Intelligent Control Method and System for DC Lighting in Smart City

Abstract

The present invention relates to the technical field of smart city lighting, solves the problem in the prior art that the balance between energy saving and lighting effect cannot be achieved, and provides an intelligent control method and system for direct current lighting in a smart city. The method includes: obtaining a target strategy according to the position information of lighting facilities and the real-time ambient illuminance in a target area under the direct current lighting scenario of the city, in combination with a timing strategy; controlling the lighting facilities to perform lighting according to the target strategy, and obtaining initial operation state parameters and quality evaluation parameters; obtaining a preset operation state parameter template of the lighting facilities in the target area under the control of the target strategy; adjusting the initial operation state parameters according to the preset operation state parameter template in combination with the quality evaluation parameters to obtain target operation state parameters; controlling the lighting facilities in the target area to perform lighting according to the target strategy and the target operation state parameters. The present invention can improve the lighting effect of the city on the premise of energy saving.

Description

Technical Field

[0001] The present invention relates to the technical field of smart city lighting, and in particular, 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, it is usually difficult for them to achieve 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 qualified rate of lighting, 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 the brightness, due to the lack of close integration with real-time environmental 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, which is used to solve the problem that the balance between energy saving and lighting effect cannot be achieved in the existing lighting control technology for smart cities.

[0007] The technical solution adopted by the present invention is as follows:

[0008] In a first aspect, the present invention provides an intelligent control method for DC lighting in a smart city, and the method includes:

[0009] According to the position information of lighting facilities and the real-time ambient light intensity in a target area in the DC lighting scenario of the city, combined with the preset timing strategy for DC lighting control, obtain the target strategy for DC lighting control;

[0010] According to the target strategy, control the lighting facilities to conduct 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;

[0011] Obtain the preset operating state parameter template of the lighting facilities in the target area under the control of the target strategy. Among them, 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;

[0012] According to the preset operating state parameter template, combined with the quality evaluation parameters, adjust the initial operating state parameters to obtain the target operating state parameters;

[0013] According to the target strategy and the target operating state parameters, control the lighting facilities in the target area to conduct lighting.

[0014] 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.

[0015] In summary, the beneficial effects of the present invention are as follows:

[0016] The intelligent control method and system for smart cities provided by the present invention using DC lighting effectively achieve a balance between energy conservation and lighting effects by precisely combining the location information of lighting facilities, the real-time ambient light intensity, and the preset DC lighting control timing strategy. First, based on the ambient light intensity 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 lighting qualification rate of 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

[0017] 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 them are within the protection scope of the present invention.

[0018] Figure 1 It is a schematic flowchart of the overall operation of the intelligent control method for smart cities using DC lighting in Embodiment 1 of the present invention;

[0019] Figure 2 It is a schematic flowchart of obtaining the target strategy for DC lighting control in Embodiment 1 of the present invention;

[0020] Figure 3 It is a schematic flowchart of adjusting the lighting strategy during the period and the lighting strategy within the period in Embodiment 1 of the present invention;

[0021] Figure 4 It is a schematic flowchart of calculating the light intensity correction coefficient in Embodiment 1 of the present invention;

[0022] Figure 5 It is a schematic flowchart of correcting the lighting start time point and / or the lighting end time point in Embodiment 1 of the present invention;

[0023] Figure 6 It is a schematic flowchart 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;

[0024] Figure 7Schematic flowchart of obtaining a preset operation state parameter template of lighting facilities in a target area under the control of the target policy in Embodiment 1 of the present invention;

[0025] Figure 8 Schematic flowchart of adjusting the initial operation state parameters to obtain target operation state parameters in Embodiment 1 of the present invention;

[0026] Figure 9 Schematic flowchart of weighted fusion calculation of 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 in Embodiment 1 of the present invention;

[0027] Figure 10 Schematic diagram of the management interface of the national-level intelligent lighting management platform in Embodiment 3 of the present invention;

[0028] Figure 11 Schematic diagram of the management interface of the area-level intelligent lighting management platform in Embodiment 3 of the present invention;

[0029] Figure 12 Schematic diagram of the structure of the intelligent lighting management platform in Embodiment 3 of the present invention. Detailed implementation manners

[0030] 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 order 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 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 therefore should not be construed as a limitation of the present invention. Moreover, the term "comprising", "including" or any other variation thereof is intended to cover a non-exclusive inclusion, so that a process, method, article or device comprising a series of elements not only includes those elements, but also includes other elements not expressly listed, or elements inherent to such process, method, article or device. Without further limitation, elements defined by the statement "comprising..." do not preclude the existence of additional identical elements in the process, method, article or device comprising 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.

[0031] Embodiment 1

[0032] 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:

[0033] According to the position information of lighting facilities and the real-time ambient light intensity in a target area under the urban direct current lighting scenario, and in combination with a preset timing strategy for direct current lighting control, obtain a target strategy for direct current lighting control;

[0034] Specifically, first collect the position data of all lighting facilities and the real-time ambient light intensity 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 light at different positions within the area. The real-time ambient light intensity data is used to understand the current natural lighting conditions in real time, so as to avoid providing excessive artificial lighting when the light is sufficient. Next, by combining the preset timing strategy for direct current lighting control (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 within the area, and ensures that the lighting requirements in the target area are met at different time periods.

[0035] 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;

[0036] Specifically, according to the foregoing target strategy, the system controls the lighting facilities to start working and adjusts parameters such as their brightness. At this time, the system will obtain the initial operating state parameters of each lighting facility in real time, including current, voltage, 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 (that is, the proportion of each lamp working normally and meeting the requirements) and the lighting uniformity (that is, 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.

[0037] 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;

[0038] 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 under 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 regional requirements.

[0039] According to the preset operating state parameter template, combined with the quality evaluation parameters, adjust the initial operating state parameters to obtain the target operating state parameters;

[0040] Specifically, it is adjusted based on a preset operating status parameter template, quality evaluation parameters collected in real time, and initial operating status parameters. Quality evaluation parameters (such as the qualified rate of lit lamps and lighting uniformity) provide feedback on the lighting effect, helping the system determine whether the current lighting meets the standards. When it is found that the lighting effect is poor (such as uneven lighting or insufficient lighting in some areas), the system will optimize and adjust by regulating 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 in different environments and energy consumption is minimized to the greatest extent.

[0041] According to the target strategy and the target operating status parameters, control the lighting facilities in the target area for lighting.

[0042] Specifically, based on the adjusted target operating status parameters, the system controls the working status of the lighting facilities again. The target operating status parameters are obtained by adjusting and optimizing the initial operating status, 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 in different time periods and 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, can respond to external environmental changes in real time, and ensures that the lighting system is always in the best operating state.

[0043] In one embodiment, please refer to Figure 2 , the obtaining of the target strategy for DC lighting control according to the position information of the lighting facilities in the target area and the real-time ambient illuminance in the urban DC lighting scenario, combined with the preset timing strategy for DC lighting control, includes:

[0044] Obtain the target area attribute category according to the lighting facility position information;

[0045] Specifically, by obtaining the specific position information of the lighting facilities and combining the regional characteristics such as the urban planning, road type, commercial area or residential area where the position 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.

[0046] Obtain the inter - cycle lighting strategy and intra - cycle 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;

[0047] Specifically, according to the attribute category of the target area and the preset timing lighting control strategy, formulate the corresponding inter - cycle lighting strategy and intra - cycle lighting strategy. The inter - cycle lighting strategy includes the lighting plan information for weekdays and holidays, while the intra - cycle 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, the commercial area may quickly turn on the lighting at dusk and maintain a high brightness, while the residential area 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 it can not only meet the lighting needs but also save energy consumption.

[0048] Compare the real - time ambient light intensity with the preset light intensity threshold, and judge whether it is necessary to adjust the inter - cycle lighting strategy and the intra - cycle lighting strategy according to the comparison result;

[0049] 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 it is necessary to turn on the lighting facilities 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 the lighting equipment is always accurately adjusted according to the actual light conditions, avoiding turning on or continuously lighting in unnecessary situations, so as to achieve the purpose of energy conservation.

[0050] When it is necessary to adjust the inter - cycle lighting strategy and the intra - cycle lighting strategy, obtain the target area level and the target reference light intensity according to the target area attribute category;

[0051] Specifically, if after comparing the real - time light intensity with the threshold, it is found that it is necessary to adjust the inter - cycle lighting strategy and the intra - cycle 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, the main traffic arteries may be given a higher level, requiring stronger lighting intensity and longer lighting periods; while the 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 to ensure that the lighting effect meets the actual needs when adjusting the strategy.

[0052] Adjust 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.

[0053] Specifically, adjust the inter-cycle lighting strategy and the intra-cycle lighting strategy according to the target area level and the target reference illuminance. 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 classified as a high-level area, higher brightness and longer lighting periods may be required; 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 strategies will form the target strategy, ensuring that the lighting effect in the target area can not only meet the functional requirements but also achieve the energy-saving goal.

[0054] In one embodiment, please refer to Figure 3 , the adjusting 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:

[0055] Obtain the illuminance adjustment weight according to the target area level;

[0056] 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 illuminance adjustment according to the functional requirements of different areas, ensuring that the lighting effect matches the importance of the area.

[0057] Calculate the illuminance deviation value according to the target reference illuminance and the real-time ambient illuminance;

[0058] Specifically, calculate the illuminance deviation value between the real-time ambient illuminance and the target reference illuminance by comparison. If the actual illuminance is lower than the target illuminance, it means that the lighting brightness needs to be increased; otherwise, 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 meets the lighting requirements while avoiding unnecessary energy waste.

[0059] Calculate the illuminance correction coefficient according to the illuminance deviation value and the illuminance adjustment weight;

[0060] Specifically, once the illuminance deviation value is calculated, a 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.

[0061] According to the illuminance correction coefficient, the original brightness value corresponding to the illumination brightness level is corrected to obtain a corrected brightness value;

[0062] 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, thus 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.

[0063] 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;

[0064] 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 users 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.

[0065] According to the corrected brightness value, the corrected start time point and / or the corrected end time point, the target strategy is determined.

[0066] In one embodiment, please refer to Figure 4 , the calculating the illuminance correction coefficient according to the illuminance deviation value and the illuminance adjustment weight includes:

[0067] 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;

[0068] 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 can better meet the gentle lighting adjustment requirements through piecewise linear fitting. For example, the exponential function model obtained according to the attribute category of the target area 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;

[0069] Another example, the piecewise linear function model obtained according to the attribute category of the target area 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 in the second segment to ensure the continuity of the second segment and the first segment at L1; B2 represents the constant value in the third segment, indicating the maximum or saturation value that the illuminance correction coefficient maintains when ΔL exceeds L2, 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;

[0070] 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 corresponding illuminance correction function models according to the attribute categories of different target regions, it can more accurately meet the actual needs of various scenarios for lighting adjustment. Residential areas are usually more sensitive to lighting changes and pursue a mild and comfortable lighting experience. Therefore, it is suitable to adopt a 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. In commercial areas or transportation hubs where lighting demands fluctuate violently and change rapidly, an 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 system's adaptability to environmental changes and the overall energy efficiency control level are enhanced.

[0071] Substitute 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.

[0072] Specifically, take the calculated illuminance deviation value and illuminance adjustment weight as input variables and substitute them 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 amplitude of the correction coefficient according to the importance and function of the target region. 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 regions and environmental changes and generate a reasonable preliminary correction coefficient.

[0073] Normalize the initial illuminance correction coefficient according to the preset correction coefficient interval to obtain the illuminance correction coefficient.

[0074] 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 safe range of the system or affect the quality of the lighting effect when adjusting lighting equipment.

[0075] In one embodiment, please refer toFigure 5 , adjusting the lighting start time point and / or the lighting end time point according to the preset lighting time adjustment step and the illuminance deviation value to obtain the corrected start time point and / or the corrected end time point includes:

[0076] 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 lighting start and end times;

[0077] Specifically, determine the response sensitivity of the area to the adjustment of lighting start and end times 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 business district may have a higher sensitivity to lighting adjustment because strong lighting support is needed during peak business hours; while residential areas are more tolerant of lighting time adjustment. 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.

[0078] Obtain the lighting time adjustment step, where the lighting time adjustment step is used to characterize the basic time adjustment amplitude corresponding to the unit illuminance deviation value;

[0079] Specifically, obtain the lighting time adjustment step. The lighting time adjustment step refers to the basic adjustment amplitude of the lighting start or end 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 area's requirements 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 adjustments meet the actual needs of the area.

[0080] Calculate a basic time offset according to the illuminance deviation value and the lighting time adjustment step;

[0081] Specifically, based on the illuminance deviation value and the lighting time adjustment step, calculate the basic time offset. The illuminance deviation value represents the gap between the current environmental 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 required for the lighting start or end time.

[0082] Adjust the base time offset according to a preset segmented time adjustment function to obtain an adjusted time offset, where the segmented time adjustment function distinguishes different adjustment speeds according to the magnitude of the illuminance deviation value;

[0083] Specifically, correct the base time offset according to a preset segmented time adjustment function. The segmented time adjustment function defines 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 segmented time adjustment function can be set as: where ΔL represents the illuminance deviation value, with the unit of lux; N represents a coefficient used to adjust the lighting response speed, and multiplying it by the base time offset gives the adjusted time offset.

[0084] By setting the 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 slow adjustment speed to avoid frequent adjustments 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 while also taking into account energy conservation and smooth operation, and is particularly suitable for smart lighting scenarios where the environment changes frequently and flexible response is required.

[0085] Correct the adjusted time offset according to the time correction sensitivity parameter to obtain a target time offset;

[0086] Specifically, further correct the adjusted time offset 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 a commercial area, regions with higher sensitivity may require more refined time correction to meet the lighting needs of high-density activities; while in a relatively quiet residential area, 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 conforms to the specific requirements of the region.

[0087] Correct the lighting on time point and / or the lighting off time point according to the target time offset to obtain a corrected on time point and / or a corrected off time point.

[0088] 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 will be applied to the lighting on time point and / or off time point to optimize the lighting schedule. For example, in the case of insufficient light, the system may turn on the lighting earlier, while in the case of excessive light, the system will delay turning off the lighting. This process ensures that the lighting system can flexibly respond to environmental changes, and also effectively balances the lighting effect and energy efficiency optimization.

[0089] In one embodiment, please refer to Figure 6 , controlling the lighting facilities to perform lighting according to the target strategy, and obtaining the initial operation state parameters of the lighting facilities and the quality evaluation parameters of the lighting in the target area includes:

[0090] According to the target area level, obtain the data collection frequency corresponding to this area level;

[0091] Specifically, the corresponding data collection 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, high-level areas such as commercial centers and transportation hubs have large changes in lighting needs and require more accurate real-time monitoring, so a higher data collection frequency will be set; while for lower-level areas, such as residential areas or parks, a lower collection frequency may be sufficient. By assigning reasonable data collection frequencies to each area level, the system can ensure the flexibility and efficiency of lighting management while avoiding unnecessary data redundancy.

[0092] According to the data collection frequency, perform current value detection, voltage value detection and power value calculation on the lighting facilities in the target area under the control of the target strategy, and determine the initial current value, initial voltage value and initial power value as the initial operation state parameters;

[0093] Specifically, based on the set collection frequency, the system will perform real-time detection of current, voltage and power on 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 operation 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.

[0094] 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, judge whether each lighting facility is qualified for lighting;

[0095] Specifically, compare and analyze the collected initial current, voltage, and power data 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 is determined that the facility fails the judgment of passing the lighting qualification, 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.

[0096] Calculate the lighting qualification rate based on the number of lighting facilities that pass the lighting qualification and the total number of lighting facilities in the target area.

[0097] Specifically, obtain the lighting qualification rate by calculating the ratio of the number of lighting facilities that pass the lighting qualification 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 lighting qualification rate means that most lighting facilities are working properly and providing sufficient lighting; on the contrary, a lower lighting qualification rate may imply that there are a large number of lighting facility failures and need to be repaired or adjusted. The lighting qualification 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.

[0098] Compare the corrected brightness values of each lighting facility in the target area, and calculate the illumination uniformity based on the maximum brightness value and the minimum brightness value in the target area.

[0099] Specifically, compare the corrected brightness values of each lighting facility in the target area, and calculate the illumination uniformity based on the maximum brightness value and the minimum brightness value. The illumination uniformity is an important indicator to measure the lighting quality, usually indicating the balance of the light distribution in the area. Uniform light distribution helps to reduce shadows and bright spots, ensuring that each part of the area obtains appropriate lighting. By analyzing and adjusting the illumination uniformity, the system can optimize the layout of lighting facilities and lighting strategies to ensure that the lighting effect of the entire area meets the expected standards, while improving the user's comfort and visual experience.

[0100] In an 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:

[0101] According to the target strategy, control the lighting facilities in the target area to perform lighting, and obtain the optimization target corresponding to the target area, where the optimization target includes minimizing the total power consumption in the area, the illumination 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;

[0102] Specifically, according to the target strategy, start controlling the lighting facilities in the target area for lighting, and obtain the optimization objectives of the target area through real-time monitoring and data analysis. The optimization objectives usually include multiple dimensions. First, minimize the total power consumption in the area, which helps to save energy and reduce operating costs. Second, ensure that the lighting uniformity in the area is greater than or equal to the preset uniformity threshold to guarantee a balanced lighting effect in the area and avoid over-bright or over-dark areas. Finally, ensure that the brightness value in the area is greater than the preset brightness threshold to prevent the normal operation of the area function from being affected due to insufficient lighting. These optimization objectives provide clear performance indicators for the lighting control system, helping the system to ensure that the lighting quality meets the requirements while saving energy.

[0103] Determine the constraint conditions according to the optimization objectives;

[0104] Specifically, determine the relevant constraint conditions based on the above optimization objectives. Constraint conditions refer to the restrictive requirements that must be met in the process of achieving the optimization objectives, including: lighting equipment working parameter limitations, power grid and system resource constraints, and lighting spatial distribution constraints. For example, the maximum power consumption of the lighting facilities may be limited 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 reality during the optimization process and avoid 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.

[0105] According to the optimization objectives and the constraint conditions, combined with the multi-objective optimization algorithm, determine the preset operating state parameter template, where the multi-objective optimization algorithm includes the genetic algorithm and the particle swarm optimization algorithm.

[0106] Specifically, adopt a multi-objective optimization algorithm, such as the genetic algorithm and the particle swarm optimization algorithm, to solve 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 particle swarm searching for the optimal position in the solution space and has strong global search ability, which can quickly find a solution close to the optimal. By combining these algorithms, the system can consider the constraint conditions while meeting the optimization objectives, obtain a suitable preset operating state parameter template, and provide accurate data support for subsequent lighting control.

[0107] In one embodiment, please refer to Figure 8, adjusting the initial operating state parameters according to the preset operating state parameter template in combination with the quality evaluation parameters to obtain target operating state parameters includes:

[0108] Calculating the difference between the preset operating state parameter template and the initial operating state parameters to obtain the lighting facility state parameter difference;

[0109] Specifically, by comparing the preset operating state parameter template with the initial operating state parameters, the differences between the two are 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 target 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, thus providing a necessary basis for subsequent adjustment steps.

[0110] According to the lighting facility state parameter difference, performing a first adjustment on the initial operating state parameters to obtain the adjusted lighting facility state parameters;

[0111] Specifically, based on the lighting facility state parameter difference, the system will perform a first adjustment on the initial operating state parameters. The adjustment process will refer to the magnitude of the difference and gradually correct parameters such as the current and voltage of the lighting facilities to make them closer to the optimal state and achieve a more ideal lighting effect. For example, if the difference indicates that the current is too low, the system will increase the current to increase the light intensity; if the difference 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 facilities gradually approaches the preset target.

[0112] 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;

[0113] Specifically, according to two main parameters of lighting quality: the qualified lighting rate and the lighting uniformity, to 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 defect of 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.

[0114] According to the lighting quality compensation coefficient, performing a second adjustment on the adjusted lighting facility state parameters to obtain the target operating state parameters.

[0115] Specifically, a lighting quality compensation coefficient is used to perform a second adjustment on the status parameters of the lighting facilities. Based on the compensation coefficient calculated in the previous step, the system further adjusts the 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 rate of lighting and the lighting uniformity) reaches the preset requirements, and the final target operating status parameters are the optimal lighting settings. This process not only improves the lighting quality but also ensures the efficient use of energy.

[0116] In one embodiment, please refer to Figure 9 , the 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 to obtain the lighting quality compensation coefficient includes:

[0117] According to the lighting facility location information, the target area is classified into a main lighting area and a secondary lighting area, and the environmental data of the target area is obtained, where the environmental data includes weather and season;

[0118] Specifically, through the location information of the lighting facilities, the target area is divided into a main lighting area and a secondary lighting area. The main lighting area is usually an area with frequent activities and higher lighting quality requirements, while the secondary lighting area is an area with lower requirements. Then, according to the environmental data (such as weather, season), the lighting requirements of the target area are further analyzed. For example, during the day or in sunny weather, the demand for the main lighting area may be lower, while in winter or cloudy days, the lighting demand may increase. The acquisition of environmental data helps to dynamically adjust the lighting strategy and make the lighting scheme more in line with the actual needs.

[0119] Obtain the first initial weight corresponding to the main lighting area and the second initial weight corresponding to the secondary lighting area, where the initial weight includes the weight corresponding to the qualified rate of lighting and the weight corresponding to the lighting uniformity;

[0120] Specifically, according to the classification of the target area, initial weights are assigned to the main lighting area and the secondary lighting area respectively. The initial weight reflects the requirements of each area for the qualified rate of lighting and the lighting uniformity. For example, the main lighting area usually has higher requirements for the qualified rate of lighting and the lighting uniformity, so higher weights will be assigned; while the requirements for the secondary lighting area are relatively lower, so the weights are smaller. The setting of the weights 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.

[0121] According to the environmental data, in combination 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;

[0122] Specifically, according to the real-time environmental data (such as weather changes and seasonal factors), the initial weight is corrected in combination with the preset mapping table. 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, thereby adjusting the weights of the main and secondary areas to obtain the first target weight and the second target weight. These target weights can more accurately reflect the lighting demand under the current environmental conditions, ensuring that the lighting system can provide the most suitable lighting effect in different situations.

[0123] 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 the lighting quality compensation coefficient.

[0124] Specifically, in combination with the first target weight and the second target weight, perform weighted fusion calculation on the deviation between the qualified lighting rate and the preset qualified rate threshold and the deviation between the lighting 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 lighting rate and the lighting uniformity, which can more accurately reflect the lighting demands of different areas. For example, the main lighting area may have a higher requirement for lighting uniformity, while the secondary lighting area may pay more attention to the qualified lighting rate. Through the weighted fusion calculation, the lighting quality compensation coefficient is obtained, providing a basis for subsequent adjustments to ensure the optimization of the final lighting effect.

[0125] Embodiment 2

[0126] 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, 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, a smooth transition 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, thereby 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:

[0127] Sending a control instruction to the front-end lighting facilities through the control platform center;

[0128] 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, so that the lighting facilities can verify the legality and timeliness of the instructions, ensure the effective execution of the instructions and improve the system security.

[0129] 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;

[0130] 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 length of the non-response time 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 this 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.

[0131] 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;

[0132] 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 preset backup control strategy and backup operating parameters 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, timing execution period, gradient control function, etc., ensuring that the lighting maintains an acceptable, safe and stable operating state during the disconnection. This design ensures the lighting continuity, safety, and user experience stability in the case of disconnection.

[0133] When the front-end lighting facility responds to the control instruction, the corresponding continuous response duration is obtained;

[0134] 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. Monitor the response of the front-end lighting facility in real time and record the time interval from receiving the control instruction to the facility making a response; 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.

[0135] 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;

[0136] 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 strategy and target operating state parameters before the disconnection are obtained.

[0137] According to the target strategy and the target operating state parameters, adjust the standby control strategy and standby operating parameters, and control the front-end lighting facility to perform lighting through the adjusted standby control strategy and adjusted standby operating parameters.

[0138] Specifically, after obtaining the target strategy and target operating state parameters, it is necessary to adjust the standby control strategy and standby 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 standby control strategy and standby operating parameters are usually the best predictions or default values based on the target strategy and the current device state 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 strategy indicates adjusting the lighting to a specific brightness, and the actual operating state of the current device shows that its power supply is slightly insufficient, the standby parameters will be adjusted to select a more energy-efficient mode to avoid overload. Finally, the adjusted standby strategy and standby operating parameters will be applied to the front-end lighting facility to ensure that the operation of the device after restoration still meets the expected lighting requirements while ensuring the stability and security of the system.

[0139] In one embodiment, the adjusting the standby control strategy and standby operating parameters according to the target strategy and the target operating state parameters, and controlling the front-end lighting facility to perform lighting through the adjusted standby control strategy and adjusted standby operating parameters includes:

[0140] Calculate the control parameter difference according to the target strategy and the standby control strategy, in combination with the target operating state parameters and the standby operating parameters;

[0141] Specifically, according to the target strategy and the standby control strategy, in combination with the target operating state parameters and the standby 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 state from the current standby operating state. For example, assume that the target strategy requires adjusting the lighting intensity from the current 100 lux to 300 lux, and the lighting intensity set by the standby control strategy 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.

[0142] 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 range of the control parameters corresponding to each adjustment step stage is not greater than a preset user-perceivable change threshold;

[0143] 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 the preset user-perceivable change threshold. The change range 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 range of each stage are usually adjusted according to the response speed of the device and the user experience.

[0144] 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;

[0145] 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.

[0146] Send the adjustment target value of the current stage to the front-end lighting facility according to the preset sending period. When the adjustment target value 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;

[0147] Specifically, after calculating the adjustment target values for each adjustment step phase, the adjustment target values for the current phase are sent to the front-end lighting facilities at regular intervals according to a preset sending period. The sending timing and frequency need to match the response capabilities of the devices to ensure that the devices can complete the adjustment on time within each adjustment step phase. When the actual operating state of the front-end lighting facilities reaches the parameter threshold range set by the target operating state parameters, the adjusted backup control strategy and backup operating parameters are obtained. These adjusted strategies and parameters will ensure that the front-end devices can not only achieve the target lighting effect but also maintain the stable and long-term operation of the devices during the lighting process.

[0148] The front-end lighting facilities are controlled for lighting by the adjusted backup control strategy and the adjusted backup operating parameters.

[0149] Embodiment 3

[0150] 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, and 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.

[0151] Specifically, for the intelligent control system for a smart city using DC lighting provided in the embodiments 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 the information of the device repair work orders to be processed currently in the form of a list or cards, such as work order numbers, the 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 to help users quickly identify the peak hourly 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 to assist in long-term energy management decisions; as Figure 11 shown. Figure 11It is a schematic diagram of the management interface of the regional 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, and total mileage. A bar chart and a line chart are juxtaposed to compare the energy consumption trends of yesterday and today. The total daily energy consumption 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 area includes multiple geographical markings: the inpatient area, the North Campus, the residential area, the community, the bank, the old block, the storage area, etc. The lighting equipment status, energy consumption density, or fault alarms in different areas are distinguished by colors or icons. The real-time monitoring module on the right side includes: real-time current, which is associated with the operating status of the equipment; hourly power consumption: a line chart shows the hourly power fluctuations; hourly energy consumption statistics: the energy consumption data is displayed hourly.

[0152] 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 the smart city is centered around the collaborative work between the intelligent lighting management platform and the control unit. By integrating 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 data such as ambient light, personnel activities, and traffic flow collected in real time, 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 to process local data and operate offline, 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, the energy use of urban lighting can be significantly optimized, maintenance costs can be reduced, and the safety and livability of urban spaces can be improved. The intelligent control system for DC lighting in the smart city precisely combines the location information of lighting facilities, the real-time ambient illuminance, and the preset DC lighting control timing strategy, effectively achieving the balance between energy conservation and lighting effects. 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 in 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 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 lighting qualification rate of 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.

[0153] In addition, in combination with Figure 1 The intelligent control method for DC lighting in the smart city described in Embodiment 1 of the present invention can be implemented by the 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.

[0154] The intelligent lighting management platform may include a processor 401 and a memory 402 storing computer program instructions.

[0155] 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.

[0156] The memory 402 may include a mass storage 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 disk, a magneto-optical disk, 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.

[0157] 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.

[0158] 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.

[0159] The communication interface 403 is mainly used to implement communication between the modules, devices, units, and / or devices in the embodiments of the present invention.

[0160] The bus 410 includes hardware, software, or both, and couples the components of the device together. By way of example and not limitation, the 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, the bus 410 may include one or more buses. Although embodiments of the present invention describe and illustrate specific buses, the present invention contemplates any suitable bus or interconnect.

[0161] In summary, embodiments of the present invention provide an intelligent control method and system for a smart city using DC lighting.

[0162] 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.

[0163] The functional blocks shown in the above-described 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 on a transmission medium or a communication link. A "machine-readable medium" can include any medium capable of storing or transmitting information. Examples of machine-readable media include electronic circuits, semiconductor memory devices, ROM, flash memory, Erasable ROM (EROM), 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.

[0164] 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 the relevant laws, regulations, and standards of the relevant location, and corresponding operation entrances are provided for users to choose to authorize or reject.

[0165] 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, or different from the order in the embodiments, or several steps can be executed simultaneously.

[0166] As described above, the above are only the 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 a smart city using DC lighting, characterized in that, The method includes: Based on the location information of lighting facilities and the real-time ambient illuminance in a target area under the urban DC lighting scenario, and in combination with a preset timing strategy for DC lighting control, obtaining a target strategy for DC lighting control; 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. 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; Obtaining 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 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 parameters, adjusting the initial operating state parameters to obtain target operating state parameters; The adjusting the initial operating state parameters to obtain target operating state parameters according to the preset operating state parameter template and in combination with the quality evaluation parameters includes: Calculating the difference between the preset operating state parameter template and the initial operating state parameters to obtain the difference in the state parameters of the lighting facilities; According to the difference in the state parameters of the lighting facilities, performing a first adjustment on the initial operating state parameters to obtain the adjusted state parameters of the lighting facilities; 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 a lighting quality compensation coefficient; According to the lighting quality compensation coefficient, performing a second adjustment on the adjusted state parameters of the lighting facilities to obtain the target operating state parameters; According to the target strategy and the target operating state parameters, controlling the lighting facilities in the target area to perform lighting.

2. The intelligent control method for DC lighting in the smart city according to claim 1, characterized in that The obtaining a target strategy for DC lighting control based on the location information of lighting facilities and the real-time ambient illuminance in a target area under the urban DC lighting scenario, and in combination with a preset timing strategy for DC lighting control includes: Obtaining the attribute category of the target area according to the location information of the lighting facilities; According to the timing strategy and the attribute category of the target area, obtaining the lighting strategy between periods and the lighting strategy within a period, where the lighting strategy includes the lighting turn-on time point, the lighting turn-off time point, and the lighting brightness level; Comparing the real-time ambient illuminance with a preset illuminance threshold, and according to the comparison result, determining whether it is necessary to adjust the lighting strategy between periods and the lighting strategy within a period; When it is necessary to adjust the lighting strategy between periods and the lighting strategy within a period, obtaining the target area level and the target reference illuminance according to the attribute category of the target area; According to the target area level and the target reference illuminance, adjusting the lighting strategy between periods and the lighting strategy within a period to obtain the target strategy.

3. The intelligent control method for DC lighting adopted by the smart city according to claim 2, characterized in that Adjusting the periodic lighting strategy and the in-period lighting strategy according to the target area level and the target reference illuminance to obtain the target strategy includes: Obtaining an illuminance adjustment weight according to the target area level; Calculating an illuminance deviation value according to the target reference illuminance and the real-time ambient illuminance; Calculating an illuminance correction coefficient according to the illuminance deviation value and the illuminance adjustment weight; Performing a correction process on the original luminance value corresponding to the lighting luminance level according to the illuminance correction coefficient to obtain a corrected luminance value; Performing a correction process on the lighting turn-on time point and / or the lighting turn-off time point according to a preset lighting time adjustment step and the illuminance deviation value to obtain a corrected turn-on time point and / or a corrected turn-off time point; Determining the target strategy according to the corrected luminance value, the corrected turn-on time point and / or the corrected turn-off time point; 4. The intelligent control method for DC lighting in the smart city according to claim 3, characterized in that, The calculating an illuminance correction coefficient according to the illuminance deviation value and the illuminance adjustment weight includes: Selecting an illuminance correction mathematical model corresponding to the scene according to the target area attribute category, 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; 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; Performing a normalization process on the initial illuminance correction coefficient according to a preset correction coefficient interval to obtain the illuminance correction coefficient; 5. The intelligent control method for DC lighting in the smart city according to claim 3, characterized in that, The performing a correction process on the lighting turn-on time point and / or the lighting turn-off time point according to a preset lighting time adjustment step and the illuminance deviation value to obtain a corrected turn-on time point and / or a corrected turn-off time point includes: Obtaining 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 turn-on and turn-off times; Obtaining the lighting time adjustment step, where the lighting time adjustment step is used to characterize the basic time adjustment amplitude corresponding to a unit illuminance deviation value; Calculating a basic time offset according to the illuminance deviation value and the lighting time adjustment step; Adjusting 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; Performing a correction process on the adjusted time offset according to the time correction sensitivity parameter to obtain a target time offset; Performing a correction process on the lighting turn-on time point and / or the lighting turn-off time point according to the target time offset to obtain a corrected turn-on time point and / or a corrected turn-off time point.

6. The intelligent control method for DC lighting in the smart city according to claim 3, characterized in that 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 lighting in the target area includes: Obtaining the data collection frequency corresponding to the area level according to the target area level; Detecting the current value, voltage value, and calculating the power value of the lighting facilities in the target area under the control of the target strategy according to the data collection frequency, and determining the initial current value, initial voltage value, and initial power value as the initial operating state parameters; Judging whether each lighting facility lights up qualifiedly according to the preset standard current range, standard voltage range, and standard power range, in combination with the initial current value, initial voltage value, and initial power value; Calculating the lighting qualification rate according to the number of lighting facilities that light up qualifiedly and the total number of lighting facilities in the target area; Comparing the corrected brightness values of each lighting facility in the target area, and calculating the lighting uniformity according to the maximum brightness value and the minimum brightness value in the target area.

7. The intelligent control method for DC lighting in the smart city according to claim 2, characterized in that, Obtaining the preset operating state parameter template of the lighting facilities in the target area under the control of the target strategy includes: Controlling the lighting facilities in the target area to perform lighting according to the target strategy, and obtaining the optimization objectives corresponding to the target area, where the optimization objectives include minimizing the total power consumption in the area, the lighting uniformity in the area being greater than or equal to the preset uniformity threshold, and the brightness value in the area being greater than the preset brightness threshold; Determining the constraint conditions according to the optimization objectives; Determining the preset operating state parameter template according to the optimization objectives and the constraint conditions, in combination with the multi-objective optimization algorithm, where the multi-objective optimization algorithm includes the genetic algorithm and the particle swarm optimization algorithm.

8. The intelligent control method for DC lighting in the smart city according to claim 1, characterized in that, Performing weighted fusion calculation on the deviation value between the lighting qualification rate and the preset qualification rate threshold and the deviation value between the lighting uniformity and the preset uniformity threshold to obtain the lighting quality compensation coefficient includes: Classifying the target area into a main lighting area and a secondary lighting area according to the lighting facility location information, and obtaining the environmental data of the target area, where the environmental data includes weather and season; Obtaining the first initial weight corresponding to the main lighting area and the second initial weight corresponding to the secondary lighting area, where the initial weight includes the weight corresponding to the lighting qualification rate and the weight corresponding to the lighting uniformity; According to the environmental data, in combination with the preset mapping table between the environmental data and the correction coefficient, performing correction processing on the first initial weight and the second initial weight to determine the first target weight and the second target weight; Performing weighted fusion calculation on the deviation value between the lighting qualification rate and the preset qualification rate threshold and the deviation value between the lighting uniformity and the preset uniformity threshold according to the first target weight and the second target weight to obtain the lighting quality compensation coefficient.

9. An intelligent control system for a smart city using DC lighting, characterized in that, The control system includes an intelligent lighting management platform, which is communicatively connected to a 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 1-8 is implemented.

Images