A method and system for controlling the lighting of an endless yard light, and an endless yard light

Abstract

The application belongs to the technical field of intelligent lighting control, and discloses a lighting control method and system of an electrodeless courtyard lamp and the electrodeless courtyard lamp, which comprise the following steps: constructing an initial functional multi-dimensional rule matrix, defining a mapping triple, generating a standardized multi-dimensional data set based on real-time data collected by calibrated hardware, matching a lighting response action through the multi-dimensional rule matrix and solving multi-rule matching conflicts, simultaneously obtaining target light domain parameters of a current scene in combination with the mapping triple, generating a lighting control instruction set, triggering an executor system to execute corresponding operations, comparing an execution state with the target light domain parameters in real time, recording an execution result to generate an execution state evaluation report, associating and integrating user feedback data and equipment statistical data to generate a comprehensive data set, obtaining a total evaluation value, dynamically adjusting a multi-dimensional rule matrix parameter interval and the mapping triple according to the total evaluation value, generating an optimized configuration package, and replacing an initial configuration to form a closed-loop iterative lighting control link.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of intelligent lighting control, more particularly, the present application relates to a lighting control method and system for a dim courtyard lamp and the dim courtyard lamp. BACKGROUND

[0002] With the deep integration of smart home and courtyard landscape, courtyard lighting has developed from a simple lighting function to a scene-based and intelligent direction. Users increasingly demand that it adapt to different activity scenes (such as family gatherings and night rest), balance energy saving and experience, and respond to environmental changes. However, current traditional lighting methods rely on timing or manual control and cannot dynamically adjust according to actual scenes. Some intelligent solutions can only achieve simple responses in a single dimension (such as light intensity) and cannot meet the fine needs of complex scenes. Moreover, they lack effective use of user feedback and device status, resulting in a gap between the level of intelligence and actual needs.

[0003] Although some intelligent lighting solutions in the prior art introduce sensors and simple rule control, there are obvious limitations. First, the rule logic is fixed and is based on a single or a small number of dimensions to develop control strategies, which cannot link decision-making with multi-dimensional information such as target characteristics, scene space, and environmental state, resulting in a mismatch between response actions and actual scenes. Second, there is a lack of conflict resolution mechanism, which cannot reasonably arbitrate when multiple scene requirements conflict, easily leading to control chaos. Third, the execution process lacks precise monitoring and correction mechanisms, making it difficult to correct execution deviations and affecting control effectiveness. Fourth, the solutions lack scalability and cannot integrate custom dimension parameters or continuously optimize rules based on actual operation data, resulting in decreased adaptability over time. SUMMARY

[0004] To overcome the above-mentioned defects of the prior art, in order to achieve the above-mentioned purposes, the present application provides the following technical solutions: a lighting control method for a dim courtyard lamp, comprising:

[0005] S1: deploying and calibrating multi-dimensional sensors and actuator hardware, synchronously constructing an initial functional multi-dimensional rule matrix, and defining a geographic-scene-light domain mapping triple; collecting real-time data based on the calibrated hardware to generate a standardized multi-dimensional data set;

[0006] S2: based on the standardized multi-dimensional data set, matching lighting response actions through the multi-dimensional rule matrix and resolving multi-rule matching conflicts, while obtaining target light domain parameters of the current scene based on the mapping triple, to generate a lighting control instruction set;

[0007] S3: triggering the actuator system to perform corresponding operations according to the lighting control instruction set, real-time comparing the execution state with the target light domain parameters, triggering a retry mechanism if there is a deviation, recording the execution results to generate an execution state evaluation report;

[0008] S4: Based on the execution state evaluation report, the user feedback data and the device statistical data are associated and integrated to generate a comprehensive data set;

[0009] S5: Based on the comprehensive data set, a total evaluation value is obtained, the multi-dimensional rule matrix parameter interval and the mapping triple are dynamically adjusted according to the total evaluation value, an optimized configuration package is generated, and the initial configuration is replaced to form a closed-loop iterative lighting control link.

[0010] Further, the generation of the standardized multi-dimensional data set comprises:

[0011] Deploy a multi-dimensional sensor network and an executor system, calibrate the precision of the sensors, and calibrate the action range of the executors;

[0012] Meanwhile, define target features, scene space-time, and environmental state as three types of basic dimensions, and reserve an extended dimension interface for custom dimensions;

[0013] According to the preset dimension combination and response action mapping rule, an initial functionized multi-dimensional rule matrix is constructed based on the basic dimensions and the extended dimension interface;

[0014] Based on the GIS system to mark the geographic region coordinates, configure the scene state and the light domain parameters through the visual interface, and form a user-defined geographic-scene-light domain mapping triple;

[0015] Through the calibrated sensors to collect real-time data, and through standardized processing to map the parameters interval recognizable by the multi-dimensional rule matrix, a standardized multi-dimensional data set is generated.

[0016] Further, the matching of the lighting response action and the resolution of the multi-rule matching conflict comprises:

[0017] Parse and extract the specific parameters of each dimension in the standardized multi-dimensional data set, match the scene space-time dimension first, and then match the target feature dimension, the environmental state dimension, and the extended dimension according to the priority order, and traverse the parameter combination in the multi-dimensional rule matrix;

[0018] Call the response action bound to the matched parameter combination in the multi-dimensional rule matrix, and filter according to the matching accuracy priority principle, and reserve the response action as the potential lighting response action.

[0019] Further, the generation of the lighting control instruction set comprises:

[0020] Conflict arbitration is performed on the potential lighting response action according to the preset priority rule to determine a unique response action;

[0021] Meanwhile, the target light field parameter of the current scene is obtained by locating the geographical region coordinates in the standardized multi-dimensional data set to the corresponding geographical region and combining the scene state query mapping triplets;

[0022] The arbitrated unique response action and the target light field parameter are integrated to be converted into specific operation instructions recognizable by the executor to generate a lighting control instruction set containing specific execution parameters.

[0023] Further, the manner of real-time comparison between the execution state and the target light field parameter includes:

[0024] According to the lighting control instruction set, the modules of the executor system are driven to complete physical operations in linkage, and the actual output parameters of the modules are monitored in real time at a preset frequency;

[0025] The collected actual parameters are compared with the target light field parameters in the control instruction set one by one to obtain parameter deviation rates as execution accuracy of the executor.

[0026] Further, the generation manner of the execution state evaluation report includes:

[0027] If any parameter deviation rate does not meet the expectation, it is determined that there is a deviation, and a retry mechanism is triggered to dynamically adjust the execution parameters;

[0028] After each retry, the parameter deviation rate is reacquired, and it is re-determined whether the retry mechanism needs to be triggered according to the new parameter deviation rate, until all parameter deviation rates meet the expectation or the maximum number of retries is reached;

[0029] The state identifier, key parameters and time data of the retry execution result are recorded and integrated into a structured execution state evaluation report.

[0030] Further, the generation manner of the comprehensive data set includes:

[0031] The user feedback data and the equipment statistical data are collected in a targeted manner, and the execution state evaluation report is used as execution data, and a control period is delimited based on the timestamp of the execution state evaluation report;

[0032] The three types of data in the same control period are associated and bound according to the timestamp to form an execution-feedback-equipment data group;

[0033] The data groups of all control periods are integrated to generate a structured comprehensive data set.

[0034] Further, the generation manner of the optimization configuration package includes:

[0035] The fields of the user feedback index, the equipment state index and the execution deviation index are extracted from each data group of the comprehensive data set, and then the fields of the three types of indexes are quantified into standard values, respectively;

[0036] According to three types of standard values, the total evaluation value of each data set is obtained by a preset evaluation mechanism, and is arranged in descending order to form an optimization sequence;

[0037] According to the order of the optimization sequence, the multi-dimensional rule matrix parameter interval and the mapping triple corresponding to the total evaluation value are adjusted and updated one by one by a parameter optimization mechanism;

[0038] According to the updated multi-dimensional rule matrix and mapping triple, a plurality of complete control cycles are run, real-time execution data, user feedback data and device state data are obtained, and real-time three types of indicators are checked;

[0039] If the checking result meets the expectation, it is determined that the adjustment is effective, and if the checking result does not meet the expectation, the parameter optimization mechanism is re-optimized;

[0040] For the verified parameters, an optimization configuration package is generated to replace the initial configuration to form a closed-loop iterative lighting control link.

[0041] Further, a lighting control system of an endless courtyard lamp, characterized in that, comprising:

[0042] An initial configuration unit: deploying and calibrating multi-dimensional sensor and actuator hardware, synchronously constructing an initial functional multi-dimensional rule matrix, and defining a geographical-scene-light domain mapping triple; based on the calibrated hardware, collecting real-time data to generate a standardized multi-dimensional data set;

[0043] A rule matching unit: based on the standardized multi-dimensional data set, matching lighting response actions through the multi-dimensional rule matrix and solving multi-rule matching conflicts, while combining the mapping triple to obtain the target light domain parameters of the current scene, and generating a lighting control instruction set;

[0044] A monitoring and retry unit: triggering the actuator system to perform corresponding operations according to the lighting control instruction set, real-time comparing the execution state and the target light domain parameters, and if there is a deviation, triggering a retry mechanism, recording the execution result to generate an execution state evaluation report;

[0045] A multi-source data integration unit: based on the execution state evaluation report, combining user feedback data and device statistical data for association and integration to generate a comprehensive data set;

[0046] An optimization iteration unit: based on the comprehensive data set, obtaining a total evaluation value, dynamically adjusting the multi-dimensional rule matrix parameter interval and the mapping triple according to the total evaluation value, generating an optimization configuration package, and replacing the initial configuration to form a closed-loop iterative lighting control link.

[0047] Further, the dimmer yard lamp comprises a computer readable storage medium, and the computer readable storage medium stores a computer program.

[0048] The dimmer yard lamp lighting control method, system and dimmer yard lamp of the present application have the following technical effects and advantages:

[0049] The present application deploys calibration multi-dimensional sensors and actuators, constructs an initial functional multi-dimensional rule matrix and defines a geographic-scene-light domain mapping triple, while generating a standardized multi-dimensional data set, to provide accurate basis and standardized input for subsequent intelligent control, and lay a multi-dimensional adaptation capability.

[0050] Secondly, based on the standardized multi-dimensional data set, the present application realizes accurate matching of the multi-dimensional rule matrix, solves multi-action conflicts through priority arbitration, and generates a control instruction set in combination with the mapping triple, effectively solving the problems of rule solidification and conflict handling in the prior art, and realizing intelligent decision-making and accurate instruction output in multiple scenes.

[0051] Then, according to the instruction set, the actuator is driven to operate, and the execution state is compared with the target parameter in real time, so as to ensure the accuracy and reliability of the execution process, avoid the problem that the execution deviation cannot be corrected in the prior art, and improve the stability of the control effect.

[0052] Next, the multi-source data is integrated to form a comprehensive data set, which provides a comprehensive and related data basis for optimization, solves the problem of scattered data and ineffective utilization in the prior art, and makes the system have the possibility of continuous improvement based on actual operation data.

[0053] Finally, based on the comprehensive data set, the rule matrix and the mapping triple are adjusted to form a complete closed loop of collection-decision-execution-optimization, solve the problem of rule evolution and insufficient expansion in the prior art, and make the system continuously adapt to scene changes and user needs, continuously improve the intelligent level and user experience. BRIEF DESCRIPTION OF DRAWINGS

[0054] Figure 1 The present application is a dimmer yard lamp lighting control method schematic diagram;

[0055] Figure 2 The present application is a multi-dimensional rule matrix matching process schematic diagram in a dimmer yard lamp lighting control method;

[0056] Figure 3 The present application is a dimmer yard lamp lighting control system schematic diagram. DETAILED DESCRIPTION

[0057] With reference to the drawings of the embodiments of the present application, the technical solutions in the embodiments of the present application will be clearly and completely described. Obviously, the described embodiments are only a part of the embodiments of the present application, but not all the embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those of ordinary skill in the art without creative work fall within the scope of the present application.

[0058] Embodiment one

[0059] Please refer to Figure 1 and Figure 2 , the lighting control method of the endless courtyard lamp described in the embodiment includes:

[0060] S1: deploy and calibrate multi-dimensional sensor and actuator hardware, synchronize to build an initial functional multi-dimensional rule matrix, and define a geographic-scene-light domain mapping triple. Based on the calibrated hardware, real-time data is collected to generate a standardized multi-dimensional data set;

[0061] S2: based on the standardized multi-dimensional data set, match the lighting response action through the multi-dimensional rule matrix and solve the multi-rule matching conflict, and at the same time, combine the mapping triple to obtain the target light domain parameter of the current scene, generate a lighting control instruction set;

[0062] S3: according to the lighting control instruction set, trigger the actuator system to execute the corresponding operation, real-time compare the execution state with the target light domain parameter, if there is deviation, trigger the retry mechanism, record the execution result to generate an execution state evaluation report;

[0063] S4: based on the execution state evaluation report, combine user feedback data and device statistical data for association and integration to generate a comprehensive data set;

[0064] S5: based on the comprehensive data set, obtain a total evaluation value, dynamically adjust the multi-dimensional rule matrix parameter interval and the mapping triple according to the total evaluation value, generate an optimized configuration package, replace the initial configuration to form a closed-loop iterative lighting control link.

[0065] The generation method of the standardized multi-dimensional data set includes:

[0066] Deploy a multi-dimensional sensor network (including target feature sensors, scene space-time sensors, and environment state sensors) and an actuator system (including brightness adjustment modules, light domain directional modules, and spectrum switching modules), calibrate the accuracy of the sensors, and calibrate the action range of the actuators. Specifically:

[0067] One way to calibrate the accuracy of the sensors includes:

[0068] For target feature sensors (including infrared thermal imager, millimeter wave radar): use standard heat source (simulate human body 36℃±0.5℃) and moving platform (set 0.3m / s, 1m / s, 3m / s three standard speeds) to verify; then record the deviation of the measured value and the standard value of the sensor, when the deviation greater than expected (such as thermal imager temperature measurement deviation >±2℃), automatically superimposed preset compensation value, finally ensure that the target temperature identification error and the moving speed measurement error meet the expectation (such as target temperature identification error ≤±1℃, moving speed measurement error ≤±0.1m / s);

[0069] For scene space-time sensors (including GPS module, clock module): calibrate the GPS module through satellite positioning to ensure that the geographic coordinate error meets the expectation (such as ≤±2m); synchronize the clock module with network time service to ensure that the time period division (such as "rest period 22:00-6:00") error meets the expectation (such as ≤±1 minute);

[0070] For environmental state sensors (including light sensor, temperature and humidity sensor): calibrate the light sensor in the standard light intensity environment (including 50lux, 500lux, 1000lux), adjust the gain resistor to correct the reading, ensure that the error meets the expectation (such as ≤±5%); calibrate the temperature and humidity sensor with a standard temperature and humidity box (i.e. 25℃±0.5℃, 50%RH±2%), so that the error is controlled within the expectation (such as temperature ±0.3℃, humidity ±3%);

[0071] One way to calibrate the action range of the actuator includes:

[0072] For brightness adjustment module (including PWM dimming circuit): connect the light meter, adjust in 10% steps within 0%-100% brightness interval, record the actual brightness value; establish a mapping table of adjustment instruction-actual brightness (such as instruction 30% corresponds to measured 28%, automatically correct instruction to 32%), ensure that the final brightness output error meets the expectation (such as ≤±5%);

[0073] For light field orientation module (including stepper motor + rotating lens): use laser positioner to mark 0°, 30°, 60°, 90° these four reference angles; then control the lens to rotate to each reference position, record the actual angle deviation (such as instruction 30° measured 28°), through stepper motor pulse compensation (increase the corresponding pulse number), control the final positioning error within the expectation (such as ≤±2°);

[0074] For the spectrum switching module (including multi-spectrum LED module + relay): use the spectrometer to detect the spectral parameters of ecological amber light (wavelength 590nm-620nm) and active white light (wavelength 450nm-650nm); then calibrate the response time of the relay switching (ensure ≤100ms), so as to avoid spectral mixing during switching;

[0075] At the same time, the target feature, scene space-time and environment state are defined as three types of basic dimensions, and the extension dimension interface of self-defined dimension is reserved. Specifically:

[0076] Target feature dimension: the parameter interval is divided into static (such as speed <0.3m / s), slow moving (such as 0.3-1m / s) and fast moving (such as >1m / s) by threshold segmentation method;

[0077] Scene space-time dimension: according to the common work and rest habits of residents, the time period is divided into rest (such as 22:00-6:00), daily (such as 6:00-18:00) and evening (such as 18:00-22:00), and then the area type is divided into core area (such as inside the residential courtyard) and transition area (such as within 5m of the courtyard boundary);

[0078] Environment state dimension: according to the acceptable degree of light intensity to the human eye, the light intensity is divided into dark light (such as <200lux), medium light (such as 200lux-800lux) and strong light (such as >800lux), and then according to the visibility of naked eye under different weather conditions, the weather is divided into sunny, rainy and foggy;

[0079] The extension dimension interface is defined as: the access channel of self-defined dimension such as device power (low / medium / high) and user preference (energy saving / comfort) is reserved to facilitate dynamic addition by users in the later stage;

[0080] According to the basic dimensions and the extension dimension interface, the initial function of the multi-dimensional rule matrix is constructed according to the preset dimension combination and response action mapping rule;

[0081] Among them, the mapping relationship between dimension combination and response action is preset according to the actual needs of users;

[0082] The function logic of the mapping rule is defined as: target = target feature (slow moving / fast moving) + scene space-time = time period (daily / rest) + area type + environment = light intensity, corresponding response action = brightness adjustment (gradual change according to preset proportion / abrupt rise according to preset proportion) + light domain control (directional following / omnidirectional coverage);

[0083] The exemplary multi-dimensional rule matrix is: target = slow moving + scene = daily + environment = dark light → response action = brightness gradual change to 50%, light domain directional following target;

[0084] Target = fast moving + scene = rest + environment = dark light, corresponding response action = sudden brightness rise to 80% (for security warning), full- range light field coverage;

[0085] It should be noted that the initial function matrix of multi-dimensional rules constructed here is a dynamic and expandable mapping relationship model, the core structure of which takes dimension set as input, parameter combination as intermediate variable, and response action as output, realizes flexible association through preset function logic, and the specific structure can be divided into four layers, including dimension definition layer (input dimension pool), parameter combination layer (intermediate association logic), action mapping layer (output response rule) and function driving layer.

[0086] The dimension definition layer (input dimension pool) includes the basic dimension area and the extended dimension interface area.

[0087] The basic dimension area: fixedly contains three types of core dimensions, each type of dimension has a preset configurable parameter interval: target feature dimension, scene space-time dimension and environment state dimension.

[0088] The extended dimension interface area: reserves standardized interfaces, supports users to add new dimensions through configuration, and automatically includes new dimension parameters in matrix operation without the need to reconstruct the underlying structure.

[0089] The parameter combination layer (intermediate association logic) takes cross combination of dimension parameters as the core, defines the legal parameter combination form through preset rules, for example: basic combination: "target = slow moving + scene space-time = daily + core area + environment state = dark light"; combination containing extended dimensions: "target = fast moving + scene space-time = rest + transition area + environment state = fog + device state = device state is in medium power".

[0090] Each combination needs to meet the logical self-consistency, for example, the combination of rest period and strong light is abnormal, which needs to be marked as illegal, so as to avoid participating in matching.

[0091] The action mapping layer (output response rule) binds a unique response action for each legal parameter combination, and the action includes quantifiable control parameters, for example:

[0092] For the combination "slow moving + daily + core area + dark light", the action "brightness adjustment (gradual change to 50%, step 10% / 2s) + light field control (directionally follow the target, angle error ≤ 2°) + spectrum (white light)" is bound; for the combination "fast moving + rest + transition area + fog + medium power", the action "brightness adjustment (sudden rise to 80%, response time ≤ 500ms) + light field control (full- range coverage, angle 360°) + spectrum (warning white light)" is bound.

[0093] The function-driven layer (dynamic association engine) realizes dynamic calling through the core function rule matrix = f (dimension set, parameter combination). Specifically:

[0094] When a new dimension set is input (such as adding a user mode = security), the extended dimension is identified and included in the parameter combination pool; when the parameter combination changes (such as the addition of an ecological area to the regional type), the function only needs to supplement the combination rule of the parameter with other dimensions, and the original combination mapping relationship remains unchanged.

[0095] Therefore, a function-driven multi-dimensional rule matrix is constructed, which has a structure similar to a splicable building block: the basic dimension is a fixed module, the extended dimension is an addable module, the parameter combination is the splicing method of the module, the response action is the output result after splicing, and the function-driven logic ensures that the module can be spliced flexibly and the splicing rule is consistent.

[0096] Based on the GIS system, the courtyard electronic map is imported, the user frames the region on the visual interface and names it, such as the courtyard core area (coordinates X1-Y1 to X2-Y2) and the boundary transition area (X2-Y2 to X3-Y3), which are marked as geographic region coordinates.

[0097] The scene state and light field parameters are configured through the visual interface to form a user-defined geographic-scene-light field mapping triple.

[0098] For example, triple 1: geographic area = core area + scene state = family gathering, corresponding light field parameter = brightness 70%-90%, angle 360° omnidirectional, light spectrum = white light.

[0099] Triple 2: geographic area = transition area + scene state = night rest, corresponding light field parameter = brightness ≤ 20%, angle ≤ 30° (avoiding the bedroom window), light spectrum = amber light (low glare).

[0100] Through the calibrated sensor to collect real-time data, including target feature data (acquired by infrared thermal imager and radar to obtain target moving speed, heat source area (such as 0.5㎡, determined as a single person)), scene space-time data (GPS module acquires current geographic coordinates (such as in the core area), clock module records the current period (such as 19:30 corresponding to evening)), environmental state data (light sensor reading (150 lux corresponding to dark light), weather sensor identification (sunny day)); Then, according to the user-defined extended dimension, extended data can be collected, for example, through the device power sensor reading (80% corresponding to medium power);

[0101] Further, through standardization processing, it is mapped to a parameter interval that can be recognized by the multi-dimensional rule matrix, for example: moving speed 0.6 m / s is mapped to slow movement; geographic coordinates (in the core area) are mapped to the core area; light 150 lux is mapped to dark light.

[0102] Integrate all parameters to generate a standardized multi-dimensional dataset;

[0103] An exemplary standardized multi-dimensional dataset, target feature: slow moving, scene space-time: evening + core area, environment state: dim light + sunny day, device power: medium.

[0104] The way to match the lighting response action and resolve multi-rule matching conflicts includes:

[0105] Analyze and extract specific parameters of each dimension in the standardized multi-dimensional dataset, including specific parameters of basic dimensions (target feature, scene space-time, environment state), and parameters of extended dimensions (such as device state);

[0106] According to the priority order of the scene space-time dimension first, the target feature dimension second, the environment state dimension third, and the extended dimension last, traverse the parameter combinations in the multi-dimensional rule matrix;

[0107] Specifically: first match the scene space-time parameters (such as daily + core area), filter out the parameter combination subset containing this scene in the multi-dimensional rule matrix; then match the target feature parameters (such as slow moving) in the subset to further narrow down the range; then continue to match the environment state parameters (such as dim light + sunny day) and the extended dimension parameters (such as medium power), and finally locate one or more parameter combinations (such as "slow moving + daily + core area + dim light + sunny day + medium power") that completely match the standardized multi-dimensional dataset;

[0108] Call the response actions in the action mapping layer of the multi-dimensional rule matrix that are bound to the matched parameter combinations, filter them according to the matching accuracy priority principle, and keep the actions corresponding to the completely matched parameter combinations first, and the actions of partial matching (such as lacking extended dimension parameters but basic dimensions completely match) as alternatives; finally, select a certain number (in order to reduce the complexity of subsequent conflict arbitration, the number is best limited to 1-3) of response actions to keep, and keep the reserved response actions as potential lighting response actions.

[0109] The generation method of the lighting control instruction set includes:

[0110] Conflict arbitration of potential lighting response actions according to pre-set priority rules to determine a unique response action, specifically:

[0111] Define the priority rules as safety rules > core demand rules > regular rules;

[0112] Among them, the first priority is the safety rule (such as security trigger, corresponding to strong light warning), which is suitable for scenes such as target rapid movement and strange area intrusion; the second priority is the core demand rule (such as activity scene, corresponding to adaptive brightness), which is suitable for scenes such as human gathering and daily activities; and the third priority is the regular rule (such as ecological protection, corresponding to low brightness), which is suitable for scenes such as unmanned area and night ecological area.

[0113] Example: If the potential action contains activity highlight (core demand) and ecological low light (regular), and the current area is a human activity core area, the activity highlight is retained after arbitration.

[0114] At the same time, based on the geographic area coordinates in the standardized multi-dimensional data set, the corresponding geographic area is located through the GIS system.

[0115] Combined with the scene state parameters (such as family gathering and night rest) in the standardized multi-dimensional data set, the user-defined geographic-scene-light domain mapping triplets are queried to obtain the target light domain parameters of the current scene, including brightness parameters, angle parameters and spectrum parameters.

[0116] Specifically, the brightness parameter includes a specific interval (such as 50%-70%) and an adjustment method (gradual change / rapid rise); the angle parameter includes an irradiation direction (such as 30°-60°) and an accuracy requirement (such as an error ≤2°); and the spectrum parameter includes a spectrum type (such as white light and amber light) and a response time of switching (such as ≤100ms).

[0117] The unique response action after arbitration is combined with the target light domain parameters to convert into specific operation instructions recognizable by the actuator, including brightness adjustment instructions, light domain directional instructions and spectrum switching instructions.

[0118] Among them, the brightness adjustment instruction includes the starting value (such as the current 20%), the target value (such as 60%), the step (such as +10% every 2 seconds) and the duration (such as 8 seconds) of the light intensity; the light domain directional instruction includes the lens rotation angle (such as from the current 15° to 60°) and the rotation speed (such as 15° per second); and the spectrum switching instruction includes the switching target (such as from amber light to white light) and the execution time (synchronized with brightness adjustment).

[0119] The integrated structured lighting control instruction set includes instruction ID, specific operation instruction, execution sequence and parameter threshold (such as triggering retry when the deviation exceeds 10%).

[0120] The real-time comparison of the execution state and the target light domain parameters includes:

[0121] According to the lighting control instruction set, the actuator system modules are driven to complete physical operations in linkage, specifically:

[0122] For the brightness adjustment module, the brightness parameter in the lighting control instruction set is received (e.g., from 20% to 60% at a step of +10% every 2 seconds), and then the output voltage is adjusted through the PWM (pulse width modulation) circuit to update the duty cycle at a fixed frequency (default 100 ms) (e.g., from 20% to 60% at a step), ensuring smooth and flicker-free brightness changes, while the current brightness value is fed back in real time through the built-in photometer;

[0123] For the light field orientation module, according to the angle parameter in the lighting control instruction set, the step motor is driven to operate at a preset speed (e.g., 15° per second), and the lens rotates synchronously with the motor; then the current angle is collected in real time through the encoder, and the data is fed back to the control system to form a closed-loop positioning;

[0124] For the spectrum switching module, after receiving the spectrum parameter in the lighting control instruction set (i.e., the instruction to switch from amber light to white light), the relay switching circuit is controlled to switch the path, disconnect the ecological spectrum module (wavelength 590-620 nm) power supply, and connect the active spectrum module (wavelength 450-650 nm), while recording the switching response time;

[0125] At the same time, the actual output parameters of each module are monitored in real time at a preset frequency (e.g., 100 ms / time), including the current brightness percentage fed back by the brightness adjustment module, the real-time angle fed back by the light field orientation module, and the current spectrum type fed back by the spectrum switching module;

[0126] The actual parameters collected are compared with the target light field parameters in the control instruction set one by one, and the parameter deviation rate of each actuator is calculated (parameter deviation rate = (actual parameter value - corresponding target light field parameter value) ÷ corresponding target light field parameter value x 100%), which is used as the execution accuracy of the actuator.

[0127] The generation method of the execution state evaluation report includes:

[0128] If all parameter deviation rates are within the expected range (e.g., all parameter deviation rates are within ±10%), it is marked as normal execution;

[0129] If any parameter deviation rate does not meet the expectation, it is determined that there is a deviation, and a retry mechanism is triggered to dynamically adjust the execution parameters;

[0130] In the first retry, the execution parameters are dynamically adjusted according to the deviation type in proportion, for example, for brightness deviation (e.g., -30%), the adjustment step is increased from the original +10% every 2 seconds to +15% every 2 seconds;

[0131] After each retry, the actual parameters of the executor are re-collected and the parameter deviation rate is calculated. According to the new parameter deviation rate, it is re-determined whether to trigger the retry mechanism until all parameter deviation rates meet the expectation or the maximum number of retries is reached (the maximum number of retries should not be too large, and can be set to 3 times, and the interval between each retry can be set to 500ms, so as to avoid mechanical wear caused by frequent operation of the executor);

[0132] The state identifier of the retry execution result (execution success (including after retry) or execution failure (maximum retry times without meeting the standard) ), key parameters (final brightness value, final angle value and final deviation rate (i.e. the final standard meets the expected parameter deviation rate, for example, brightness deviation 0%, angle deviation -1°) and time data (total execution time, execution time of each execution (including initial execution time and subsequent each retry time) are recorded, and are integrated into a structured execution state evaluation report, including report number, associated instruction set ID, execution state details (such as execution success, final brightness 60%, angle 59°, total time 8 seconds).

[0133] The generation method of the comprehensive data set includes:

[0134] The user feedback data and the device statistical data are collected in a targeted manner. The user feedback data input by the user is collected in a targeted manner through a mobile phone APP, a physical control panel and the like, including qualitative evaluation (such as brightness suitable, angle narrow), quantitative suggestion (such as brightness needs to be reduced to 50%, angle increased by 5°) and feedback timestamp; the device state indicators are automatically summarized from system logs as device statistical data, including sensor level (such as infrared thermal imager failure rate 0%, light sensor data validity 98%), executor level (such as brightness adjustment module response success rate 100%, lens rotation average error 1.2°), and the statistical period of the device statistical data needs to be aligned with the timestamp of the execution data;

[0135] The execution data of the execution state evaluation report is combined, and the timestamp of the execution state evaluation report is taken as a reference to define a control period (the control period is in units of minutes, such as ten minutes a period, for example, 19:30-19:39 as a period);

[0136] The three types of data in the same control period are associated and bound according to the timestamp, such as execution data (19:30 execution), user feedback data (19:32 submission) and device statistical data (19:30-19:39 period), to form an execution-feedback-device data group;

[0137] The scattered data across periods (such as 19:30 period feedback submitted at 19:45) is supplemented and bound through the manually marked associated instruction ID of the user, so as to ensure the accuracy of data attribution;

[0138] Integrate the data sets of all control cycles to generate a structured comprehensive data set.

[0139] The generation mode of the optimization configuration package includes:

[0140] Extract the fields of three types of core optimization indicators, including user feedback indicators, device state indicators, and execution deviation indicators, from each data set of the comprehensive data set, and then quantify the fields of the three types of indicators into standard values. Specifically:

[0141] The standard value quantification method of the user feedback indicators is to convert qualitative evaluations (such as angle narrowing, brightness comfort) into quantitative values (1 indicates optimization, 0 indicates compliance), and quantitative suggestions (such as reducing brightness by 5%) are marked as specific deviation requirements.

[0142] The standard value quantification method of the device state indicators is to extract sensor data efficiency (such as 98% quantified as 0.98), actuator action success rate (such as 100% quantified as 1), and fault frequency (such as 0 times quantified as 1), and convert them into standard values according to the proportion;

[0143] The standard value quantification method of the execution deviation indicators is to calculate the compliance degree according to the final deviation rate (such as a brightness deviation of 2% ≤ threshold of 5% quantified as 0.9, and 0 for exceeding the threshold).

[0144] Through the pre-set evaluation mechanism, the total evaluation value of each data set is evaluated according to the three types of standard values, and the data sets are ranked in descending order to form an optimization sequence;

[0145] Among them, the evaluation mechanism is to pre-set a weight for each type of standard value.

[0146] Among them, the purpose of user feedback is to capture problems, and the higher the value, the more explicit the problems that must be solved, so the weight needs to be overwhelmingly high, such as 0.6; The purpose of device data is to evaluate support capability, i.e. device stability, which is the basic constraint of optimization. The higher the value, the more the device can support the rule landing, and there is no need to adjust it first, so the weight is only second to user feedback, but the weight value should not be too large, such as 0.3; The purpose of execution deviation is to evaluate rule adaptability. The smaller the deviation, the smaller the standard value of execution deviation, indicating that the current rule matches the actual execution better, and the weight value should not be too large, which needs to be very small, such as 0.1.

[0147] User feedback is a backward indicator, focusing on explicit problems, and device operation and execution deviation is a forward indicator, focusing on implicit constraints. The purpose of this design is to accurately capture the nature and urgency of optimization requirements through multi-dimensional directional complementarity. The combination of the two can fully outline the overall picture of optimization requirements. The weight of user feedback indicators (0.6) is much higher than that of devices (0.3) and execution (0.1). Through weight allocation, the directional difference is balanced. Even if the device and execution indicators perform well (high score in the positive direction), as long as the user feedback indicator is 1 point (high score in the negative direction), the total score will still be high (such as 1 x 0.6 + 1 x 0.3 + 1 x 0.1 = 1 points), ensuring that scenarios where users are not satisfied are always at the forefront of the optimization sequence.

[0148] On the contrary, if the user feedback meets the standard (0 points), even if the device and execution indicators have low scores (such as 0.5), the total score will be lower (0 x 0.6 + 0.5 x 0.3 + 0.5 x 0.1 = 0.2 points), avoiding scenarios where there are no user problems but small defects in the device being overemphasized. This weight tilt + directional complementarity design not only retains the independent meaning of each indicator but also ensures the core logic of prioritizing user needs.

[0149] Then, the total evaluation value of each data group is obtained by weighted fusion; for example: the user feedback angle needs to be increased (1 x 0.6 = 0.6) + the device success rate is 100% (1 x 0.3 = 0.3) + the angle deviation is 3% (0.7 x 0.1 = 0.07), and the total evaluation value is 0.97 (very high priority).

[0150] According to the order of the optimization sequence, the multi-dimensional rule matrix parameter interval and mapping triple corresponding to the total evaluation value is adjusted and updated one by one through the parameter optimization mechanism. Specifically:

[0151] Multi-dimensional rule matrix optimization adjustment: for the scene corresponding to the data group that needs to be adjusted (such as the activity scene angle is insufficient), adjust the corresponding dimensional parameter interval and mapping relationship;

[0152] For example, the original scene space-time = activity + region type = core area angle parameter interval is 60° ± 5°, which is expanded to 60° ± 12° (to adapt to the user's demand for increasing the angle). Then update the dimensional combination, and the corresponding response action mapping, for example, the target feature = multiple people moving + scene = activity, the response action is upgraded from directional light domain to directional + range expansion, covering a wider area.

[0153] Geography-scene-light domain mapping triple is updated: adjust the light domain parameters in combination with the geographical region characteristics;

[0154] For example, the original geographical area = transition zone + scene state = evening activity with a brightness parameter of 50%-70%, adjusted to 45%-75% (compatible with more user brightness preferences); new special scene triplets are added, such as geographical area = children's playground + scene = weekend binding brightness ≥ 60%, angle 360° omnidirectional, soft white light spectrum;

[0155] According to the updated multi-dimensional rule matrix and mapping triplets, a plurality of complete control cycles (such as 3 days, covering weekdays, weekends, daytime and nighttime scenes) are run to obtain real-time execution data, user feedback data and device state data, and then real-time three types of indicators are checked;

[0156] Among them, the index is checked, if the user satisfaction feedback proportion meets the expectation (such as ≥92%), and the execution parameter deviation meets the expectation (such as ≤3° (angle) / 5% (brightness)), and the device has no continuous failure, then it is determined that the check result meets the expectation, and it is determined that the adjustment is effective; otherwise, if any one of them does not meet the requirement, it is determined that the check result does not meet the expectation, and it is re-optimized through the parameter optimization mechanism;

[0157] For the verified parameters, an optimization configuration package is generated, including the updated mapping triplets, multi-dimensional rule matrix and version information;

[0158] Then the initial configuration (i.e., the initial multi-dimensional rule matrix and mapping triplets) is automatically replaced through the system interface to form a closed-loop iterative lighting control link.

[0159] Embodiment two

[0160] Please refer to Figure 3 The embodiment does not describe some parts in detail, see the description of embodiment one, and provides a lighting control system for an endless courtyard lamp, which comprises:

[0161] An initial configuration unit: deploy and calibrate multi-dimensional sensor and actuator hardware, synchronize to build an initial functionized multi-dimensional rule matrix, and define geographical-scene-light domain mapping triplets; based on the calibrated hardware, collect real-time data to generate a standardized multi-dimensional data set;

[0162] A rule matching unit: based on the standardized multi-dimensional data set, match lighting response actions through the multi-dimensional rule matrix and solve multi-rule matching conflicts, while combining the mapping triplets to obtain the target light domain parameters of the current scene, and generate a lighting control instruction set;

[0163] A monitoring and retry unit: according to the lighting control instruction set, trigger the actuator system to perform corresponding operations, real-time compare the execution state and the target light domain parameters, if there is a deviation, trigger the retry mechanism, record the execution result to generate an execution state evaluation report;

[0164] Multi-source data integration unit: based on the execution state evaluation report, the user feedback data and the equipment statistical data are associated and integrated to generate a comprehensive data set;

[0165] Optimization iteration unit: based on the comprehensive data set, a total evaluation value is obtained, the multi-dimensional rule matrix parameter interval and the mapping triple are dynamically adjusted according to the total evaluation value, an optimized configuration package is generated, and the initial configuration is replaced to form a closed-loop iterative lighting control link.

[0166] Embodiment three

[0167] The embodiment discloses a kind of yard lamp of endless, and the yard lamp of endless includes computer readable storage medium, computer program is stored on computer readable storage medium, when computer program is executed, the steps of the lighting control method of a kind of yard lamp of endless as described above are implemented.

[0168] Since the yard lamp of endless introduced in the embodiment is the electronic device used to implement the lighting control method of a kind of yard lamp of endless in the embodiment, the specific implementation of the electronic device of the embodiment and its various forms of change can be understood by those skilled in the art based on the lighting control method of a kind of yard lamp of endless introduced in the embodiment, so the electronic device how to implement the method in the embodiment will not be introduced in detail here. As long as the electronic device used to implement the lighting control method of a kind of yard lamp of endless in the embodiment is implemented by those skilled in the art, it belongs to the scope of the present application.

[0169] The above formulas are all dimensionless numerical calculations, and the formulas are obtained by collecting a large amount of data to simulate the most recent real situation, and the preset parameters and threshold values in the formulas are set by those skilled in the art according to actual conditions.

[0170] The above is only the preferred embodiment of the present application, and the protection scope of the present application is not limited to the above-mentioned embodiments. Any technical solution falling within the scope of the present application is also within the protection scope of the present application. It should be noted that, for ordinary technical users in the technical field, some improvements and refinements without departing from the principles of the present application are also considered within the protection scope of the present application.

Claims

1. A method for controlling illumination of an endless yard light, characterized by, The method comprises the following steps: S1: deploying and calibrating multi-dimensional sensor and actuator hardware, synchronously constructing an initial functional multi-dimensional rule matrix, and defining a geographical-scene-light domain mapping triple; collecting real-time data based on the calibrated hardware, and generating a standardized multi-dimensional data set; The generation of the standardized multi-dimensional data set comprises: deploying a multi-dimensional sensor network and an actuator system, calibrating the accuracy of the sensors, and calibrating the action range of the actuators; simultaneously defining target features, scene space-time and environmental state as three types of basic dimensions, and reserving an extended dimension interface for self-defined dimensions; combining the preset dimension combinations and response action mapping rules, constructing an initial functional multi-dimensional rule matrix based on the basic dimensions and the extended dimension interface; labeling geographical region coordinates based on a GIS system, configuring scene state and light domain parameters through a visual interface, and forming a user-defined geographical-scene-light domain mapping triple; collecting real-time data through the calibrated sensors, and mapping the data to a parameter interval recognizable by the multi-dimensional rule matrix through standardized processing, thereby generating a standardized multi-dimensional data set; S2: based on the standardized multi-dimensional data set, matching lighting response actions through the multi-dimensional rule matrix, solving multi-rule matching conflicts, obtaining target light domain parameters of the current scene in combination with the mapping triple, and generating a lighting control instruction set; The matching of the lighting response actions and the solving of the multi-rule matching conflicts comprise: analyzing and extracting specific parameters of each dimension in the standardized multi-dimensional data set, matching the parameters in the order of scene space-time dimension first, target feature dimension, environmental state dimension and extended dimension, and traversing the parameter combinations in the multi-dimensional rule matrix; calling the response actions bound to the matched parameter combinations in the multi-dimensional rule matrix, screening the response actions according to the matching accuracy priority principle, and retaining the response actions as potential lighting response actions; S3: triggering the actuator system to perform corresponding operations according to the lighting control instruction set, comparing the execution state with the target light domain parameters in real time, triggering a retry mechanism if there is a deviation, recording the execution result and generating an execution state evaluation report; S4: based on the execution state evaluation report, integrating associated user feedback data and equipment statistical data to generate a comprehensive data set; S5: obtaining a total evaluation value based on the comprehensive data set, dynamically adjusting the parameter interval of the multi-dimensional rule matrix and the mapping triple according to the total evaluation value, generating an optimized configuration package, and replacing the initial configuration to form a closed-loop iterative lighting control link; The generation of the optimized configuration package comprises: based on the comprehensive data set, extracting three types of indexes including user feedback, equipment state and execution deviation and quantifying them; obtaining a total evaluation value by weighting and fusing the quantified three types of indexes through a preset evaluation mechanism, and sorting the total evaluation value; sequentially dynamically adjusting the parameter interval and the mapping relationship of the multi-dimensional rule matrix, and adjusting the mapping triple in combination with the geographical region characteristics; running the multi-dimensional rule matrix and the mapping triple for multiple complete cycles based on the adjusted multi-dimensional rule matrix and the mapping triple, obtaining real-time execution data, user feedback data and equipment state data, and verifying the three types of indexes; generating an optimized configuration package containing the updated mapping triple, the multi-dimensional rule matrix and version information based on the verification result.

2. The method of claim 1, wherein the method further comprises: The generation of the lighting control instruction set comprises: Conflict arbitration of potential lighting response actions according to preset priority rules to determine a unique response action; Simultaneous positioning to a corresponding geographical area based on geographical area coordinates in the standardized multidimensional data set, and querying a mapping triple according to a scene state to obtain target light domain parameters of the current scene; Integration of the arbitrated unique response action and the target light domain parameters to convert into specific operation instructions recognizable by the executor, and generation of a lighting control instruction set containing specific execution parameters.

3. The method of claim 2, wherein the method further comprises: The real-time comparison of the execution state with the target light domain parameters comprises: Driving of the executor system modules according to the lighting control instruction set to complete physical operations in linkage, and real-time monitoring of actual output parameters of the modules at a preset frequency; Comparison of the collected actual parameters with the target light domain parameters in the control instruction set to obtain parameter deviation rates as execution accuracy of the executor.

4. The method of claim 3, wherein the method further comprises: The generation of the execution state evaluation report comprises: If any parameter deviation rate does not meet the expectation, it is determined that there is a deviation, and a retry mechanism is triggered to dynamically adjust the execution parameters; After each retry, the parameter deviation rate is reacquired, and it is determined again whether the retry mechanism needs to be triggered according to the new parameter deviation rate, until all parameter deviation rates meet the expectation or the maximum number of retries is reached; Recording of state identifiers, key parameters and time data of the retry execution results, and integration into a structured execution state evaluation report.

5. The method of claim 4, wherein the method further comprises: The generation of the comprehensive data set comprises: Directional collection of user feedback data and equipment statistical data, and taking the execution state evaluation report as execution data, and taking the timestamp of the execution state evaluation report as a basis to demarcate a control period; Binding of the three types of data in the same control period according to timestamps to form an execution-feedback-equipment data group; Integration of data groups of all control periods to generate a structured comprehensive data set.

6. The method of claim 5, wherein the method further comprises: The generation of the optimization configuration package comprises: Extraction of fields of user feedback indicators, equipment state indicators and execution deviation indicators from each data group of the comprehensive data set, and then quantification of the fields of the three types of indicators into standard values; Obtaining of total evaluation values of each data group according to the three types of standard values by a preset evaluation mechanism and arranging the total evaluation values into an optimization sequence in descending order; Adjustment and update of a multi-dimensional rule matrix parameter interval and a mapping triple corresponding to the total evaluation values one by one according to the optimization sequence by a parameter optimization mechanism; Running of multiple complete control periods according to the updated multi-dimensional rule matrix and the mapping triple, and acquisition of real-time execution data, user feedback data and equipment state data, and then verification of real-time three types of indicators; If the verification result meets the preset requirement, it is determined that the adjustment is effective, and if the verification result does not meet the preset requirement, the parameter optimization mechanism is re-optimized; Generation of an optimization configuration package for the verified parameters to replace the initial configuration to form a closed-loop iterative lighting control link.

7. A lighting control system for an electrodeless yard light for implementing the method of any one of claims 1 to 6, characterized by Comprise: An initial configuration unit: deploying and calibrating multidimensional sensors and executor hardware, synchronously constructing an initial functional multi-dimensional rule matrix, and defining geographical-scene-light domain mapping triples; Generation of a standardized multidimensional data set based on real-time data collected from the calibrated hardware; The rule matching unit matches the lighting response action through a multi-dimensional rule matrix based on the standardized multi-dimensional data set, solves multi-rule matching conflicts, obtains the target light field parameters of the current scene in combination with the mapping triplets, and generates a lighting control instruction set; The monitoring and retry unit triggers the actuator system to perform corresponding operations according to the lighting control instruction set, compares the execution state with the target light field parameters in real time, triggers the retry mechanism if there is a deviation, and records the execution result to generate an execution state evaluation report; The multi-source data integration unit integrates the comprehensive data set based on the execution state evaluation report, in combination with user feedback data and equipment statistical data; The optimization iteration unit obtains a total evaluation value based on the comprehensive data set, dynamically adjusts the multi-dimensional rule matrix parameter interval and the mapping triplets according to the total evaluation value, generates an optimized configuration package, and replaces the initial configuration to form a closed-loop iterative lighting control link.

8. An endless yard light, characterized by The electrodeless yard lamp includes a computer readable storage medium, and the computer readable storage medium stores a computer program. When the computer program is executed, the lighting control method of the electrodeless yard lamp according to any one of claims 1-7 is realized.

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