120366 results about "Water resource management" patented technology

The invention provides an urban intelligent drainage management system based on big data analysis, and relates to the technical field of urban drainage management, and the system comprises a multi-source data collection module which collects historical climate changes, rainfall curves, satellite meteorology, pipe network node water level flow and topological structure data in real time; the dynamic three-dimensional modeling module constructs a pipe network three-dimensional model according to a fluid mechanics principle, and binds real-time sensor data by a spatio-temporal data fusion algorithm; the drainage limit analysis module calculates the maximum drainage threshold value and the failure probability of the node under extreme rainfall; the intelligent early warning module fuses LSTM and ARIMA models, generates a drainage pressure thermodynamic diagram in the future 72 hours in combination with satellite meteorological data and triggers early warning; the health assessment module generates a node health index and a maintenance priority order; the resource scheduling engine generates a dynamic scheduling scheme. The urban drainage problem is effectively solved, the ability of a drainage system to deal with extreme weather and pipe network aging problems is improved, and accurate early warning and efficient resource allocation are achieved.

The invention discloses an expressway service area sewage treatment system based on the Internet of Things, and relates to the technical field of sewage treatment.The expressway service area sewage treatment system is provided with a multi-modal sensor and an edge computing unit, real-time monitoring and data processing of sewage flow and water quality parameters are achieved, the water quality change trend and the parameter change rate are rapidly recognized, and the sewage treatment efficiency is improved. The sensing capacity of the system to load changes is remarkably improved, the system conducts real-time adjustment according to the water quality changes, fluctuation of the treatment effect and waste of energy consumption are avoided, an LSTM model is adopted for conducting dynamic prediction on water quality parameters, in combination with real-time monitoring data, the aeration strategy is optimized through intelligent self-adaptive adjustment and closed-loop fine control, and the aeration efficiency is improved. The LSTM model can predict the future sewage load and ammonia nitrogen concentration change, the aeration intensity and time are adjusted in advance, the fluctuation of the ammonia nitrogen concentration is quickly responded through PID control and closed-loop control of a feedback mechanism, and the ammonia nitrogen removal efficiency and the aeration accuracy are improved.

A scheduling method and system for the operation of reservoirs to recharge freshwater for repelling saltwater intrusion under changing conditions. Research data of a research area is collected, the research area is generalized, and the river network topology of the area is constructed; the research data acquire the seawater flow data of each station in the research area for N time periods, analyze the correlation between the flow of a predetermined station and the saltwater intrusion and build a seawater flow spatial-temporal evolution model; rainfall data and freshwater runoff of each station are acquired to analyze the variation trends of freshwater flow and hydrological regime of each station and a first ending point and build a freshwater flow spatial-temporal evolution model; and a scheduling model for recharging freshwater for repelling saltwater intrusion is built for simulation, a scheduling method is provided, and a scheduling scheme set is formed.

The invention provides a drainage basin water quality pollution traceability analysis method and system fused with space-time big data, and relates to the technical field of pollution analysis, and the method comprises the steps: collecting water quality, weather, surface runoff and other data, and generating a data set through space-time label association; and on the basis of the data set, constructing a pollutant migration and diffusion model containing a pollutant concentration attenuation and flow direction prediction sub-model, and calculating a pollutant concentration change rate and a migration path. And finally, the pollution sources are divided into point source pollution, non-point source pollution and endogenous pollution through the pollution source identification model, the contribution rate of each pollution source is calculated, and a pollution traceability analysis report is generated. The method can comprehensively consider the influence of various factors on the water quality, realizes the accurate positioning and quantitative analysis of the pollution source, and improves the traceability efficiency and accuracy.

The invention relates to the technical field of environment monitoring, in particular to an underground water pollution source traceability identification method and system, and the method comprises the following steps: S1, collecting the flow velocity, flow direction and water level change data of underground water in a polluted region in real time; s2, constructing a preliminary underground water flow model; s3, simulating a migration path of pollutants in underground water, and predicting a potential pollution source position; s4, processing the collected underground water flow velocity and pollutant diffusion path data, and removing abnormal data interference; s5, generating a spatial distribution map of the potential pollution source in combination with a geographic information system; and S6, verifying pollutant components and concentration distribution thereof, and confirming the accuracy of a traceability result. According to the invention, by combining a multi-pollutant traceability algorithm, an underground water flow model and a geographic information system technology, a pollutant migration path is accurately simulated and a pollution source spatial distribution map is generated, so that the precision and reliability of underground water pollution source traceability are greatly improved.

The invention relates to the technical field of data processing, and discloses a hazardous chemical substance leakage and diffusion prediction method and system based on an unmanned ship, and a storage medium. The method comprises the following steps: acquiring water quality, weather and geographic data through an unmanned ship sensor, and processing to obtain an initial data set; calculating a diffusion range according to the data, optimizing a monitoring area, and generating a cooperative monitoring track; performing exception elimination and smoothing processing on the data, and constructing spatial distribution; solving a convection diffusion equation, and establishing a three-dimensional flow field model; analyzing a hazardous chemical substance diffusion path, and predicting pollutant distribution; and establishing a risk assessment system, and generating emergency disposal suggestions and decision-making schemes. According to the application, rapid and accurate monitoring of the polluted area is realized through the multi-parameter sensor array carried by the unmanned ship, and accurate prediction of the hazardous chemical substance pollutant diffusion process is realized in combination with multi-source data fusion processing and a three-dimensional flow field simulation technology.

The invention discloses a modularized full-process high-quality direct drinking water treatment system and a control method, and belongs to the technical field of direct drinking water treatment.The modularized full-process high-quality direct drinking water treatment system is characterized in that an online sensor is deployed at a water inlet of a flocculation basin, raw water turbidity, temperature and flow parameters are collected in real time, and qualified samples are screened to construct a standardized water quality characteristic data set in combination with historical water quality and agent adding records; based on the data set, performing multi-dimensional clustering on historical water quality parameters, generating a characteristic working condition cluster, calculating a three-dimensional efficiency index, generating a dynamic dosage reference interval by using a sliding window confidence interval and a time decay factor, establishing a mapping relation between water quality characteristics and medicament dosage, and generating a graded dosage strategy; the transmembrane pressure difference and the membrane flux change rate are continuously monitored at the water inlet end in the membrane treatment stage, the membrane pollution trend is predicted through time sequence analysis, the prediction result is corrected according to the agent adding deviation, the precipitation effluent turbidity and the membrane inflow COD data, a cleaning early warning signal is generated, and graded response is performed according to the pollution degree.

The invention provides an underground water pollution source tracing and evaluation method for a riverside water source in a karst area, and the method comprises the following steps: collecting and preprocessing multi-source information, and obtaining a multi-source data set; a water quality sample is collected and analyzed, the surface water-underground water interaction process and pollution characteristics are comprehensively analyzed, and a pollution source type is obtained; performing space-time analysis on the multi-source data set to obtain a pollution activity time period and a potential pollution source area; constructing a karst area hydrological model, simulating the hydrological characteristics of the karst area, constructing a pollutant migration model, and simulating the migration process of pollutants; and constructing a traceability algorithm, tracking pollutants, confirming a pollution source, carrying out risk partitioning and risk assessment, and carrying out visual display of a result. According to the invention, interaction between surface water and underground water can be effectively assessed, accurate traceability of pollutants and multi-angle accurate identification of pollution sources can be realized, and management efficiency can be optimized through reliable risk assessment prediction.

The invention discloses an underground cable pipeline abnormity monitoring method and system, and the method comprises the following steps: S1, building a three-dimensional grid based on the regional soil distribution condition, and obtaining a collection point data set based on the three-dimensional grid and underground cable pipeline data; s2, acquiring acquisition distribution corresponding to each to-be-arranged sensor type based on the to-be-arranged sensor type and the acquisition point data set; s3, acquiring underground cable pipeline time sequence data acquired by each sensor based on acquisition distribution, and performing clustering analysis on the underground cable pipeline time sequence data to acquire abnormal data points; and S4, obtaining an abnormal position according to the abnormal data points and the collection distribution, and outputting abnormal information of the underground cable pipeline according to the abnormal position. The method has the beneficial effects that the physical position of the cable pipeline is considered, meanwhile, the soil environment characteristics are considered, the accuracy of sensor arrangement in the pipeline is improved, the abnormal data point analysis efficiency is improved, and the underground cable pipeline abnormity can be conveniently and timely checked.

The invention relates to the technical field of data processing, and discloses a water quality and water quantity accurate simulation method and system based on an SWAT model and a storage medium. The method comprises the following steps: analyzing rainfall and evapotranspiration data through a two-parameter trend test, and generating standard hydrological data by adopting a triple configuration algorithm; dividing sub-basins by combining topographic information, and calculating a hydrological response unit; performing water balance operation and water conservation evaluation; pollutant diffusion is analyzed, and a diffusion equation is solved; running state monitoring is implemented, and an early warning system is designed; and comparing and correcting measured data, and constructing a hierarchical monitoring mechanism. According to the invention, the whole-process precise management from hydrological data acquisition, water quality evaluation to early warning monitoring is realized, and the accuracy and reliability of water quality and water quantity monitoring are remarkably improved.

The invention relates to the technical field of environment monitoring, in particular to an underground water pollution real-time monitoring method and system, and the method comprises the following steps: analyzing the underground water flow direction and original pollution records in geographic information, combining the geologic structure and hydrological characteristics of a monitoring area, and through the water flow propagation characteristics; and marking the position of the pollution source and matching the pollution range to generate a matching result of the pollution source and the range. According to the invention, the underground water flow direction, the pollution record and the geological and hydrological characteristics are analyzed, the position and the range of a pollution source are accurately marked, the identification precision and the monitoring pertinence are improved, monitoring points are deployed at key positions, diffusion information is extracted in real time, an early warning threshold value is dynamically generated, early warning is issued in time, and emergency response is started, so that the pollution control efficiency is improved; rapid development of isolation and water quality treatment is ensured, closed-loop adjustment and optimization of monitoring parameters are realized, so that the method dynamically adapts to environmental changes, and comprehensive control of groundwater pollution is realized.

The invention discloses an intelligent water quality monitoring system and method based on a turbidity sensor, and relates to the technical field of water quality monitoring. Data acquisition nodes are arranged in a water area to be monitored, data are acquired by using the turbidity sensor and an intelligent water quality monitoring equipment group, an environment data set S is constructed, and preprocessing is performed; acquiring a turbidity change coefficient # imgabs0 # according to a turbidity data set in the preprocessed environment data set S, performing primary evaluation, marking abnormal data acquisition nodes, acquiring a particulate matter dynamic index KL and a pollution index WR according to a particulate matter data set and an organic pollutant data set in the environment data set S, and performing secondary evaluation according to the turbidity change coefficient # imgabs1 # and the turbidity change coefficient # imgabs0 # in combination with the particulate matter dynamic index KL and the pollution index WR. Acquiring a comprehensive water quality score Q, performing secondary evaluation, and constructing a water quality prediction model to predict the water quality change and regulate and control the water quality for the data acquisition nodes which are normally evaluated for the second time; the intelligent level of water quality monitoring is improved, the accuracy of water quality monitoring is enhanced, and the safety of water quality is ensured.

The invention discloses a riverway flood control and disaster reduction risk point AI identification method and device based on a digital twinborn computable engine. The method comprises the following steps: acquiring three-dimensional scene basic data and hydraulic engineering parameters in a drainage basin; acquiring real-time rain condition, water condition, soil moisture content, reservoir condition and dike monitoring data to obtain real-time data; establishing a physical entity and a twin simulation scene according to the three-dimensional scene basic data and hydraulic engineering parameters; performing AI simulation calculation of water regimen according to the real-time data to obtain a simulation result; carrying out twinborn computable simulation according to the physical entity, the twinborn simulation scene and the simulation result to obtain a simulation result; and identifying the risk point of the river channel in the drainage basin according to the simulation result. By implementing the method, the problem that the prediction accuracy is affected due to the fact that the digital twinborn technology mainly lacks intelligent risk identification and multi-factor integration in flood control and disaster reduction of the river channel can be solved.

The invention provides an intelligent runoff pollution monitoring and response method and system, and the method comprises the steps: arranging a plurality of monitoring points in a runoff region, collecting water quality, hydrological and meteorological data in real time through a sensor, transmitting the data to a data processing center through a wireless network, carrying out the preprocessing, storage and analysis, and calculating the comprehensive pollution index of each monitoring point. And comparing with a set index threshold value. When the comprehensive pollution index exceeds a threshold value, the system identifies and evaluates key water quality parameters so as to determine a reasonable parameter threshold value; once data of a monitoring point exceeds a preset pollution threshold value, an alarm mechanism is triggered, then a pipe network water flow model and a geographic information system are combined to reversely track a pollution path, accurately position a pollution source and provide a basis for pollution control, and the process comprises the steps of screening suspected pollution source nodes, calculating a propagation path probability and preferentially checking a high-probability path. The traced pollution source or path probability is lower than a preset value.

The invention relates to the technical field of energy efficiency management, in particular to a water conservancy sensing system based on edge computing. The system comprises the following modules: a riverway edge sensing module, a water conservancy characteristic analysis module, a sediment migration simulation module and a deposition scouring early warning module. Constructing a river channel water conservancy sensing network; performing real-time water conservancy monitoring data acquisition according to the river channel water conservancy sensing network to obtain river channel water conservancy sensing data; performing three-dimensional flow field model processing on the river channel water conservancy sensing data to obtain a three-dimensional sediment flow field network model; carrying out particle flow field simulation on the three-dimensional sediment flow field network model to generate sediment migration space-time distribution data; and according to the sediment migration space-time distribution data, carrying out siltation and scour area identification, and uploading the siltation and scour area data to a cloud platform through an edge computing node to carry out abnormal event alarm so as to obtain river section monitoring data. According to the invention, real-time, accurate and intelligent monitoring and early warning of the sediment deposition and scouring process of the river channel are realized.

The invention provides an intelligent sewage treatment process optimization method and system. The method comprises the following steps: continuously collecting the flux attenuation rate, transmembrane pressure difference and pollutant spectrum data of a ceramic membrane, carrying out time sequence analysis, constructing a pollution accumulation dynamic model, and predicting a critical threshold value; when a threshold value is reached, triggering an ultrasonic cavitation device, adjusting high-frequency vibration to generate a microbubble group, stripping pollutants by utilizing shock waves, and calculating membrane flux recovery data; fusing the spectral data and the recovery data to extract an actual pollution stripping efficiency value, and comparing a theoretical value to obtain a difference proportion; if the actual value is lower than the theoretical value, the cleaning period is shortened, the fluid pressure is increased to strengthen the stripping effect, and meanwhile, dynamic model parameters are reversely corrected based on the pressure adjustment amplitude to form closed-loop regulation and control. According to the invention, intelligent prediction, self-adaptive cleaning and closed-loop optimization of ceramic membrane pollution are realized, the sewage filtering efficiency is improved, and the energy consumption and cleaning cost are reduced.

The invention relates to the technical field of municipal pipeline detection, and discloses a sewage pipe network full pipe operation early warning analysis method comprising the following steps: S1, arranging sensors at key nodes of a sewage pipe network, and collecting real-time operation data of the sewage pipe network; s2, acquiring real-time meteorological data including rainfall capacity, rainfall intensity and other related meteorological factors; s3, performing data cleaning and standardization processing on the collected sewage pipe network data and meteorological data; s4, on the basis of multivariable regression analysis, establishing a relation model among the flow, the liquid level and the pipe fullness risk; and S5, performing time sequence prediction by using a long short-term memory network, and predicting future flow and liquid level trend. Time sequence prediction is carried out through the long-short-term memory network, the early warning threshold value is dynamically adjusted in combination with the self-adaptive algorithm, the running state change of the sewage pipe network is responded in real time, the future flow and liquid level trend is accurately predicted, and the early warning accuracy and the response speed to the sudden pipe fullness risk are improved.

The present application relates to a carbon stock monitoring technique, and specifically relates to an evaluation method and system for the carbon sink effect of a coastal wetland. The evaluation method comprises: acquiring a remote sensing image set, within a preset time period, of a coastal wetland to be subjected to evaluation; respectively identifying evolution data of different types of coastal wetlands in the remote sensing image set, wherein the evolution data comprises conversion data between different types of wetlands, and net change data, other than the conversion data, of each type of coastal wetland; and on the basis of the conversion data and the net change data, evaluating the carbon sink effect of the coastal wetland to be subjected to evaluation, so as to obtain a carbon sink effect evaluation result. In addition to performing qualitative analysis on a mature wetland area in the prior art, the present application further takes into comprehensive consideration factors which represent a carbon sink effect, such as evolution data and evolution types before and after the evolution of a coastal wetland to be subjected to evaluation, so as to comprehensively perform carbon sink effect evaluation on said coastal wetland, thereby more accurately obtaining the carbon sink effect of said coastal wetland.

The invention relates to the technical field of water quality monitoring, in particular to a mining area groundwater environment monitoring system and method, and the system comprises a mining area groundwater partition recognition module, a groundwater pollution risk assessment module, a groundwater monitoring point optimization module, a groundwater pollution path analysis module and a groundwater dynamic monitoring planning module. According to the invention, through data-driven zoning and risk assessment processes, fine and dynamic management is realized in underground water environment monitoring, functional zone zoning boundaries are accurately calibrated, understanding of an underground water flowing mode is enhanced, pollution source control is more targeted, diffusion risk intensity is assessed in combination with flow velocity and pollutant release intensity, and the risk assessment accuracy is improved. The risk management strategy is optimized, the pollution diffusion range is predicted and identified more efficiently, the emergency response accuracy is improved, monitoring point arrangement is optimized through risk data, reasonable monitoring resource allocation is ensured, the sampling task weight and the time interval are dynamically adjusted, and resource optimization and monitoring efficiency improvement are achieved.

The invention provides an agricultural source solid waste pollution reduction and carbon reduction synergistic effect calculation method and system. According to the agricultural solid waste pollution reduction and carbon reduction synergistic effect calculation method, a livestock and poultry manure and straw mixture serves as a treatment object, an environmental parameter set of microbial metabolism intensity is obtained, and then a microbial agent feeding acceleration rate and a flora activity attenuation curve are dynamically matched. In the aerobic fermentation stage, through linkage of pile turning operation and a microbial inoculum adding strategy, activity balance of surface and deep flora is maintained, and a microbial inoculum adding time window is corrected in combination with historical data. And establishing a quantitative model with a carbon-nitrogen ratio imbalance threshold value as a constraint, iteratively optimizing a nonlinear association relationship between the inoculant feeding acceleration rate and the pile turning operation frequency, and outputting a full-period synergistic effect evaluation result. According to the technical scheme, the pollution reduction and carbon reduction synergistic effect of agricultural source solid waste treatment is improved, and the dual purposes of resource utilization and environmental protection are achieved.

A method and apparatus for evaluating vulnerability of monopile foundations of offshore wind turbines are provided. The method includes collecting offshore wind farm location data and wind-wave characteristic data, and simulating a wind-wave time course according to the offshore wind farm location data and the wind-wave characteristic data; determining a wind-wave dynamic load based on the wind-wave course; obtaining lateral soil resistance data of monopile foundations with a plurality of rock-soil strength parameters, and inputting the wind-wave dynamic load into a 3D finite element model; using the lateral soil resistance data of monopile foundations with a plurality of rock-soil strength parameters as boundary conditions of the 3D finite element model; and giving a limit state of monopile foundations, and determining vulnerability of monopile foundations on basis of the dynamic response result of the monopile foundations and the limit state of monopile foundations.

The invention relates to the technical field of water quality and water level monitoring, and discloses a water quality and water level monitoring method for a water conservancy project, which comprises the following steps: S1, arranging a multi-parameter water quality and water level monitoring sensor at a key position of the water conservancy project; s2, performing real-time processing on the data acquired by the multiple sensors based on a data fusion algorithm, wherein the data fusion algorithm is based on a Kalman filtering model; s3, acquiring external data through an environment sensor, and dynamically adjusting a water level and a water quality monitoring threshold value based on environment change; s4, predicting the water level and the water quality by using a deep learning algorithm based on LSTM (long short-term memory network); and S5, if the monitoring data exceed the dynamic threshold value, automatically triggering an early warning mechanism. By arranging the multi-parameter water quality sensor and the water level sensor at the key positions of the water conservancy project, the water quality and the water level can be comprehensively monitored, the coverage range and the precision of the monitoring system are greatly improved, and the complex monitoring requirements of multi-source pollution can be effectively met.

The present invention belongs to the technical field of environmental monitoring, in particular to an environmental monitoring device for air pollution, comprising a monitoring frame, a monitoring shell arranged on a top end of the monitoring frame and an environmental monitor fixedly installed inside the monitoring shell through a connecting plate. An air sampling assembly is installed inside the environmental monitor; the air sampling assembly comprises air intake covers, and an electric push rod, a rack I, a gear I, a spur gear, an internal gear, a rotating disk, limiting blocks, limiting rods, a cross limiting track, an L-shaped frame and a strip-shaped plate which are used for driving the air intake covers. A cleaning assembly is installed on the air sampling assembly.

The invention relates to a sensor control method of an air purification system. The pollutant concentration gradient is monitored in real time by combining initial distribution of the sensors, and a pollutant diffusion path is simulated by utilizing a fluid dynamic model; a pollutant source is reversely deduced through sensor data, and the acquisition range of the sensor is dynamically changed; the method comprises the following steps: acquiring multi-dimensional data through physical sensors including particulate matters, temperature and humidity and chemical sensors including VOC and harmful gas, and extracting pollutant characteristics by utilizing PCA (principal component analysis); constructing hazard indexes of pollutants including AQI grading standards, and dynamically evaluating the priority of the pollutants in combination with real-time monitoring data of a sensor; for pollutants with different priorities, resources of the air purification system are distributed, and the air volume of a filter, the adsorption strength of activated carbon and the turn-on time of an ultraviolet germicidal lamp are adjusted; a self-adaptive calibration algorithm is introduced, and sensor output including interference correction of temperature and humidity on the particulate matter sensor is adjusted in real time according to the environment reference value; and dynamically adjusting the maintenance and replacement period of the sensor.

The invention discloses a flood discharge gate opening degree real-time automatic distribution method for a centralized control center, and relates to the technical field of water conservancy gate control, and the method comprises the steps: setting a monitoring point in each sub-region, and collecting the mechanical state, the vibration stress parameter and the surrounding geological parameter of a flood discharge gate, so as to construct a gate wear index Msz; therefore, the state of the gate can be monitored in real time, and abrasion and fault problems can be found and early warned in time. And establishing a sub-region prediction model, extracting water flow characteristics and river volume characteristics, calculating an average water flow index Slzs and a regional river clogging index Ydzs of each sub-region, correlating the obtained predicted river load index Fzz, and performing evaluation. And setting a first difference threshold value C1 and a second difference threshold value C2, calculating and obtaining a load difference value FCz according to the predicted river load index Fzz and the load threshold value R, generating an opening instruction, and setting a priority distribution mechanism. The opening degree of the gate is optimized, and the accuracy and response speed of flood discharge control are ensured.

The invention discloses a monitoring point distribution method and device based on industrial park gas monitoring and a medium, and relates to the technical field of carbon monitoring, triangular mesh division is carried out based on DT triangular mesh division, and according to the difference of monitored areas, the DT triangular mesh division method is used for setting point distribution of the monitored areas, so that the monitoring point distribution accuracy is improved. At least one monitoring point is selected in each grid for carbon dioxide concentration monitoring, point distribution setting can be carried out in different area ranges of prevailing wind directions in different states, the optimal monitoring result can be obtained through the least carbon dioxide gas monitoring points, the accuracy and credibility of the final data result are improved, and the method is suitable for popularization and application. The problems that the current industrial park monitoring coverage range is not wide, the device cost is high, and improvement of the carbon monitoring device distribution position affects the accuracy of the carbon ground monitoring technology are solved.

The invention discloses a small watershed hydrological runoff and pollution load short-term prediction refinement method, which comprises the following steps of: constructing a modeling data set, constructing a small watershed foundation base model, segmenting hydrological response units according to land utilization types, crop planting structures and reservoir pond / wetland distribution data in a refinement manner respectively, and calculating the hydrological runoff and pollution load short-term prediction of the small watershed foundation base model. A small watershed foundation base model corresponding to the optimal segmentation scheme is screened out, and a small watershed depth base model is generated; constructing a reservoir pond / wetland simulation module; coupling the small-watershed depth base model and the reservoir pond / wetland simulation module to form a small-watershed hydrology and water quality early warning model, and optimizing the small-watershed hydrology and water quality early warning model; rolling to generate a hot start file for short-term prediction; constructing a future short-term weather enhancement forecasting model; the small watershed hydrology and water quality early warning model is driven to operate, the future water volume and load output are calculated in a rolling mode, and hydrology and water quality results are output; and calibrating and updating the small watershed hydrology and water quality early warning model. The precision and timeliness of hydrology and water quality prediction of the small watershed are remarkably improved.

The invention relates to the field of environmental pollution monitoring, in particular to an on-line environmental pollution monitoring method and system, and the method comprises the steps: collecting the pollutant concentration data of a parking lot, and carrying out the data preprocessing to obtain the pollutant concentration preprocessing data; extracting spatial distribution characteristics and time characteristics of pollutant diffusion from the pollutant concentration preprocessing data according to a multivariable space-time prediction model, and comprehensively analyzing the space-time trend of pollutant diffusion to obtain the diffusion trend of the pollutant concentration and obtain the predicted concentration of the pollutant; performing data analysis on the predicted pollutant concentration and a preset safe concentration threshold value, and when the predicted pollutant concentration is greater than the preset safe concentration threshold value, triggering an alarm and performing ventilation operation; the problems that pollutant monitoring in a parking lot is not comprehensive enough, pollutant concentration cannot be effectively predicted in time, and a high-concentration area of pollutants cannot be judged in time, so that air quality cannot be optimized and managed in time, and personnel health cannot be guaranteed are solved.

The invention discloses a coal chemical industry heavy oil sewage treatment system based on the Internet of Things, and relates to the technical field of coal chemical industry sewage treatment.The coal chemical industry heavy oil sewage treatment system achieves real-time monitoring of sewage and membrane surface pollutant attachment conditions through an Internet of Things sensor, processes data through a machine learning algorithm, evaluates the current membrane pollution degree, and improves the membrane pollution degree. According to the invention, pollution is accurately identified, a response is made immediately when pollution occurs, the cleaning period and the cleaning strength are intelligently adjusted by dynamically analyzing the pollution degree and the sewage treatment load, the starting time of cleaning is determined according to the actual pollution condition, excessive cleaning is avoided, the cleaning period can be accelerated when needed, and the resource utilization efficiency is improved. The membrane pollution trend is predicted through the long short-term memory network LSTM, the potential pollution problem is recognized in advance, the system is helped to take prevention measures before pollution deterioration, and the problem of system shutdown or treatment capacity reduction caused by membrane blockage is effectively avoided.

The invention relates to the technical field of water pollution management, and discloses a water pollution tracing method and device and electronic equipment, and the method comprises the steps: determining at least one problem point location according to a water quality monitoring value time sequence corresponding to each monitoring point location in a selected range region in a target river channel; according to the position of each problem point location and / or the water quality analysis sequence corresponding to each problem point location, determining at least one to-be-checked river reach in the target river channel; and determining a first pollution source corresponding to the target river channel according to the water quality monitoring value time sequence and the flow monitoring value time sequence corresponding to each discharge port in each to-be-checked river reach. According to the embodiment of the invention, through decomposition and correlation analysis of the water quality index monitoring value time sequence, the change rule of the water quality index at the problem point location can be deeply excavated, reliable data support is provided for water pollution tracing, and the water pollution tracing efficiency is improved in combination with segmented troubleshooting capable of narrowing the water pollution tracing range. And a reliable basis is provided for water pollution treatment.