329 results about "Environment management" patented technology

The invention discloses an intelligent monitoring and early warning system and method for agricultural non-point source pollution, and relates to the technical field of environmental monitoring, accurate prediction of water pollutant concentration is realized through multi-source heterogeneous data acquisition and fusion, a dynamic attention mechanism and a PINN-Transformer coupling model, the system extracts data spatial and temporal characteristics by using an optimized Transformer model, and the method is applied to the intelligent monitoring and early warning of agricultural non-point source pollution. A water pollution diffusion physical constraint is embedded, it is ensured that a prediction result conforms to an actual hydrodynamic law, and based on high-precision spatial-temporal distribution data, an intelligent algorithm is adopted to track a pollution diffusion path and rapidly lock a pollution source; meanwhile, the cellular automaton model simulates pollution risk dynamic diffusion and assists regional risk assessment, the system also combines a block chain technology to carry out credible evidence storage on key monitoring data, and real-time data processing and early warning pushing are realized through a cloud edge collaborative architecture. And an efficient and reliable technical solution is provided for agricultural water environment management and pollution prevention and control.

The invention discloses a forestry ecological environment real-time monitoring and management method based on big data, and belongs to the technical field of forestry ecological environment management, and the method comprises the following steps: S1, multi-source heterogeneous data collection and sensor network deployment; s2, multi-modal data fusion and intelligent transmission: developing an adaptive communication protocol dynamic switching module, and automatically switching to a satellite communication link in a 4G / 5G network blind area; s3, mass data storage and distributed calculation: constructing a hybrid cloud storage architecture, and storing real-time monitoring data into a Redis cache queue; s4, intelligently extracting ecological environment indexes; s5, dynamically evaluating the ecological bearing capacity; s6, performing multi-level early warning and emergency response; s7, making a precise forestry management decision; and S8, carrying out system self-optimization and closed-loop management. According to the method, the air-space-ground integrated monitoring network is constructed, so that the comprehensiveness and the real-time performance of forestry ecological environment perception are remarkably improved; multi-source data of the unmanned aerial vehicle, the satellite remote sensing and the ground sensor are complementary.

The invention discloses a non-point source pollution and waterlogging collaborative four-pre management and control system based on short temporary rainfall forecast, which relates to the technical field of urban water environment management and comprises a short temporary rainfall forecast module, a non-point source pollution control module, a waterlogging management module, a four-pre management and control platform, an intelligent decision support system, a real-time monitoring and feedback system and a water ecological management module. By integrating meteorological monitoring, hydrological monitoring and environment monitoring data, high-precision short and temporary rainfall forecast is realized by using a machine learning algorithm, the operation strategies of the intelligent catch basin and the initial rain storage pond are dynamically adjusted to control non-point source pollution, and meanwhile, the waterlogging risk is predicted and preventive measures are taken in combination with real-time hydrological data. According to the technology, integrated management of forecasting, early warning, rehearsal and plans is achieved through a four-pre-management and control platform, an intelligent decision support system, a real-time monitoring and feedback system and a water ecological management module under the sponge city design concept are used in an auxiliary mode, and the efficiency and effect of urban water environment management are comprehensively improved.

The invention relates to the field of environmental protection, and discloses an emergency pollution diffusion model construction method, which comprises the following steps: constructing a pollutant diffusion basic model, and describing the diffusion process of pollutants in a water body along with time and space; dynamically optimizing control parameters of the pollution diffusion model, adjusting control variables in real time, and optimizing a pollution diffusion path through an adaptive optimization control method; based on the real-time monitoring data and the prediction result of the pollution diffusion model, performing state estimation and correction on the pollution diffusion path by using a Kalman filtering algorithm; in combination with real-time data from different monitoring sources, optimizing a prediction result of the pollution diffusion model by using a spatio-temporal data fusion technology; and according to the optimized pollution diffusion result, an emergency response scheme is provided for an environment management department through a decision support system. According to the method, a spatio-temporal data fusion technology is adopted, and the prediction result of the pollution diffusion model is optimized through weighted averaging of multi-source monitoring data.

The invention discloses a pigsty environment regulation and control optimization method and system, and belongs to the technical field of breeding environment management. The system comprises an intelligent sensing module, an environment analysis module, a parameter optimization module and a control management module. The intelligent sensing module is used for collecting pig house environment parameters and live pig physiological parameters through a multi-mode sensor; the environment analysis module is used for constructing a behavior recognition model, analyzing behavior characteristics based on physiological parameters and dividing abnormal regions; the parameter optimization module is used for establishing a physiological environment control model and setting an optimal optimization scheme for each abnormal region; and the control management module is used for generating an environment control instruction according to the optimal optimization scheme and controlling equipment execution. The pig house environment and the pig physiological parameters are collected and intelligently analyzed through the multi-mode sensor, automatic and precise environment optimization management is achieved, and the comfort level and the health level of the pigs are improved.

The invention relates to the technical field of soil environment monitoring, and discloses a soil remediation construction site environment monitoring method based on edge computing cloud collaboration. The method comprises the following steps: deploying an edge computing node at a restoration construction site, and collecting real-time data of soil humidity, heavy metal concentration, volatile organic compound content and meteorological parameters through a multi-source sensor; inputting the data into a spatio-temporal feature extraction network, and generating a spatio-temporal fusion feature matrix by means of hierarchical convolution and a cross-channel attention mechanism; on the basis of the matrix, the index anomaly probability is calculated by using a depth probability network, and a risk feature sequence with uncertainty measurement is generated; constructing a dynamic risk field model in combination with repair process parameters, and predicting a pollution diffusion path through a space-time propagation algorithm; and in combination with an equipment operation state, an edge side local regulation and control instruction and a cloud global optimization strategy are generated by a collaborative decision engine, and efficient and accurate environment management requirements of a construction site are met.

The invention relates to the technical field of air quality monitoring, in particular to an air quality monitoring station site selection optimization method, medium and equipment, and the method comprises the steps: S1, obtaining remote sensing monitoring data and ground station monitoring data of pollutant concentration of a certain research area; s2, correcting the remote sensing monitoring data based on a random forest model to obtain corrected monitoring data; s3, evaluating the credibility of the corrected monitoring data based on the consistency measurement index, and if the consistency measurement index of the corrected monitoring data is higher than the consistency measurement index of the remote sensing monitoring data, entering S4; otherwise, returning to S2; and S4, according to the corrected monitoring data, optimizing the monitoring station at the pollution view angle, and obtaining a monitoring station site selection result after the pollution view angle optimization. According to the invention, overall consideration of monitoring efficiency and health protection is realized, future development change is considered, and more accurate and comprehensive data support can be provided for air quality monitoring and environment management.

The invention relates to the technical field of environment management, in particular to a carbon emission data management method and device based on a block chain, and the method comprises the following steps: screening missing information data based on the block chain, eliminating abnormal calculation efficiency, extracting user behavior analysis stability, adjusting authority mapping to generate a credible index, screening illegal nodes, and writing the illegal nodes into a tracking block. And comparing policy marking abnormity to obtain a compliance state. According to the method and the system, the data with missing identity labels and timestamps are screened out, the data validity ratio is improved, the timeliness and the credibility of written information are ensured, the uploading action is identified, the frequency and the operation interval are modified, the node behavior stability is described, the compliance degree is reflected, the access permission is dynamically adjusted according to the stability, and the hyper-permission operation records are screened out; high-frequency violation writing behaviors are detected and recorded, the real-time monitoring capability is enhanced, abnormity is dynamically marked, compliance evaluation and response of carbon emission data are achieved, and the credibility, precision and intelligent level of data management are comprehensively improved.

The invention discloses a carbon right-green certificate collaborative transaction method based on a block chain, and belongs to the field of block chain technology and environment management. The method specifically comprises the following steps: 1) deploying an intelligent contract based on an Ethereum platform, and integrating power transaction, carbon quota delivery and green certificate issuing process chains to realize automatic execution of transaction rules and non-tampering of data; (2) a Carbon Token excitation mechanism is innovatively designed, a DPoS-CT consensus algorithm considering the right of the Carbon Token is proposed, and a market subject is excited to continuously reduce emission; 3) a dynamic reputation model and a reward and punishment mechanism are used to quantify subject performance behaviors and distribute on-chain rights and interests; and 4) resetting the transaction cycle every 24 hours, and optimizing quota allocation and consensus parameters based on historical data. According to the mechanism provided by the invention, renewable energy transaction can be effectively stimulated, and after the block chain carbon pass system is introduced, the quota completion rate, the green electricity utilization rate, the carbon emission, the carbon right-green certificate transaction volume and the economic benefit are optimized to a certain extent.

The invention provides a computing power center resource centralized self-adaptive control scheduling system and method, and the method comprises the steps: S1, a user submits a computing power training task through an API, and sends the task to a DAG task composer, and forms a task list to be scheduled; s2, the intelligent monitoring analysis module is used for continuously collecting node data and calculating real-time CS and HS scores of each node; s3, analyzing the dependency relationship type data by a task composer, and calling a dynamic programming algorithm in an adaptive scheduler to make a decision; s4, the adaptive scheduler performs dynamic task distribution according to the task list of the DAG task orchestrator and the intelligent monitoring analysis module, and S5, the distributed runtime and environment management module is used for uploading the prepared Docker mirror image to the distributed storage; and S6, through the unified communication adaptation layer, the mirror image is pulled from the distributed storage on the target node and the container is started, the user does not need to concern the difference of the operating system in the whole process, and efficient and intelligent adaptive scheduling is realized.

The invention provides an ecological system quality quantitative analysis method and system, and the method comprises the steps: carrying out the standardization processing of a multi-dimensional data factor, and obtaining the evaluation results of three dimensions, i.e., an ecological system background state, an ecological system landscape structure, and an ecological system service function, based on the processed data factor. And performing weight distribution and comprehensive calculation on evaluation results of the background state, the landscape structure and the service function of the ecological system to obtain an ecological system quality index. Based on this, regression analysis is performed on the ecological system quality index and a plurality of data factors, and then the core driving factor is accurately identified. According to the scheme, multiple dimensions such as the background, the function and the structure of the ecological system are coupled to perform ecological system quality evaluation, the defects of single dimension, evaluation framework limitation and the like in the prior art are avoided, and an effective basis can be provided for regional ecological environment management, ecological restoration project layout and protection decision by determining the core driving factor.

The invention discloses a thermal comfort monitoring robot system and method based on multi-modal body language feature recognition and fusion, and aims to realize individual thermal comfort monitoring, regulation and control in a dynamic indoor environment. The intelligent mobile platform carries multiple types of environment sensors and visual acquisition equipment, and performs autonomous navigation and acquires environment parameters and human body image data; the multi-modal feature recognition module performs human body detection, posture recognition and identity maintenance on a video stream frame by frame based on a deep learning network, and extracts multi-modal human body features; the data processing and fusion module realizes cross-frame identity consistency through an algorithm and fuses multi-modal human body features and environmental parameters; the thermal comfort calculation module dynamically adjusts a metabolic rate parameter based on a predicted average voting model, incorporates the metabolic rate parameter into a psychological correction factor and calculates an individual thermal comfort index; the three-dimensional visualization and regulation and control module generates a comfort distribution map, is in butt joint with a building environment automatic control system to achieve dynamic regulation and control, and provides support for intelligent building environment management.

The invention relates to the field of environment management, and discloses a watershed digital twinning environment real-time simulation and interaction platform fusing cloud edge collaboration and intelligent modeling, and the platform comprises the steps: carrying out the dynamic collection of the Yangtze River and Yellow River watershed, and generating environment state information organized according to the temporal-spatial resolution; associating the generated environment state information with multi-source environment data to form a multi-source knowledge basis of the drainage basin pollution field; establishing a rule knowledge base covering pollution identification, early warning and prevention and control business processes by utilizing a generative knowledge representation method, and generating a pollution event candidate identification result; carrying out fusion calculation on the pollution event candidate recognition result and multi-source heterogeneous data, constructing a digital twin simulation model, and eliminating data islands between modules and data sources; and executing linkage calculation on the pollution area and the risk node calibrated in the digital twinborn simulation model, generating environment state interaction information and synchronously updating the environment state interaction information to the digital twinborn environment. The method has the advantage that the regional water environment risk prevention and control capability is improved.

The invention relates to the technical field of environment management information systems, in particular to a method and a system for extracting an ecological environment access list rule of an intelligent agent. The method comprises the steps of collecting ecological environment policy and regulation data from a plurality of data sources, and performing data cleaning and labeling to obtain a standardized text data set; training and optimizing the data set to obtain an ecological environment professional knowledge large model; designing a prompt project template including input, instructions, examples and output requirements; inputting the cleaned new policy data into the large model, and automatically extracting a structured access list rule according to a prompt template; and finally outputting and storing the rule. According to the method, automatic conversion from an unstructured policy text to a structured access rule is realized, the problems of low efficiency, poor accuracy and difficulty in updating and maintenance of a traditional manual extraction mode are effectively solved, and the intelligent level and decision support capability of ecological environment partition management and control are remarkably improved.

The invention relates to the technical field of information management, in particular to an automatic modeling environment management method and system based on Kubernetes, and the automatic modeling environment management method based on Kubernetes comprises the following steps: in Kubernetes, a user logs in, and safety verification is carried out; calling a preset resource prediction model to predict and output an optimal resource configuration file according to resource configuration selected when a task is submitted: calling a Kubernetes API to create a Deployment, binding a PVC to a dynamically generated storage path, and deploying a container; a user uploads a data set, and the data set is synchronized to a preset persistent storage module through a Sidear container. According to the method, a series of work such as safety reinforcement of a whole link, prediction and output of an optimal resource configuration file through a resource prediction model, high-performance storage isolation and efficient integration of tool chains can be realized.

The invention discloses an urban thermal exposure risk optimization method and system based on carbon emission dynamic regulation and control, and belongs to the technical field of urban climate adaptation and low-carbon planning, and the method comprises the steps: obtaining real-time carbon emission data and a weather short-time forecast result; and inputting the obtained real-time carbon emission data and the weather short-time forecast result into the trained thermal exposure risk transfer model, outputting a future thermal exposure risk level, and combining an early warning threshold value to realize the optimization of the urban thermal exposure risk by adopting differential regulation and control strategy matching. The method solves the problems that a dynamic correlation mechanism of carbon emission and thermal exposure is not clear, a regulation strategy lacks multi-scene adaptability and real-time performance and the like, supports rapid early warning, accurate regulation and effect verification of thermal exposure risks, provides scientific support for urban thermal environment management, low-carbon development planning and resident health guarantee, and is suitable for popularization and application. The method is suitable for climate toughness optimization of multiple scenes such as industrial parks and high-density residential areas.

The invention discloses a metering equipment remote calibration method and device, a medium and equipment. The method comprises the following steps: calculating a loss index according to current characteristics of an extracted current signal in a monitoring period, and determining a phase offset of each harmonic based on the loss index; constructing an environment gain coefficient according to the environment temperature and the environment humidity in the environment management period; constructing a current correction coefficient according to the fundamental wave amplitude of the current signal in the monitoring period and the environment gain coefficient; and correcting each harmonic amplitude in the next monitoring period according to the current correction coefficient, and correcting each harmonic phase in the next monitoring period according to the phase offset of each harmonic to obtain a calibration current in the next monitoring period.

The invention discloses a hotel environment governance intelligent evaluation method integrating ESG indexes, and relates to the technical field of hotel environment monitoring, and the method comprises the following steps: collecting multi-source environment data in real time, and obtaining hotel data and guest room check-in information by deploying Internet of Things sensing equipment and docking with an existing hotel management system; based on the obtained guest room check-in state information, the number of check-in rooms is counted according to set time slices, and the real-time check-in rate of each time slice is calculated; performing standard unit conversion on the acquired environment data, and combining the obtained occupancy rate information to form a total environment load vector; matching a preset parameter according to the hotel type, and if no matching type exists, calculating to obtain an optimal parameter group of the hotel; on the basis of the parameters, the load efficiency of each time slice is calculated firstly, and then a DO-ELE coefficient is obtained through calculation and serves as an evaluation index; and according to the calculated DO-ELE coefficient, determining the ESG governance grade of the hotel by comparing with a preset grade division standard, and generating a visual evaluation report of a related data curve.

The invention discloses an active city cooling method based on a three-dimensional city form and a circuit theory, and belongs to the technical field of city environment regulation and heat island effect governance, and the method comprises the steps: S1, recognizing long-term stable cold and heat source patches through obtaining multi-temporal surface temperature (LST) data and combining mathematical form spatial pattern analysis (MSPA) and a landscape connectivity index; s2, adopting a spatial principal component analysis (SPCA) method to construct a comprehensive resistance surface fused with the three-dimensional urban form factors; s3, connecting a cold and heat source to simulate an airflow conduction path based on a circuit theory, extracting a cooling gallery and identifying key nodes; and S4, finally, through a stable surface-connecting line-key point mode active cooling network, space optimization is carried out. According to the method, accurate identification and efficient communication of cold and heat sources can be realized, the heat island effect relieving efficiency is improved, the long-term adaptability of a cooling network is ensured, and a popularized urban thermal environment governance path is provided.

The invention discloses a slope protection structure for mine geological environment governance, and belongs to the technical field of mine geological environment governance, the slope protection structure comprises a slope body, grooves located in the surface of the slope body, anchor rods and a vegetation net, the anchor rods are implanted into the slope body at intervals, the vegetation net is laid on the surfaces of the grooves and preliminarily positioned through the anchor rods, and the vegetation net is in a movable state in the initial state. In order to solve the problems that a traditional vegetation net cannot adapt to an irregular slope of a mine and water and soil loss is caused due to the fact that gaps are easily reserved, the vegetation net is attached in a self-adaptive mode through an outer metal protective net pressure applying-attaching mechanism driving-elastic stainless steel rod deformation linkage mechanism, an outer metal net applies pressure to push a push rod, and the vegetation net is attached to the slope. The elastic stainless steel rods are pertinently deformed according to the concave and convex shapes of the slope surface, the vegetation net is driven to fill gaps and fit the slope, the releasing mechanism releases the steel wire rope, adjustment allowance is provided for the vegetation net, wrinkles and suspension are avoided, stable attachment of soil and a spray-seeding matrix is ensured, and the survival rate of vegetation is greatly increased.

The invention discloses a method for monitoring VOC (Volatile Organic Compounds) unorganized emission by utilizing an ultrasonic imaging technology, and belongs to the technical field of environment monitoring. The method comprises the following steps: acquiring ultrasonic data of a chemical industry park production device through an ultrasonic imaging module; 20-100 kHz leakage ultrasonic signals are separated, and sound pressure is read; positioning a leakage source in combination with coordinate mapping and a digital twinborn model, and marking sound pressure with a color code; a fitting coefficient is obtained through laboratory calibration, the leakage rate is calculated, the total leakage volume is calculated according to the duration, and gas density can be combined to be converted into the total mass. The method has the advantages of wide-area coverage, real-time response, accurate positioning, small monitoring deviation and the like, solves the problems of multiple blind areas and difficulty in quantification of a traditional method, and provides data support for safety and environment management of chemical industrial parks.

The invention discloses a safety and environmental protection management system and method based on multi-pollutant cooperative treatment, and relates to the technical field of environmental management. According to the invention, multi-pollution data is collected in real time through a multi-parameter sensor network; optimizing and constructing an optimized pollutant relevance model by adopting a graph neural network and a Nelder-Mead simplex method, analyzing a collaborative / antagonistic relationship among pollutants, and generating a multi-pollutant processing list; multi-target optimization is carried out on a three-dimensional target function containing the removal rate, the cost and the by-product amount through an improved genetic algorithm, an optimal scheme is selected, balance between the environment and economic benefits is achieved, a dynamic multi-pollution map is constructed, and a pollution migration path is accurately tracked; a by-product material flow network analysis system is established, and resource recycling is achieved through a directional separation and reprocessing technology; according to the method, the combined pollution analysis precision is improved, the treatment cost is reduced, and the occurrence rate of secondary pollution is reduced.

The invention relates to the technical field of intelligent storage environment management, in particular to an intelligent storage environment management method and system based on artificial intelligence, and the method comprises the steps: calculating a theoretical humidity value of an internal cavity of closed power equipment according to an external environment parameter and an equipment sealing grade; obtaining cavity response characteristics including a shell vibration spectrum and microwave dielectric response data; inputting the cavity response features into a pre-trained humidity inversion neural network to obtain an actually measured humidity value of the internal cavity; according to the absolute deviation value of the theoretical humidity value and the actually measured humidity value, a cavity risk index is calculated in combination with the key grade coefficient of the closed power equipment; and when the cavity risk index exceeds a preset risk threshold, generating an active intervention instruction for the closed power equipment. And the risk that the closed power equipment is affected with damp due to humidity change in a storage environment is effectively solved.

The invention discloses an environmental protection management system based on big data service integrated management, and the system comprises a data collection layer which is used for collecting multi-source environmental data; the data management layer is used for storing, cleaning and standardizing the collected data and encrypting the data transmission and storage process; the data analysis layer is used for carrying out deep mining and intelligent analysis on the processed data; the application service layer is used for visually displaying the analysis result and realizing query, management and sharing of environment information through a user interface; and the block chain traceability layer is used for recording a source, a timestamp and a processing process of the data, and realizing tampering prevention and traceability of the data through a block chain technology. By integrating various advanced technologies, efficient acquisition, processing, analysis and management of environment data are realized, and comprehensive and scientific technical support is provided for environment management.

The invention belongs to the technical field of building management, and particularly relates to a building management service system and an operation method, and the system comprises a central processor module, a power supply module, a user management module, an equipment management module, a security monitoring module, an energy management module, a property management module, and an environment management module. Through the arrangement of the sliding block structure, the design is simple and convenient to operate, and when different crowds use the access control machine body, the height of the access control machine body can be adjusted, so that the trouble that too high or too short users need to bend down or tiptoe during recognition is reduced, and the access control machine can be used by the disabled such as people sitting on wheelchairs, such as the disabled. The door control equipment can be adjusted to a proper height, so that the door control equipment can be operated without effort, the care for special crowds is reflected, meanwhile, the flexibility is improved, and meanwhile, wind power can be generated to remove dust and impurities adhered to the door control machine body.

The invention discloses a garden environment informatization management system based on diversified analysis, which belongs to the technical field of garden environment management and comprises a management platform, a parameter monitoring module, a vegetation growth evaluation module, an environment influence analysis module, an early warning unit and a decision execution module. According to the method, a partition management mode is adopted, the vegetation growth state of a local area is comprehensively analyzed based on soil data and vegetation apparent images of a single area, the vegetation abnormal growth type of an abnormal management area is obtained through abnormal recognition, and historical data tracing analysis is combined, so that the vegetation abnormal growth state of the abnormal management area is obtained. The method specifically comprises the steps of performing root cause judgment based on historical meteorological data and facility data so as to generate different strategy information according to a root cause judgment result, constructing a closed-loop management system from anomaly recognition to data attribution to decision execution, and performing decision execution by using diversified data and an intelligent analysis technology and taking data as driving. And comprehensive monitoring, multi-dimensional analysis and accurate decision making of environmental elements are realized.

The invention discloses a method for determining industrial soil and underground water preferential management and control pollutants through multistage screening, and belongs to the technical field of environment management and pollutant risk assessment.The method comprises the steps that an industrial pollutant database of an area to be managed and controlled is constructed; forming a specific pollutant list; quantitative indexes are determined, a TOPSIS method is adopted to sort the pollutants, and preferential control pollutants are determined; according to the method, a three-stage progressive screening framework of'suspected pollutant library-particular pollutant-preferential control pollutant 'is carried out, a multi-criterion comprehensive evaluation system of a weight and TOPSIS sorting model is fused, multi-dimensional risk quantitative sorting is carried out on the pollutants, and the pollutants needing preferential control are accurately locked; the defects that a traditional screening technology is high in subjectivity, single in consideration dimension, lack of industry pertinence and the like are overcome, the comprehensiveness, scientificity and accuracy of pollutant screening are remarkably improved, and effective technical support is provided for environmental risk management and control.

The invention relates to the technical field of pollution risk assessment, and provides an AI-based karst region soil-underground water cooperative pollution assessment system. According to the system, multi-source soil and underground water heavy metal time sequence monitoring data are fused, cross-medium collaborative characterization characteristics are constructed, an enhanced time sequence modeling method with a parameter efficient adaptation capability is introduced, and a composite dynamic loss function oriented to non-stationary pollution evolution characteristics is designed; and collaborative prediction and uncertainty description of the heavy metal pollution states of the soil and the underground water are realized. Furthermore, a prediction result is combined with spatial gridding analysis, a collaborative pollution risk index and a risk zoning result are constructed, technical conversion from pollution evolution modeling to spatial risk assessment and early warning output is realized, and reliable technical support is provided for dynamic early warning, graded prevention and control and environment management decision of heavy metal pollution in the karst region.

The invention relates to the technical field of environment management, in particular to an intelligent aquatic plant community optimization system which comprises a community recognition module, an adaptive screening module, a spacing adjustment module, a growth monitoring module and a response regulation and control module. According to the invention, through dynamic monitoring of plant growth states and optimization treatment of spatial configuration, accurate management of aquatic plant communities is realized, the matching degree of plant species and environmental conditions is enhanced, spacing and density configuration of plant planting are improved, resource competition among plants is effectively dealt with, and the yield of aquatic plants is improved. Through multi-dimensional plant growth state feedback and nutrition state monitoring, the plant configuration is adjusted in real time, so that the dynamic management of the community is more flexible, the singleness of the community structure is avoided, and effective intervention is performed aiming at the water eutrophication problem. The adaptability and growth quality of the plants are improved, overgrowth or decline of the plants in an unsuitable environment is avoided, and ecological restoration and water health are promoted.

The invention discloses a vehicle-mounted microbial environment management system based on multi-mode sterilization control and a method thereof, and relates to the technical field of vehicle-mounted air purification and microbial control. The system comprises a microorganism sensing module used for collecting and detecting the concentration of microorganisms in air in a vehicle in real time, a state monitoring module used for feeding back the irradiation state of an ultraviolet light source and the activity state of a photocatalytic material, and a control module used for judging the pollution risk level based on multi-source information fusion and generating a control instruction. The safety and interaction module is used for passenger state detection and remote control interaction, and the ultraviolet disinfection module, the photocatalytic purification module and the ozone release module cooperatively execute disinfection operation according to a control instruction. Through a closed loop mechanism of pollution detection, risk determination, safety verification, linkage control and effect verification, high-precision, intelligent, safe and reliable vehicle-mounted microbial environment management is realized, the operation efficiency and the use safety of the system are improved, and the system is suitable for various intelligent cabins and high-standard vehicle-mounted environment control application scenes.