4598 results about "Light equipment" patented technology

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 discloses a tunnel traffic control method and system for multi-mode traffic variable analysis, and relates to the field of general control or regulation systems, and the method comprises the steps: obtaining vehicle operation state information and pollutant concentration distribution data, determining a pollutant generation region based on a vehicle state, and calculating a concentration gradient value and a diffusion rate value. And analyzing the concentration change trend according to the spatial-temporal distribution relationship, and dividing a vertical control region. And setting initial operation parameters of the jet fan in a preset adjustment range and a step length according to the pollutant distribution characteristics of each area. And monitoring area concentration distribution in real time, when a target area exceeds the standard, dynamically adjusting fan parameters of the area and an adjacent area to preset values, and setting illumination parameters of illumination equipment in the vertical control area according to pollutant concentration distribution characteristics. By implementing the method, the accuracy of tunnel partition environment parameter adjustment can be improved.

The invention relates to the technical field of automatic induction, and discloses an automatic induction lamplight angle adjustment control method and device and lighting equipment. The method comprises the following steps: acquiring ambient light parameters in real time to obtain ambient light sensing data; performing multi-scale space division and feature fusion on the ambient light sensing data to obtain a three-dimensional ambient light distribution diagram; inputting the three-dimensional ambient light distribution diagram into a light angle calculation network for light change characteristic analysis to obtain a light optimal angle parameter group; performing smooth transition light sequence calculation according to the light optimal angle parameter group and the current light configuration state to obtain a sectional light adjustment control instruction; and performing motion path planning on the end effector of the lamp based on the sectional light adjustment control instruction to obtain an effector motion instruction set. According to the invention, light change characteristics of different spatial scales can be captured at the same time, and the adjustment accuracy and adaptability of the actuator are improved.

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 discloses a context awareness voice control lighting relieving method and system, and relates to the technical field of intelligent lighting control, and the method comprises the steps: obtaining a user voice instruction and environment data; performing semantic analysis on the user voice instruction, and extracting a control intention and a parameter requirement from the user voice instruction; determining target lighting parameters according to the control intention, the parameter requirements and the environment data; obtaining a current lighting state, and calculating a transition path from the current lighting state to the target lighting parameters; the transition path comprises a gradual change sequence of illumination parameters; and controlling the lighting equipment to perform lighting adjustment according to the transition path. According to the method, through technologies of multi-dimensional environment data fusion, deep semantic analysis, smooth transition control and the like, precise matching of the illumination parameters and user requirements is realized, and the user comfort and the system intelligence level are greatly improved.

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 invention relates to the technical field of self-adaptive control, in particular to an operation period building energy-saving low-carbon control method and system based on artificial intelligence, and the method comprises the following steps: collecting and analyzing the room use condition and illumination intensity, and obtaining an activity type recognition result; according to the invention, based on real-time analysis of room use conditions and illumination intensity, use modes of different areas are identified, and in combination with natural light changes and indoor activity requirements, required illumination intensity and color temperature adjustment parameters are dynamically calculated, so that accurate matching of illumination environments is realized. A dynamic feedback mechanism is established by monitoring the adjustment state of the lighting equipment in real time in combination with the change of the room use mode, the lighting deviation is adaptively corrected, and energy waste is avoided. By introducing reinforcement learning, the ventilation strategy can be continuously optimized through historical data and real-time feedback, personalized air quality management is achieved, and single adjustment is not executed based on a fixed threshold value.

The invention discloses a dynamic resource allocation system and method for smart travel. The system comprises a multi-source data acquisition module, a data fusion module, a prediction module, a framework construction module, an algorithm optimization module, a feedback module and a resource allocation module. According to the method, environment data, energy consumption data, renewable energy supply data and tourist flow data in a plurality of sub-regions of the tourist attraction are collected, and fusion and deep learning prediction are carried out on the data, so that future energy consumption, energy supply and flow data are obtained. And a reinforcement learning scheduling framework is constructed, and intelligent scheduling of the charging pile, the electric sightseeing vehicle, the lighting equipment and the monitoring equipment is realized. And carrying out global optimization on the resource scheduling scheme by adopting a speed pause particle swarm optimization algorithm so as to output a resource allocation scheme with optimal energy consumption. The scheduling scheme is further optimized based on user feedback data, and the dynamic adaptability of resource configuration is ensured. According to the invention, the energy utilization efficiency in the smart travel scene is improved, and the operation cost is reduced.

The invention relates to the technical field of illumination control, in particular to an LED illumination efficiency optimization method and system, and the method comprises the following steps: recognizing an illumination use mode and a change trend of an environment condition based on real-time external environment data and historical LED illumination operation data, and obtaining an environment and operation data analysis result. According to the invention, prediction analysis is carried out on the LED illumination demand through the Gaussian process regression model, accurate prediction of the illumination demand under differentiated environmental conditions and time periods is realized, the responsiveness and adaptability of the illumination equipment are improved, the illumination control decision process is optimized by comprehensively considering the real-time external environment data and the historical illumination operation data, and the accuracy of the illumination control decision process is improved. The introduction of the hybrid dynamic Bayesian network enhances the real-time evaluation capability of the energy efficiency state of the LED lighting equipment, so that the energy efficiency management is more precise and efficient, and the use of a multi-objective optimization strategy provides a more comprehensive solution for balancing the energy efficiency, the illumination quality and the user comfort.

The invention discloses a smart city energy management system based on energy conservation and emission reduction, and relates to the technical field of smart city energy management. By using an intelligent sensor group, illumination related data of illumination equipment is obtained, an illumination related data set R is constructed, and a light attenuation factor Gs, a convective heat transfer index DL and a use intensity factor Qd are extracted; the method comprises the following steps: dynamically evaluating the thermal load intensity of an urban area, scientifically dividing thermal risk grades, combining performance brightness prediction and control strategy matching to realize subarea and lamp-divided refined dimming control, using a feedback self-evaluation and optimization regulation and control mechanism, carrying out power reestimation and strategy alternation on an area with a substandard control effect, and carrying out power control on the area with the substandard control effect. Redundant energy consumption is effectively reduced, heat accumulation is restrained, and the lighting efficiency and the environment comfort degree are improved.

The invention discloses an excavation part surrounding rock image-based blasting parameter real-time adjustment technology, which comprises the following working steps of: S1, equipment selection and arrangement: selecting photographic equipment with a frame rate of 100,000 frames per second and a resolution ratio of 4K or more, arranging a plurality of cameras to shoot a blasting process from different angles, and then configuring strong lighting equipment, and a strain sensor, a vibration sensor, a pressure sensor and a sonic sensor are installed, and blasting data are collected in real time. By improving the performance of the high-speed photographic equipment and applying technical means such as a three-dimensional reconstruction technology, a real-time feedback control system, AI auxiliary analysis, sensor fusion, numerical simulation, unmanned operation and the like, the precision and efficiency of researching the expansion rule of the blasting crack can be further improved. According to the improved technology, more accurate and dynamic support is provided for blasting design, blasting damage control is optimized, and the safety and efficiency of engineering application are improved.

A multimode lighting system is disclosed. Due to industry standards, manufacturers of lighting devices are incentivized to create high initial light outputs that drop off quickly. Portable lighting devices with multiple modes of operation that can maximize light output and runtime according to industry standards (e.g., FL-1) as well as other lighting modes with more consistent light output over the device runtime. Lighting modes may be adjusted automatically based on sensor input. In an extreme mode, light output may be adjusted based on the temperature of the lights. Automatic modes may be adjusted based on ambient lighting or distance to a target. Lifecycle adjustments may be made to output current levels to obtain consistent light output throughout the lifecycle of lights by adjusting lighting based on accumulated usage.

The invention provides a load balancing method for intelligent lighting collaborative management and related equipment, and the method comprises the steps: collecting the environment parameters of each lighting region in real time, and carrying out the preprocessing of the environment parameters; inputting the preprocessed environment parameters into a preset deep neural network model, and determining a load prediction sequence of each illumination area; judging the load state of each lighting area according to the load prediction sequence; based on the load state and the real-time environment data, generating a multi-region collaborative dimming rate set through a region layering collaborative strategy; and performing illumination control on the illumination equipment in the target illumination area according to the multi-area cooperative dimming rate set. Through the implementation of the scheme of the invention, intelligent dimming control under cross-region, dynamic perception and prediction driving is realized, and the dynamic adaptive capacity and the load control precision of the illumination system are improved.

The present invention relates to a home appliance comprising: a cabinet having a storage space; and a door configured by a door body for opening or closing the cabinet and a panel assembly detachably mounted to the door body, wherein the panel assembly includes: a panel forming the front surface of the door; and a lighting device provided behind the panel, and the door body is provided with a grounding member for inducing static electricity generated in the panel assembly to the door body.

The invention discloses an intelligent courtyard ecological collaborative management system and method. The system comprises a sensing layer, a control layer and an execution layer. The sensing layer is provided with a multi-mode sensor array, comprises an environment monitoring module, an equipment state monitoring module and a biological recognition module, can collect multi-mode data such as illumination, temperature and humidity, equipment operation parameters and plant growth states, and transmits the multi-mode data to the control layer through wireless communication. The control layer adopts a federated learning framework to fuse multi-modal data, extracts features through a deep residual network, generates an environment state matrix by using an attention mechanism, and operates a Markov decision model to output a decision control command and a response level. And the execution layer adjusts the on-off state and operation parameters of the regulation and control equipment according to the output, so that intelligent cooperative control of the irrigation system, the lighting equipment and the like is realized. According to the system, through multi-modal data acquisition and deep fusion analysis, comprehensive perception and accurate regulation and control of the ecological environment of the courtyard are realized, and the management efficiency and the resource utilization rate are improved.

The invention relates to a portable light apparatus configured to be worn by a user, the portable light apparatus comprising a front frame to house eyeglasses and a pair of side frames connected to the front frame, an operating device having at least a battery and at least one auxiliary electronic part having a light device configured to emit light towards the eyeglasses and / or the user's eyes. Further, the invention relates to a charging case for a portable light apparatus and a control system providing remote control for a portable light apparatus.

The invention discloses a waste lithium battery classification processing method and system based on image segmentation identification, and relates to the technical field of waste lithium battery recycling, and the method comprises the steps: configuring a high-resolution camera, a lighting device and an ambient light sensor, collecting multi-view images of waste lithium batteries in real time, obtaining a two-dimensional image data set, and carrying out the recognition of the two-dimensional image data set; inputting the two-dimensional image data set into an SIFT algorithm to detect and match feature points, generating a three-dimensional model through an MVS technology based on the matched feature points, and obtaining geometric information of the surface of the battery by using a triangulation method; according to the method, the high-quality three-dimensional model is generated by combining high-resolution multi-view image acquisition with SIFT feature point matching and the MVS technology, and the quality of the model is optimized through denoising, curvature enhancement and dynamic parameter adjustment, so that accurate modeling of a complex geometrical shape is ensured. And the optimized three-dimensional model is analyzed by using the deep convolutional neural network, so that the robustness and accuracy of defect detection are greatly improved.

One or more reduced, same form, light emitting apparatus(es) spaced apart and configured to be mounted at various heights and / or spacing employ the same power consuming light source input that is covered by a symmetrical or asymmetrical redirecting linear lens optics apparatus that is configured for use in a range of mounting heights to uniformly illuminate at least one legal path of egress below. An exemplary light apparatus is a horizontally rotatable device configured to project an illuminated directional building evacuation symbol / text / image onto an illuminated egress path below.

The invention provides an energy-saving optimization method and device for intelligent city lighting and energy management. The method comprises the following steps: acquiring multi-source fusion data acquired by a multi-mode sensor configured at a lighting node in real time; carrying out coupling analysis on junction temperature fluctuation characteristics of the lighting equipment and a harmonic spectrum of a power supply system according to the multi-source fusion data, and determining dynamic characteristic parameters of the lighting equipment; constructing a multi-objective optimization function according to the dynamic characteristic parameters; and processing the multi-objective optimization function to generate a multi-domain collaborative optimization control strategy. Through implementation of the scheme of the invention, the finally output multi-domain cooperative control strategy can dynamically adjust illumination output and power supply deployment in real time according to the sensing data, and the overall energy consumption of the illumination system is effectively reduced.

The invention provides a landscape design identification method and system based on a neural network model. The method comprises the following steps: by acquiring landscape design data, lighting equipment data and energy supply network real-time load data in a target area, establishing an optical model to analyze a spatial attenuation effect of vegetation shielding and artificial structure reflectivity on a lighting beam; calculating an energy consumption mapping relation between the lamp power distribution and the energy network load based on an energy transfer model; generating a dynamic dimming strategy in combination with a spatial attenuation effect and an energy consumption mapping relation, coupling the dynamic dimming strategy with a tourist distribution thermodynamic diagram and environment illumination intensity data which are acquired in real time, inputting the dynamic dimming strategy into a neural network model for iterative optimization, and dynamically adjusting lamp power distribution, a light beam angle coverage range and a light source color temperature parameter; dynamic optimization of the landscape lighting effect and minimization of energy consumption are achieved, and meanwhile the visual experience and comfort of tourists are improved. The invention provides an intelligent dynamic optimization technical scheme of a landscape lighting effect.

The invention provides a multi-scene illumination management system integrating voice control and remote monitoring, and relates to the technical field of illumination management, and the system comprises the steps: receiving a scene wake-up instruction collected by a microphone array and a scene switching instruction sent by a remote monitoring terminal; adding priority labels and timestamps to the scene wakeup instruction and the scene switching instruction, and when it is detected that a timestamp difference value between the scene wakeup instruction and the scene switching instruction is smaller than a conflict time threshold value, determining an instruction arbitration coefficient through preemptive priority weights of the scene wakeup instruction and the scene switching instruction, determining an effective instruction according to the instruction arbitration coefficient and all the priority labels; and when the instruction priority of the effective instruction is greater than the instruction priority of the currently executed illumination scene instruction, generating a coverage execution signal, otherwise, generating an instruction discarding signal, further outputting an illumination control signal, and adjusting light parameters of the illumination equipment through the illumination control signal. According to the invention, multi-control-source conflicts in a lighting management system can be eliminated.

The invention provides a hyperbolic glass curtain wall damage prediction method, device and system. The method comprises the following steps: acquiring sensor acquisition information of a hyperbolic glass curtain wall; a preset unmanned aerial vehicle is controlled to collect a visible light image and a thermal imaging image corresponding to the hyperbolic glass curtain wall; the unmanned aerial vehicle carries visible light equipment and a thermal infrared imager; inputting the visible light image and the thermal imaging image into a damage feature recognition model based on a convolutional neural network, and outputting image feature information; inputting information acquired by the sensor into a physical parameter analysis model based on a time sequence, and outputting parameter characteristic information; fusing the image feature information with the parameter feature information to obtain a damage feature recognition result; and constructing a health state prediction model according to the damage feature recognition, inputting the real-time sensor acquisition information, the real-time visible light image and the real-time thermal imaging image corresponding to the hyperbolic glass curtain wall into the health state prediction model, and outputting a damage prediction result corresponding to the hyperbolic glass curtain wall.

A lighting device includes a connector body defining a first axis and a second axis, and a light head rotatably coupled to the connector body for rotation about the first axis. The light head includes a housing and a light source supported by the housing. The lighting device also includes a first leg rotatably coupled to the connector body for rotation about the second axis. The first leg extends to a first distal end. The lighting device also includes a second leg rotatably coupled to the connector body for rotation about the second axis independent from the first leg. The second leg extends to a second distal end. The first distal end of the first leg removably engages the second distal end of the second leg. The first leg and the second leg are configurable to support the light head.

The invention relates to the technical field of intelligent control, and discloses an intelligent lighting management control system and method based on the Internet of Things. Comprising an illumination data capturing module, a personnel activity monitoring module, an illumination equipment parameter module, an illumination environment recording module, a scene mode presetting module, a multi-dimensional data preprocessing module, a multi-dimensional data analysis module, an auxiliary management module, an illumination management module, an illumination control module and a user interaction module which cooperate with one another, the illumination data capturing module and the personnel activity monitoring module sense environment and personnel dynamic information in real time, the multi-dimensional data preprocessing module and the multi-dimensional data analysis module deeply process and analyze the information, and the illumination management module and the illumination control module accurately control illumination equipment according to an analysis result. Finally, the intelligent, energy-saving and scene-based control of the lighting system is realized, the energy utilization efficiency is improved, and the diversified lighting requirements of users are met.

The invention provides an AI artificial intelligence machine learning system and an intelligent gateway, and relates to the technical field of AI artificial intelligence control, and the system comprises a communication module which is in bidirectional connection with an air conditioning unit, a security and protection sensor array and an intelligent illumination network in a building through a plurality of Internet of Things protocols, collects equipment operation data flow in real time, and sends the data flow to a server; comprising an air conditioner compressor current waveform, a security alarm code and lighting equipment light intensity time sequence data; and the edge calculation module is used for extracting an air conditioner energy consumption characteristic value, a security alarm signal and an environment temperature and humidity data set according to the equipment operation data flow, and storing the processed structured data set to a simulation object memory area through a simulation object classification algorithm. Through cooperation of multiple modules, real-time acquisition and processing of multi-source equipment data, analysis of personnel and environment information, intelligent generation of control instructions and adaptation to various equipment through protocol conversion are realized, so that the building environment comfort, safety and energy utilization efficiency are improved, and system compatibility and emergency response capability are enhanced.

The invention discloses a livestock and poultry health state intelligent evaluation method based on multi-sensor fusion and an AI prediction model, and belongs to the technical field of livestock breeding, and the method comprises the following steps: setting multiple types of sensors in a livestock and poultry breeding area, collecting multi-source data such as temperature, humidity, carbon dioxide concentration, ammonia gas concentration, illumination intensity, weight and current, and carrying out the analysis of the data; wherein the weight data is obtained through the weighing platform, and the current data is used for sensing the operation state of drinking, ingestion, ventilation or lighting equipment; various types of sensors such as temperature and humidity sensors, carbon dioxide sensors, ammonia gas sensors, illumination sensors, weight sensors and current sensors are deployed in livestock and poultry breeding areas, all-directional data acquisition of environments and behavior states is realized, and dynamic modeling and feature extraction of key behavior nodes are realized by introducing a deep neural network structure of a gating circulation unit and an attention mechanism.

The invention provides a wind and light equipment predictive maintenance system and method based on big data and hierarchical weight. The system comprises a data acquisition and edge processing layer, a data management and storage layer, a hierarchical weight analysis and model construction layer and a fault prediction and intelligent decision-making layer. Multi-source data are collected by deploying various sensors, and the multi-source data are transmitted to a cloud for deep cleaning and storage after being preprocessed by edge computing. The index weight of each level is determined by using an improved algorithm, and a fault prediction model is constructed by fusing a plurality of intelligent algorithms. The model combines real-time data and hierarchical weights, predicts the fault probability, type and remaining service life of equipment components, and gives an alarm when a threshold value is exceeded. Meanwhile, a multi-objective optimization model is constructed according to a fault prediction result to formulate a maintenance strategy, and the maintenance strategy is executed after digital twinborn rehearsal, so that the operation and maintenance efficiency is improved. According to the method, multi-source data fusion, accurate fault prediction and intelligent maintenance decision making are realized, the operation and maintenance cost can be effectively reduced, and the equipment reliability and the power generation efficiency are improved.

A head-mounted display compares a brightness in a surrounding environment based on a result of measurement by a surrounding light sensor with a surrounding light threshold predetermined for providing a user with a warning, and when the brightness in the surrounding environment is equal to or less than the surrounding light threshold and also when detecting that the user wearing the head-mounted display has performed a surrounding-environment-recognition-preparation-action for switching an action of viewing the display to an action of viewing the surrounding environment, executes control of outputting notification information for letting the user know that a visibility in the surrounding environment reduces, or executes control of outputting a control signal for a lighting fixture.

The invention belongs to the technical field of intelligent control, and discloses a scene self-adaptive intelligent lighting dimming and color modulation control method and system, and the method comprises the steps: S1, carrying out the data collection operation, and obtaining the multi-mode data, such as CSI physiological features, ambient light, user interaction, and the like; s2, feature extraction operation: extracting features of a user cognitive state, ambient light and a user behavior intention; s3, performing model reasoning operation, inputting the features into the fusion model, and reasoning a scene state vector; s4, performing parameter generation operation, and dynamically generating illumination control parameters according to the scene state vector; and S5, in order to execute the control operation, sending parameters, so that the illumination equipment adaptively adjusts the brightness and the color temperature. According to the method, accurate understanding of deep states such as fatigue and concentration of the user is realized through non-intrusive multi-mode perception, non-sensitive and personalized light environment adjustment is provided while the privacy of the user is protected, and the user experience, the working efficiency and the visual health are remarkably improved.

Devices, systems, methods, and processes for operating illumination devices on network devices are described herein. Illumination devices, such as light-emitting diodes, on network devices can provide useful status information when being observed by a technician. However, these illumination devices are often not being looked at in large data centers. As such, energy is often wasted on powering these illumination devices. In order to avoid this wasted power usage and increase sustainability, various embodiments described herein turn off illumination devices, such as network indicator lights and overhead lights, as a default state and illuminates them in response to a specific need. This need can be in response to a work order as well as to illuminate a path form an access point of the server room to the target network device that requires work by the network technician. Dynamically engaging illumination devices associated with network devices can reduce overall power usage.