11738results about "Energy saving control techniques" patented technology

The invention relates to the technical field of smart home, and discloses a festival lamplight contextual model automatic adjusting system based on a smart home system, which comprises a main controller, a lamplight contextual model recognition module, a dynamic adjustment execution module, an environmental parameter acquisition module, a user behavior analysis module and the like. The light contextual model recognition module generates an initial contextual model according to festival types and time, the environment parameter acquisition module acquires environment data in real time, the user behavior analysis module analyzes user data to generate preference feature vectors, and the main controller fuses multi-dimensional information to generate a target contextual model instruction. And the dynamic adjustment execution module adjusts the light equipment accordingly. In addition, the system also has the functions of anomaly detection, adaptive correction, contextual model optimization, equipment compatibility detection, energy consumption balance and the like. According to the invention, intelligent and personalized adjustment of the festival light contextual model is realized, the equipment compatibility and the energy consumption management efficiency are improved, and better festival light experience is brought to users.

The invention discloses a green building intelligent lighting and energy collaborative optimization system based on multi-source data fusion. According to the system, firstly, multi-source information such as indoor and outdoor illumination, weather, personnel occupation and electricity price is subjected to weighted fusion through dynamic confidence, and an accurate real-time environment state is constructed; then, model predictive control is combined with a multi-objective optimization strategy, and a sunshade device, intelligent lighting and a heating ventilation air conditioner are cooperatively adjusted, so that the comprehensive energy consumption or operation cost is minimized on the premise that the indoor illumination and temperature comfort requirements are met; besides, the self-adaptive module continuously learns and adjusts the thermal characteristics and the use mode of the building through online model parameter correction and occupancy probability prediction, and it is ensured that the energy-saving effect is stable for a long time; the system drives each execution device through a standard building self-control interface, is easy to integrate in a newly built or reformed project, and can significantly improve the energy utilization efficiency and the indoor environment quality.

The invention relates to the technical field of intelligent dimming control, and discloses an intelligent dimming control method and system based on an LED driver, and the method comprises the steps: carrying out the current and light intensity data collection of the LED driver under different dimming depth values, and obtaining a response characteristic data set; inputting the response characteristic data set into a convolutional block attention module and convolutional neural network combined architecture for training to obtain an LED response characteristic prediction model; the ratio of the light intensity change rate to the current change rate is calculated, and a piecewise linear dimming sensitivity index is obtained through piecewise linear function fitting; constructing a first-order inertia controller and a brightness feedback loop, and generating a brightness self-compensation control strategy; according to the LED driver, the brightness change response is predicted, and the PWM dimming control signal is generated according to the trajectory smoothing algorithm and the PID controller, so that the adaptive capacity of the LED driver to external interference and parameter change is enhanced, and the stability and reliability of the LED driver are improved.

The invention relates to the technical field of urban lighting control, and provides an urban lighting control fusion gateway system which comprises a multi-mode sensing network module, a causal reasoning diagnosis module, an survivability topology reconstruction module, a physiological adaptation dimming module and a disaster chain blocking module. The multi-mode sensing network module collects structural displacement, environmental data and weather prediction of the lighting facility through the unmanned aerial vehicle, the ground node and the meteorological radar. And the causal reasoning diagnosis module analyzes the facility aging reason through causal graph modeling. And the survivability topology reconstruction module optimizes the topology of the power supply network. The physiological adaptive dimming module generates color temperature-brightness parameters according to the flow of people and atmospheric optical characteristics. And the disaster chain blocking module identifies the disaster propagation node and triggers a reinforcement instruction. The reliability, the energy-saving performance and the safety of the lighting system can be improved, and the comfort level and the emergency response capability of the urban environment are optimized.

The present application relates to the technical field of light-emitting diodes, and discloses an intelligent heat dissipation control method for improving the light efficiency of light-emitting diodes. The method comprises: measuring the temperature-light efficiency of the light-emitting diode, establishing a junction temperature-light efficiency mapping model and determining an optimal working junction temperature range; hierarchically configuring the heat dissipation unit based on the junction temperature-light efficiency mapping model and the optimal working junction temperature range to obtain a multi-level heat dissipation control system; deploying a temperature sensor array and a light sensor array in the light-emitting diode to collect real-time data and obtain a temperature-light efficiency relationship curve; adjusting the parameters of the multi-level heat dissipation control system according to the temperature-light efficiency relationship curve to obtain a heat dissipation control instruction sequence; dynamically compensating the driving current of the light-emitting diode based on the heat dissipation control instruction sequence to obtain the optimal driving parameters, thereby realizing the stable operation of the LED within the optimal working junction temperature range and significantly improving the photoelectric conversion efficiency.

The invention belongs to the technical field of intelligent lighting, and discloses an intelligent adjustment method and system for the spectrum of a quantum dot light-emitting lamp. The objective of the invention is to solve the problem that an existing lighting system cannot meet personalized healthy lighting requirements. The method comprises the following steps: firstly, acquiring user biological rhythm, environment spectrum, use scene, user preference and physiological health data through multi-dimensional data acquisition, and constructing a feature data set; then human factor optical feature extraction and cross-situation demand analysis are carried out, and a spectral response model is established; carrying out quantum dot material photoelectric characteristic mapping and spectrum synthesis modeling based on the model, and determining a luminescence parameter space; constructing a spectrum optimization model, performing multi-objective optimization by comprehensively considering visual comfort, energy efficiency and health influence, and generating a dynamic spectrum regulation and control strategy; closed-loop verification and adaptive optimization are carried out based on real-time physiological feedback, and an intelligent spectrum adjustment scheme is formed. According to the invention, the advantage of spectrum adjustability of the quantum dot material is fully exerted, and real personalized intelligent illumination is realized.

The invention provides a cooperative control method and system for a distributed intelligent lamp network, and the method comprises the steps: obtaining the real-time operation state data of each lamp in the intelligent lamp network, recognizing the failure position of the lamp, generating a fault node coordinate according to the failure position of the lamp, and obtaining the distribution information of the failure lamp; extracting spatial position data and current illumination parameters of surrounding lamps according to the distribution information of the failed lamps, calculating an illumination dead angle range and a local illumination decline region by adopting a geometric algorithm, and determining an affected light environment region range; acquiring communication time delay and response rate between the lamps, and if the communication time delay exceeds a preset time delay threshold, reducing the adjustment frequency and reallocating the compensation task to obtain an optimized cooperative compensation scheme; and extracting residual range data of the illumination dead angle according to the adjusted illumination distribution result, carrying out secondary adjustment on the illumination angle and the luminous intensity through an iterative algorithm, and determining a light environment continuity parameter after the illumination dead angle is eliminated.

The invention relates to a light control method and system based on AI model analysis, and the method comprises the steps: obtaining environment illumination data of a target scene and user interaction input, and carrying out the semantic demand analysis, and obtaining semantic description information; performing illumination demand analysis on the semantic description information through a pre-trained light driving model to obtain illumination demand parameters; performing light field demand analysis on the illumination demand parameters according to the environment illumination data and the user interaction input, and generating light field control information; and acquiring power load data, performing instruction construction on the light field control information, and generating a light control instruction. According to the invention, dynamic self-adaptive regulation and control of the light environment can be realized, and the limitation that the existing method only depends on static compensation and cannot adapt to complex scene changes is overcome.

The invention provides a highway tunnel intelligent illumination control method and system, and the method comprises the steps: collecting a real-time perception data set of a plurality of monitoring nodes in a target tunnel, covering a light source operation parameter, an illumination intensity parameter and an environment state parameter sequence, carrying out the feature extraction of the real-time perception data set, and carrying out the feature extraction of the real-time perception data set; generating a global feature set including light source operation stability, regional illumination coordination and environmental coupling influence features, and then inputting the global feature set into a preset dynamic decision model for strategy decision to obtain a multi-stage illumination regulation and control strategy set covering different regions, including target brightness, dimming time sequence and equipment cooperation parameters; and finally, generating an executable instruction set according to the multi-stage illumination regulation strategy set, issuing the executable instruction set to each partition illumination control terminal, and triggering adaptive dimming of the illumination equipment, thereby realizing intelligent management and control of tunnel illumination, improving an energy-saving effect and illumination quality, and ensuring driving safety.

The invention relates to the technical field of intelligent control, and discloses a vehicle-mounted atmosphere lamp control method and system based on environmental perception. The method comprises the following steps: acquiring in-vehicle image data and vehicle-mounted sensor data, and inputting the data into a double-branch Mama information fusion module for feature extraction and fusion processing to obtain a fusion feature map; performing situation recognition and analysis on the fused feature map to obtain a driving situation feature vector and a situation incidence matrix; according to the driving situation feature vector and the situation incidence matrix, vehicle-mounted atmosphere lamp parameters are decoupled, and decoupled illumination parameters are obtained; and performing situation self-adaptive lighting regulation and control and dynamic situation weighted loss calculation on the decoupled lighting parameters and the driving situation feature vectors to obtain target lighting control parameters. According to the invention, the problem of unbalanced illumination requirements in different driving scenes is solved, and the adjustment of the vehicle-mounted atmosphere lamp is more accurate.

The invention relates to the technical field of smart lighting, in particular to a smart lighting decision optimization method based on big data, which comprises the following steps of: firstly, acquiring data of a lighting area in real time, performing spatial-temporal feature extraction on the data, the method comprises the steps of generating a region illumination demand feature vector based on a real-time feature vector, then generating a dynamic illumination optimization strategy based on a reinforcement learning model in combination with a historical illumination strategy library and the real-time feature vector, and finally adjusting brightness parameters and spectral distribution of each intelligent lamp in a region according to the dynamic illumination optimization strategy. According to the method, the data of the illumination area is collected in real time, the optimization strategy is dynamically generated in combination with the reinforcement learning model, illumination requirements of different time periods and different areas can be accurately matched, and therefore the problem that in the prior art, real-time optimization of the illumination strategy in the dynamic environment is insufficient is effectively solved.

The invention provides a scene adaptive projection vehicle lamp system based on deep reinforcement learning and a control method, and relates to the technical field of intelligent vehicle lamps and automatic driving perception systems. Comprising a multi-modal sensing module, a feature fusion module, a strategy generation module and an execution module. The multi-mode sensing module is used for collecting environment state data and performing primary processing to form an environment data information flow; the feature fusion module is used for generating a unified environment feature vector for the environment data information flow; the strategy generation module is used for receiving the environment feature vector and generating a vehicle lamp adjustment strategy through multi-layer neural network calculation; evaluating a result obtained by executing the vehicle lamp adjustment strategy based on the vehicle lamp, and optimizing strategy parameters of the strategy network based on a PPO algorithm; the execution module is used for controlling the vehicle lamp according to the vehicle lamp adjustment strategy output by the strategy network. The intelligent level of the vehicle lamp is remarkably improved, and the system is widely applied to night driving assistance, urban interaction prompt and low-visibility driving scenes.

The invention relates to the technical field of light attenuation compensation control, in particular to an automatic light source control method and system. The method comprises the following steps: acquiring historical light source operation state parameters, performing long-time-sequence operation state change evolution, and constructing a long-time-sequence light source state change curve; performing nonlinear light source attenuation analysis and multi-period light source attenuation evolution on the long-time sequence light source state change curve to construct a light source attenuation evolution model; acquiring real-time light source operation state monitoring parameters and environment illumination signals; inputting into a light source attenuation evolution model, and carrying out light source attenuation evolution simulation to obtain a light source attenuation gradient situation; and acquiring real-time working current and voltage parameters of the automatic light source, and performing adaptive light attenuation compensation optimization based on the attenuation gradient situation of the light source so as to generate an adaptive light attenuation compensation optimization engine. According to the invention, the accuracy and effect of overall compensation control of light attenuation of the light source are improved.

The invention relates to the technical field of electrical performance testing, and particularly discloses an LED vehicle lamp operation monitoring system and method based on data analysis, and the system can accurately obtain the illumination parameters of the environment where an LED vehicle lamp is located, further scientifically analyzes and determines the reference illumination intensity of the LED vehicle lamp, and on this basis, comprehensively monitors and carefully collects the circuit information of the LED vehicle lamp, thereby improving the reliability of the LED vehicle lamp. Through a data analysis technology, each abnormal lamp bead existing in the LED vehicle lamp is accurately positioned, the abnormal lamp beads are specifically adjusted according to predetermined reference illumination intensity, after adjustment is completed, the running state parameters of the LED vehicle lamp are further monitored, the adjustment adaptation index of the LED vehicle lamp is evaluated accordingly, and the adjustment adaptation index of the LED vehicle lamp is evaluated according to the running state parameters of the LED vehicle lamp. Therefore, whether further performance adjustment needs to be carried out or not is intelligently judged, the adjustment effect is fed back in time, and therefore it is ensured that the made adjustment can fully meet set performance indexes.

The present invention provides a method, device, equipment and storage medium for calibrating an optical detection light source, the method comprising: performing multi-parameter data collection on a target light source, iteratively optimizing light source parameters, and obtaining optimal parameter settings and performance indicators. Based on the optimal parameter settings and performance indicators, the target light source is monitored and processed in real time, the drift trend data of the light source parameters are obtained, and automatic compensation is performed according to the drift trend to generate corrected light source parameters. By cumulatively analyzing the corrected light source parameters, an association model between the light source parameters and environmental conditions is constructed. According to the association model and the corrected light source parameters, a standard reference spectrum matching the current detection task is selected, and the actual output of the target light source is calibrated based on the reference spectrum. The present invention combines multi-parameter data collection and optimization, drift trend monitoring and automatic compensation processing to realize dynamic association modeling of light source parameters and environmental conditions, perform adaptive calibration, and improve the accuracy and stability of the detection system.

The invention provides an intelligent control method for a floodlight illumination system, and the method comprises the steps: obtaining an environment surface roughness coefficient, spectral reflection distribution and spatial geometric change data, determining the wall surface material absorptivity and shielding region coordinates, and obtaining environment reflection characteristics and shielding distribution data; analyzing shielding boundary sharpness and shielding angle distribution according to the spatial geometric change and the coordinates of the shielding area, calculating a luminous flux distribution curve of a local dark area, and judging whether the influence range of the dark area exceeds a preset threshold range or not; calculating the illumination coverage integrity according to the updated light field distribution and polarization reflection characteristics, determining the boundary sharpness of a light beam, and obtaining a light field uniformity parameter; and according to the light field uniformity parameter and the shielding thermal radiation effect, calculating and optimizing light field parameters.

The invention discloses an intelligent lighting management system and method based on multi-source data, and relates to the technical field of intelligent lighting management, and the system comprises a multi-source data collection module, an environment feature anchoring module, a dynamic error modeling and calibration module, an edge-cloud collaborative decision module and a lighting strategy execution module. The multi-source data acquisition module fuses environment sensor, visual perception and laser radar data to construct a'sensor original data + environment characteristic data 'dual-input system; the environment feature anchoring module extracts stable features from the visual / laser radar data to serve as a calibration reference; the dynamic error modeling and calibration module quantifies the error in real time based on the reference and generates calibration parameters; the edge-cloud collaborative decision-making module and cloud long-term optimization form a hierarchical collaborative architecture through edge node real-time control; and the lighting strategy execution module dynamically adjusts lighting parameters according to the calibration data and feeds back an effect to form a closed loop.

The invention relates to the technical field of light source adjustment, in particular to an automatic light source adjustment method and system based on real-time environment change. The method comprises the following steps: collecting environment illumination monitoring parameters of an automatic light source, and carrying out real-time light path tracking and dynamic light environment perception modeling to construct a real-time light environment perception map; obtaining an automatic light source historical operation report, carrying out light source parameter preference mining, and carrying out adaptive light source adjustment according to a real-time light environment perception map so as to construct an initial light source regulation and control strategy; performing light source control execution according to the initial light source regulation and control strategy, performing space light source disturbance detection, and generating disturbance light source multi-dimensional features; and performing light source change situation evolution analysis on the multi-dimensional characteristics of the disturbed light source, performing intelligent light disturbance reverse compensation, and constructing an intelligent anti-interference light source regulation and control strategy. According to the invention, real-time light source compensation adjustment is carried out according to environment light source changes, and accurate and rapid user light source demand response is realized.

The invention belongs to the technical field of face recognition, and particularly relates to a face recognition algorithm adaptive to illumination variation, which uses Gaussian filtering to reduce noise caused by illumination variation, convert a color image into a grey-scale image, reduce calculation complexity, perform adaptive histogram equalization, estimate global illumination conditions in the image and improve the face recognition accuracy. Calculating the main direction and intensity of illumination in the image, predicting the current illumination condition, and enabling the image brightness to adapt to different environment illumination; identifying a face region in the image, using a deep learning method to position face related points, using an LBP to extract local features insensitive to illumination variation, and using a deep convolutional neural network to extract global features; introducing a multi-illumination data set; the Euclidean distance is used for comparing the extracted feature vectors, the similarity between the extracted feature vectors and known faces in a database is recognized, according to the similarity score, threshold judgment is adopted for AQW to obtain a final recognition decision, and the method has the effect of being capable of accurately adapting to facial features under different illumination conditions in real time.

The invention discloses an LED street lamp multi-scene intelligent regulation and control method and system for road illumination. The method comprises the steps that environment sensing parameters and equipment state parameters are collected; constructing a dynamic light scattering model according to the environment perception parameters and the equipment state parameters, predicting effective illumination distribution from the LED light source to the road surface in the current environment, and generating an LED spectrum compensation strategy; the real value of effective illumination distribution from the LED light source to the road surface is monitored in real time, the deviation between the real value and a predicted value is analyzed, and if the deviation exceeds a preset threshold value, the light attenuation coefficient, the road surface equivalent reflectivity and the LED working temperature are calculated in a reverse iteration mode according to the deviation so as to update the LED spectrum compensation strategy; and generating a PWM (Pulse Width Modulation) driving signal according to the updated LED spectrum compensation strategy, controlling the duty ratio of each sub light source in the LED array, and dynamically adjusting the LED spectrum distribution. According to the method, the LED operation parameters are dynamically regulated and controlled through the deviation between the true value and the predicted value of the effective illumination distribution, the light attenuation is compensated in real time, the spectral efficiency is optimized, and the LED power consumption is reduced on the premise of ensuring the illumination quality.

The invention discloses a matrix layout illumination state detection method, device and equipment, and the method comprises the steps: collecting and analyzing a power supply bus current waveform and a single lamp feedback signal, and generating a node feature cluster; extracting a power consumption difference value of adjacent lamps, identifying an abnormal observation point and constructing a fault diffusion chain; marking a timestamp for the fault diffusion chain, determining a fault source, and marking current by injecting characteristics to delimit an influence domain; deploying monitoring anchor points at the boundary of the influence domain, collecting the light color parameter variation and predicting the residual life; extracting the oscillation envelope of the starting current peak, evaluating the health degree of the driver and generating a maintenance density field; and a three-dimensional detection field is constructed by fusing multi-dimensional detection data, singular points are searched, and coordinates of a fault lamp are accurately analyzed through fault positioning pulses. According to the invention, three-dimensional monitoring from electrical characteristics and optical performance to driver states is realized, a single lamp fault can be accurately positioned, a life trend can be predicted, fault propagation can be tracked, and technical support is provided for intelligent operation and maintenance of a large-scale illumination system.

The invention relates to an intelligent dimming method and device for a multispectral light source and a storage medium, and the method comprises the steps: obtaining the spectral parameters and environment illumination data of the multispectral light source, carrying out the analysis processing of the spectral parameters based on the environment illumination data, and obtaining the corresponding target spectral information; acquiring real-time output data of the multispectral light source, and performing association processing on the real-time output data and the target spectral information to obtain a corresponding real-time spectral group; acquiring illumination feedback data of the multispectral light source, and performing spectral prediction on the target spectral information to obtain corresponding spectral adjustment information; performing dimming planning analysis on the real-time spectrum group and the spectrum adjustment information to obtain a corresponding initial light source control scheme; performing spectrum identification on the illumination feedback data to obtain corresponding characteristic spectrum information; and performing dimming optimization on the initial light source control scheme according to the characteristic spectral response parameters to obtain a corresponding global dimming strategy. According to the invention, global optimization of the system can be realized through optimization and adjustment of the characteristic spectral response parameters.

The invention discloses a personalized illumination adjustment system based on artificial intelligence, and relates to the field of illumination adjustment, and the system comprises an identity recognition module which is used for providing user identity registration, distributing a user ID, and allowing login after identity verification; the attention recognition module is used for capturing a user face image through a camera part, judging the attention concentration direction of the user and generating current state data of the user; the behavior prediction module is used for collecting historical moving paths and dwell time data of the user in the control area, predicting future behaviors of the user through a time sequence prediction algorithm, and generating a behavior track diagram of the user; illumination is adjusted in advance to adapt to the current demand of the user, manual operation is reduced, convenience is improved, the moving path and stay time of the user are predicted, lamplight configuration can be actively adjusted, energy is saved, it is ensured that the user can obtain the optimal illumination effect in the place where illumination is most needed, and the adjusting scheme can adapt to complex and changing use scenes.

The invention relates to the technical field of LED dimming control, in particular to an LED ceiling lamp control system based on dynamic light source adjustment, which comprises a brightness sensing module, a dimming decision module, a light source regulation and control module, an anomaly detection module and a brightness optimization module. According to the invention, the operation load of the lamp is dynamically measured and calculated by combining ambient light and thermal radiation data, the collaborative perception of illumination intensity and thermal energy distribution is realized, the response sensitivity to weak brightness change is improved by comparing the brightness demand with the real-time output deviation and accurately identifying the dimming trigger condition, and the response sensitivity to weak brightness change is improved by comparing the initial brightness with the feedback difference value. The brightness of a plurality of lamps can be adjusted coordinately, the spatial light environment is kept stable and consistent, overload and temperature rise abnormity can be checked and abnormal lamps can be identified by combining current fluctuation and temperature abrupt change analysis, an intervention record and reaction duration comparison mechanism is introduced into a regulation and control instruction, the response efficiency is improved, and the efficiency is improved. And brightness priority adjustment and overall illumination balance control of the key area are realized.

The invention discloses a lighting data management system and method for street lamp networking, relates to the field of lighting data management, and aims to solve the problem of waste of lighting resources. The technical scheme is characterized in that all street lamp nodes are networked according to physical positions, and a geographic information database is constructed; collecting motion data of a moving target and environment illumination intensity data; when the moving target is detected to be a pedestrian or a vehicle, switching the current street lamp node and the adjacent street lamp node to a normal mode; predicting the trajectory of the moving target, and calculating the number of street lamps needing to be turned on in advance according to the moving target speed and the safety response time; when the moving target approaches the intersection, the street lamp nodes of the intersection branches are converted from an energy-saving mode to a normal mode; and when the moving target leaves the detection range of the sensor, the street lamp nodes of the branch paths which are not actually passed are recovered to the energy-saving mode, so that on-demand illumination is achieved, and the effect of reducing the energy consumption of the street lamp is achieved.

The invention relates to a tunnel illumination control method considering visual adaptability of a driver, and belongs to the technical field of tunnel illumination control, and the method comprises the following steps: S1, employing a volume scattering point location method to obtain visual adaptability parameters of visual adaptation states of all segments in a tunnel; s2, dynamically constructing a predictive visual adaptation model of the driver group based on the visual adaptation parameters, and outputting expected visual states of the drivers according to the predictive visual adaptation model; s3, according to the expected visual state, a parameter control mechanism is adopted to control target illumination parameters of all the sections of the tunnel; s4, according to the target lighting parameters, the working state of lighting equipment in a corresponding section in the tunnel is regulated and controlled, so that the light environment in the tunnel is matched with the dynamic visual adaptability of a driver, and safe visual guidance is achieved; the method has the beneficial effects that the target illumination parameters of all the sections of the tunnel are controlled by adopting a parameter control mechanism according to the expected visual state according to the target illumination parameters.

The invention relates to the technical field of LED lamp adjustment, in particular to a multi-path adjusting system of an LED lamp. The method comprises the following steps that: a parameter acquisition module acquires multi-path real-time light intensity parameters and performs noise covariance estimation and channel interference analysis to generate a noise matrix and a channel crosstalk matrix, a change simulation module predicts light intensity change based on the matrixes and generates a simulation LED lamp group, and a dead zone compensation module calculates a duty ratio and performs compensation. According to the method, an anti-overlapping sequence is formed, in the phase distribution module, phase quantization and peak shifting distribution are carried out on the anti-overlapping sequence to obtain a peak shifting control sequence, the channel coordination module generates a multi-path control sequence according to temperature compensation processing, and the feedback optimization module continuously adjusts an LED lamp set by collecting a feedback strong light value to achieve accurate multi-path adjustment. According to the invention, the accuracy of LED lamp adjustment is improved.

The invention discloses a backlight source partition dimming control method, and belongs to the field of data security, and the control method comprises the following specific steps: I, analyzing the data features of an input image, recognizing a highlight motion region, and predicting and optimizing a current backlight partition dimming strategy; iI, adjusting a backlight area in real time according to the brightness, contrast and color change of the input content, and constructing a multi-level light diffusion coupling model after partition adjustment; the backlight partition can be adaptively adjusted according to the image content, the local contrast ratio and energy efficiency are improved, more uniform light distribution is achieved, the problems of halo and uneven brightness are reduced, the dimming precision is improved, the service life of a light source is prolonged, the light overflow effect of the partition edge is effectively reduced, and the picture layering sense is improved; the subjective image quality experience is effectively improved, the light efficiency utilization rate is improved, meanwhile, image quality and power consumption optimization can be considered, brightness adjustment better conforms to human eye visual characteristics, visual fatigue is reduced, and it is ensured that the optimal image quality is maintained under the lowest power consumption.

The invention relates to the field of illumination control, and discloses a regional illumination control method and system, and the method comprises the steps: obtaining the equipment state information, illumination intensity and personnel image information of each sub-region of a target region; the sub-regions are determined based on the building layout and function purpose division of the target region; identifying a personnel activity type and a personnel position based on the personnel image data; obtaining a static illumination demand of each sub-region of the target region; the static illumination demand comprises a brightness value and a color temperature; inputting the personnel position, the personnel activity type, the illumination intensity and the static illumination demand of each sub-region into an illumination demand prediction model; the illumination demand prediction model outputs an expected illumination demand of each sub-region; and generating a lighting control strategy for an optimization target based on the expected lighting demand of each sub-region in combination with the lighting comfort and the service life of the lighting equipment. The method has the following effect that the light requirements of people in different activity scenes are met.

The present invention provides a fault diagnosis and maintenance method and system for a smart street lamp, the method comprising: collecting data on the operating parameters of each component node of the smart street lamp, performing noise reduction processing using wavelet transform, and generating structured data. By combining principal component analysis and sliding time window technology with Mahalanobis distance calculation, feature extraction and spatiotemporal correlation analysis are performed on the structured data to obtain key features and spatiotemporal correlation information between nodes. The above information is input into a spatiotemporal hybrid model to generate fault detection results, and a machine learning algorithm is used to locate the faulty components, predict their performance degradation trends, and generate targeted maintenance strategies. The present invention realizes intelligent management of the entire process from fault detection to maintenance, effectively improving the operating stability and management efficiency of smart street lamps.