14 results about "Pollution management" patented technology

The invention discloses a risk management and control zoning method and system based on multi-medium interactive pollution data, and relates to pollution management and control, and the method comprises the steps: delimiting an initial risk pollution region through random pollution point detection, and determining main pollutants of each medium and the content of the main pollutants; analyzing the content change gradient of the pollution point, and constructing a content reduction vector line; setting a multidirectional edge region, analyzing vector line difference, and if the criterion does not reach the standard, expanding the edge until the criterion is met or crossed; accurately measuring an actual pollution range, extracting geographic features, and establishing a correlation group of pollutants, vector distribution and the geographic features; according to the method, vector distribution, geographic features and pollutants are taken as elements, a multi-medium interactive pollution comparison model is constructed, and real-time data are analyzed, so that the accuracy, dynamic adaptability and real-time response efficiency of multi-medium pollution risk management and control are improved, and efficient partitioning and early warning in a complex terrain scene are supported.

The invention discloses a pollution risk identification and early warning method based on a multi-level scale. The method comprises the following steps: dividing county level grids, town level grids, village level grids and extensive plot grids; selecting a pressure index, a state index and a response index as risk identification indexes, collecting corresponding remote sensing data, ground sensor network data and agricultural data, and then performing space-time matching by adopting a Bayesian fusion model to obtain a standardized data set of each level of grid unit; a Delphi method is adopted to carry out multiple times of assignment to determine the weights of the three indexes, then a risk identification model is constructed, then a risk value is calculated, and a total quantity Quantile grading method is adopted to divide risk levels to identify the risk of each grid unit; a quantile and exponential smoothing method is adopted to dynamically adjust a threshold value, then early warning grades are divided according to the threshold value, and finally early warning is carried out according to the early warning grades. The agricultural non-point source pollution multi-level scale high-precision identification and real-time early warning are realized, and the precision and timeliness of pollution management are improved.

The invention discloses a GIS-based pollution prevention and control management method and system, and belongs to the technical field of pollution management, and the method comprises the steps: collecting the wind power information at a plurality of time points and the actual concentration value of pollutants based on a detection sensor; measuring points with actual concentration values exceeding a first threshold value are determined and defined as pollution points, corresponding time points are defined as first time points, and a first sequence of actual pollutant concentration values and a second sequence of wind power information are collected and constructed by taking the first time points as starting points; the pollution points where the same pollutants are detected are defined as first correlation points, and first topographic data between the first correlation points are obtained based on the GIS data; performing pollution correlation analysis on the first correlation point based on the first topographic data, the first sequence and the second sequence, and extracting a second correlation point from the first correlation point; and analyzing the second association point by using a traceability model, and determining a pollution source area. According to the invention, the pollution source area generating pollution can be rapidly and accurately positioned.

A novel reverse osmosis or nanofiltration (RO / NF) system is developed that utilizes a uniquely configured membrane permeate flow path within the system to detect and respond to the onset of fouling, generating time-sensitive data. Membrane performance data under real-time operating conditions is then used to rapidly detect membrane fouling, fouling rate, and fouling causes. Subsequently, controller-based system-generated actions are employed to stop fouling and recover from or slow it down. Furthermore, operator intervention steps are anticipated, planned, and scheduled, if necessary, to restore optimal system operating conditions. The end result is a novel, energy-efficient, and advanced (machine learning) reverse osmosis system for brackish water desalination and fouling management.

The invention discloses an environmental data denoising and feature enhancement method based on physical and data dual drive, which relates to the technical field of data processing, and comprises the following steps: S1, collecting original environmental data of an area, and performing abnormal value elimination processing to obtain standard environmental data; s2, constructing a physical prior model according to the standard environment data of each grid in the region, and determining spatial feature vectors of the grids; s3, determining time feature vectors of the grids according to the standard environment data of each grid in the area; and S4, performing enhancement processing on the spatial feature vectors and the time feature vectors of the grids, and determining regional standard-exceeding grids and standard-reaching grids. According to the method, the spatial-temporal features are subjected to enhancement processing such as dynamic fusion and neighborhood aggregation, the environment enhancement interaction features are obtained, the standard-exceeding grids and the standard-reaching grids are finally determined, scientific support is provided for pollution traceability and precise treatment, and a refined basis is provided for regional pollution treatment.

The invention relates to the technical field of mine pollution management, in particular to an intelligent mine management system and method based on the Internet of Things. The system is characterized in that a mine pollution data acquisition unit uses a mobile Internet of Things sensing device to acquire flow path data and pollutant concentration data of underground water in real time; the event-driven pollution identification unit identifies and analyzes an underground pollution dynamic evolution event of the mine based on the flowing path data and the pollutant concentration data of the underground water; the pollution path evolution identification unit constructs a groundwater pollution propagation evolution diagram covered by a full path, and identifies and traces an upstream pollution source starting point, a downstream terminal pollution area and a midstream potential pollution source; and the pollution situation visualization unit is used for constructing a mine pollution risk grade zoning map and visually displaying the mine pollution risk grade zoning map on the terminal equipment. According to the invention, post-rain pollution surge events are identified and monitored, and potential pollution conditions of the upstream, the middle and the downstream of the whole mine geologic structure are traced and managed.

The utility model relates to a standardized booth device capable of automatically supplying energy and treating garbage and a using method thereof. The standardized booth device comprises an umbrella-shaped supporting system, a photovoltaic power generation and energy storage system and a garbage treatment system, wherein the photovoltaic power generation and energy storage system and the garbage treatment system are arranged at the top and the bottom of the umbrella-shaped supporting system respectively. The utility model has the advantages of simple structure and reasonable design, and is favorable for solving the problems of environmental pollution, disordered management and low space utilization rate in the existing urban stalls.

The invention relates to the technical field of resource management, and discloses a marine oil spill emergency resource multistage linkage global sharing system and method, and the system comprises an oil spill management unit, a pollution management unit, a scheduling management unit, and a linkage management unit. Two jurisdictions accurately grasp the diffusion state of spilled oil, the jurisdictional dynamic responsibility coefficient of the pollution management unit and the cross-domain pollution influence field, responsibility division can be determined, the global resource scheduling vector linkage management unit of the scheduling management unit generates emergency linkage instructions of the jurisdictions, cross-domain collaboration is enhanced, resource waste and responsibility prevarication are avoided, and the risk of oil spilling is reduced. The disposal accuracy is improved, and the damage of oil spill to marine ecology is reduced.

The invention relates to the technical field of hydrological monitoring, in particular to a flow detection method and system for an electromagnetic measuring water tank, and the system comprises the electromagnetic measuring water tank, an electromagnetic induction module, an electrode-containing assembly, a space adjustment module, a water flow initial speed collection part containing a telescopic partition plate, a data processing module, and a water inlet pipeline. The electromagnetic induction module is used for generating an alternating magnetic field and collecting an induced electromotive force signal, and the space adjusting module is used for adjusting the effective volume of the water tank through a telescopic partition plate so as to adapt to the flow; the data processing module realizes signal conversion, flow comparison, pollution value calculation and AI pollution trend pre-judgment, the water inlet pipeline is used for introducing to-be-detected water flow, various sensors support pollution data acquisition, and the whole flow detection and pollution management process is jointly completed.

The invention discloses a robot camera pollution state management method, device and equipment, relates to the technical field of robot visual system operation state maintenance, and can provide a camera pollution state management method capable of automatically identifying pollution types and pollution degrees and performing adaptive decision processing according to the pollution types and the pollution degrees. The scheme comprises the following steps: acquiring an environment image acquired by a camera on the robot in real time; pollution state identification is carried out on the environment image to obtain an identification result, the identification result comprises pollution types of the camera, the pollution types comprise a first pollution type, a second pollution type and a third pollution type, the first pollution type indicates that the camera is locally shielded, and the second pollution type indicates that the camera is blurred in imaging but still has a visual function; the third pollution type indicates that the optical window of the camera has physical damage; and executing corresponding processing strategies according to different pollution types so as to carry out pollution management on the robot camera.

A novel reverse osmosis or nanofiltration system (RO / NF) capable of utilizing uniquely configured membrane permeate flow paths within the system that produce time sensitive data to detect and respond to the onset of contamination within the system. Membrane contamination, rate of contamination, and cause of contamination are then rapidly detected using membrane performance data under real-time operating conditions, then system-generated actions based on a controller are used to stop contamination and restore or slow contamination from contamination, and if desired operator intervention steps are predicted, planned, and scheduled to restore optimal system operating conditions. The final result is a novel advanced (machine learning) reverse osmosis system for energy saving and pollution management for brackish water desalination.

This invention relates to the field of mine pollution management technology, specifically to an intelligent mine management system and method based on the Internet of Things (IoT). The system includes: a mine pollution data acquisition unit that uses mobile IoT sensors to collect real-time groundwater flow path data and pollutant concentration data; an event-driven pollution identification unit that identifies and analyzes dynamic evolution events of underground pollution in the mine based on the groundwater flow path data and pollutant concentration data; a pollution path evolution identification unit that constructs a groundwater pollution propagation evolution map covering the entire path, identifying and tracing upstream pollution source origins, downstream terminal pollution areas, and midstream potential pollution sources; and a pollution situation visualization unit that constructs a mine pollution risk level zoning map and displays it visually on terminal devices. This invention enables the identification and monitoring of post-rain pollution surge events and the traceability and management of potential pollution conditions in the upstream, midstream, and downstream of the entire mine geological structure.

The invention provides a low-hill mountainous area non-point source pollution management and tail water reutilization method and system, and the method comprises the steps: obtaining multi-source water quality environment data corresponding to a target low-hill mountainous area based on a multi-mode intelligent environment sensing device; and inputting the multi-source water quality environment data into the low-hill mountainous area non-point source pollution management model to obtain target control parameters corresponding to each target water and fertilizer flow regulation and control device output by the low-hill mountainous area non-point source pollution management model, and performing water and fertilizer putting control on each target water and fertilizer flow regulation and control device according to the target control parameters. The target water and fertilizer flow regulation and control equipment is water and fertilizer flow regulation and control equipment arranged in each farmland area in the target low-hill mountainous area; and on the basis of each target water and fertilizer flow regulation and control device after water and fertilizer putting control, tail water of the farmland runoff key node is purified, and the purified tail water is conveyed to the farmland area of the low mountainous area. The non-point source pollution load is obviously reduced, and the water and fertilizer utilization efficiency is improved.

The invention relates to the technical field of data processing, in particular to a detection data anomaly identification method of an LIMS laboratory system, and is used for solving the technical problem that the current atmospheric pollution identification accuracy is relatively low. The method comprises the following steps: acquiring pollution gas concentration data and environmental parameter data of each monitoring point in a monitoring area, and gas emission data of each chemical enterprise; based on the pollution gas concentration data and the environmental parameter data, determining the pollution management attention degree of each monitoring point on each type of pollution gas; based on the pollution management attention degree and wind speed and wind direction data in the environmental parameters, determining a strong pollution source point location; calculating pollution early warning indexes of the adjacent chemical enterprises based on the gas emission data of the adjacent chemical enterprises of each strong pollution source point location; the pollution early warning index is used for representing the contribution degree of the chemical enterprise to the pollution influence; and based on the pollution early warning indexes, chemical enterprises with abnormal pollution gas emission are detected.