154 results about "Water quality management" patented technology

The invention relates to the technical field of water quality monitoring, and discloses a water quality multi-parameter real-time monitoring system. The system comprises a monitoring point position configuration module, a water quality parameter acquisition module, a pollution index calculation module, an anomaly detection module, a central control unit and the like. The monitoring point position configuration module sets monitoring point positions and generates acquisition rules; the water quality parameter acquisition module acquires a water quality parameter set according to rules; the pollution index calculation module calculates a pollution index; the anomaly detection module obtains an anomaly detection index; and the central control unit comprehensively analyzes and generates water quality evaluation parameters. In addition, the system is further provided with a pollution source tracking module, a storage unit and an alarm module, pollution sources can be tracked, data can be stored, and an alarm can be given according to evaluation parameters. The system realizes multi-parameter real-time monitoring, accurate analysis and evaluation and pollution source tracking, provides comprehensive support for water quality management, effectively improves the water environment monitoring level, and guarantees the safety of water resources.

The invention discloses a dynamic water quality monitoring system based on an unmanned ship and a data acquisition and distribution algorithm. Comprising an unmanned ship platform module, an initial navigation path setting module, a water quality data acquisition module, a dynamic adjustment and optimization module, a control interaction module and a dynamic adjustment and optimization module, wherein the dynamic adjustment and optimization module dynamically adjusts the navigation strategy and sampling frequency of the unmanned ship in a target to-be-detected water area through a second branch of a first neural network model; the unmanned ship can sail autonomously, continuous and global water quality monitoring is achieved, through an efficient data processing algorithm, the accuracy and reliability of data are improved, a scientific basis is provided for water quality management, a distributed algorithm model is achieved to conduct predictive analysis on each specific target sampling point, the accurate predictability of unmanned ship monitoring is improved, and the water quality monitoring efficiency is improved. The monitoring strategy is dynamically adjusted according to actual requirements, optimal configuration of monitoring resources is achieved, the monitoring cost is reduced, the water quality change trend is found in advance through prediction analysis of the neural network model, and powerful support is provided for early warning and emergency response.

The invention discloses a marine ranching early warning method and system based on a knowledge graph, and relates to the technical field of marine ranching management, and the method comprises the knowledge graph of large-class keywords of water quality management, equipment management and biological resource management and progressive-level subclass keywords of the large-class keywords, terminal subclass association preset acquisition parameter groups and state description; generating a marine ranching plane graph; equipment states and detection parameters are collected to form a normal state parameter group, and a normal planar graph representation model is constructed; generating an exception model based on a preset exception adjustment normal parameter group, and dynamically associating the exception model with small-class keywords in the knowledge graph; and collecting data in real time to construct a real-time model, comparing the real-time model with an abnormal model to trigger an alarm, and marking an abnormal root in the knowledge graph. According to the method, the limitation of traditional single-dimensional monitoring is broken through, multi-source data are integrated through knowledge graph semantization, dynamic threshold and spatial correlation analysis are combined, abnormal accurate positioning and cross-dimensional risk early warning are achieved, and the marine ranch management efficiency and safety are remarkably improved.

The invention discloses an AI-driven unattended water environment quality monitoring system, and relates to the technical field of water environment monitoring, and the system comprises a data collection module, a cloud processing module, an edge calculation module, an intelligent analysis and early warning module, and a system management module. Through comprehensive and real-time intelligent monitoring of a water body, monitoring of water quality physical indexes is concerned, aquatic organism behavior monitoring is introduced, so that the health condition of the water body can be reflected more comprehensively, and meanwhile, through the data preprocessing and local model fine tuning functions of the edge calculation module, the water quality monitoring accuracy is improved. The intelligent analysis and early warning module can perform correlation analysis, set an early warning threshold value and generate early warning information based on the AI model after cloud side end collaborative optimization, and provides powerful decision support for water quality management.

The invention relates to an intelligent regulation and control system for multi-phase conversion of water quality of a gate-controlled river reach, in particular to the field of water treatment, and realizes accurate dynamic perception of the multi-phase conversion process of the water quality of the gate-controlled river reach by constructing a high-fidelity digital twinborn body and fusing a real-time data assimilation technology; by means of a time-space diagram neural network agent model based on an attention mechanism, the system can predict a complex time-space pattern of pollutant concentration field and phase evolution under different regulation and control strategies in an ultra-fast manner; on the basis, a multi-agent reinforcement learning algorithm is adopted to automatically generate a globally optimal gate group coordinated regulation scheme, and multiple targets of water quality improvement, ecological protection, engineering operation and the like are effectively coordinated; and finally, a theoretical strategy is reliably converted into a physical action through rolling optimization and a closed-loop execution mechanism, and adaptive adjustment can be performed according to environmental feedback, so that the emergency response speed of sudden water pollution events, the scientificity of regulation and control decision and the intelligent level of water quality management of the whole river network are comprehensively improved.

The invention provides a water quality on-line monitoring method and system for a large-volume water tank, and the method comprises the steps: obtaining original data of a plurality of water quality sensors, estimating the water quality state of the whole water tank through a weighted interpolation method, and forming a water quality space distribution baseline; for multi-sensor data, the pollution deviation degree of the sensor data and the water quality space distribution base line is calculated, then according to the pollution deviation degree and a dynamic self-adaptive threshold value, an abnormal pollution event is recognized, and abnormal detection data is obtained; according to the abnormal detection data, utilizing a hydrodynamic model to predict the diffusion trend of pollutants, and evaluating future water quality change; determining an optimal water quality management strategy according to the pollution prediction data in combination with water tank physical parameters and water treatment resource information to obtain a water quality optimization decision scheme; and dynamically adjusting the hydrodynamic model according to the execution result of the water quality optimization decision scheme and the latest monitoring data. According to the method, the defects of an existing method in the aspects of monitoring comprehensiveness, real-time performance and accuracy are overcome.

The invention provides a marine ranch water quality management method and system, electronic equipment and a storage medium, and the method comprises the steps that a water quality monitoring device, an edge computing terminal and a water quality adjusting device are arranged on a navigation mark in a marine ranch in advance, and the edge computing terminal obtains water quality parameter data of the marine ranch at a plurality of continuous moments; the water quality parameter data is collected through a water quality monitoring device, and if the water quality parameter predicted value exceeds a preset water quality normal range, a target adjusting amount is determined based on the water quality parameter predicted value; the water quality adjusting device adjusts the water quality according to the target adjusting quantity; near-end water quality prediction and water quality deterioration accident treatment can be completed at the navigation mark, the defect that water quality data cannot be monitored in real time and water quality deterioration accidents cannot be treated in time due to the fact that the time interval of Beidou satellite data transmission is long is overcome, and ecological risks and economic losses are effectively reduced.

The invention discloses a water pollution composite treatment method and system based on water quality pollution real-time monitoring, and relates to the technical field of water quality monitoring. Sensor equipment is arranged to dynamically monitor the water quality of a specified water body in real time, and collected data is uploaded to a water quality management cloud platform; according to monitoring data, the concentration change trend of various pollutants in a water body is evaluated, the pollutant concentration is predicted and analyzed in combination with a long-short-term memory neural network and a short-term difference method, then an appropriate composite treatment scheme is determined based on the change trend of the pollutant concentration, and water pollution treatment measures are evaluated and optimized by utilizing the effects of different treatment means. Finally, whether the treatment scheme needs to be further optimized or not is determined by dynamically evaluating the treatment effect, the pollution condition of the water body can be monitored in real time and accurately predicted, the machine learning and data analysis technologies are combined, the treatment measures can be dynamically adjusted and optimized, and the accuracy of the treatment effect is improved.

The invention provides a water quality environment detection method and system based on 5G communication, and the method comprises the steps: determining a target detection node through obtaining the spatial distribution data of a mobile detection node in a to-be-detected water area and the water area topographic feature data, and obtaining a detection data set based on the target detection node; heavy metal ion migration tracks in the detection data set are processed, a pollutant diffusion boundary prediction map is generated to simulate and generate a multi-scene diffusion envelope range, and an emergency management and control instruction set is generated based on the multi-scene diffusion envelope range; determining a pollution diffusion trend in combination with the emergency management and control instruction set and the environmental influence factor, and generating a water quality environment detection result based on the pollution diffusion trend; according to the technical scheme, the 5G communication technology and a traditional water quality detection method are effectively combined, automation, refinement and intelligentization of water quality environment detection are achieved, and the water quality management and protection capacity is improved.

The invention provides a water quality detection method based on combination of machine learning and spectrophotometry, and the method comprises the steps: measuring the absorbance of a water sample under a plurality of preset wavelengths through a spectrophotometer to form a multi-dimensional absorbance data set, mapping the multi-dimensional absorbance data set to a high-dimensional space through a kernel function technology to obtain a data set with enhanced non-linear features, and carrying out the detection of the non-linear features of the multi-dimensional absorbance data set. Extracting a known water sample and the pollutant concentration corresponding to the known water sample from historical water quality data, generating a training sample set, performing pollutant concentration prediction on the data set with the enhanced nonlinear characteristics by applying a machine learning model, and dynamically adjusting the training sample set by adopting an active learning strategy to obtain a pollutant concentration prediction value, and performing safety grade evaluation on the water sample and outputting a water quality report by using the predicted value of the pollutant concentration in combination with a water quality safety standard, the technical scheme provided by the invention improves the efficiency and accuracy of water quality detection, provides powerful technical support for environmental protection and public health guarantee, and has a wide application prospect. The whole process realizes integrated operation from data acquisition to result interpretation, and ensures scientificity and reliability of water quality management decision.

The invention discloses an intelligent high-density pool water quality control method and system, and relates to the technical field of intelligent water quality treatment.The intelligent high-density pool water quality control method comprises the steps that newest data and local data in a high-density pool are collected, the newest data are preprocessed, the preprocessed data are input into a three-dimensional digital twinborn model to update the state of the three-dimensional digital twinborn model, and the state of the three-dimensional digital twinborn model is obtained; and meanwhile, exchanging the local data between adjacent agents to obtain local interaction data of the agents. Extreme working conditions are simulated in the digital twinborn model, a water quality change prediction result is obtained, a bionic swarm intelligence algorithm is started for distributed collaborative optimization, an optimized control instruction is obtained and distributed to each agent, a water quality control task is executed, and a high-density pool water quality state report is generated. According to the method, the ant colony algorithm is used for optimization, the requirement that the water quality reaches the standard is considered, the requirement of saving energy consumption is also considered, the economic adaptability is greatly improved, and it is ensured that efficient water quality management can be achieved through control instructions under various environment conditions.

The invention relates to the technical field of water quality monitoring, in particular to an automatic river water quality monitoring and analyzing method and system.The method comprises the following steps that on the basis of real-time and historical water quality monitoring data, multi-source monitoring information is integrated through the data fusion technology, and flow characteristics of a river water body are simulated through a finite element analysis method; and carrying out weighted average on data collected at multiple time points by implementing a Kalman filtering algorithm to generate an integrated hydrodynamics and spatial distribution prediction result. According to the analysis method, the analysis depth and accuracy of complex water body system behaviors such as rivers are improved through the analysis method integrating the water quality monitoring data and the fluid dynamic model, and the relation between the water quality change and the water flow dynamic process is comprehensively analyzed and predicted. The scientificity and effectiveness of a water quality management strategy are enhanced, and the capability of coping with complicated water environment challenges is improved.

The invention discloses a hydrogen production water quality management system, which comprises an electrolytic bath device, a water storage device, a hydrogen separation device, an oxygen separation device and a water quality filtering device, and the hydrogen separation device and the oxygen separation device are respectively communicated with a hydrogen electrolysis outlet and an oxygen electrolysis outlet of the electrolytic bath device. A first water return main path of the oxygen separation device guides separated water to a water inlet of the electrolytic bath device, the first water return main path is provided with a first conductivity sensor and is in bypass connection with a water return bypass, and the water return bypass or the first water return main path located between the water return bypass and the electrolytic bath device is provided with a first valve. The first valve is in communication connection with the first conductivity sensor, and the water quality filtering device is connected with the water return bypass and a water supplementing pipeline of the water storage device in a converging mode and can guide filtered water to the first water return main path, so that water entering the system from the water storage device and circulating water from the first water return main path can be filtered at the same time. The electric conductivity fluctuation is avoided by reducing the electric conductivity in the water path of the system.

The present invention may provide a water quality management device including a spectral camera, a memory, and a processor, and an operating method thereof. The processor is configured to collect the plurality of spectral images for at least a portion of the stored water in response to a predefined event occurrence, classify the plurality of spectral images into a suspended material data set and a non-suspended material data set based on a presence or absence of a suspended material in the spectral images, perform learning to generate a water quality detection model used to detect water quality by using at least a portion of the suspended material data set and the non-suspended material data set, and store the water quality detection model generated through the learning.

The invention discloses an intelligent monitoring system and method for outlet water of a central air-conditioning cooling tower, and relates to the technical field of cooling tower outlet water quality monitoring. The intelligent outlet water monitoring system for the central air-conditioning cooling tower comprises an operation fluctuation analysis module, an outlet water quality monitoring module and a water quality discharge and supplement optimization module. According to the invention, fluctuation analysis is carried out on the operation efficiency of the central air-conditioning cooling tower, the outlet water flow of the central air-conditioning cooling tower is adjusted and the outlet water quality data is collected based on the fluctuation analysis result, and then the water quality of the outlet water of the central air-conditioning cooling tower is monitored. And finally, combining a water quality warning analysis result to carry out effluent water quality discharge compensation optimization on the effluent water quality of the central air-conditioning cooling tower so as to realize more efficient effluent water quality management in the intelligent effluent water monitoring process of the central air-conditioning cooling tower. The problem that in the prior art, interaction between water quality and operation is not considered when the water quality of the outlet water is managed in the intelligent monitoring process of the outlet water of the central air conditioner cooling tower is solved.

Provided are a water quality control method capable of performing control for maintaining water quality management items at appropriate values at low cost, a method for creating a control table used therefor, and a control table creation program. 【Solution means】This method for creating a control table and the control table creation program create a control table using actually measured data in an operating management system. Further, for the insufficient part, it is calculated by an operation based on the actually measured data. Therefore, the control table can be created without using expensive equipment. Further, the acquisition of data necessary for creating the control table can be handled by existing equipment, and the introduction cost can be kept low. Further, in this water quality control method, a large calculation load does not occur in the management value setting device. Therefore, it is possible to use existing equipment for the management value setting device, and the introduction cost of the present invention can be kept low.

The invention discloses a water quality monitoring method and system based on multi-source data. The method comprises the following steps: acquiring multiple types of monitoring sensing data of a target water area; determining a plurality of pollution origin positions of the target water area based on the monitoring sensing data belonging to the first monitoring level; based on the pollution origin position, screening associated sensing data belonging to a second monitoring level from all the monitoring sensing data; and analyzing the water quality pollution condition of the target area according to the associated sensing data and the pollution origin position. Therefore, accurate water quality pollution assessment based on multi-stage monitoring and multi-source data can be realized, the accuracy and response efficiency of water quality management of the target water area are improved, and the risk of pollution diffusion is reduced.

The invention discloses a migratable surface water quality prediction method based on representation learning, and the method comprises the steps: 1, obtaining historical monitoring data, so as to construct a data set in a multi-site sequence format, carrying out the mask processing of the historical monitoring data in the data set, so as to obtain mask data, forming a training test set by the historical monitoring data and the mask data; 2, selecting a Transform model framework with the same total number of source domains to construct a prediction network; step 3, training the prediction network to obtain a prediction model; and step 4, inputting the water quality data collected in the station and the meteorological data of the current day into the prediction model to obtain the water quality data of the source domain where the station is located. The invention further provides a device for predicting the water quality of the transferable surface water. According to the method provided by the invention, the key water quality index of the source domain river monitoring section is predicted through the change of the water quality information of each station in the source domain, and more accurate and comprehensive reference is provided for subsequent water quality management.

In-stream water quality management via monitoring, reporting, and verification sensor-geospatial fusion networks may be provided by a source sensor in a watershed configured measure in-stream water quality and a machine learning model configured to combine local data from the source sensor with remote sensing data to generate a near-realtime estimation of environmental conditions, determine that a change to a configuration of a water treatment system can be made while maintaining environmental conditions within a predetermined range of parameters, and modify the configuration of the water treatment system, responsive to the determination.

The invention provides a device and a method for purifying culture circulating water in a higher-place pond, and the method specifically comprises the following steps: the culture circulating water and residual feed and excrement in the higher-place pond flow out from a sewage draining exit at the center of the pond bottom, and gradually flow into a self-settling filter well through a water inlet at the bottom of the well; aquaculture circulating water is filtered by an immersion filtering device in the well and overflows out of the well, and residual feed and excrement settle to the bottom of the well and then are discharged through a shrimp shell excrement drain outlet; the breeding circulating water overflowing out of the well flows through a hypochlorous acid oxidation device to be disinfected; the culture circulating water treated by the hypochlorous acid oxidation device flows into an aeration dechlorination tank to remove harmful gas; the culture circulating water treated by the aeration dechlorination tank flows into the ecological tank, so that the contents of carbon, nitrogen, phosphorus and the like in the water are reduced; and the culture circulating water treated by the ecological pond is pumped into the higher-place pond through a reflux pump. The system is efficient, energy-saving, small in occupied area, high in automation degree and capable of improving the water quality management efficiency and stability of higher-place pond culture circulating water.

Provided is a loach fry cultivation method, the method comprising fry pond clearing, water quality management, and feeding management. First, performing fry pond clearing, controlling the depth of a cleared fry pond at 40-60 cm, placing loach fry hatched on the same day into the fry pond and controlling the stocking density of the loach fry at 450-600 fish per square meter; after placing the loach fry into the fry pond, performing water quality management on the fry pond and performing feeding management for the loach fry in the fry pond until the loach fry reach a length of 3-5 cm. During the loach fry feeding period, feeding is skipped every other day. A one-day period without feeding allows the gastrointestinal tracts of the loach fry to rest and adjust, and effectively prevents excessive fish feed from accumulating in the fry pond.

The invention relates to the technical field of water distribution regulation and control, and discloses an ecological pond water distribution method based on the Internet of Things and a regulation and control system. The method comprises the following steps: collecting water quality parameters of different depths of an ecological pond through a vertical layered sensor to form a depth gradient data set; quantitatively analyzing the layering state of the water body by using a thermocline recognition algorithm to obtain thermocline position, dissolved oxygen vertical gradient and nutritive salt layering state dynamic variables; comparing the dynamic variable with a preset threshold value, and generating a layering abnormal trigger signal and a target water distribution depth; cooperatively scheduling the multi-depth water distribution equipment, and generating a water distribution execution instruction; executing directional water distribution treatment to obtain water quality improvement effect data and updating the parameter optimization database. The problems that in ecological pond water quality management, the water layering state cannot be accurately recognized, targeted water distribution control is lacked, and the water distribution effect is difficult to quantify and optimize are solved.

The present invention relates to a method for predicting the phosphorus removal performance of machine learning-driven metal-modified biochar, comprising the following steps: obtaining the original data under the loading of Mg or La on the biochar to form a data set, the data set including input features and output variables; performing data preprocessing and input feature analysis on the data set; dividing the data set into a training set and a test set, training six machine learning models including random forest (RF), gradient boosting (GBR), extreme gradient boosting (XGB), support vector machine (SVM), ridge regression, and artificial neural network (ANN), and determining the training model after evaluation; performing hyperparameter optimization on the training model through Bayesian optimization combined with five-fold cross-validation to obtain the optimized training model; using the optimized training model to predict the phosphorus removal performance of the metal-modified biochar, and predicting the corresponding preparation process parameters with the adsorption capacity and the remaining phosphate concentration as the targets, providing a new idea for the directional application of the biochar preparation process under different water quality management objectives.

The application discloses a fluoride regional river water sampling device and relates to the technical field of river water sampling. The device comprises a surrounding mechanism for building a stable water area space, a sampler in the surrounding mechanism, at least two symmetrical chains, one end of each chain being connected to the surrounding mechanism and the other end of each chain being connected to the sampler. The surrounding mechanism comprises a plurality of floating plates which are sequentially connected in a head-to-tail mode. An underwater propeller is embedded in each floating plate. The device can meet the demand of fluoride sampling in a complex and changeable river water environment and provide strong support for water quality management and environmental protection.

The invention discloses a water quality treatment system which comprises an impurity removal device, a liquid mixing device, a dosing device, a precipitation device and a filtering device, a pump body assembly is fixedly connected to the lower end of the liquid mixing device and comprises a driving assembly, pump shells and piston blocks, the driving assembly is fixedly connected to the lower end of the liquid mixing device, and the pump shells are fixedly connected to the two sides of the driving assembly respectively; wherein one group of pump shells is connected with an impurity removal device and a liquid mixing device through a water inlet pipe, the other group of pump shells is connected with a filtering device and a liquid mixing device through a water return pipe, the liquid mixing device is connected with the precipitation device through a water guide pipe, one side of the precipitation device is fixedly connected with the filtering device, and the dosing device is connected with the liquid mixing device through a dosing pipe. The invention aims to provide the water quality treatment system which effectively improves the water quality management efficiency and accuracy, is good in sewage treatment effect and can reduce the environmental influence.

The application discloses a kind of comprehensive water quality promotion algae inhibitor and its preparation method and application, belong to water quality management field.The comprehensive water quality promotion algae inhibitor is according to mass percentage component: lanthanum iron modified bentonite 15-35%, modified sodium percarbonate 30-45%, polyaluminum chloride 8-15%, binder 20-30%;The mass ratio of lanthanum iron modified bentonite and modified sodium percarbonate is 1-3:1;The binder is composed of natural porous mineral and cement.The comprehensive water quality promotion algae inhibitor disclosed in the application can inhibit algae, eliminate algal toxins, oxidize ammonia nitrogen, increase oxygen and activate water environment ecology on the one hand, and the modified lanthanum component can more stably remove phosphorus on the other hand, and can reduce the pH increase caused by the use of sodium percarbonate, and can promote water quality under the coupling of other adsorption materials, adsorb pollutants, and fundamentally solve the problem of water eutrophication.

The invention discloses a secondary water supply residual chlorine prediction method based on a deep learning model, and relates to the technical field of water quality management, and the method comprises the following steps: carrying out the data collection of historical hydraulic power and water quality parameters, and obtaining original feature data; generating a feature sequence according to the original feature data to obtain a time sequence feature sequence; performing nonlinear relation extraction according to the time sequence feature sequence to obtain residual chlorine features; performing future residual chlorine prediction according to the residual chlorine characteristics to obtain a residual chlorine prediction value; performing error evaluation according to the residual chlorine prediction value to obtain a prediction precision index; and performing prediction optimization according to the prediction precision index to obtain an optimization result. According to the method, multiple nonlinear mapping is used, the coupling relation between time dependence and features is mined, the dynamic change trend of the residual chlorine concentration is reflected more accurately, the prediction precision is improved, and the prediction robustness and stability are enhanced.

The invention provides an intelligent farm water quality management and regulation method, and relates to the technical field of ecological agriculture. The method comprises the following steps: dividing a planting area into a full-sunny area, a semi-shaded area and a full-shaded area according to daily average illumination intensity L, and configuring corresponding illumination adaptive plants; the poultry breeding house is divided into a brooding house, a breeding house and a fattening house according to the area ratio of 1: 2: 1.5; the planting area is provided with a slope terrain and a poultry area isolation belt; the net bed breeding system is connected with the manure scraping device and the underground fermentation tank. The output end of the fermentation tank is connected with the biogas combustion furnace. Plant requirements are accurately matched through illumination partition, and efficient utilization of land below the photovoltaic module is achieved; by combining poultry house function division and feces resource circulation, the unit area composite output rate is remarkably increased, the environmental pollution risk is reduced, and a systematic solution is provided for efficient utilization of land resources.

The invention discloses a device and method for increasing the survival rate of ricefield eel breeding, and relates to the technical field of aquaculture equipment, and the method comprises a water quality management measure, a temperature regulation measure, a breeding system, a sewage treatment system, a water storage system, a stress period management measure, a feeding strategy, a feeding density and a disease prevention strategy. Through cooperative operation of the culture system, the sewage treatment system and the water storage system, in combination with water quality regulation and control and an automatic temperature control strategy, accurate management of key water quality indexes and stable regulation of air temperature and water temperature are realized, so that water body replacement is quickly and efficiently completed, and the disease problem caused by too large temperature difference is effectively avoided; on the basis, stress period management, a scientific feeding strategy, reasonable putting density and systematic disease prevention measures are matched, the habitat environment of the ricefield eels is improved fundamentally, the physical health of the ricefield eels is enhanced, and finally the breeding survival rate is effectively increased.

The utility model provides a modularization container type intelligent fish pond system, include: a plurality of containers, annular arrangement and interconnect to enclose a central space, the central space forms a fish pond structure, the bottom of fish pond structure is equipped with a waterproof layer, a plurality of passageways are formed in each container respectively, a control system is arranged in at least one container of container, and a modularization functional device is arranged in container and is electrically connected control system, the modularization functional device can include water quality management module, fish population monitoring module, temperature control module, fish receiving module etc, each module can be configured according to the breeding demand, effectively promotes the breeding efficiency, reduces the manpower demand, and can automatically adjust the feeding amount and environmental parameter according to the fish growth condition, greatly improves the health and yield of fish.