63 results about "Intelligent environment" patented technology

The invention discloses a highway service area intelligent environment monitoring and management system based on the Internet of Things, and relates to the field of environment monitoring and management, and the system comprises an acquisition module which is used for uploading the carbon emission source data of each energy consumption unit of a target service area, synchronously acquiring the carbon concentration in the environment of the target service area and the associated meteorological parameters of the same time interval, and transmitting the acquired data to a cloud server; constructing a carbon footprint basic data set; the traceability module is used for receiving the carbon footprint basic data set, constructing a traceability link based on the data set, analyzing carbon emission key nodes, and identifying a carbon emission ratio and a generation path of each node; according to the method, carbon emission related data and associated meteorological information are collected, a complete carbon footprint data basis is constructed, carbon emission key links and formation paths are carded out through reasonable analysis, the emission reduction potential of each link is calculated in combination with the actual operation condition of a service area, and links needing to be regulated and controlled are determined according to double judgment standards.

The invention discloses an unmanned aerial vehicle GNSS-free relative positioning method and device and a medium, and relates to the technical field of unmanned aerial vehicle autonomous navigation and intelligent environment perception. According to the method, a traditional PnP pose estimation framework and dependence on the physical size of an identifier are abandoned, the relative geometric center position of the visual identifier in the image is extracted by using deep learning, and the real height reference provided by the millimeter wave radar and the real-time attitude information of the unmanned aerial vehicle are combined; and a scale-adaptive, analytic and non-iterative relative position calculation model is constructed, and high-precision estimation of the three-dimensional relative position of the unmanned aerial vehicle relative to the landing mark center is realized.

The invention relates to the technical field of data processing and intelligent environment control, in particular to a sleep environment feedback control data processing method based on cognitive behavior therapy logic, which comprises the following steps: a reference model construction step: acquiring a non-contact multi-mode time sequence signal, and reconstructing a reference signal balance curve to construct a target signal manifold model; a simulation flow generation step of converting the preset interference characteristics into signal modulation operators and injecting the signal modulation operators into the model to generate a simulation signal flow; a double-track difference calculation step: executing double-track difference operation to respectively extract residual features representing system deviation and theoretical interference; a similarity judgment and control step: calculating the topological similarity of the residual features in a time-frequency domain, judging a deviation dominant type, generating a corresponding control instruction, and driving an execution mechanism to act; according to the method, psychological anxiety and environmental discomfort are effectively distinguished by using a double-track differential mechanism, and accurate attribution analysis of sleep interference sources is realized.

The invention discloses an environment gas leakage intelligent detection method based on big data analysis. The method comprises the following steps: collecting monitoring data and constructing a sensor network space-time diagram fused with meteorological conditions; predicting the background concentration of each node by using a sequence decomposition attention model; calculating a concentration residual error and constructing a space-time residual error map; extracting an abnormal feature vector through a physical information enhanced graph attention network; calculating an abnormal score in combination with the normal mode memory bank and generating a leakage source probability distribution diagram; when the conditions are met, calling a computational fluid dynamics model to simulate a theoretical concentration field; and determining a leakage event through spatial correlation analysis. According to the invention, the false alarm rate of gas leakage detection in an open environment is obviously reduced, and the leakage source positioning precision is improved.

The invention relates to the technical field of container houses, and discloses an intelligent environment control system for a container house, a temperature acquisition module deploys temperature sensing nodes in a plurality of temperature control areas divided in the vertical direction of the container house, and obtains the internal air temperature value and the envelope surface temperature value of each temperature control area; the model construction module determines a thermal resistance characteristic coefficient according to the surface temperature value and the internal air temperature value of the enclosure structure, determines a ventilation heat exchange coefficient according to the ventilation flow value and the internal and external temperature difference, and constructs a dynamic thermal resistance model based on the thermal resistance characteristic coefficient and the ventilation heat exchange coefficient; a deviation analysis module performs deviation analysis on the internal air temperature value and a preset target temperature field to obtain a temperature field deviation degree, and calculates a temperature control demand level; the temperature control module generates a cooperative control sequence of variable frequency air conditioner power adjustment and ventilation device opening adjustment according to the temperature control requirement level and a preset energy consumption constraint condition, and the uniformity, comfort and energy efficiency of temperature control of the container house are improved.

The utility model relates to a kind of intelligent environment monitoring devices running on domestic operating system, including temperature and humidity sensor, noise sensor, network interface, remote signalling lightning protection module, smoke sensor, water leakage sensor, vibration sensor, infrared intrusion detector, PM2.5 sensor, audible and visual alarm, monitoring equipment, temperature and humidity sensor, noise sensor, network interface, remote signalling lightning protection module, smoke sensor, water leakage sensor, vibration sensor, infrared intrusion detector, PM2.5 sensor, monitoring equipment, audible and visual alarm are connected with host computer, host computer uses 32 industrial ARM embedded processor main chip and uses domestic embedded real-time operating system RT-Thread, can monitor UPS detailed parameter, through with UPS communication acquisition, real-time monitoring the operating parameter of UPS, and the data of acquisition is uploaded to monitoring system platform, can monitor UPS input voltage, output voltage, output current, load percentage, UPS temperature, frequency, battery pack voltage, alarm failure etc.

The application discloses a low-cost, high-precision and high-reliability method for unmanned ship intelligent environment perception by fusing image segmentation and millimeter wave radar, which can acquire the environment information of the route and the surrounding of the unmanned ship in real time during the driving of the unmanned ship, including the shoreline, the sailing ship, the navigation mark and the floating object, and provide decision support for the real-time route adjustment and obstacle avoidance of the unmanned ship. The method comprises four parts of the millimeter wave radar, the binocular camera, the image segmentation module and the information fusion module, the image segmentation module is responsible for reading the image data, executing the image segmentation algorithm, identifying the target and generating the minimum fitting rectangle of the target, the information fusion module is responsible for receiving the data of the radar and the image segmentation module, acquiring the polar coordinates of the fusion target, matching the target size and outputting the result to the controller.

The invention provides an intelligent environment-friendly industrial laser cutting robot, and belongs to the technical field of laser cutting robots. Comprising a machining table, a cutting mechanical arm and a waste recycling mechanism, and the waste recycling mechanism is composed of a fixed grid plate, a storage plate, a collecting groove, a sliding filter plate, a knocking assembly, a collecting cavity, a first collecting box, a second collecting box, a limiting groove, a limiting plate, a ball, a telescopic spring, a first check block, a second check block and a protective door. The storage plates are integrally formed by triangular blocks and symmetrically arranged on the two sides of the through hole of the grid plate, and the positioning precision of the plates is guaranteed. The inclined filter plate cooperates with the check block to achieve efficient classification of large, medium and small chippings. The knocking assembly drives the filter plate to slide through slight shock and cooperates with the telescopic spring to prevent blockage. The problems that in the prior art, the structure is complex, manufacturing and maintaining cost is high, energy consumption is large, scrap classification is insufficient, and positioning precision is low are solved.

The invention discloses an intelligent environment regulation and control method and system for concrete winter maintenance, and relates to the technical field of environment monitoring, the system comprises a control center, and the control center is connected with a building acquisition module, an intelligent processing module, a maintenance analysis module and a strategy execution module; the method comprises the following steps: constructing a virtual-real twin space, carrying out graph conversion on collected data, obtaining a concrete monitoring dynamic graph and an environment monitoring dynamic graph, carrying out curve extraction on the concrete monitoring dynamic graph, obtaining a local monitoring coefficient, carrying out anomaly capture, obtaining a raw material mutation monitoring section, and carrying out time checking on the environment monitoring dynamic graph according to the raw material mutation monitoring section. Obtaining an environment sudden change time period; performing optimization simulation through a virtual-real twin space based on the environment sudden change time period to obtain an optimization regulation and control strategy; parameters are accurately controlled, personal errors are reduced, the concrete quality is guaranteed, and the curing efficiency is improved.

The invention relates to the technical field of computer technology and garden management, and discloses an intelligent environment response type park scenic spot sightseeing system and method and an edge computing architecture.The system comprises a distributed environment monitoring network, an edge computing server and an AR visual interaction interface, the edge computing server integrates multi-modal data through a data fusion module, and the AR visual interaction interface is connected with the edge computing server; and dynamically planning and generating an optimal touring route which optimizes the environmental comfort, the path distance and the tourist congestion degree at the same time by using a reinforcement learning algorithm based on a multi-dimensional reward function, and carrying out real-time touring on the optimized route information and real-time environmental data by using an AR visual interaction interface. And the function of adaptively adjusting the display information according to the sight focus of the user is realized. According to the invention, through deep integration of environment, position and congestion degree data, dynamic adaptive adjustment of a touring route is realized, scientificity and real-time performance of navigation are effectively improved, and more intelligent, comfortable and efficient garden touring service is provided for tourists.

The utility model discloses an acquisition board for an intelligent environment quality monitor, and belongs to the field of environment monitoring equipment, and the acquisition board comprises a bottom plate, the top of the bottom plate is provided with a main controller, the top of the bottom plate is provided with a mainboard, the top of the mainboard is provided with a 485 chip, the top of the mainboard is provided with a W5500 chip, and the 485 chip and the W5500 chip are connected with a power supply. Six connecting interfaces are formed in the top of the bottom plate, and a high-speed SPI interface and a network port are formed in the outer side of the main controller; a W5500 chip is arranged to support 10 / 100Mbps high-speed Ethernet data transmission, so that the requirements of most network applications on the data transmission speed can be met, quick and stable data transmission can be ensured in application scenes such as real-time data acquisition, video monitoring data transmission, network communication and the like, and three 485 chips are expanded to be connected with six interfaces, so that the data transmission speed can be greatly improved. And simultaneous access of multiple devices is supported.

The invention belongs to the technical field of power distribution, and particularly relates to an intelligent environment-friendly ring main unit power distribution switch control system and method, which are used for forming closed-loop control through real-time acquisition, state evaluation and instruction execution based on a sensor deployment scheme, configuration parameters, equipment state data and calibration parameters output by an intelligent monitoring system deployment and calibration module. According to the method, differential regulation and control strategies can be adopted for different operation states, control parameters are dynamically optimized in combination with machine learning, and an equipment operation state evaluation result, instruction execution feedback information, a load transfer execution result and optimized control parameters are output; on the basis, by means of an intelligent monitoring system and a cooperative control mechanism, the defect that a traditional control process lacks intelligent cooperation is overcome, real-time sensing of the operation state and rapid recognition, response and disposal of faults are achieved, accurate positioning can be achieved without tedious manual troubleshooting, and the fault repairing time is remarkably shortened.

This invention belongs to the field of computer vision and intelligent environmental perception technology, specifically relating to a method for anomaly detection and intensity estimation of sandstorms based on event cameras. It includes constructing and training an estimation model based on a multi-stream regression framework, and using the trained estimation model to predict sandstorm concentration. The estimation model includes an encoding module, a temporal distillation module, a cross-channel interaction module, and a regression prediction module. The encoding module includes three parallel color spectral encoders for red, blue, and green. This invention effectively overcomes the technical limitations of traditional air quality prediction methods based on RGB images, such as insufficient temporal resolution, limited dynamic information expression capabilities, and insufficient utilization of information from a single data source. It achieves high-precision estimation of air particulate matter concentration and maintains good robustness and adaptability even under complex environmental conditions.

Methods, systems, and apparatus for an intelligent environmental drone are described. The aeronautical drone includes an environmental condition generator. A camera system is configured to capture an image of an environment near the aeronautical drone and an image and sensor processing module is configured to identify a target entity by processing the image captured by the camera system. A tracking and guidance module is configured to track the target entity and determine a location for the aeronautical drone to create a generated condition area of a specified size and location and to position the generated condition area around the target entity.

The invention relates to the technical field of intelligent environment control, and discloses a microenvironment adaptive regulation and control method and system based on multi-modal perception and dynamic cooperation, and a storage medium. The method comprises the following steps: acquiring data through a multi-source sensor to form a multi-modal data set; performing feature extraction and fusion analysis on the set to generate a user state matrix and an environment state matrix; according to the number of the users, generating a regulation and control instruction by adopting an individual matching degree calculation or multi-objective optimization method; the actuator is driven to change the environment; and the model is optimized online based on feedback.

The application discloses a space intelligent environment perception and decision method and system based on consistency check, relates to the field of space intelligence, solves the problem of insufficient precision of existing multi-sensor fusion perception, and comprises the following steps: S1, collecting data of a space environment; S2, acquiring local perception data, classifying the local perception data, obtaining a time series data list, and judging data accuracy of different sensors; S3, integrating collected data of each sensor to obtain optimized space data; S4, performing space modeling according to the optimized space data to obtain a navigation world model, constructing a space semantic graph based on the navigation world model; S5, acquiring task information, extracting a route from the space semantic graph to obtain a task route, and simulating the route through the navigation world model; and S6, feeding back the navigation world model according to a simulation result, so that the accuracy of space perception can be effectively improved.

A central controller for an intelligent environmental air management system includes at least one processor and memory storing instructions executable by the at least one processor. The instructions, when executed, cause the central controller to detect and communicate with an air hazard sensor, an environmental condition monitor, and an air hazard mitigation device of the intelligent environmental air management system.

A PM2.5 prediction system and method based on dynamic weighting and anomaly correction are proposed, relating to the interdisciplinary fields of air pollution control and intelligent environmental monitoring. The PM2.5 prediction system based on dynamic weighting and anomaly correction includes, from front to back, a data preprocessing module, an adjacency matrix construction module, a spatiotemporal graph construction module, a spatial feature extraction module, a spatiotemporal feature fusion module, and an outlier adaptive correction module, all connected in a data flow. The outlier adaptive correction module and the spatiotemporal graph construction module are connected in a data flow. The PM2.5 prediction method based on dynamic weighting and anomaly correction comprises the following steps: data input and preprocessing; construction of a dynamically weighted adjacency matrix; spatiotemporal graph construction and spatial feature extraction; multimodal spatiotemporal feature fusion; and outlier adaptive correction. This invention dynamically fuses three types of weights using trainable coefficients, enabling the model to automatically learn the importance of spatial proximity, meteorological conditions, and pollutant correlations under different scenarios.

This invention proposes an intelligent monitoring system for underground coal mines. It utilizes technologies such as fiber optic networking, wireless communication, positioning, digital image processing, and artificial intelligence. Through integrated system networking and real-time intelligent monitoring of sensor installation status, it achieves intelligent monitoring of the underground coal mine system. The intelligent monitoring system includes a monitoring server, a positioning server, at least one positioning substation, at least one intelligent inspection terminal, at least one monitoring substation, at least one fiber optic splitter, and at least one intelligent environmental monitoring device. The system supports real-time inspection and monitoring of the entire mine environment, sensor status monitoring, and spatiotemporal synchronization of environmental and geological exploration data. It solves existing problems in underground coal mine monitoring systems, such as equipment compatibility, sensor location monitoring, sensor calibration monitoring, and sensor data monitoring, and has broad application and promotion potential.

The invention discloses a temperature and humidity independent control system, which relates to the field of environment control, and comprises an acquisition module for acquiring real-time physiological data and fusing the real-time physiological data into a comprehensive data packet; the receiving module is used for receiving the real-time physiological data of the corresponding user and the local environment parameters of the position based on the comprehensive data packet and the personal heat and humidity comfort digital twinborn model, operating an internal biothermodynamic algorithm and generating a personalized temperature set value and a personalized somatosensory humidity set value; according to the fusion module, the central controller inputs the full-personalized temperature set value and the personalized somatosensory humidity set value into a multi-objective optimization algorithm for dynamic fusion by taking minimization of collective dissatisfaction as an objective, and global set temperature and global set somatosensory humidity are generated; and the judgment module is used for comparing and judging the global set somatosensory humidity with the outdoor air humidity and generating a mode instruction. According to the invention, refined and intelligent environment control considering individual comfort requirements and overall system energy efficiency in a multi-user scene is realized.

The invention discloses an intelligent environment monitoring, regulation and control method and system for an ultrahigh-voltage submarine cable joint. The monitoring, regulation and control system comprises an environment control module, a sensor detection module and an automatic control module, the monitoring regulation and control method comprises the steps that the sensor detection module collects characteristic parameters of a submarine cable connector installation environment in real time and then uploads the characteristic parameters to the automatic control module, the automatic control module carries out analysis and calculation through a built-in intelligent algorithm model based on uploaded detection data, a regulation and control strategy is generated, and the regulation and control strategy is used for monitoring the submarine cable connector installation environment. The analysis and calculation comprises calculation of comprehensive abnormal probability, specific abnormal probability, regulation and control priority, regulation and control resource allocation quantity, instantaneous regulation and control intensity, feedback regulation and the like, then the automatic control module sends a regulation and control strategy to the environment control module, and the environment control module dynamically regulates and controls each characteristic parameter of the installation environment according to the regulation and control strategy. The problems of slow environment monitoring response, low precision, poor fault-tolerant capability and the like in the prior art are solved.

The invention discloses a posture correcting writing teaching method based on myopia and spinal column deformation prevention, and belongs to the technical field of posture correcting writing teaching. The system comprises a terminal APP, and the interior of the terminal APP is provided with a three-dimensional health assessment and baseline establishment module, an intelligent environment and tool adaptation module, an immersive posture correction teaching and training module, a real-time monitoring and intelligent feedback module, and a data driving and home-school collaborative management module. And the three-dimensional health assessment and baseline establishment module is used for comprehensively assessing the current physical state and writing habit of the student. According to the invention, systematized curriculums, 3D animation demonstration, real person demonstration videos and VR scene games are fused through the immersive posture correction teaching and training module, and multi-sensory and interesting teaching is realized in combination with teaching pithy formulas including a double-posture pithy formula, a pen wielding pithy formula and a Chinese character structure pithy formula; students can master correct sitting postures, pen holding methods and writing skills in interaction and games, so that the learning enthusiasm and the posture memory effect are remarkably improved.

The invention discloses a home safety monitoring method and system based on AI behavior analysis, and belongs to the technical field of home safety monitoring. According to the method, firstly, historical behavior data of a user and corresponding room environment parameters are collected, and a three-dimensional knowledge graph fusing personal behavior modes, environment states and predefined risk rules is constructed accordingly; and a personalized dynamic behavior baseline is generated by using a machine learning model in combination with associated information in the map. And by comparing real-time behavior data with a baseline, when a significant deviation is detected, triggering association reasoning based on a three-dimensional knowledge graph, tracing a causal path between behavior abnormality and a potential risk, and outputting a risk assessment result. And finally, automatically executing graded early warning and intelligent environment regulation and control according to an evaluation result. According to the invention, through unified modeling of user individual habits, dynamic environments and complex risks, real personalized and explainable home safety active protection with self-evolution ability is realized, and monitoring accuracy, adaptability and reliability are improved.

The application discloses a temperature and humidity independent control system, and relates to the field of environment control.The system comprises an acquisition module, which acquires real-time physiological data and fuses the data into a comprehensive data package; a receiving module, which receives real-time physiological data of a corresponding user and local environmental parameters of a location where the user is based on the comprehensive data package, runs an internal biological thermodynamic algorithm, and generates personalized temperature setting values and personalized sensible humidity setting values; a fusion module, which inputs the personalized temperature setting values and the personalized sensible humidity setting values into a multi-objective optimization algorithm for dynamic fusion to generate globally set temperature and globally set sensible humidity by taking minimizing collective dissatisfaction as a target in a central controller; and a judgment module, which compares and judges the globally set sensible humidity and outdoor air humidity to generate a mode instruction.The application realizes fine and intelligent environment control of individual comfort demand and overall system energy efficiency in a multi-user scenario.

The invention relates to a multi-dimensional Internet of Things perception data prediction method based on deep learning, and belongs to the technical field of Internet of Things data intelligent analysis, and the method comprises the steps: constructing a space-time decoupling double-branch prediction network, and employing a one-dimensional convolutional neural network to process the spatial correlation of multi-dimensional perception data in a spatial feature extraction branch, capturing key spatial features through a multi-scale convolution kernel and a channel attention mechanism; the time feature extraction branch adopts a bidirectional long-short-term memory network to model a time sequence, and reinforces a long-term dependency relationship in combination with a time attention mechanism; a self-adaptive gating fusion mechanism is introduced, the fusion weight of the spatial features and the time sequence features is dynamically adjusted according to the data features, and intelligent selection and fusion of the features in different scenes are achieved. According to the method, through decoupling extraction and adaptive fusion of the spatial-temporal characteristics, the prediction precision and generalization ability of the model to the multi-dimensional Internet of Things perception data are effectively improved, and the method is suitable for multi-dimensional time series data prediction scenes such as intelligent environment monitoring and industrial equipment state prediction.

The invention belongs to the technical field of pasture planting regulation and control, and particularly relates to an intelligent environment regulation and control method and system based on pasture growth monitoring data. Abnormal values are eliminated through a preprocessing module, a standardized matrix and a feature vector are generated through normalization, a growth stage recognition module recognizes a growth stage through a support vector machine algorithm in combination with historical data and dynamically distributes environment parameter weights, and a growth state evaluation module calculates growth state indexes in combination with the weights and an environment parameter response function. The intelligent decision-making module generates a regulation and control threshold in combination with historical optimal data, a regulation and control decision is generated by comparing an index with the threshold in combination with a proportionality coefficient and a growth trend prediction factor, and the execution and feedback module drives equipment operation and then collects a parameter optimization model; during use, the data storage module retains historical data, equipment faults can be manually intervened, and full-period regulation and control are guaranteed to adapt to pasture requirements.

The invention relates to the technical field of computers, discloses an intelligent environmental control monitoring method and system for an archive, and aims to solve the problems of missing detection and false detection of remnants caused by shielding, static misjudgment or hidden behaviors in a complex scene in the existing security technology. Comprising a video acquisition unit, an environment sensing unit, a data preprocessing unit, a multi-modal feature extraction unit, a spatio-temporal context modeling unit, an abnormal confidence evaluation unit and an alarm linkage control unit. A static region recognition model independent of a target movement track is constructed by fusing visible light images, infrared thermal imaging, micro-vibration and temperature, humidity and air pressure data, spatio-temporal context features are enhanced in combination with a graph attention mechanism, and an environment disturbance compensation and self-learning optimization mechanism is introduced to dynamically adjust a judgment threshold. According to the invention, high-precision identification and three-level linkage alarm of suspicious remnants are realized, the anti-shielding capability and the false alarm suppression effect are significantly improved, and the method is suitable for all-weather intelligent monitoring of high-security-demand places such as archives.

The invention relates to the technical field of intelligent medical assistance, and discloses an intelligent environment control system and method for an asymptomatic patient, and the method comprises the steps: obtaining biological signal data of a user, and environment data and equipment state data of an environment where the user is located; dynamically evaluating the interaction capability of the user based on the biological signal data, and selecting an interaction channel based on the interaction capability; historical behavior data of the user is obtained, and prediction control options of the user are generated in combination with the environment data; acquiring actual control options of the equipment, fusing the predicted control options with the actual control options to obtain fusion options, and presenting the fusion options to the user through the interaction capability; and identifying a control instruction sent by the user through the interaction channel, and executing a corresponding environment control operation. The method can dynamically adapt to the interaction capability of the user in different illness state stages, simplifies the operation process, improves the control accuracy and convenience, and helps the patient to adjust the surrounding environment and equipment autonomously.

The invention relates to the field of egg fresh-keeping equipment, and discloses an egg efficient fresh-keeping and quality grading method and device with intelligent environment regulation and control, and the key point of the technical scheme is that the egg efficient fresh-keeping device with intelligent environment regulation and control comprises a fresh-keeping box body; the first partition plates are arranged in the fresh-keeping box body and divide the interior of the fresh-keeping box body into a plurality of fresh-keeping layers; the first box body, the second box body and the air inlet paths corresponding to the fresh-keeping layers are arranged on the outer side of the fresh-keeping box body, so that cold air can be conveyed into the corresponding fresh-keeping layers according to layers, and the problem that the regulation and control pertinence on the egg storage environment of each layer is insufficient when air is supplied to the whole cabinet in a unified mode is solved. Secondly, by arranging a structure in which drawer position change is matched with air inlet switching, when the drawer leaves the preset position, direct air inlet of the corresponding layer is stopped, cold air is stored, the stored cold air is conveyed to the corresponding fresh-keeping layer after the drawer returns to the original position again, and therefore invalid leakage of the cold air along an opening path is reduced; and the time required for the corresponding fresh-keeping layer to recover to the fresh-keeping state before and after pulling is shortened.