the illuminance correction coefficient will not exceed the safety range of the system or affect the quality of the lighting effect when adjusting the lighting equipment.

[0036] In an embodiment, please refer to Figure 5 , the correcting the lighting on-time point and / or the lighting off-time point according to the preset lighting time adjustment step and the illuminance deviation value to obtain the corrected on-time point and / or the corrected off-time point includes: Obtain a time correction sensitivity parameter according to the target area attribute category, where the time correction sensitivity parameter is used to characterize the response sensitivity of different areas to the adjustment of the lighting on and off times; Specifically, the response sensitivity of the area to the adjustment of lighting on and off times is determined according to the attribute category of the target area. The lighting requirements and environmental conditions of different areas will affect their sensitivity to time adjustment. For example, the commercial area may have a higher sensitivity to lighting adjustment because strong lighting support is needed during peak business hours; while the residential area is more tolerant of the adjustment of lighting time. Therefore, the system will select a suitable time correction sensitivity parameter according to the functionality and activity type of the area to measure the response degree of the area to time adjustment. The setting of this parameter helps the system to customize the lighting time adjustment strategy according to the area demand.

[0037] Obtain the lighting time adjustment step, where the lighting time adjustment step is used to represent the basic time adjustment amplitude corresponding to the unit illuminance deviation value; Specifically, obtain the lighting time adjustment step. The lighting time adjustment step refers to the basic adjustment amplitude of the lighting on or off time under the unit illuminance deviation. The selection of this step depends on the lighting requirements of the target area and the response speed of the lighting system. If the lighting requirements of the target area are more sensitive, the step will be smaller to avoid instability caused by frequent adjustments; if the requirements of the area fluctuate greatly, the step can be increased accordingly. The lighting time adjustment step provides a basic adjustment amount for subsequent time adjustments to ensure that the time adjustment meets the actual needs of the area.

[0038] Calculate the basic time offset according to the illuminance deviation value and the lighting time adjustment step; Specifically, based on the illuminance deviation value and the lighting time adjustment step, the basic time offset will be calculated. The illuminance deviation value represents the gap between the current ambient illuminance and the preset target illuminance, and the lighting time adjustment step determines the specific impact of this gap on the lighting time. By combining the illuminance deviation value with the adjustment step, the system obtains a preliminary time offset, indicating the basic adjustment amplitude that needs to be made to the lighting on or off time.

[0039] Adjust the basic time offset according to a preset piecewise time adjustment function to obtain an adjusted time offset, where the piecewise time adjustment function distinguishes different adjustment speeds according to the magnitude of the illuminance deviation value; Specifically, correct the basic time offset according to a preset piecewise time adjustment function. The piecewise time adjustment function will define different adjustment speeds according to the magnitude of the illuminance deviation value. When the illuminance deviation is small, the adjustment speed may be slow to reduce unnecessary frequent adjustments; while when the deviation is large, the adjustment speed can be increased to quickly respond to changes in lighting requirements. For example, the piecewise time adjustment function can be set as: Among them, ΔL represents the illuminance deviation value, with the unit of lux; N represents the coefficient for adjusting the lighting response speed, which is multiplied by the base time offset to obtain the adjusted time offset.

[0040] By setting a segmented time adjustment function, differential adjustment responses are achieved for different degrees of illuminance deviation, thereby enhancing sensitivity and stability. When the illuminance deviation is small, the base time offset is corrected at a slower adjustment speed to avoid frequent adjustment due to minor fluctuations, reducing resource consumption and equipment wear; while when the deviation is large, the response is adjusted at a faster speed to ensure that the lighting promptly matches the environmental requirements, improving lighting comfort and safety. This segmented adjustment mechanism enables the system to balance real-time performance, energy conservation, and smooth operation, and is particularly suitable for smart lighting scenarios where the environment changes frequently and flexible responses are required.

[0041] According to the time correction sensitivity parameter, the adjusted time offset is corrected to obtain the target time offset; Specifically, the adjusted time offset is further corrected based on the previously obtained time correction sensitivity parameter. The response sensitivity of time adjustment in different regions affects the adjustment range of the lighting on and off times. For example, in commercial areas, regions with higher sensitivity may require more refined time correction to meet the lighting needs of high-density activities; while in relatively quiet residential areas, when the sensitivity is low, the adjustment range can be appropriately reduced. Through this correction process, the system finally obtains a target time offset to ensure that the lighting time adjustment meets the specific requirements of the region.

[0042] According to the target time offset, the lighting on time point and / or the lighting off time point are corrected to obtain the corrected on time point and / or the corrected off time point.

[0043] Specifically, the on and off times of the lighting are corrected according to the target time offset. The target time offset provides an accurate time adjustment value, which is applied to the lighting on time point and / or the off time point to optimize the lighting time arrangement. For example, in the case of insufficient light, the system may turn on the lighting in advance, while in the case of excessive light, the system will postpone turning off the lighting. This process ensures that the lighting system can flexibly respond to environmental changes while effectively balancing the lighting effect and energy efficiency optimization.

[0044] In one embodiment, please refer to Figure 6 , controlling the lighting facilities to perform lighting according to the target strategy, and obtaining the initial operating state parameters of the lighting facilities and the quality evaluation parameters of the target area lighting includes: According to the target area level, obtain the data collection frequency corresponding to this area level; Specifically, the corresponding data acquisition frequency is determined according to the level of the target area. Areas of different levels have different requirements for the change speed and stability of lighting needs. For example, in high-level areas such as commercial centers and transportation hubs, the lighting demand changes greatly and relatively precise real-time monitoring is required, so a higher data acquisition frequency will be set; while in lower-level areas, such as residential areas or parks, a not-so-high acquisition frequency may be sufficient. By allocating reasonable data acquisition frequencies for each area level, the system can ensure the flexibility and efficiency of lighting management while avoiding unnecessary data redundancy.

[0045] According to the data acquisition frequency, the current value, voltage value, and power value of the lighting facilities in the target area under the target strategy control are detected and measured to determine the initial current value, initial voltage value, and initial power value as the initial operating state parameters; Specifically, based on the set acquisition frequency, the system will perform real-time detection of the current, voltage, and power of the lighting facilities in the target area. The current value, voltage value, and power value are key parameters for evaluating the performance of lighting facilities and can reflect the working conditions of lighting facilities. By regularly collecting these data, the system can accurately obtain the initial operating state of the lighting facilities, and these initial parameters provide a basis for subsequent lighting control strategies. This detection can not only help the system monitor the health status of the equipment but also provide feedback for lighting adjustment.

[0046] According to the preset standard current range, standard voltage range, and standard power range, combined with the initial current value, initial voltage value, and initial power value, it is determined whether each lighting facility is qualified for lighting; Specifically, the collected initial current, voltage, and power data are compared and analyzed with the preset standard ranges. The normal operation of lighting facilities should comply with these standard current, standard voltage, and standard power ranges. If the detected current, voltage, or power value exceeds the set standard range, it will be determined that the facility fails to pass the lighting qualification judgment, indicating that there may be equipment failures or abnormal operations. Through this comparison, the health status of lighting equipment can be monitored in real time to ensure the normal operation of lighting facilities and avoid affecting the lighting effect in the area.

[0047] According to the number of lighting facilities that pass the lighting qualification and the total number of lighting facilities in the target area, the lighting qualification rate is calculated; Specifically, the qualified lighting rate is obtained by calculating the ratio of the number of qualified lighting facilities to the total number of lighting facilities in the target area. This indicator can reflect the overall operation effect of the lighting system. A higher qualified lighting rate means that most lighting facilities are working properly and providing sufficient lighting; on the contrary, a lower qualified lighting rate may imply that there are a large number of lighting facility failures and need to be repaired or adjusted. The qualified lighting rate is a key parameter to measure the stability and reliability of the lighting system, which helps to optimize the lighting effect and resource allocation in the area.

[0048] Compare the corrected brightness values of each lighting facility in the target area, and calculate the light uniformity according to the maximum brightness value and the minimum brightness value in the target area.

[0049] Specifically, compare the corrected brightness values of each lighting facility in the target area, and calculate the light uniformity based on the maximum brightness value and the minimum brightness value. The light uniformity is an important indicator to measure the lighting quality, which usually represents the balance of the light distribution in the area. A uniform light distribution helps to reduce shadows and bright spots, ensuring that each part of the area receives appropriate lighting. By analyzing and adjusting the light uniformity, the system can optimize the layout of lighting facilities and lighting strategies, ensuring that the lighting effect of the entire area meets the expected standards, while improving the user's comfort and visual experience.

[0050] In one embodiment, please refer to Figure 7 , the obtaining of the preset operation state parameter template of the lighting facilities in the target area under the target strategy control includes: According to the target strategy, control the lighting facilities in the target area to conduct lighting, and obtain the optimization objectives corresponding to the target area, where the optimization objectives include minimizing the total power consumption in the area, the light uniformity in the area being greater than or equal to a preset uniformity threshold, and the brightness value in the area being greater than a preset brightness threshold; Specifically, start to control the lighting facilities in the target area to conduct lighting according to the target strategy, and obtain the optimization objectives of the target area through real-time monitoring and data analysis. The optimization objectives usually include multiple dimensions. First, it is to minimize the total power consumption in the area, which helps to save energy and reduce operating costs; second, it is to ensure that the light uniformity in the area is greater than or equal to the preset uniformity threshold to ensure the balance of the lighting effect in the area and avoid areas that are too bright or too dark; finally, it is to ensure that the brightness value in the area is greater than the preset brightness threshold to avoid affecting the normal operation of the area function due to insufficient lighting. These optimization objectives provide clear performance indicators for the lighting control system, which helps the system to ensure that the lighting quality meets the requirements while saving energy.

[0051] Determine the constraint conditions according to the optimization objectives; Specifically, relevant constraint conditions are determined based on the above optimization objectives. Constraint conditions refer to the restrictive requirements that must be met during the process of achieving the optimization objectives, including: lighting equipment operating parameter limitations, power grid and system resource constraints, and lighting spatial distribution constraints. For example, the maximum power consumption of lighting facilities may be restricted by the power grid supply capacity, the lighting uniformity must be within a specified range, and the power of each lighting facility cannot exceed its rated value. By clearly defining these constraint conditions, the system can maintain operability and realism during the optimization process, avoiding unrealistic solutions. The constraint conditions ensure the feasibility and safety of the lighting control strategy in practical applications and help the system balance the conflicts between different objectives.

[0052] According to the optimization objective and the constraint conditions, in combination with a multi-objective optimization algorithm, the preset operating state parameter template is determined, where the multi-objective optimization algorithm includes a genetic algorithm and a particle swarm optimization algorithm.

[0053] Specifically, a multi-objective optimization algorithm, such as a genetic algorithm and a particle swarm optimization algorithm, is used to solve for the optimal preset operating state parameter template under the constraint conditions. These algorithms can consider multiple optimization objectives simultaneously and find the optimal solution. The genetic algorithm can efficiently explore the solution space by simulating the process of natural selection and is suitable for solving complex non-linear, multi-objective optimization problems; the particle swarm optimization algorithm simulates the search for the optimal position by a particle swarm in the solution space and has strong global search capabilities, being able to quickly find a solution close to the optimal one. By combining these algorithms, the system can, while meeting the optimization objectives, consider the constraint conditions to obtain a suitable preset operating state parameter template, providing accurate data support for subsequent lighting control.

[0054] In one embodiment, please refer to Figure 8 , adjusting the initial operating state parameters according to the preset operating state parameter template and in combination with the quality evaluation parameters to obtain the target operating state parameters includes: Calculating the difference between the preset operating state parameter template and the initial operating state parameters to obtain the lighting facility state parameter difference; Specifically, by comparing the preset operating state parameter template with the initial operating state parameters, the difference between the two is calculated. These differences represent the deviation between the current state and the optimal state of the lighting facilities, helping the system identify performance defects or non-compliance with the objectives of the lighting equipment. For example, deviations in current, voltage, or power values may indicate insufficient energy efficiency or weak light intensity of the lighting equipment. Through this difference calculation, the system can clarify the aspects that need to be adjusted, thereby providing a necessary basis for subsequent adjustment steps.

[0055] According to the difference value of the lighting facility state parameters, perform the first adjustment on the initial operating state parameters to obtain the adjusted lighting facility state parameters; Specifically, based on the difference value of the lighting facility state parameters, the system will perform the first adjustment on the initial operating state parameters. During the adjustment process, the system will refer to the magnitude of the difference value and gradually correct parameters such as the current and voltage of the lighting facility to make them approach the optimal state and achieve a more ideal lighting effect. For example, if the difference value indicates that the current is too low, the system will increase the current to increase the light intensity; if the difference value indicates that the voltage is too high, the system will reduce the voltage to ensure the long-term stability and energy conservation of the equipment. Through the first adjustment, the operating state of the lighting facility gradually approaches the preset target.

[0056] Perform a weighted fusion calculation on the deviation value between the qualified lighting rate and the preset qualified rate threshold and the deviation value between the lighting uniformity and the preset uniformity threshold to obtain the lighting quality compensation coefficient; Specifically, according to two main parameters of lighting quality: the qualified lighting rate and the lighting uniformity, evaluate whether the lighting effect meets the requirements. First, calculate the deviation value between the qualified lighting rate and the preset qualified rate threshold, and the deviation value between the lighting uniformity and the preset uniformity threshold. These deviation values reflect the degree of defects in the current lighting quality. Then, the system performs a weighted fusion calculation on these two deviation values to obtain a lighting quality compensation coefficient. The weighted fusion process enables the two quality indicators to be assigned different weights according to their importance during the comprehensive scoring, so as to more accurately reflect the severity of the lighting quality problem and guide the next adjustment.

[0057] According to the lighting quality compensation coefficient, perform the second adjustment on the adjusted lighting facility state parameters to obtain the target operating state parameters.

[0058] Specifically, use the lighting quality compensation coefficient to perform the second adjustment on the state parameters of the lighting facility. According to the compensation coefficient calculated in the previous step, the system further adjusts parameters such as the adjusted current, voltage, and power to optimize the lighting effect. The larger the compensation coefficient, the greater the deviation of the lighting quality, and the greater the adjustment amplitude. Conversely, the adjustment amplitude will be reduced. The goal of this step is to ensure that after the first adjustment, the lighting quality (including the qualified lighting rate and the lighting uniformity) meets the preset requirements, and the finally obtained target operating state parameters are the optimal lighting settings. This process not only improves the lighting quality but also ensures the efficient use of energy.

[0059] In one embodiment, please refer to Figure 9 , the performing a weighted fusion calculation on the deviation value between the qualified lighting rate and the preset qualified rate threshold and the deviation value between the lighting uniformity and the preset uniformity threshold to obtain the lighting quality compensation coefficient includes: According to the lighting facility location information, classify the target area into a primary lighting area and a secondary lighting area, and obtain the environmental data of the target area, where the environmental data includes weather and season; Specifically, divide the target area into a primary lighting area and a secondary lighting area through the location information of the lighting facilities. The primary lighting area is usually an area with frequent activities and a higher requirement for lighting quality, while the secondary lighting area is an area with lower requirements. Then, further analyze the lighting requirements of the target area according to the environmental data (such as weather, season). For example, during the day or in sunny weather, the demand for the primary lighting area may be lower, while in winter or on cloudy days, the lighting demand may increase. The acquisition of environmental data helps to dynamically adjust the lighting strategy and make the lighting plan more in line with the actual needs.

[0060] Obtain a first initial weight corresponding to the primary lighting area and a second initial weight corresponding to the secondary lighting area, where the initial weight includes the weight corresponding to the qualified lighting rate and the weight corresponding to the lighting uniformity; Specifically, according to the classification of the target area, assign initial weights to the primary lighting area and the secondary lighting area respectively. The initial weight reflects the requirements of each area for the qualified lighting rate and the lighting uniformity. For example, the primary lighting area usually has higher requirements for the qualified lighting rate and the lighting uniformity, so a higher weight will be given; while the requirements for the secondary lighting area are relatively lower, so the weight is smaller. The setting of the weight enables the system to adjust the lighting control strategy according to the different requirements of the areas and ensure that the lighting effects of different areas meet the expectations.

[0061] According to the environmental data, combined with a preset mapping table between the environmental data and the correction coefficient, perform correction processing on the first initial weight and the second initial weight to determine the first target weight and the second target weight; Specifically, according to the real-time environmental data (such as weather changes and seasonal factors), combine the preset mapping table to correct the initial weight. Environmental factors may affect the lighting demand. For example, the lighting demand increases when the weather is gloomy, and seasonal changes also affect the lighting time and intensity. Through the mapping table, the system combines the environmental data with the correction coefficient to adjust the weights of the primary and secondary areas, and obtains the first target weight and the second target weight. These target weights can more accurately reflect the lighting demand under the current environmental conditions and ensure that the lighting system can provide the most suitable lighting effect in different situations.

[0062] According to the first target weight and the second target weight, perform weighted fusion calculation on the deviation value between the qualified lighting rate and the preset qualified rate threshold and the deviation value between the lighting uniformity and the preset uniformity threshold to obtain a lighting quality compensation coefficient.

[0063] Specifically, by combining the first target weight and the second target weight, a weighted fusion calculation is performed on the deviation between the qualified rate of lit lamps and the preset qualified rate threshold and the deviation between the illumination uniformity and the preset uniformity threshold. According to the aforementioned corrected target weights, the system assigns different weights to the deviation values of the qualified rate of lit lamps and the illumination uniformity, which can more accurately reflect the lighting requirements of different areas. For example, the main lighting area may have higher requirements for illumination uniformity, while the secondary lighting area may pay more attention to the qualified rate of lit lamps. Through the weighted fusion calculation, a lighting quality compensation coefficient is obtained, providing a basis for subsequent adjustments to ensure the optimization of the final lighting effect.

[0064] Embodiment 2

[0065] After controlling the lighting facilities in each area for lighting by using the intelligent control method of DC lighting in the smart city of the above-mentioned Embodiment 1, due to reasons such as the instability of the communication network or equipment failures, the control platform center is prone to disconnection and disconnection with the front-end lighting facilities, resulting in the front-end lighting facilities entering the reset state; when the front-end lighting facilities resume connection, if stable and progressive autonomous adjustment fails to be achieved during the communication interruption period and the equipment is already in a state seriously deviating from the target lighting strategy, directly jumping to the target parameters after recovery may cause lighting mutations, triggering visual discomfort to users or interfering with normal activities; at the same time, large parameter changes may also cause load impacts on the lighting equipment, affecting its lifespan and stability. Therefore, smoothly transitioning through progressive autonomous adjustment during the disconnection period not only helps to maintain the basic usability of environmental lighting and the user experience, but also lays a foundation for the smooth switching and parameter fusion after the system reconnects, thus ensuring the safety, comfort, and continuity of the entire lighting system. For this reason, the intelligent control method of DC lighting adopted by the smart city further includes: Sending a control instruction to the front-end lighting facilities through the control platform center; Specifically, the control platform center generates specific control instructions through an algorithm module based on the real-time data collected by environmental sensors (such as illuminance sensors) deployed in different areas, combined with the geographical location information of the lighting facilities and the lighting strategy model. The control instructions include, but are not limited to, parameters such as lighting brightness level, color temperature setting value, switch state, dimming curve, response delay threshold, etc. The platform sends control instructions to each front-end lighting facility periodically or on demand through a wired or wireless network to ensure that the lighting system maintains dynamic coordination with environmental changes. In addition, when the platform sends control instructions, it will attach a timestamp, a strategy number, and identity authentication information to facilitate the front-end lighting facilities to verify the legality and timeliness of the instructions, ensuring the effective execution of the instructions and enhancing the system security.

[0066] When the front-end lighting facility does not respond to the control instruction, obtain the corresponding non-response duration, and compare the non-response duration with a preset first duration threshold; Specifically, under normal communication conditions, the front-end lighting facility should return a response signal to the platform within a set feedback period after receiving a control instruction. This signal can include receipt confirmation, execution status, or current operating parameter values. When the control platform does not receive the corresponding response within a continuous time period, it records the start time of the non-response and continuously accumulates the non-response time length to form the non-response duration. To avoid misjudgment, a first duration threshold (such as 3 seconds, 5 seconds, or multiple feedback periods) is set, representing the maximum tolerable communication gap time. The platform compares the currently accumulated non-response duration with this threshold. When it exceeds the threshold, it determines that the communication anomaly is not an instantaneous fluctuation, and thus enters the next disconnection handling process. This mechanism enhances the anti-interference ability of the system and avoids the problem of mistakenly switching to the standby mode due to short-term network jitter.

[0067] When the non-response duration is greater than the first duration threshold, it is determined that a disconnection has occurred between the control platform center and the front-end lighting facility, and the backup control strategy and backup operating parameters stored on the front-end lighting facility are obtained; Specifically, once it is determined that a disconnection has occurred between the platform and a certain front-end lighting facility, it enters the local automatic control mode. The front-end lighting facility will automatically call the backup control strategy and backup operating parameters preset in the local non-volatile memory 402. The backup control strategy is a set of strategies downloaded by the platform to the local according to specific scenarios (such as teaching areas, office areas, corridors, etc.) when the platform communication is normal, covering content such as minimum lighting requirements, energy-saving lighting limits, predefined dimming rules, and user safety priorities; the backup operating parameters include the current brightness state, timed execution period, gradient control function, etc., to ensure that the lighting maintains an acceptable, safe, and stable operating state during the disconnection. This design ensures lighting continuity, safety, and user experience stability in the case of disconnection.

[0068] When the front-end lighting facility responds to the control instruction, the corresponding continuous response duration is obtained; Specifically, after the front-end lighting facility receives a control instruction, it will start to execute operations related to this instruction, such as adjusting brightness, color, or switch state. The response of the front-end lighting facility is monitored in real time, and the time interval from receiving the control instruction to the facility making a response is recorded; this time interval is the continuous response duration; the monitoring of this duration is to ensure that the front-end device can respond to the control instruction in a timely and accurate manner, thus ensuring the efficient operation of the lighting system.

[0069] When the continuous response duration is greater than the preset second duration threshold, it is determined that a successful reconnection has occurred between the control platform center and the front-end lighting facility, and the target strategy and the target operating state parameters are obtained; Specifically, once it is detected that the continuous response duration of the front-end lighting facility exceeds the preset second duration threshold, it is considered that the connection between the control platform and the front-end lighting facility has been successfully restored. This means that the temporary disconnection problem that may have occurred due to network or communication interruptions before has been resolved, and effective control of the device can be restarted. After confirming the successful connection, the target policy and target operating status parameters before the disconnection are obtained.

[0070] According to the target policy and the target operating status parameters, the backup control policy and backup operating parameters are adjusted, and the front-end lighting facility is controlled to perform lighting through the adjusted backup control policy and adjusted backup operating parameters.

[0071] Specifically, after obtaining the target policy and target operating status parameters, it is necessary to adjust the backup control policy and backup operating parameters. This step is to ensure that the system can continue to maintain the normal operation of the lighting facility in the event of possible equipment failures, communication interruptions, or other abnormalities. The backup control policy and backup operating parameters are usually the best predictions or default values based on the target policy and the current device status parameters. After adjustment, they can ensure that the lighting facility continues to operate when the system is restored and meets the environmental or user requirements. For example, if the target policy indicates adjusting the lighting to a specific brightness, and the actual operating status of the current device shows that its power supply is slightly insufficient, the backup parameters will be adjusted to select a more energy-efficient mode to avoid overload. Finally, the adjusted backup policy and backup operating parameters will be applied to the front-end lighting facility to ensure that the operation of the device after recovery still meets the expected lighting requirements while ensuring the stability and security of the system.

[0072] In an embodiment, the adjusting the backup control policy and backup operating parameters according to the target policy and the target operating status parameters, and controlling the front-end lighting facility to perform lighting through the adjusted backup control policy and adjusted backup operating parameters includes: Calculating a control parameter difference according to the target policy and the backup control policy, in combination with the target operating status parameters and the backup operating parameters; Specifically, according to the target policy and the backup control policy, in combination with the target operating status parameters and the backup operating parameters, it is first necessary to calculate the difference between them as the control parameter difference. The control parameter difference represents the amount of adjustment required to reach the target operating status from the current backup operating status. For example, assume that the target policy requires adjusting the lighting intensity from the current 100 lux to 300 lux, and the lighting intensity set by the backup control policy in the current state is 150 lux. Then the control parameter difference is 150 lux. This difference is crucial for the subsequent adjustment process as it determines the gap that needs to be overcome during the adjustment.

[0073] Determine the total transition duration required for adjustment according to the difference in the control parameters, and divide the total transition duration into multiple adjustment step stages, where the change amplitude of the control parameters corresponding to each adjustment step stage is not greater than a preset user-perceivable change threshold; Specifically, after calculating the difference in the control parameters, determine the total transition duration required for adjustment according to the difference in the control parameters. The total transition duration refers to the time required to adjust from the current state to the target state; the determination of this duration needs to consider the comfort of user perception and the safety of the device. To avoid discomfort to the user or burden on the device caused by too rapid changes, divide the total transition duration into multiple adjustment step stages according to a preset user-perceivable change threshold. The change amplitude of the control parameters in each adjustment step stage must not exceed the user-perceivable change threshold, so that the user will not feel abrupt or uncomfortable when observing the lighting change. The duration and change amplitude of each stage are usually adjusted according to the response speed of the device and the user experience.

[0074] According to each of the adjustment step stages, calculate the adjustment target value corresponding to each adjustment step stage according to the difference in the control parameters and the number of adjustment step stages; Specifically, with the division of the adjustment step stages, calculate the adjustment target value corresponding to each adjustment step stage according to the difference in the control parameters and the number of adjustment step stages. This means that the system needs to evenly distribute the difference in the control parameters to each stage, so that the adjustment of the control parameters in each stage is smooth and linear. For example, if the difference in the control parameters is 200 lux and the total transition duration is divided into 4 stages, then the control target value for each stage will be 50 lux. The purpose of this is to ensure the stability of the entire adjustment process and avoid inconsistent lighting effects caused by too large or too small adjustment amplitudes.

[0075] According to a preset sending period, send the adjustment target value of the current stage to the front-end lighting facility. When the adjustment target values corresponding to each adjustment step stage and the actual operating state of the front-end lighting facility reach within the parameter threshold range corresponding to the target operating state parameters, obtain the adjusted standby control strategy and adjusted standby operating parameters; Specifically, after calculating the adjustment target value of each adjustment step stage, send the adjustment target value of the current stage to the front-end lighting facility regularly according to a preset sending period. The sending timing and frequency need to match the response ability of the device to ensure that the device can complete the adjustment on time in each adjustment step stage. When the actual operating state of the front-end lighting facility reaches within the parameter threshold range set by the target operating state parameters, obtain the adjusted standby control strategy and standby operating parameters. These adjusted strategies and parameters will ensure that the front-end device can not only achieve the target lighting effect but also maintain the stable and long-term operation of the device during the lighting process.

[0076] Control the front-end lighting facilities for lighting by means of the adjusted standby control strategy and the adjusted standby operating parameters.

[0077] Embodiment 3

[0078] Embodiment 3 of the present invention also provides an intelligent control system for a smart city using DC lighting. The control system includes an intelligent lighting management platform, which is communicatively connected to the control unit. The intelligent lighting management platform includes at least one processor 401, at least one memory 402, and computer program instructions stored in the memory 402. When the computer program instructions are executed by the processor 401, the method described in Embodiment 1 is implemented.

[0079] Specifically, for the intelligent control system for a smart city using DC lighting provided in the embodiment of the present invention, the control system includes an intelligent lighting management platform, as Figure 10 shown Figure 10 is a schematic diagram of the management interface of a national-level intelligent lighting management platform. The management interface displays information on device repair work orders to be processed currently in the form of a list or cards, such as work order numbers, locations of faulty devices, reporting times, processing status (such as "in progress" or "resolved"), etc., for real-time tracking of maintenance tasks; the hourly energy consumption statistics module includes a bar chart or a real-time data table, which displays the energy consumption data (such as electricity consumption, power) of the lighting system by the hour, helping users quickly identify peak daytime energy consumption periods; the monthly energy consumption trend module shows the monthly energy consumption change trend in the form of a line chart or an area chart, comparing the electricity consumption on different dates / weeks, and assisting in long-term energy management decisions; as Figure 11 shown Figure 11 is a schematic diagram of the management interface of a regional-level intelligent lighting management platform. The project statistics module on the left side of the management interface includes global data such as total power, total cumulative consumption, total mileage, etc.; a bar chart and a line chart are juxtaposed to compare the energy consumption trends of yesterday and today. The daily energy consumption total and the daily load curve are supplemented at the bottom of the interface to show the all-day load fluctuations. The regional map module in the middle includes multiple geographical markings: inpatient areas, North Campus, residential areas, communities, banks, old blocks, reservoirs, etc., which distinguish the lighting device status, energy consumption density, or fault alarms of different regions through colors or icons. The real-time monitoring module on the right side includes: real-time current, associated with the operating status of the device; hourly power consumption: a line chart shows the hourly power fluctuations; hourly energy consumption statistics: the energy consumption data is displayed by the hour.

[0080] The intelligent lighting management platform is communicatively connected to the control unit. The intelligent lighting management platform includes at least one processor 401, at least one memory 402, and computer program instructions stored in the memory 402. When the computer program instructions are executed by the processor 401, the method described in Embodiment 1 is implemented. The intelligent control system for DC lighting in a smart city is centered around the collaborative work between the intelligent lighting management platform and the control unit. By integrating multiple technologies such as environmental perception, dynamic regulation, and remote management, a set of efficient, flexible, and highly adaptable lighting control systems is constructed. The system can not only intelligently judge lighting requirements based on real-time collected data such as environmental light, personnel activities, and traffic flow, but also implement differential lighting scheduling in different areas (such as residential, commercial, and transportation hubs) through preset or self-learning dimming strategies. At the same time, the edge control unit has the ability of local data processing and off-grid operation, ensuring the continuous operation of the system in case of communication anomalies. The management platform provides a unified remote monitoring and operation and maintenance interface, enabling energy consumption analysis, fault warning, and remote strategy upgrade, comprehensively improving the intelligent level of the lighting system and the energy-saving efficiency of urban operation. Through the deployment of this system, it is possible to significantly optimize the use of urban lighting energy, reduce maintenance costs, and enhance the safety and livability of urban spaces. The intelligent control system for DC lighting in a smart city precisely combines the position information of lighting facilities, the real-time environmental illuminance, and the preset DC lighting control timing strategy, effectively achieving a balance between energy conservation and lighting effects. First, based on the environmental illuminance in the target area and the position information of lighting facilities, combined with the preset timing control strategy, an accurate lighting control target strategy is generated. By obtaining the initial operating state parameters of lighting facilities and the quality evaluation parameters of the target area, the change in lighting effects can be monitored in real time and compared with the preset operating state template, which is a parameter setting with the optimal energy efficiency and meeting the basic lighting requirements, enabling the lighting facilities to be adjusted to the lowest energy consumption state while ensuring lighting quality. Finally, by precisely adjusting the initial operating state parameters of lighting facilities, the target operating state parameters are obtained, so that under real-time control, both the lighting uniformity and the qualified rate of lighting in the lighting area can be ensured, and unnecessary energy consumption can be significantly reduced, successfully achieving the best balance between energy conservation and lighting effects.

[0081] In addition, in combination with Figure 1 The intelligent control method for DC lighting in a smart city described in Embodiment 1 of the present invention can be implemented by an intelligent lighting management platform. Figure 12 FIG. shows the hardware structure schematic diagram of the intelligent lighting management platform provided in Embodiment 3 of the present invention.

[0082] The intelligent lighting management platform may include a processor 401 and a memory 402 storing computer program instructions.

[0083] Specifically, the above-mentioned processor 401 may include a central processing unit 401 (CPU), or an application specific integrated circuit (ASIC), or may be configured as one or more integrated circuits for implementing the embodiments of the present invention.

[0084] The memory 402 may include a mass memory 402 for data or instructions. By way of example and not limitation, the memory 402 may include a hard disk drive (HDD), a floppy disk drive, a flash memory, an optical disc, a magneto-optical disc, a magnetic tape, or a universal serial bus (USB) drive, or a combination of two or more of these. In a suitable case, the memory 402 may include a removable or non-removable (or fixed) medium. In a suitable case, the memory 402 may be internal or external to the data processing device. In a specific embodiment, the memory 402 is a non-volatile solid state memory 402. In a specific embodiment, the memory 402 includes a read-only memory 402 (ROM). In a suitable case, the ROM may be a mask-programmed ROM, a programmable ROM (PROM), an erasable PROM (EPROM), an electrically erasable PROM (EEPROM), an electrically rewritable ROM (EAROM), or a flash memory, or a combination of two or more of these.

[0085] The processor 401 reads and executes the computer program instructions stored in the memory 402 to implement any one of the intelligent control methods for smart cities using DC lighting in the above embodiments.

[0086] In one example, the intelligent lighting management platform may further include a communication interface 403 and a bus 410. Among them, as Figure 12 shown, the processor 401, the memory 402, and the communication interface 403 are connected through the bus 410 and complete communication with each other.

[0087] The communication interface 403 is mainly used to implement communication between the various modules, devices, units, and / or devices in the embodiments of the present invention.

[0088] Bus 410 includes hardware, software, or both, and couples components of the device to each other. By way of example and not limitation, bus 410 may include an Accelerated Graphics Port (AGP) or other graphics bus, an Enhanced Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), a HyperTransport (HT) interconnect, an Industry Standard Architecture (ISA) bus, an InfiniBand interconnect, a Low Pin Count (LPC) bus, a memory bus, a MicroChannel Architecture (MCA) bus, a Peripheral Component Interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a Serial Advanced Technology Attachment (SATA) bus, a Video Electronics Standards Association Local (VLB) bus, or other suitable bus or a combination of two or more of these. Where appropriate, bus 410 may include one or more buses. Although embodiments of the invention describe and illustrate a particular bus, the invention contemplates any suitable bus or interconnect.

[0089] In summary, embodiments of the present invention provide an intelligent control method and system for a smart city using DC lighting.

[0090] It should be clear that the present invention is not limited to the specific configurations and processes described above and shown in the figures. For the sake of brevity, detailed descriptions of known methods are omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method process of the present invention is not limited to the specific steps described and shown, and those skilled in the art can make various changes, modifications, and additions, or change the order between steps after understanding the spirit of the present invention.

[0091] The functional blocks shown in the above block diagrams can be implemented as hardware, software, firmware, or a combination thereof. When implemented in hardware, it can be, for example, an electronic circuit, an Application Specific Integrated Circuit (ASIC), appropriate firmware, a plug-in, a functional card, and so on. When implemented in software, the elements of the present invention are programs or code segments for performing the required tasks. The program or code segment can be stored in a machine-readable medium or transmitted via a data signal carried in a carrier wave over a transmission medium or a communication link. "Machine-readable medium" can include any medium capable of storing or transmitting information. Examples of machine-readable media include electronic circuits, semiconductor memory devices, ROMs, flash memories, Erasable ROMs (EROMs), floppy disks, CD-ROMs, optical discs, hard disks, fiber optic media, radio frequency (RF) links, and so on. The code segment can be downloaded via a computer network such as the Internet, an intranet, and so on.

[0092] The user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, displayed data, etc.) involved in this application are all information and data that have been authorized by the user or fully authorized by all parties. Moreover, the collection, use, and processing of relevant data need to comply with relevant laws, regulations, and standards in the relevant location, and corresponding operation entrances are provided for users to choose to authorize or reject.

[0093] It should also be noted that the exemplary embodiments mentioned in the present invention describe some methods or systems based on a series of steps or devices. However, the present invention is not limited to the order of the above steps. That is to say, the steps can be executed in the order mentioned in the embodiments, can be different from the order in the embodiments, or several steps can be executed simultaneously.

[0094] As mentioned above, the above are only specific implementation manners of the present invention. Those skilled in the art can clearly understand that for the convenience and brevity of description, the specific working processes of the above-described systems, modules, and units can refer to the corresponding processes in the foregoing method embodiments and will not be elaborated herein. It should be understood that the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention can easily think of various equivalent modifications or substitutions, and these modifications or substitutions should all be covered within the protection scope of the present invention.

Claims

1. An intelligent control method for DC lighting in a smart city, characterized in that: The method comprises: According to the location information of lighting facilities in a target area of ​​an urban DC lighting scene and the real-time ambient light intensity, combined with the preset timing strategy of DC lighting control, a target strategy of DC lighting control is obtained; According to the target strategy, the lighting facility is controlled to perform lighting, and initial operating state parameters of the lighting facility and quality evaluation parameters of the lighting in the target area are obtained, wherein the initial operating state parameters include an initial current value, an initial voltage value, and an initial power value, and the quality evaluation parameters include a lighting pass rate and light uniformity; Acquire a preset operating state parameter template of the lighting facilities in the target area under the control of the target strategy, wherein the preset operating state parameter template is an operating state parameter collected when the basic lighting demand of the target area is met and the energy consumption is minimized; According to the preset operating state parameter template and in combination with the quality evaluation parameter, the initial operating state parameter is adjusted to obtain the target operating state parameter; According to the target strategy and the target operating state parameters, the lighting facilities in the target area are controlled to perform lighting.

2. The intelligent control method for DC lighting in smart cities according to claim 1 is characterized in that: The target strategy of DC lighting control is obtained based on the lighting facility location information and real-time ambient light illumination in a target area of ​​an urban DC lighting scene, combined with a preset DC lighting control timing strategy, including: According to the lighting facility location information, obtaining a target area attribute category; According to the timing strategy and the target area attribute category, obtaining the inter-cycle lighting strategy and the intra-cycle lighting strategy, wherein the lighting strategy includes a lighting on time point, a lighting off time point and a lighting brightness level; Comparing the real-time ambient light illumination with a preset light illumination threshold, and judging whether it is necessary to adjust the inter-cycle lighting strategy and the intra-cycle lighting strategy according to the comparison result; When the inter-cycle lighting strategy and the intra-cycle lighting strategy need to be adjusted, the target area level and the target reference illuminance are obtained according to the target area attribute category; According to the target area level and the target reference light illuminance, the inter-cycle lighting strategy and the intra-cycle lighting strategy are adjusted to obtain the target strategy.

3. The intelligent control method for DC lighting in smart cities according to claim 2 is characterized in that: The step of adjusting the inter-cycle lighting strategy and the intra-cycle lighting strategy according to the target area level and the target reference light illuminance to obtain the target strategy includes: According to the target area level, obtaining a light intensity adjustment weight; Calculating an illumination deviation value according to the target reference illumination and the real-time ambient illumination; Calculating an illumination correction coefficient according to the illumination deviation value and the illumination adjustment weight; According to the illumination correction coefficient, the original brightness value corresponding to the illumination brightness level is corrected to obtain a corrected brightness value; According to the preset lighting time adjustment step and the illuminance deviation value, the lighting on time point and / or the lighting off time point are corrected to obtain a corrected on time point and / or a corrected off time point; The target strategy is determined according to the corrected brightness value, the corrected turn-on time point and / or the corrected turn-off time point.

4. The intelligent control method for DC lighting in smart cities according to claim 3 is characterized in that: The calculating the illumination correction coefficient according to the illumination deviation value and the illumination adjustment weight comprises: According to the target area attribute category, selecting a light intensity correction mathematical model corresponding to the scene, wherein the mathematical model is used to describe the nonlinear relationship between the light intensity deviation value and the light intensity correction coefficient, and the mathematical model includes an exponential function model and a piecewise linear function model; Substituting the illuminance deviation value and the illuminance adjustment weight as input variables into the illuminance correction mathematical model to obtain an initial illuminance correction coefficient; According to a preset correction coefficient interval, the initial illumination correction coefficient is normalized to obtain the illumination correction coefficient.

5. The intelligent control method for DC lighting in smart cities according to claim 3 is characterized in that: The step of correcting the lighting on time point and / or the lighting off time point according to the preset lighting time adjustment step and the illuminance deviation value to obtain the corrected on time point and / or the corrected off time point includes: According to the target area attribute category, a time correction sensitivity parameter is obtained, wherein the time correction sensitivity parameter is used to characterize the response sensitivity of different areas to the adjustment of the lighting on and off time; Acquire the lighting time adjustment step, wherein the lighting time adjustment step is used to represent the basic time adjustment amplitude corresponding to the unit illuminance deviation value; Calculating a basic time offset according to the illumination deviation value and the lighting time adjustment step; According to a preset segmented time adjustment function, the basic time offset is adjusted to obtain an adjusted time offset, wherein the segmented time adjustment function distinguishes different adjustment speeds according to the magnitude of the illumination deviation value; According to the time correction sensitivity parameter, the adjusted time offset is corrected to obtain a target time offset; According to the target time offset, the lighting on time point and / or the lighting off time point are corrected to obtain a corrected on time point and / or a corrected off time point.

6. The intelligent control method for DC lighting in smart cities according to claim 3 is characterized in that: According to the target strategy, controlling the lighting facilities to perform lighting, and obtaining the initial operating state parameters of the lighting facilities and the quality evaluation parameters of the lighting in the target area include: According to the target area level, obtaining the data collection frequency corresponding to the area level; According to the data collection frequency, current value detection, voltage value detection and power value calculation are performed on the lighting facilities in the target area under the control of the target strategy, and an initial current value, an initial voltage value and an initial power value are determined as the initial operating state parameters; According to the preset standard current range, standard voltage range and standard power range, combined with the initial current value, initial voltage value and initial power value, it is judged whether each lighting facility is qualified to light up; The lighting pass rate is calculated based on the number of lighting facilities that are qualified and the total number of lighting facilities in the target area; The corrected brightness values ​​of the lighting facilities in the target area are compared, and the illumination uniformity is calculated based on the maximum brightness value and the minimum brightness value in the target area.

7. The intelligent control method for DC lighting in smart cities according to claim 2 is characterized in that: The step of obtaining a preset operating status parameter template of lighting facilities in a target area under the control of the target strategy includes: According to the target strategy, the lighting facilities in the target area are controlled to perform lighting, and the optimization target corresponding to the target area is obtained, wherein the optimization target includes minimizing the total power consumption in the area, the illumination uniformity in the area is greater than or equal to a preset uniformity threshold, and the brightness value in the area is greater than a preset brightness threshold; Determining constraint conditions according to the optimization objective; According to the optimization target and the constraint condition, the preset operation status parameter template is determined in combination with a multi-objective optimization algorithm, wherein the multi-objective optimization algorithm includes a genetic algorithm and a particle swarm optimization algorithm.

8. The intelligent control method for DC lighting in a smart city according to any one of claims 1 to 7, characterized in that: The adjusting the initial operating state parameters according to the preset operating state parameter template and in combination with the quality evaluation parameters to obtain the target operating state parameters comprises: Performing difference calculation on the preset operating state parameter template and the initial operating state parameter to obtain a lighting facility state parameter difference; According to the lighting facility state parameter difference, the initial operation state parameter is adjusted for the first time to obtain the adjusted lighting facility state parameter; Perform weighted fusion calculation on the deviation value between the lighting qualified rate and the preset qualified rate threshold and the deviation value between the illumination uniformity and the preset uniformity threshold to obtain the lighting quality compensation coefficient; According to the lighting quality compensation coefficient, the adjusted lighting facility state parameter is adjusted for the second time to obtain the target operating state parameter.

9. The intelligent control method for DC lighting in smart cities according to claim 8 is characterized in that: The weighted fusion calculation of the deviation between the lighting qualified rate and the preset qualified rate threshold and the deviation between the illumination uniformity and the preset uniformity threshold to obtain the lighting quality compensation coefficient includes: According to the lighting facility location information, the target area is classified into a primary lighting area and a secondary lighting area, and environmental data of the target area is acquired, wherein the environmental data includes weather and season; Obtaining a first initial weight corresponding to the main lighting area and a second initial weight corresponding to the secondary lighting area, wherein the initial weights include a weight corresponding to the lighting pass rate and a weight corresponding to the illumination uniformity; According to the environmental data, in combination with a preset mapping table between the environmental data and the correction coefficient, the first initial weight and the second initial weight are corrected to determine a first target weight and a second target weight; According to the first target weight and the second target weight, a weighted fusion calculation is performed on the deviation value between the lighting qualified rate and the preset qualified rate threshold and the deviation value between the illumination uniformity and the preset uniformity threshold to obtain a lighting quality compensation coefficient.

10. An intelligent control system for DC lighting in a smart city, characterized in that: The control system includes an intelligent lighting management platform, which is communicatively connected to the control unit. The intelligent lighting management platform includes at least one processor, at least one memory and computer program instructions stored in the memory. When the computer program instructions are executed by the processor, the method described in any one of claims 1 to 9 is implemented.

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