200 results about "Source water" patented technology

The invention discloses an urban water body pollution traceability system based on multi-source sensing data fusion, and the system comprises a data acquisition module which is used for deploying a multi-source water quality sensor to collect initial multi-source water body data, and carrying out the time-space unified alignment processing, and obtaining the time-space aligned multi-source time-space water body data; the pollution factor tracing module is used for constructing a pollution event deconstructor and a factor tracing reasoning engine based on a water network topological graph neural network on the basis of multi-source space-time water body data, and outputting pollution component vectors through pollution component decomposition driven by the pollution event deconstructor; inputting the pollution component vector into a tracing reason inference engine to carry out tracing reason space-time correlation to obtain a tracing reason pollution fusion map; and the traceability decision module is used for performing inversion through a reverse traceability algorithm based on the traceability pollution fusion map, calculating the probability that each upstream area is a pollution source, mapping the probability that each upstream area is the pollution source to a GIS platform, obtaining a pollution traceability confidence distribution map, and realizing accurate traceability of the urban water pollution source.

The invention relates to the technical field of marine surveying and mapping and submarine topography modeling, and discloses a submarine topography and landform construction method based on multi-source water depth data fusion, which comprises a multi-source data acquisition module, a data preprocessing module, a feature extraction module, a fusion algorithm matching module, a three-dimensional modeling module and an uncertainty evaluation module. A historical submarine topographic map is converted into grid data, namely, submarine topography is discretized into digital representation of regular grid units, water depths of other sources are converted into the grid data, the precision of the water depths of different sources is evaluated by adopting a superposition comparison method, and an error distribution model is established to reasonably correct and fuse the water depth data of various sources. The innovation of the method lies in that topographic feature parameters including the gradient, the curvature matrix and the bionic optimization algorithm are introduced, the defect that a single algorithm is preset in a traditional method is overcome, and the precision of coral reef and fault zone complex areas is improved.

The invention relates to the technical field of water conservancy informatization and intelligent early warning, in particular to a river network water regimen big data intelligent analysis early warning system which comprises a dynamic data fusion module, a topology sensing module, an overload propagation analysis module, an intelligent early warning decision module and an early warning execution module. Wherein the dynamic data fusion module is used for collecting multi-dimensional data of a river network area in real time; the topology sensing module is used for dynamically constructing a real-time topological relation graph of the river network connectivity; the overload propagation analysis module is used for extracting an overload coefficient of each node and outputting a risk diffusion path set; and the intelligent early warning decision module is used for generating a three-level early warning instruction by combining the positions of the engineering vulnerabilities in the real-time topological relation graph. According to the method, through fusion of the multi-source water regimen data and the dynamic topological structure, linkage of accurate identification and hierarchical response of the risk path is realized, and the intelligent early warning and rapid disposal capability of the sudden water regimen of the river network is remarkably improved.

The invention relates to the technical field of sewage treatment, and discloses a chemical industry park emergency sewage treatment device abnormal discharge tracking method, which comprises the following steps: data synchronization: synchronously obtaining multi-source water quality time sequence data and hydraulic operation data of multiple monitoring points of a park pipe network; anomaly detection: establishing a time-varying adaptive baseline model based on the time sequence data, and calculating a residual error of the time-varying adaptive baseline model to detect a water quality anomaly event; response core construction: constructing a time-varying transport response core from a potential source point to a monitoring point through a dynamic model and data assimilation technology based on pipe network topology and real-time hydraulic data; and traceability inversion: inputting the residual error and the time-varying transport response kernel into an inverse problem solving model in which physical constraint and sparse prior are introduced. The abnormal emission tracking method for the emergency sewage treatment device in the chemical industry park aims at solving the problem that it is difficult to achieve accurate and reliable source tracing of abnormal emission events under the condition that the hydraulic working condition of a pipe network of the chemical industry park changes dynamically.

The invention discloses an intelligent water storage irrigation system suitable for ecological restoration of an abandoned mine, and relates to the technical field of ecological restoration, and the system comprises a multi-source water quality regulation and control module which is used for providing an irrigation water source adaptive to plant growth and soil improvement requirements in different restoration subareas; the ecological perception decision module is used for monitoring ecological indexes in real time; generating an irrigation decision executed according to the global scheduling plan through cloud data fusion analysis; the geology and hydrology safety module is used for constructing a digital twinborn model of a mine area and simulating restoration scenes under different irrigation decisions; the distributed irrigation module is used for building a distributed irrigation pipe network; and an energy circulation module. According to the method, fundamental transformation from single water supply to water-soil-plant synergistic remediation is achieved, the integrity of ecological remediation is improved, the vicious circle that traditional irrigation aggravates soil hardening or pollution leaching is effectively broken through, and a stable foundation is built for survival and growth of vegetation in the severe mine environment.

The invention provides a multi-source data fused water quality pollution monitoring method and device and a storage medium, and relates to the technical field of water quality monitoring. According to the method, through the key steps of data preprocessing, cross-modal feature fusion, pollution concentration estimation, graph neural network traceability and the like, multi-source water quality data and monitoring point space topology information are deeply integrated, and a whole-process automatic monitoring system is constructed. According to the method, end-to-end processing from data standardization to pollution emission source positioning is realized, a multi-source heterogeneous data barrier is effectively broken, the complementary value and the time-space association rule of different modal data are fully mined, the integrity, accuracy and efficiency of water quality pollution monitoring are improved, the emission source position and the pollution diffusion path can be accurately positioned, and the water quality pollution monitoring efficiency is improved. Full-link and targeted technical support is provided for water quality pollution control and treatment decision, and the problems that traditional monitoring data is low in utilization rate and insufficient in traceability accuracy are solved.

The invention provides a power station water regimen trend prediction method and system based on big data analysis, and relates to the technical field of power station water regimen prediction.The power station water regimen trend prediction method comprises the steps that firstly, multi-source water regimen associated data in a power station jurisdiction is obtained; the method comprises the following steps: generating a water regimen multi-dimensional evolution correlation graph presenting dynamic action relationships of different evolution units, then mining a key evolution path influencing a water regimen trend from the water regimen multi-dimensional evolution correlation graph, and constructing a water regimen trend dynamic deduction model containing action transfer rules based on the key evolution path; and finally, inputting the current water regimen, weather and equipment evolution unit data into the water regimen trend dynamic deduction model, executing trend deduction operation through an action transfer rule, generating a power station water regimen trend prediction sequence, and effectively improving the accuracy and reliability of power station water regimen trend prediction.

The invention relates to the field of water quality prediction, and particularly discloses a water supply pipe network water quality prediction method and system based on big data analysis. The input mixed water quality signal is decoupled into a plurality of independent component branches in one-to-one correspondence with the water sources on the characteristic level. And then, through a time-space diagram convolutional network sharing parameters, parallel and independent evolution derivation is carried out on each component flow, so that pervasive transportation and attenuation laws followed by different source water in a pipe network can be respectively captured, and the fundamental defect that a traditional single model cannot be distinguished and processed is overcome. Finally, all independently predicted future component states are subjected to self-adaptive nonlinear fusion with definite physical significance according to the accurate volume ratio of the future component states at the target point, so that a final mixed water quality prediction result with physical interpretability and high precision is generated.

The invention discloses a water pollution traceability analysis and ecological restoration decision support system. The system comprises a data acquisition layer, a data management and fusion layer, a pollution traceability analysis layer, an ecological restoration decision layer and a user interaction and visualization layer. The system collects multi-source water quality, hydrology and discharge data by deploying a distributed water quality sensing network, remote sensing and unmanned aerial vehicle monitoring equipment and a pollution discharge source online access module; through data cleaning, fusion and knowledge modeling, a pollution propagation model and a traceability inversion algorithm are constructed, and a pollution source and a contribution rate are identified; and simulating a multi-class repair measure response process in the digital twin water environment, and automatically recommending an optimal repair scheme in combination with a multi-objective optimization algorithm. The method has the advantages of accurate traceability, scientific decision, eco-friendliness, dynamic optimization and the like, and is suitable for pollution treatment and ecological restoration scenes of various water bodies such as drainage basins, lakes, urban rivers and the like.

The invention discloses a transmission and distribution pattern optimization method for a multi-water-source water supply pipe network system, and the method comprises the steps: solving a multi-water-source initial ratio at a hour level, and determining the boundary of a water supply region of each water source as an energy storage regulation and control static frame; minute-level reversible flow-water head scanning is carried out on the high-level water tank and the two-way pump station to generate a virtual pressurizing unit, reverse matching is carried out to form an energy storage dispatching pre-instruction, and the pre-instruction is locked as an executable instruction after returning to a static frame to verify water source reverse flow, water hammer overpressure and negative pressure pollution; a valve opening and closing sequence and a pump station rotating speed are coded into time-state vectors, the time-state vectors are input into a graph convolutional network transient pressure surrogate model to deduce a pressure envelope in the third hundred seconds in a rolling mode, only when the whole process is in a pipe allowable interval, the pressure envelope is issued to the site, and closed-loop collaborative optimization of the hour-level water source ratio and the minute-level energy storage scheduling is achieved. According to the method, the problems of complex calculation and control in multi-water-source, multi-energy-storage and multi-time-scale coupling are solved.

The invention relates to a water quality micro-station space-time correlation traceability analysis method based on multi-scale feature fusion. The method comprises the following steps: step (1), preprocessing and hierarchical dimensionality reduction of multi-source water quality data; step (2), measuring relevance of time-space fusion; and step (3), constructing and analyzing the space-time correlation network. According to the method, the association precision is improved through multi-scale feature fusion, the association deviation is reduced through spatial topology correction, the efficiency and the precision are considered through hierarchical dimensionality reduction, management and control are facilitated through structured network output, the precision and the practicability of water quality micro-station association mining are comprehensively improved, and a new breakthrough is brought to water quality monitoring traceability analysis.

The invention provides an underground water source water quality early warning method and system for environmental safety, and relates to the technical field of environmental protection and water quality safety, and the method comprises the steps: obtaining a plurality of water quality indexes of an underground water source in different historical periods and index values corresponding to the water quality indexes; screening the water quality indexes by combining a Lasso regression model and an FISTA algorithm, and determining key water quality indexes; constructing a two-dimensional tensor according to the key water quality index and the index value; constructing a water body pollution prediction model based on CNN and LSTM in combination with an attention mechanism; inputting the two-dimensional tensor into a water body pollution prediction model, and determining a pollution factor concentration; calculating the deviation between the pollution factor concentration and the pollution factor threshold value, and determining the water quality risk grade; and performing early warning on the water quality of the underground water source by combining an early warning grading strategy according to the water quality risk grade. The water quality safety of the underground water source can be ensured, and potential threats to the environment and human health are reduced.

The invention discloses an irrigation decision determination method considering a multi-source water conversion process, and relates to the technical field of agricultural water conservancy irrigation, and the method comprises the steps: obtaining a multi-spectral image and a thermal infrared image of crops in a target irrigation region, calculating a vegetation index and a leaf area index, and combining with the actually measured growth vigor data of the crops, a growth vigor model of crops is constructed by establishing a mapping relation, the rainfall, the irrigation volume, the canal system infiltration replenishment volume and the groundwater capillary rise volume of a target irrigation area are obtained, and a soil moisture income and expenditure model is constructed based on a water circulation process. According to the method, a plurality of paths such as rainfall, irrigation, canal system leakage and groundwater capillary rise are considered through the constructed soil water volume income and expenditure model, crop physiological moisture inflection points are accurately recognized by simulating the root zone volumetric moisture content and growth vigor response curve, threshold control irrigation based on crop requirements is achieved, and the crop yield is improved. And the multi-source input and conversion process of the farmland hydrological system is comprehensively reflected.

The invention relates to the technical field of intelligent early warning, and discloses a multi-source data driven intelligent early warning method and system for the abnormal state of a water quality meter, and the method comprises the steps: carrying out the multi-source data fusion of the collected real-time data of the water quality meter, and obtaining the multi-source water quality data of the water quality meter; performing multi-dimensional feature extraction on the multi-source water quality data to obtain water quality feature data; based on the change trend of the water quality features, performing adaptive fusion on the water quality feature data to obtain feature vectors of the multi-source water quality data; performing abnormal state association on the feature vector to obtain an abnormal probability score of the feature vector; comparing the abnormal probability score with a preset early warning grade, and performing abnormal threshold adjustment on the abnormal probability score according to a comparison result to obtain a graded early warning signal of the water quality meter; step-by-step coding is carried out on the graded early warning signal to obtain an early warning signal instruction of the water quality meter; according to the invention, the early warning efficiency of intelligent early warning of the abnormal state of the water quality meter driven by multi-source data can be improved.

The invention relates to the technical field of hydrology and water resource monitoring and emergency scheduling, in particular to a water source multi-modal monitoring fusion method and system, and the method comprises the steps: firstly obtaining multi-source water environment observation, and forming evidence graph initialization and assimilation initialization; secondly, carrying out cross-modal evidence fusion, generating topological boundary constraints, flow direction constraints and assimilation time windows, and compiling the topological boundary constraints, the flow direction constraints and the assimilation time windows into a constraint set; then executing data assimilation and source item joint inversion under the constraint of a partial differential equation to obtain a source item confidence set, the arrival time of a pollution front outer envelope and a key position, and a quantile interval of peak concentration and standard exceeding duration; and finally, constructing a risk functional and an opportunity constraint based on a quantile interval, and generating a scheduling instruction and partition early warning by adopting rolling predictive control, and performing closed-loop recharge. The method gives consideration to accuracy, robustness and performability.

The embodiment of the invention provides a pollutant source analysis method and device for underground water, equipment and a medium, and relates to the technical field of environmental chemistry analysis. The method comprises the following steps: carrying out water sample collection at candidate pollution source sampling points of target underground water to obtain candidate pollution source water samples, and carrying out water sample collection at downstream sampling points of the target underground water to obtain downstream water samples; wherein the target underground water flows from the candidate pollution source sampling point to the downstream sampling point; performing chemical component feature extraction according to the candidate pollution source water sample to obtain a first chemical feature, and performing chemical component feature extraction according to the downstream water sample to obtain a second chemical feature; performing similarity calculation according to the first chemical feature and the second chemical feature to obtain a target chemical feature similarity; and determining a target pollution source sampling point from the candidate pollution source sampling points according to the target chemical characteristic similarity. According to the embodiment of the invention, the accuracy of pollutant source analysis can be improved.

The invention discloses a fusion method and device based on multi-source water conservancy data, equipment and a medium, and relates to the technical field of water conservancy data processing, and the technical scheme is characterized in that the method comprises the steps: collecting water conservancy original data, carrying out the classified storage of the water conservancy original data according to a water conservancy data specification, and obtaining a water conservancy classification data set; preprocessing the water conservancy classification data set to obtain a preprocessed water conservancy classification data set, combining similar data of multiple sources, and carrying out missing compensation processing on the similar data to obtain a fused similar data set; and carrying out hierarchical modeling on the fused data sets of the same kind by utilizing distributed processing and a multi-bin hierarchical architecture design to obtain a standardized unified water conservancy data mart. The system has the advantages of high-efficiency water conservancy data acquisition, high-quality similar data fusion, high-standard heterogeneous data fusion, high-availability water conservancy data service and the like.

The utility model discloses a kind of compressed air energy storage systems suitable for marine environment, it is related to compressed air energy storage technical field.It includes including n group compressor, n group heat exchanger, n group cooler and closed cooling water system, it is sequentially connected through heat exchanger and cooler between adjacent compressor, nth group compressor is sequentially connected with gas storage through nth group heat exchanger and nth group cooler;Cooler one end is connected with seawater condenser closed water inlet through cooler closed water outlet pipeline, the other end is connected with seawater condenser closed water outlet through cooler closed water inlet pipeline.The utility model uses seawater as cooling water source, water source is stable, conducive to system stable operation;Adopt seawater as cold source, inexhaustible, and seawater temperature fluctuation is small, it can be regarded as constant temperature within 1 energy storage period, conducive to seawater condenser temperature control.

The invention discloses a multi-task deep learning driven COD and compensation parameter synchronous measurement method, and belongs to the field of water environment monitoring, and the measurement method specifically comprises the following steps: I, synchronously collecting various water quality data through an online water quality sensor, and preprocessing the collected various water quality data into continuous time input; according to the method, the consistency and availability of the multi-source water quality data in the time dimension are remarkably improved, high-fidelity water quality state estimation can be output at any time point, the continuous change characteristic of a real water environment can be better met, the cooperative change and mutual compensation effect of different parameters under different time scales can be dynamically reflected, and the accuracy and the reliability of the system are improved. The limitation of static correlation or artificial experience modeling is overcome, excessive self-confidence error prediction is avoided, and meanwhile high environmental adaptability and long-term operation stability are achieved; therefore, the invention provides a multi-task deep learning driven COD and compensation parameter synchronous measurement method.

The invention provides a mine disaster water source intelligent traceability system and method, and belongs to the technical field of mine safety production, flood control and disaster emergency treatment. The method comprises the steps that a hydraulic network diagram is constructed based on hydrological data collected by sensors at all observation points in a mine laneway in real time, and then a mine global flow field is reconstructed in the hydraulic network diagram; on the basis of a mine global flow field, starting from each observation point, performing path backtracking along a reverse water flow direction, and generating a plurality of reverse backtracking paths; and according to the probability weight of each reverse backtracking path, calculating a cumulative probability weight corresponding to each position of the mine, and drawing a probability thermal distribution diagram by using the cumulative probability weight of each position. According to the method, path backtracking is carried out in the reverse water flow direction, potential water source positions are speculated from all observation points at the same time, multiple reverse paths are formed, the probability weights of the reverse paths are calculated, the most probable water source area can be recognized under the conditions of a complex roadway network and multi-source water gushing, and the decision reference value of the recognition result is improved.

The application discloses a kind of multi-water source water supply pipe network system transport and distribution pattern optimization method, comprising: the application is solved by hour level and determines the initial proportion of each water source water supply area boundary as energy storage control static framework, carries out minute level reversible flow-head scanning to high-level water pool and two-way pump station, generates virtual booster unit and forms energy storage scheduling pre-instruction by reverse matching, pre-instruction back substitution static framework verifies water source backflow, water hammer overpressure and negative pressure pollution, and is locked as executable instruction, valve opening and closing sequence and pump station speed are then encoded as time-state vector input graph convolution network transient pressure surrogate model rolling deduction future three hundred seconds pressure envelope, only when the whole process is located in the allowable interval of pipe material, find the scene, realize the closed-loop collaborative optimization of hour level water source proportioning and minute level energy storage scheduling.The application solves the problem of complex calculation and control in multi-water source, multi-energy storage, multi-time scale coupling.

The application relates to a cloud platform-based water resource management method, device, equipment and medium. The method integrates multi-source water data through a cloud platform, constructs a hierarchical Bayesian model after data cleaning, uniformly quantizes model parameters, input and posterior distribution of structural errors, drives ensemble Kalman filtering dynamic assimilation of real-time observation data based on the same, generates a prediction distribution fusing multi-source uncertainty, further analyzes the contribution source of prediction variance in real time through a Sobol' index, identifies dominant uncertainty factors, constructs a coupled error model according to the same, feeds the coupled error model back to the assimilation cycle as a state variable for online correction, and finally forms an improved prediction model capable of dynamically tracking and quantifying the uncertainty coupling propagation mechanism, thereby significantly improving the accuracy and reliability of hydrological prediction, and providing risk quantification basis and optimization scheme for flood control scheduling, water resource allocation and urban drainage management decision-making.

The invention discloses a K-means clustering and BP neural network-based water source water quality monitoring method and system. The method comprises the steps of obtaining historical water quality data of all water source regions in a monitoring region; processing the historical water quality data by using a K-means clustering algorithm, dividing feature categories of abnormal water quality data and normal water quality data according to a clustering processing result, and respectively marking the feature categories of the abnormal water quality data and the normal water quality data; inputting the historical water quality data with marks after K-means clustering processing into a BP neural network for training to obtain a water quality detection model; current water quality data is collected and input into the water quality detection model, and the water quality detection model outputs the feature category of the current water quality data. The characteristic that the K-means clustering algorithm can accurately classify the data is combined with the BP neural network, repeated clustering processing does not need to be carried out on the water quality data, and rapid detection of the subsequent water quality data can be directly achieved.

The invention provides an unpowered air source water drawing device and method applied to an arid region, a water drawing device body comprises a condensate water collecting cavity located on the lower portion, an air condensation cavity is arranged above the condensate water collecting cavity, and a chimney type air duct is arranged above the air condensation cavity; the condensate water collecting cavity, the air condensing cavity and part of the chimney-shaped air duct are buried in the soil body, and an exhaust port is formed in the top of the chimney-shaped air duct; a photovoltaic PN junction patch for generating current is adhered to the outer wall of the upper part of the chimney-shaped air duct, and is electrically connected with an energy storage device and a refrigeration PN junction patch through a controller; the refrigeration PN junction patch is arranged on the air condensation cavity in a pasted mode and electrically connected with the energy storage device at the same time. An air inlet pipeline is arranged in the air condensation cavity, extends out of the chimney-shaped air duct and is used for introducing air; and a water collecting device is arranged in the condensate water collecting cavity. The device can be used for water drawing operation in the desert environment.

This invention proposes a single-point multi-source water quality monitoring system for factory-scale aquaculture, comprising an aquaculture pond, a microfiltration pond, and a biofilter pond that are sequentially fluidly connected and form a water circulation system. The system further includes a first water pump, a second water pump, and a third water pump respectively installed in the aquaculture pond, the microfiltration pond, and the biofilter pond. The output ends of the first, second, and third water pumps are fluidly connected to a measuring water tank via pipes. The measuring water tank is equipped with a multi-functional sensor for monitoring water quality. The bottom of the measuring water tank is fluidly connected to the microfiltration pond via a drain solenoid valve. The first, second, and third water pumps, the multi-functional sensor, and the drain solenoid valve are signal-connected to a core control board. This invention solves the problem of water quality monitoring and data comparison across multiple aquaculture water units in a factory-scale aquaculture workshop, and has advantages such as good stability, high integration, and low cost.

The invention provides a tunnel freezing injury prevention device utilizing geothermal energy, which comprises geothermal energy transmission equipment provided with a first water inlet and a first water outlet, and the first water inlet is externally connected with underground thermal spring water; the tunnel segment comprises a plurality of layered composite segment bodies connected in sequence and is provided with a geothermal source water inlet and a geothermal source water outlet, the geothermal source water inlet is connected with the first water outlet, and the geothermal source water outlet is connected with a tunnel drainage ditch; and the road surface anti-freezing component is laid on the road surface and provided with a second water inlet and a second water outlet, the second water inlet is connected with the first water outlet, and the second water outlet is connected with the tunnel drainage ditch. Underground thermal spring water is adopted as a heat source, energy is saved, carbon is reduced, icing is fundamentally eradicated, the possibility of frost heaving damage is eliminated, the layered composite pipe pieces can be rapidly disassembled and assembled in a lossless mode and rapidly replaced, and the operation and maintenance cost of the tunnel is reduced.

The application discloses a multi-heat-source hot water supply device and a multi-heat-source hot water supply control method. The multi-heat-source hot water supply device is provided with a circulating pipeline between a hot water outlet pipe and a return pipe, so that a circulating loop is formed between the hot water outlet and the return pipe of a hot water tank. The device starts the water pump in advance, and under the drive of the water pump, the hot water in the hot water tank and the cold water in each pipeline can circulate in the circulating loop, so that the hot water and the cold water are mixed, and the problem of the water temperature of the hot water outlet pipe being cold and hot at random when the device starts is solved. Moreover, the multi-heat-source hot water supply device can control the working states of the first pipeline switching mechanism, the electric heater and the gas water heater according to the outlet water temperature of the hot water tank detected by the temperature detection mechanism, so that hot water at different temperatures can directly flow out of the hot water supply pipe or flow out of the hot water supply pipe at a constant temperature through different heating paths, thereby solving the problem of the water temperature of the hot water outlet pipe being cold and hot at random during the working process of the device.

The application discloses a kind of multi-node collaborative balance regulation and control method and system for heating pipe network, belong to urban heating technical field, including obtaining relevant data, including with the heating source and pipe network of target city as acquisition object to carry out relevant data acquisition, relevant data includes the heating value of each heat source to water, and the heat of water into pipe network, pipe network includes primary pipe network;Carry out relevant processing, the steps of relevant processing are as follows: the water supply area of each heat source input to primary pipe network is divided into I heat source water supply, II heat source water supply and III heat source water supply, when I heat source water supply, II heat source water supply and III heat source water supply enter primary pipe network, the temperature of water supply is collected, temperature is regarded as initial temperature.The application forms complete closed loop, can carry out differentiation, collaborative scheduling according to actual heat dissipation performance in different section of each pipe network, greatly improves the overall energy efficiency and heating balance of heating pipe network.

The invention relates to the technical field of water treatment, discloses an intelligent water making and taking system and a water taking method, and aims to overcome the defects of existing intelligent water drinking equipment in the aspects of water quality monitoring, cloud control, voice interaction and the like. The system comprises: a water quality detection module arranged at a water inlet end and a water outlet end of equipment and used for detecting water quality in real time; the cloud control module receives the water quality data and generates an equipment control instruction; the voice recognition module is integrated in a local device and provides a localized voice recognition function; and the mobile terminal application module provides a remote monitoring and control interface. By adopting the technical scheme, early warning of water quality abnormity of a regional water source, accurate life prediction of filter element performance, remote intelligent configuration and scheduling of equipment operation parameters and non-sensitive equipment operation in a scene of weak network signals or interruption can be realized, and the drinking water safety and the user experience are remarkably improved.