Intelligent water quality monitoring and adjusting device based on internet of things

Abstract

The application belongs to the technical field of intelligent monitoring of aquaculture, and specifically discloses an intelligent water quality monitoring and adjusting device based on the Internet of Things, which comprises a multi-parameter water quality monitoring unit, an intelligent adjusting unit and a remote control unit.The application adopts the above-mentioned intelligent water quality monitoring and adjusting device based on the Internet of Things, and the device is designed in a modular way and is suitable for various scenes such as factory-like breeding of shrimps and crabs, breeding of precious fish and the like, realizes intelligent integration of water quality monitoring, adjusting and early warning, and further realizes all-round intelligent monitoring and accurate adjusting of water quality of aquaculture, thereby providing a new technical scheme for accurate management of aquaculture.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of intelligent monitoring of aquaculture, and particularly relates to an intelligent water quality monitoring and adjusting device based on the Internet of Things. BACKGROUND

[0002] With the development of the scale and intensification of aquaculture, water quality monitoring and adjusting has become a key link to guarantee the efficiency of aquaculture. The existing water quality monitoring technology mainly relies on the experience of aquaculture personnel for manual monitoring. This traditional method not only has strong subjectivity and low standardization, but also is difficult to achieve 24-hour continuous monitoring due to the limitation of human resources, which is easy to miss the best adjusting opportunity. The automatic monitoring equipment on the market generally has deficiencies in monitoring accuracy, especially in the data reliability under complex water quality environment, and most of them use single parameter monitoring method, lacking multi-parameter linkage analysis and adjusting capacity. These devices cannot predict the water quality trend, and can only discover and handle problems after they occur, and the simple adjusting method is difficult to achieve accurate balance of water quality. In the application level of the Internet of Things technology, the existing system still needs to be improved in the reliability of data acquisition and transmission, and lacks intelligent data analysis and early warning mechanism, and the limited remote control function is difficult to meet the actual needs of complex working conditions. These technical bottlenecks seriously restrict the intelligent development process of aquaculture.

[0003] Therefore, there is a need to develop an intelligent water quality monitoring and adjusting device based on the Internet of Things to effectively solve the above problems. SUMMARY

[0004] The purpose of the present application is to provide an intelligent water quality monitoring and adjusting device based on the Internet of Things, which adopts modular design and is suitable for various scenes such as shrimp and crab factory farming, precious fish farming, etc., realizes the intelligent integration of water quality monitoring, adjusting and early warning, and further realizes the all-round intelligent monitoring and accurate adjustment of water quality in aquaculture, providing a new technical solution for the precision management of aquaculture.

[0005] To achieve the above purpose, the present application provides an intelligent water quality monitoring and adjusting device based on the Internet of Things, which comprises a multi-parameter water quality monitoring unit, an intelligent adjusting unit and a remote control unit. The multi-parameter water quality monitoring unit adopts a new type of composite sensor, which can monitor more than 10 indexes such as temperature, pH value, dissolved oxygen, ammonia nitrogen and nitrite of the aquaculture water body in real time for 24 hours. The new type of composite sensor adopts a distributed arrangement scheme, and the built-in data calibration algorithm ensures the accuracy and reliability of the monitoring data.

[0006] The intelligent adjustment unit adopts a multi-parameter linkage control algorithm, based on the mutual relationship between various water quality parameters, and through the configuration of an independent adjustment execution system, it can correct the detected abnormal indicators in real time, and realize the accurate balance and dynamic adjustment of water quality.

[0007] The remote control unit is based on the Internet of Things technology, integrates a water quality early warning model, and through deep learning analysis of historical data, establishes a water quality change trend model to predict water quality abnormalities 12-24 hours in advance, and sets multiple warning thresholds to automatically trigger the adjustment program when detecting abnormalities.

[0008] The device adopts modular design and is suitable for shrimp and crab factory farming, precious fish farming and other scenarios, and has the functions of water quality data collection, storage, analysis, early warning and adjustment, and can realize remote monitoring and intelligent management through the Internet of Things platform, so as to realize the overall monitoring and adjustment of aquaculture water quality.

[0009] Preferably, the new composite sensor is composed of a temperature sensor array, a pH composite electrode, an optical dissolved oxygen sensor, an ion selective electrode and a spectral analyzer; wherein the temperature sensor array adopts a platinum resistance temperature measuring element, with a measurement accuracy of ±0.1℃ and a measurement range of 0-50℃; the pH composite electrode integrates a reference electrode and a working electrode, with a measurement accuracy of ±0.01 and a measurement range of 0-14; the optical dissolved oxygen sensor is based on the fluorescence quenching principle, with a measurement accuracy of ±0.1mg / L and a measurement range of 0-20mg / L; the ion selective electrode is used for ammonia nitrogen detection, with a measurement accuracy of ±0.01mg / L and a measurement range of 0-10mg / L; the spectral analyzer uses visible-near infrared spectroscopy technology to measure nitrite, with a measurement accuracy of ±0.005mg / L and a measurement range of 0-5mg / L;

[0010] The distributed arrangement scheme adopts a "3+1" four-group sensor arrangement structure, one group of new composite sensors is arranged at the water inlet, middle and water outlet of the culture pond, and one detection point is arranged at 0.5m, 1.5m and 2.5m below the water surface, and a group of standard sensor group for data calibration is additionally arranged at the center position of the culture pond; the sensors transmit data through RS485 bus, and the sampling frequency is automatically adjusted between 1-10 minutes;

[0011] The data calibration algorithm includes three links of signal preprocessing, drift correction and data fusion, to realize the accuracy and reliability of the monitoring data; wherein, the signal preprocessing adopts wavelet transform to remove high-frequency noise, the drift correction establishes a dynamic compensation model based on the measurement values of the standard sensor group, and the data fusion adopts a Kalman filtering algorithm based on an adaptive noise covariance matrix to perform weighted average on the multi-point measurement data, the algorithm dynamically adjusts the weight coefficient according to the measurement accuracy and historical data stability of each sensor, and an abnormal value detection mechanism is introduced, when the sensor data deviation exceeds the set threshold, the abnormal data points are automatically removed;

[0012] The multi-parameter water quality monitoring unit further comprises an automatic cleaning system, which cleans the sensor probe by compressed air and mechanical brush, the cleaning period is automatically adjusted in the range of 2-24 hours according to the water quality condition, and the data acquisition is automatically suspended during the cleaning process, and after the cleaning is completed, the data is calibrated to ensure the continuity and reliability of the monitoring data.

[0013] Preferably, the multi-parameter linkage control algorithm adopts a fuzzy neural network structure, including a water quality parameter correlation analysis module and a multi-objective optimization control module, wherein the correlation analysis module calculates the coupling relationship between the water quality parameters based on the Pearson correlation coefficient, and establishes a parameter correlation matrix including temperature-dissolved oxygen, pH-ammonia nitrogen, ammonia nitrogen-nitrite; the multi-objective optimization control module adopts an improved particle swarm algorithm, taking water quality stability and energy consumption as optimization objectives, to calculate the optimal operation parameters of each adjusting device in real time;

[0014] The intelligent adjusting unit includes an independent adjusting execution system, a real-time correction mechanism and an energy management system; wherein, the independent adjusting execution system includes a temperature monitoring and adjusting system, a pH monitoring and adjusting system, an oxygenation system and a water quality purification system, wherein the temperature monitoring and adjusting system is composed of a frequency conversion water pump, a heat exchanger and a temperature control valve, and the adjusting accuracy is ±0.5℃; the pH monitoring and adjusting system is configured with a two-way injection device of alkali and acid, and the dosing amount is accurately controlled by a peristaltic pump, and the adjusting accuracy is ±0.1; the oxygenation system adopts a micro-nano bubble generator combined with a jet aeration, and the dissolved oxygen adjusting accuracy is ±0.2mg / L; the water quality purification system integrates a biological filter and a microfiltration device, and the purification capacity is not less than 100m 3 / h;

[0015] The real-time correction mechanism is based on a proportional-integral-derivative (PID) control algorithm, and an independent control loop is set for each execution system, wherein the proportional coefficient (Kp) ranges from 0.5 to 2.0, the integral time (Ti) ranges from 60 to 300 seconds, and the differential time (Td) ranges from 0 to 60 seconds, the control period is 1 minute, and the proportional-integral-derivative control algorithm parameters are automatically adjusted according to the change trend of the water quality parameters;

[0016] The energy management system automatically selects the optimal device combination and operation scheme by real-time monitoring of the operation state and energy consumption data of each execution device, combining water quality regulation requirements, to minimize energy consumption while ensuring water quality stability, and has device fault diagnosis and standby switching functions to ensure the reliability of the regulation system.

[0017] Preferably, the Internet of Things technology architecture adopts an edge computing mode, including a field control layer, an edge computing layer, and a cloud platform layer, data transmission is performed through an MQTT protocol to realize real-time communication and control between devices; a water quality change trend model adopts an LSTM deep learning algorithm to predict water quality parameter changes in combination with historical data, with a prediction time window of 12-24 hours to provide early warning of water quality abnormalities;

[0018] The remote control unit is provided with an automatic adjustment mechanism to take corresponding adjustment strategies according to abnormal conditions of different water quality parameters: when the temperature is abnormal, the circulating water volume is adjusted through a variable frequency water pump, and the working state of a refrigeration unit or a heater is controlled; when the pH value is abnormal, a precise dosing system is started, the dosing amount of an acid-base adjusting agent is accurately controlled through multi-point detection combined with flow calculation; when the dissolved oxygen is insufficient, the power of a micro-nano aeration system is first increased, a standby jet oxygenation machine is started if necessary, and the water flow rate is adjusted through a water pump to increase the reoxygenation efficiency; when the ammonia nitrogen or nitrite exceeds the standard, a biological filter backwashing program is started, the circulating water volume is increased, and a microbial preparation dosing system is used for water quality adjustment;

[0019] The remote control unit has data storage and system recovery functions, maintains data caching for the last 7 days, and automatically synchronizes to the cloud platform after network recovery.

[0020] Preferably, the parameter threshold setting and adjustment triggering mechanism of the device includes:

[0021] a. For the water temperature index, three-level early warning thresholds are set: when the temperature deviates from the set value by ±1℃, a first-level early warning is triggered, and a variable frequency water pump is started; when it deviates by ±2℃, a second-level early warning is triggered, and a temperature control device is started; when it deviates by ±3℃, a third-level early warning is triggered, and the water circulation system and the temperature control system are started;

[0022] b. For the pH value index, three-level early warning thresholds are set: when the pH value deviates from the set value by ±0.3, a first-level early warning is triggered, and a weak strength dosing pump is started; when it deviates by ±0.5, a second-level early warning is triggered, and the dosing amount is increased; when it deviates by ±0.8, a third-level early warning is triggered, and an emergency dosing system is started;

[0023] c. For the dissolved oxygen index, three-level early warning thresholds are set: when the dissolved oxygen is lower than 5mg / L, a first-level early warning is triggered, and the aeration intensity is increased; when it is lower than 4mg / L, a second-level early warning is triggered, and a standby oxygenation device is started; when it is lower than 3mg / L, a third-level early warning is triggered, and all oxygenation systems are started.

[0024] d. For the ammonia nitrogen index, set three levels of early warning thresholds: trigger level one early warning when ammonia nitrogen exceeds 1 mg / L, increase the biological filter flow; trigger level two early warning when it exceeds 2 mg / L, add biological agents; trigger level three early warning when it exceeds 3 mg / L, start the emergency water replacement program;

[0025] e. For the nitrite index, set three levels of early warning thresholds: trigger level one early warning when nitrite exceeds 0.5 mg / L, increase the circulating water volume; trigger level two early warning when it exceeds 1 mg / L, start the denitrification system; trigger level three early warning when it exceeds 1.5 mg / L, add special degrading bacteria agent;

[0026] The parameter threshold setting and adjustment triggering mechanism of the device is based on water temperature monitoring and adjustment system, pH monitoring and adjustment system, ammonia nitrogen monitoring and adjustment system, and nitrite monitoring and adjustment system. When any early warning threshold is triggered, the triggering time, parameter value and adjustment measures are automatically recorded, and early warning information is sent to the management personnel through the remote control unit. When the water quality parameter returns to the normal range, the system automatically records the recovery time and adjustment effect for subsequent optimization of adjustment strategy.

[0027] Preferably, the water temperature monitoring and adjustment system uses different adjustment mechanisms according to the early warning level, including level one early warning adjustment mechanism, level two early warning adjustment mechanism and level three early warning adjustment mechanism. The level one early warning adjustment mechanism is triggered when the water temperature deviates from the set value ±1℃. This mechanism is configured with a variable frequency water pump system consisting of a main pump and a backup pump. The water pump is driven by a 380V three-phase asynchronous motor with a rated power of 7.5KW and a maximum flow of 120m 3 / h. The system automatically adjusts the water pump frequency through a Siemens S7-200 series PLC controller, gradually adjusts the water pump operating frequency from the initial 30Hz in the range of 20-50Hz at a step of 2Hz / min, and automatically waits for 5 minutes after each adjustment to observe the temperature change trend, and judges the direction and amplitude of continued adjustment according to the trend;

[0028] The level two early warning adjustment mechanism is triggered when the water temperature deviates from the set value ±2℃. This mechanism is configured with a temperature control device consisting of a chiller unit and a heater. The chiller unit has a refrigeration capacity of 60000kcal / h, uses a titanium tube heat exchanger with a heat exchange area of 20m 2 , and the refrigerant is R410A. The heater uses a titanium alloy heating pipe with a power of 12KW and the surface temperature is controlled within the range of 60±5℃. When the temperature exceeds the threshold, the system automatically starts the corresponding temperature control equipment according to the temperature deviation direction. The chiller unit operates at 50% load or the heater operates at 8KW power. At the same time, the temperature sensor records the water temperature change data every 15 minutes and uploads the data to the control system for adjustment strategy optimization.

[0029] The tertiary early warning adjustment mechanism is triggered when the water temperature deviates from the set value by ±3℃, which integrates the linkage control of the circulating system and the temperature control equipment. The circulating system is composed of a DN200 specification PVC main circulating pipeline with a wall thickness of 8 mm and a DN100 specification PVC branch pipeline with a wall thickness of 6 mm, and a 7.5KW frequency conversion water pump is used to provide power. The temperature control equipment includes a refrigeration unit with a refrigeration capacity of 60000kcal / h and a heater with a power of 12KW. When the system enters the tertiary early warning state, the controller automatically adjusts the frequency of the frequency conversion water pump to 45Hz to make the circulating water volume reach 100m 3 / h, simultaneously starts the 100% load operation of the refrigeration unit or the 12KW full power operation of the heater, and opens all branch pipeline valves through the electric valve controller to realize the rapid circulation of the whole pool water body. The system continues to run until the water temperature returns to the set range;

[0030] The water temperature monitoring and adjustment system also has a complete safety protection mechanism, including forced shutdown protection after the temperature control equipment runs continuously for 4 hours, automatic frequency reduction protection when the water pump motor temperature exceeds 60℃, and automatic pressure relief protection when the system pipeline pressure exceeds 0.5MPa. At the same time, the system uploads the equipment running state, protection action record and adjustment effect data to the remote control unit in real time, providing data support for the maintenance management and optimization upgrade of the system.

[0031] Preferably, the pH monitoring and adjustment system uses different adjustment mechanisms according to the early warning level, including a primary early warning adjustment mechanism, a secondary early warning adjustment mechanism and a tertiary early warning adjustment mechanism. The primary early warning adjustment mechanism is triggered when the pH value deviates from the set value by ±0.3. The mechanism is configured with a magnetic drive diaphragm metering pump as a weak drug injection pump. The metering pump uses a polytetrafluoroethylene diaphragm, with a maximum flow of 2L / h, a lift of 50 meters, and an injection accuracy of ±1%. The injection amount is controlled by a 4-20mA analog signal. The system automatically selects acidic or basic adjusting agent according to the pH deviation direction, and adds it through a peristaltic pump at an initial flow rate of 0.5L / h. After each addition, the pH value change trend is observed for 3 minutes;

[0032] The secondary early warning adjustment mechanism is triggered when the pH value deviates from the set value by ±0.5. The mechanism is configured with a double-head metering pump system, including a main pump and a standby pump. The metering pump uses a 316L stainless steel pump head, with a maximum flow of 5L / h and an injection accuracy of ±0.5%. The system increases the injection amount to 1.5L / h through the PLC controller, and starts the water body circulation system to increase the mixing efficiency of the adjusting agent. The circulating system uses a vertical centrifugal pump with a power of 2.2KW and a flow rate of 30m 3 / h. The pH value is collected every 5 minutes and automatically adjusted according to the change trend;

[0033] The tertiary early warning adjustment mechanism is triggered when the pH value deviates from the set value by ±0.8, and the mechanism is configured with an emergency dosing system, including a 200L storage tank of the adjusting agent, a high-precision metering pump set and a rapid mixing device, wherein the storage tank is made of PE material and is equipped with a liquid level meter and a metering scale, the metering pump set is composed of three series-connected metering pumps, the maximum flow rate of a single pump is 10L / h, the coordinated operation of multiple pumps is realized through a PLC controller, the rapid mixing device adopts a 4KW jet pump, and four injection points are arranged at different positions of the pool body to ensure rapid and uniform mixing of the adjusting agent;

[0034] The pH monitoring and adjustment system is also provided with a chemical safety protection mechanism, including liquid level monitoring of the agent storage tank, pipeline pressure monitoring and agent concentration monitoring. When the liquid level of the storage tank is lower than 20%, the system automatically alarms, when the pipeline pressure exceeds 0.4MPa, the system automatically stops the pump to protect, at the same time, the system records the pH value change every 30 seconds through the online pH meter, when the pH value change caused by single dosing exceeds 0.3, the system automatically reduces the dosing amount, to ensure the safety and controllability of the adjustment process, the system uploads the real-time data of the adjustment process to the remote control unit, for optimizing the adjustment strategy and predicting maintenance.

[0035] Preferably, the ammonia nitrogen monitoring and adjustment system adopts different adjustment mechanisms according to the early warning level, including a primary early warning adjustment mechanism, a secondary early warning adjustment mechanism and a tertiary early warning adjustment mechanism; wherein the primary early warning adjustment mechanism is triggered when the ammonia nitrogen concentration exceeds 1mg / L, the mechanism is configured with a biological filter system, including a multi-layer filter bed and a variable frequency water pump set, wherein the total volume of the filter bed is 15% of the aquaculture water body, the filter bed adopts a three-layer structure design, from top to bottom, it is quartz sand layer, volcanic rock layer and biological filler layer, the particle sizes of the filter materials are 2-3mm, 15-25mm and 35-50mm respectively, the variable frequency water pump set is composed of two 7.5KW water pumps in parallel, the system increases the filtration flow rate from the initial 60m 3 / h to 100m 3 / h through the PLC controller, and starts the backwashing program to clean the filter material at the same time, the backwashing intensity is 12L / m2·s, and the duration is 180 seconds;

[0036] The secondary early warning adjustment mechanism is triggered when the ammonia nitrogen concentration exceeds 2mg / L, the mechanism is configured with a biological agent dosing system, including a 200L mixing tank, a precision metering pump and a distributed dosing device, wherein the mixing tank is made of PP material and is equipped with a stirring device, the rotating speed can be adjusted in the range of 0-120rpm, the maximum flow rate of the metering pump is 5L / h, the precision is ±0.5%, the distributed dosing device is provided with 8 dosing points at different positions of the aquaculture pool, the system adds 5L of biological agent per 100m 3 of water body, and monitors the ammonia nitrogen change trend within 12 hours after each dosing;

[0037] The tertiary early warning adjustment mechanism is triggered when the ammonia nitrogen concentration exceeds 3 mg / L, and the mechanism is configured with an emergency water replacement system, including a water inlet treatment unit, a drainage unit and a water quality adjustment unit, wherein the water inlet treatment unit is equipped with a mechanical filter and an ultraviolet sterilization device, the filtration precision is 20 μm, the ultraviolet dose is ≥30 mJ / cm 3 2, the drainage unit adopts a 200 m 3 0> / h high-flow submersible pump, and the water quality adjustment unit is equipped with a temperature regulator and a pH automatic adjustment device. The system replaces 30% of the water body per hour. The water quality is continuously monitored by an online monitoring instrument during the replacement process to ensure that the replaced water body meets the breeding requirements.

[0038] The ammonia nitrogen monitoring and adjustment system is also provided with a process monitoring and safety protection mechanism, including biological filter backwashing pressure monitoring, biological agent addition amount recording and water quality monitoring during water replacement process. When the filter pressure difference exceeds 0.05 MPa, backwashing is automatically started. The total amount of biological agent added within 24 hours does not exceed the set threshold. If abnormal water quality is found during the water replacement process, the standby water source can be automatically switched. The system uploads the key parameters of the adjustment process to the remote control unit in real time for equipment maintenance and process optimization.

[0039] Preferably, the nitrite monitoring and adjustment system adopts different adjustment mechanisms according to the early warning level, including a primary early warning adjustment mechanism, a secondary early warning adjustment mechanism and a tertiary early warning adjustment mechanism. The primary early warning adjustment mechanism is triggered when the nitrite concentration exceeds 0.5 mg / L. The mechanism is configured with a circulating oxygenation system, including a main circulating pump group and an aeration device. The main circulating pump group is composed of two 11 KW variable frequency water pumps connected in parallel. The maximum flow of a single water pump is 150 m 3 / h, made of 316L stainless steel. The aeration device uses a nano bubble generator with a bubble particle size of 50-100 nm and a gas supply of 120 m 3 / h. The system increases the circulating water volume from the initial 80 m 3 / h to 150 m 3 / h through the PLC controller, and simultaneously starts the nano aeration system to increase the dissolved oxygen content, with the dissolved oxygen level maintained at 6-7 mg / L.

[0040] The secondary early warning adjustment mechanism is triggered when the nitrite concentration exceeds 1 mg / L. The mechanism is configured with a denitrification system, including a denitrification biological filter, a carbon source dosing device and a dissolved oxygen monitoring unit. The denitrification biological filter adopts an upflow structure, and the filler is a polyethylene carrier with a specific surface area of 800 m 2 / m 3, the carbon source adding device is equipped with a 500L storage tank and a high-precision metering pump, the flow of the metering pump is 0-10L / h adjustable, the precision is ±0.1%, the dissolved oxygen monitoring unit adopts a fluorescence dissolved oxygen meter, the measurement range is 0-20mg / L, the system adjusts the carbon source adding amount through an intelligent controller, and the C / N ratio is kept between 4-6;

[0041] The three-stage early warning regulation mechanism triggers when the nitrite concentration exceeds 1.5mg / L, the mechanism is configured with a special degrading bacteria agent adding system, including a bacteria agent culture device, an automatic adding device and a water quality monitoring module, wherein the bacteria agent culture device is composed of a 300L fermentation tank, equipped with a temperature control system and a pH monitoring and adjusting system, the fermentation temperature is controlled at 28±1℃, the automatic adding device uses a peristaltic pump to cooperate with a flowmeter to accurately control the adding amount, the adding precision is ±2%, the water quality monitoring module includes a nitrite online analyzer and an ammonia nitrogen online analyzer, the system processes 100m 3 The water body is treated by adding 10L of active bacteria liquid;

[0042] The nitrite monitoring and adjusting system is also provided with a whole-process monitoring mechanism, including water pump operation state monitoring, denitrification efficiency evaluation and bacteria agent activity detection, wherein the water pump operation parameters are recorded once every 5 minutes, the denitrification efficiency is calculated by the difference between the inlet and outlet water nitrite concentrations, the bacteria agent activity is detected once every 4 hours by an ATP fluorescence detector, and the system uploads various parameters in the adjustment process to a remote control unit, and automatically optimizes the adjustment strategy according to the treatment effect.

[0043] The intelligent water quality monitoring and adjusting device based on the Internet of Things realizes accurate monitoring and intelligent regulation of water quality in aquaculture through the organic combination of a multi-parameter water quality monitoring unit, an intelligent regulation unit and a remote control unit. Based on the new type of composite sensor and the distributed arrangement scheme, the accuracy of the monitoring data is ensured; based on the multi-parameter linkage control algorithm and the independent regulation execution system, the accurate balance of water quality is realized; based on the Internet of Things technology and the deep learning algorithm, the early warning of water quality abnormalities is realized. Through the above-mentioned mode, the intelligent level and management efficiency of aquaculture can be significantly improved, and reliable technical support is provided for the accurate management of aquaculture.

[0044] The intelligent water quality monitoring and adjusting device based on the Internet of Things has the following beneficial effects:

[0045] (1) The present application realizes technical breakthrough and application effect by organically combining new type of composite sensor technology, multi-parameter linkage control algorithm and Internet of Things technology. The new type of composite sensor used in the present application has the characteristics of high measurement accuracy and good stability, and its distributed arrangement scheme and built-in data calibration algorithm can effectively eliminate the influence of environmental interference and sensor drift, significantly improving the reliability of water quality monitoring data.

[0046] (2) The system in the application innovatively adopts a multi-parameter linkage control algorithm, realizes accurate regulation and control of water quality based on in-depth analysis of the complex correlation between water quality parameters, and can control the fluctuation range of key indicators within a smaller range compared with the traditional single-parameter adjustment mode.

[0047] (3) The application integrates a water quality early warning model based on deep learning, and the system can discover potential water quality abnormalities 12-24 hours in advance, leaving sufficient processing time for aquaculture managers and effectively reducing the adverse effects of water quality fluctuations on cultured organisms.

[0048] (4) The modular design concept of the application makes the system have good universality and expandability, which can be widely used in different scenarios such as shrimp and crab factory farming, precious fish farming, etc., and can flexibly adjust monitoring parameters and control strategies according to specific needs. The Internet of Things architecture adopted by the device realizes real-time transmission and remote management of water quality data, significantly improving the efficiency and scientificity of aquaculture management.

[0049] The technical solutions of the application will be further described in detail below with reference to the accompanying drawings and examples. BRIEF DESCRIPTION OF DRAWINGS

[0050] Figure 1 Figure 1 is a schematic diagram of the overall architecture of an embodiment of the intelligent water quality monitoring and regulating device based on the Internet of Things of the application;

[0051] Figure 2 Figure 2 is a schematic diagram of the distributed arrangement of a novel composite sensor of an embodiment of the intelligent water quality monitoring and regulating device based on the Internet of Things of the application;

[0052] Figure 3 Figure 3 is a workflow diagram of a multi-parameter linkage control algorithm of an embodiment of the intelligent water quality monitoring and regulating device based on the Internet of Things of the application;

[0053] Figure 4 Figure 4 is a schematic diagram of the network structure of a water quality early warning model of an embodiment of the intelligent water quality monitoring and regulating device based on the Internet of Things of the application;

[0054] Figure 5 Figure 5 is a schematic diagram of system early warning classification and regulating strategy of an embodiment of the intelligent water quality monitoring and regulating device based on the Internet of Things of the application. DETAILED DESCRIPTION

[0055] The technical solutions of the application will be further described in detail below with reference to the accompanying drawings and examples.

[0056] Unless otherwise defined, the technical terms or scientific terms used in the application should be understood as the usual meaning understood by those skilled in the art.

[0057] Embodiment

[0058] As Figure 1 shown, an intelligent water quality monitoring and adjusting device based on Internet of Things includes a multi-parameter water quality monitoring unit, an intelligent adjusting unit, and a remote control unit. The multi-parameter water quality monitoring unit adopts a new type of composite sensor group, and realizes all-around monitoring of aquaculture water through a distributed arrangement scheme; the intelligent adjusting unit includes an independent adjusting execution system, which can correct abnormal indicators in real time; the remote control unit integrates a water quality early warning model, and realizes early warning of water quality abnormalities.

[0059] Specifically, in the process of aquaculture, the multi-parameter water quality monitoring unit continuously collects water quality data through the composite sensor group distributed at different positions of the culture pond, the data is transmitted to the data processing module for calibration processing through the RS485 bus, the intelligent adjusting unit calculates the optimal adjusting parameters according to the processed data and drives the corresponding execution equipment, and the remote control unit (3) is responsible for the overall scheduling and early warning of the system.

[0060] As Figure 2 shown, the new type of composite sensor group of the multi-parameter water quality monitoring unit is composed of a temperature sensor array, a pH composite electrode, an optical dissolved oxygen sensor, an ion selective electrode, and a spectrum analyzer. Each sensor adopts a "3+1" distributed arrangement scheme, and one group is arranged at the water inlet, the middle, and the water outlet of the culture pond, and a standard sensor group is arranged at the center of the pond for data calibration. The system is equipped with an automatic cleaning device, including a compressed air system and a mechanical cleaning system.

[0061] Specifically, each sensor group sets detection points at 0.5 meters, 1.5 meters, and 2.5 meters below the water surface, and the sampling frequency can be automatically adjusted within the range of 1-10 minutes. The automatic cleaning system automatically adjusts the cleaning period within the range of 2-24 hours according to the water quality, suspends data collection during the cleaning process, and performs data calibration after the cleaning is completed.

[0062] As Figure 3 shown, the intelligent adjusting unit includes a multi-parameter linkage control system and an independent adjusting execution system. The multi-parameter linkage control system adopts a fuzzy neural network structure, and includes a water quality parameter correlation analysis module and a multi-objective optimization control module. The independent adjusting execution system includes a temperature monitoring and adjusting system, a pH monitoring and adjusting system, an oxygenation system, and a water quality purification system, and each system is equipped with an independent PID controller.

[0063] Specifically, the water quality parameter correlation analysis module establishes a parameter correlation matrix through Pearson correlation coefficient calculation, and the multi-objective optimization control module calculates the optimal operating parameters of each regulating device in real time with water quality stability and energy consumption as the optimization objectives. The temperature monitoring and adjusting system realizes accurate adjustment of ±0.5℃ through a frequency conversion water pump, a heat exchanger and a temperature control valve; the pH monitoring and adjusting system realizes accurate adjustment of ±0.1 through a peristaltic pump by using a two-way injection device of alkali and acid; the oxygenation system realizes a dissolved oxygen regulation accuracy of ±0.2mg / L by combining a micro-nano bubble generator and a jet aeration; and the water quality purification system has a purification capacity of more than 100m 3 / h.

[0064] As shown in Figure 4 , the remote control unit adopts an edge computing architecture, including a field control layer, an edge computing layer and a cloud platform layer. The field control layer is responsible for data acquisition and execution control; the edge computing layer contains a water quality early warning model and a device management module; and the cloud platform layer provides data storage and remote access functions. The system uses the MQTT protocol for data transmission to realize real-time communication and control between devices.

[0065] Specifically, the water quality early warning model is based on the LSTM deep learning algorithm and can make 12-24 hour advance prediction on the change of water quality parameters. The device management module is responsible for system operation state monitoring and fault diagnosis. The cloud platform can keep data cache for the latest 7 days and automatically synchronize after network recovery.

[0066] As shown in Figure 5 , the early warning and regulation flowchart of the system shows the three-level early warning mechanism and the corresponding regulation strategy of each water quality parameter. Taking water temperature regulation as an example, when the temperature deviates from the set value by ±1℃, the first level early warning is triggered, and the frequency conversion water pump is started; when it deviates by ±2℃, the second level early warning is triggered, and the temperature control device is started; and when it deviates by ±3℃, the third level early warning is triggered, and the water circulation system and the temperature control system are started.

[0067] Specifically, when any early warning threshold is triggered, the system automatically records the triggering time, parameter value and regulation measure, and sends early warning information to the management personnel through the remote control unit. Each regulation execution system is provided with an independent PID control loop, in which the proportional coefficient Kp ranges from 0.5 to 2.0, the integral time Ti ranges from 60 to 300 seconds, the differential time Td ranges from 0 to 60 seconds, and the control period is 1 minute. When the water quality parameter returns to the normal range, the system automatically records the recovery time and the regulation effect for subsequent optimization of the regulation strategy.

[0068] Through the implementation of the technical scheme of the embodiment, intelligent monitoring and accurate regulation of water quality in aquaculture are realized, and the automation level and work efficiency of breeding management are significantly improved.

[0069] Therefore, the application adopts the above-mentioned intelligent water quality monitoring and adjusting device based on the Internet of Things, which is modularly designed and suitable for various scenes such as shrimp and crab factory farming, precious fish farming, etc., realizes intelligent integration of water quality monitoring, adjusting and early warning, and further realizes all-round intelligent monitoring and accurate adjustment of aquaculture water quality, thereby providing a new technical scheme for accurate management of aquaculture.

[0070] Finally, it should be noted that: the above examples are only used to illustrate the technical solutions of the present application, but not to limit them, although the present application has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that: it can still modify or equivalently replace the technical solutions of the present application, and these modifications or equivalent replacements cannot make the modified technical solutions deviate from the spirit and scope of the technical solutions of the present application.

Claims

1. An intelligent water quality monitoring and regulation device based on the Internet of Things, characterized in that: It includes a multi-parameter water quality monitoring unit, an intelligent adjustment unit, and a remote control unit; the multi-parameter water quality monitoring unit adopts a new type of composite sensor, which is distributed and uses a built-in data calibration algorithm to ensure the accuracy and reliability of the monitoring data; The intelligent regulation unit adopts a multi-parameter linkage control algorithm. Based on the interrelationship between various water quality parameters, it uses an independent regulation execution system to correct detected abnormal indicators in real time, thereby achieving precise balance and dynamic regulation of water quality. The remote control unit is built on IoT technology and integrates a water quality early warning model. Through deep learning analysis of historical data, it establishes a water quality change trend model, predicts water quality anomalies 12-24 hours in advance, and sets multi-level early warning thresholds. When an anomaly is detected, it automatically triggers the adjustment program. The multi-parameter linkage control algorithm adopts a fuzzy neural network structure, including a water quality parameter correlation analysis module and a multi-objective optimization control module; among them, the correlation analysis module is based on... The correlation coefficient is used to calculate the coupling relationship between water quality parameters and establish a parameter correlation matrix including temperature-dissolved oxygen, pH-ammonia nitrogen, and ammonia nitrogen-nitrite. The multi-objective optimization control module adopts an improved particle swarm optimization algorithm, with water quality stability and energy consumption as optimization objectives, and calculates the optimal operating parameters of each regulating device in real time. The intelligent control unit includes an independent control execution system, a real-time correction mechanism, and an energy management system. The independent control execution system comprises a temperature monitoring and control system, a pH monitoring and control system, an oxygenation system, and a water purification system. The temperature monitoring and control system consists of a variable frequency water pump, a heat exchanger, and a temperature control valve, with a control accuracy of [insert accuracy here]. 0.5 The pH monitoring and adjustment system is equipped with a bidirectional injection device for both alkali and acid solutions, and uses a peristaltic pump to precisely control the dosage, with an adjustment accuracy of [insert accuracy here]. 0.1; The oxygenation system uses a micro-nano bubble generator combined with jet aeration, and the dissolved oxygen adjustment accuracy is [insert value here]. 0.2 The water purification system integrates biological filters and microfiltration devices, with a purification capacity of ≥100m³. 3 / h; The real-time correction mechanism is based on the proportional-integral-derivative control algorithm. It sets up an independent control loop for each execution system, with the proportional coefficient ranging from 0.5 to 2.0, the integral time ranging from 60 to 300 seconds, the derivative time ranging from 0 to 60 seconds, and the control cycle being 1 minute. It also automatically adjusts the proportional-integral-derivative control algorithm parameters according to the changing trends of water quality parameters. The energy management system monitors the operating status and energy consumption data of each device in real time, and automatically selects the optimal combination of devices and operating schemes based on water quality regulation needs. It minimizes energy consumption while ensuring stable water quality, and also has equipment fault diagnosis and backup switching functions.

2. The intelligent water quality monitoring and regulation device based on the Internet of Things according to claim 1, characterized in that: The novel composite sensor consists of a temperature sensor array, a pH composite electrode, an optical dissolved oxygen sensor, an ion-selective electrode, and a spectrometer; the temperature sensor array employs a platinum resistance thermometer, achieving a measurement accuracy of [insert accuracy here]. 0.1 The measurement range is 0-50. The pH composite electrode integrates a reference electrode and a working electrode, achieving a measurement accuracy of [missing information]. The optical dissolved oxygen sensor has a measurement accuracy of 0.01, with a measurement range of 0-14. Based on the fluorescence quenching principle, the sensor's measurement accuracy is... 0.1 mg / L, measurement range 0-20 mg / L; ion-selective electrode for ammonia nitrogen detection, measurement accuracy is... The concentration of nitrite is 0.01 mg / L, with a measurement range of 0-10 mg / L. The spectrometer uses visible-near-infrared spectroscopy to measure nitrite, with a measurement accuracy of [missing information]. 0.005 mg / L, measurement range is 0-5 mg / L; The distributed deployment scheme adopts a four-group sensor arrangement structure. A new type of composite sensor is placed at the inlet, middle and outlet of the aquaculture pond, and a detection point is placed at 0.5 meters, 1.5 meters and 2.5 meters below the water surface. At the same time, a standard sensor group for data calibration is added at the center of the aquaculture pond. The sensors transmit data through RS485 bus, and the sampling frequency is automatically adjusted between 1 and 10 minutes. The data calibration algorithm comprises three stages: signal preprocessing, drift correction, and data fusion. Signal preprocessing uses wavelet transform to remove high-frequency noise; drift correction establishes a dynamic compensation model based on measurements from a standard sensor set; and data fusion employs an adaptive noise covariance matrix. The filtering algorithm performs a weighted average of multi-point measurement data. The algorithm dynamically adjusts the weight coefficients based on the measurement accuracy of each sensor and the stability of historical data, and introduces an outlier detection mechanism. When the sensor data deviation is detected to exceed the set threshold, the outlier data points are automatically removed. The multi-parameter water quality monitoring unit also includes an automatic cleaning system, which uses compressed air and mechanical brushes to clean the sensor probes. The cleaning cycle is automatically adjusted from 2 to 24 hours according to the water quality conditions. Data acquisition is automatically paused during the cleaning process, and data calibration is performed after the cleaning is completed to ensure the continuity and reliability of the monitoring data.

3. A smart water quality monitoring and regulation device based on the Internet of Things according to claim 1, characterized in that: The IoT technology architecture adopts an edge computing model, including a field control layer, an edge computing layer, and a cloud platform layer. Data transmission is carried out through the MQTT protocol to realize real-time communication and control between devices. The water quality change trend model uses the LSTM deep learning algorithm to predict changes in water quality parameters by combining historical data, with a prediction time window of 12-24 hours. The remote control unit is equipped with an automatic adjustment mechanism that adopts corresponding adjustment strategies based on abnormal water quality parameters: when the temperature is abnormal, the circulating water volume is adjusted by the variable frequency water pump, while the working status of the chiller or heater is controlled; when the pH value is abnormal, the precision dosing system is activated, and the dosage of acid-base regulators is precisely controlled by multi-point detection combined with flow calculation; when dissolved oxygen is insufficient, the power of the micro-nano aeration system is increased, the backup jet aerator is activated, and the water flow rate is adjusted by the water pump to increase the reoxygenation efficiency; when ammonia nitrogen or nitrite exceeds the standard, the biological filter backwashing program is activated, the circulating water volume is increased, and the water quality is adjusted by the microbial agent dosing system. The remote control unit has data storage and system recovery functions, maintaining a data cache for the most recent 7 days and automatically synchronizing it to the cloud platform after the network is restored.

4. A smart water quality monitoring and regulation device based on the Internet of Things according to claim 1, characterized in that: The device's parameter threshold setting and adjustment trigger mechanism includes: a. For water temperature indicators, set a three-level warning threshold: when the temperature deviates from the set value... 1 When a level one warning is triggered, the variable frequency water pump is started for adjustment; when the deviation is... 2 A level 2 warning is triggered, and the temperature control equipment is activated; when the deviation exceeds ±3... The system triggers a Level 3 warning and simultaneously activates the water circulation system and temperature control system. b. For pH level, set a three-level warning threshold: when the pH value deviates from the set value... A level 1 warning is triggered at 0.3, and the weak-injection pump is activated; when the deviation is... A level 2 warning is triggered at 0.5, increasing the dosage; when it deviates... At 0.8, a Level III early warning was triggered, and the emergency dosing system was activated; c. For dissolved oxygen levels, a three-level warning threshold is set: when dissolved oxygen is below 5 mg / L, a level one warning is triggered, and the aeration intensity is increased; when it is below 4 mg / L, a level two warning is triggered, and the backup oxygenation equipment is activated; when it is below 3 mg / L, a level three warning is triggered, and the entire oxygenation system is activated. d. For ammonia nitrogen levels, a three-level warning threshold is set: when ammonia nitrogen exceeds 1 mg / L, a level one warning is triggered, and the flow rate of the biological filter is increased; when it exceeds 2 mg / L, a level two warning is triggered, and biological agents are added; when it exceeds 3 mg / L, a level three warning is triggered, and the emergency water exchange procedure is initiated. e. For nitrite levels, a three-level warning threshold is set: when nitrite exceeds 0.5 mg / L, a level one warning is triggered, and the circulating water volume is increased; when it exceeds 1 mg / L, a level two warning is triggered, and the denitrification system is started; when it exceeds 1.5 mg / L, a level three warning is triggered, and a special degradation bacteria agent is added. The parameter threshold setting and adjustment triggering mechanism of the device is based on the water temperature monitoring and adjustment system, pH monitoring and adjustment system, ammonia nitrogen monitoring and adjustment system, and nitrite monitoring and adjustment system. When any warning threshold is triggered, the triggering time, parameter value and adjustment measures are automatically recorded, and the warning information is sent to the management personnel through the remote control unit. When the water quality parameters return to the normal range, the system automatically records the recovery time and adjustment effect for subsequent optimization of the adjustment strategy.

5. A smart water quality monitoring and regulation device based on the Internet of Things according to claim 4, characterized in that: The water temperature monitoring and regulation system employs different regulation mechanisms based on the warning level, including a level 1 warning regulation mechanism, a level 2 warning regulation mechanism, and a level 3 warning regulation mechanism. The level 1 warning regulation mechanism is triggered when the water temperature deviates from the set value by ±1℃. This mechanism is equipped with a variable frequency water pump system consisting of a main pump and a standby pump. The pumps are driven by a 380V three-phase asynchronous motor with a rated power of 7.5KW and a maximum flow rate of 120m³ / h. 3 / h, the system uses a Siemens S7-200 series PLC controller to automatically adjust the water pump frequency, changing the pump operating frequency from the initial 30Hz to 2 The adjustment step size is 20-50Hz. After each adjustment, the system automatically waits for 5 minutes to observe the temperature change trend and judges the direction and magnitude of the adjustment based on the trend. The secondary early warning and regulation mechanism detects that the water temperature deviates from the set value. 2 Triggered by time, this mechanism is equipped with a temperature control device consisting of a refrigeration unit and a heater, wherein the refrigeration unit has a cooling capacity of 60,000. A heat exchange area of ​​20m² is adopted. 2 The titanium tube heat exchanger uses R410A as the refrigerant, and the heater employs a 12kW titanium alloy heating tube with a surface temperature controlled at 60°C. 5 When the temperature exceeds the threshold, the system automatically starts the corresponding temperature control equipment according to the direction of temperature deviation. The refrigeration unit runs at 50% load or the heater runs at 8KW power. At the same time, the water temperature change data is recorded every 15 minutes by the temperature sensor and the data is uploaded to the control system for optimization of the adjustment strategy. The three-level early warning and control mechanism detects that the water temperature deviates from the set value. 3 Triggered by time, this mechanism integrates the linkage control of the circulation system and temperature control equipment. The circulation system consists of a DN200 PVC main circulation pipe with a wall thickness of 8mm and a DN100 PVC branch pipe with a wall thickness of 6mm, powered by a 7.5KW variable frequency water pump. The temperature control equipment includes a 60,000 kcal / kg cooling capacity system. The system includes a refrigeration unit and a 12KW heater. When the system enters a level three warning state, the controller automatically adjusts the frequency of the variable frequency water pump to 45Hz to achieve a circulating water volume of 100m³ / h. 3 / h, at the same time, the chiller unit is started to run at 100% load or the heater is run at 12KW full power, and all branch pipeline valves are opened through the electric valve controller to achieve rapid circulation of the water in the whole pool. The system continues to run until the water temperature returns to the set range. The water temperature monitoring and regulation system is also equipped with a complete safety protection mechanism, including forced shutdown protection after the temperature control equipment has been running continuously for 4 hours, and protection in case the water pump motor temperature exceeds 60 degrees Celsius. Automatic frequency reduction protection and system pipeline pressure exceeding 0.5 ______ The system provides automatic pressure relief protection and simultaneously uploads equipment operating status, protection action records, and adjustment effect data to the remote control unit in real time, providing data support for system maintenance, management, and optimization upgrades.

6. A smart water quality monitoring and regulation device based on the Internet of Things according to claim 4, characterized in that: The pH monitoring and adjustment system employs different adjustment mechanisms based on the warning level, including a first-level warning adjustment mechanism, a second-level warning adjustment mechanism, and a third-level warning adjustment mechanism. The first-level warning adjustment mechanism is triggered when the pH value deviates from the set value by ±0.

3. This mechanism is equipped with a magnetically driven diaphragm metering pump as a weak-injection pump. The metering pump uses a polytetrafluoroethylene diaphragm and has a maximum flow rate of 2... The pump head is 50 meters, and the injection accuracy is... The dosage is controlled by a 4-20mA analog signal, and the system automatically selects either an acidic or alkaline adjuster based on pH deviation. The medication is administered via a peristaltic pump at a rate of 0.5%. Add the initial flow rate, and wait 3 minutes after each addition to observe the pH value trend; The secondary early warning and regulation mechanism detects a pH value deviating from the set value. Triggered at 0.5, this mechanism is equipped with a dual-head metering pump system, including a main pump and a standby pump. The metering pump uses a 316L stainless steel pump head and has a maximum flow rate of 5. The injection accuracy is The system increases the dosage from 0.5% to 1.5% via a PLC controller. Simultaneously, the water circulation system is activated to increase the mixing efficiency of the regulator. The circulation system uses a 2.2KW vertical centrifugal pump with a flow rate of 30m³ / h. 3 / h, collect pH value every 5 minutes and automatically adjust the injection volume according to the trend; The three-level early warning and regulation mechanism is triggered when the pH value deviates from the set value by ±0.

8. This mechanism is equipped with an emergency dosing system, including a 200L regulator storage tank, a high-precision metering pump set, and a rapid mixing device. The storage tank is made of PE material and equipped with a level gauge and metering scale. The metering pump set consists of three metering pumps connected in series, with a maximum flow rate of 10 L / min per pump. The PLC controller enables multi-pump coordinated operation. The rapid mixing device uses a 4KW jet pump with four spray points set at different locations in the pool to ensure rapid and uniform mixing of the regulator. The pH monitoring and adjustment system also includes chemical safety protection mechanisms, such as monitoring of the liquid level in the storage tank, pipeline pressure, and reagent concentration. It automatically alarms when the liquid level in the storage tank falls below 20% and when the pipeline pressure exceeds 0.4%. The system features automatic pump stop protection and records pH changes every 30 seconds via an online pH meter. If a single dosing causes a pH change exceeding 0.3, the dosing amount is automatically reduced to ensure the safety and controllability of the adjustment process. The system uploads real-time data of the adjustment process to a remote control unit for optimizing adjustment strategies and predictive maintenance.

7. A smart water quality monitoring and regulation device based on the Internet of Things according to claim 4, characterized in that: The ammonia nitrogen monitoring and control system employs different control mechanisms based on the warning level, including a level-one warning control mechanism, a level-two warning control mechanism, and a level-three warning control mechanism. The level-one warning control mechanism activates when the ammonia nitrogen concentration exceeds 1... Triggered by time, this mechanism is equipped with a biological filter system, including a multi-layer filter bed and a variable frequency pump set. The total volume of the filter bed is 15% of the aquaculture water volume, and it adopts a three-layer structure design, from top to bottom: a quartz sand layer, a volcanic rock layer, and a biological packing layer. The filter media particle sizes are 2-3mm, 15-25mm, and 35-50mm, respectively. The variable frequency pump set consists of two 7.5KW pumps connected in parallel. The system uses a PLC controller to adjust the filtration flow rate from the initial 60m³ / h. 3 / h increased to 100m 3 At the same time, the backwashing program is started to clean the filter media, with a backwashing intensity of 12 L / m. 2 ·s, duration 180 seconds; The secondary early warning and control mechanism will activate when the ammonia nitrogen concentration exceeds 2. Triggered by time, this mechanism is equipped with a biological agent dosing system, including a 200L mixing tank, a precision metering pump, and a distributed dosing device. The mixing tank is made of PP material and equipped with a stirring device with a rotation speed of 0-120. Adjustable within the range, the maximum flow rate of the metering pump is 5. The accuracy is 0.5%, the distributed dosing device sets up 8 dosing points at different locations in the aquaculture pond, the system according to a dosing ratio of 100m. 3 The biological agent was added to the water at a ratio of 5L, and the ammonia nitrogen change trend was monitored for 12 hours after each addition. The three-level early warning and control mechanism will be activated when ammonia nitrogen concentration exceeds 3... Triggered by a time-sensitive mechanism, this system is equipped with an emergency water exchange system, including an inlet water treatment unit, a drainage unit, and a water quality conditioning unit. The inlet water treatment unit is equipped with a mechanical filter and an ultraviolet disinfection device, with a filtration accuracy of 20μm and an ultraviolet dose ≥30. The drainage unit adopts a 200m 3 The system features a high-flow-rate submersible pump and a water quality conditioning unit equipped with a temperature regulator and an automatic pH adjustment device. The system replaces 30% of the water every hour, and continuously monitors the incoming water quality through an online monitoring instrument during the replacement process to ensure that the replaced water meets the requirements for aquaculture. The ammonia nitrogen monitoring and control system is also equipped with process monitoring and safety protection mechanisms, including monitoring of backwash pressure in the biological filter, recording of biological agent dosage, and monitoring of water quality during water exchange. When the filter pressure difference exceeds 0.05... The system automatically starts backwashing when needed, ensures that the total amount of biological agents added within 24 hours does not exceed the set threshold, and automatically switches to a backup water source if abnormal influent water quality is detected during water exchange. The system also uploads key parameters of the adjustment process to the remote control unit in real time for equipment maintenance and process optimization.

8. A smart water quality monitoring and regulation device based on the Internet of Things according to claim 4, characterized in that: The nitrite monitoring and regulation system employs different regulation mechanisms based on the warning level, including a primary warning regulation mechanism, a secondary warning regulation mechanism, and a tertiary warning regulation mechanism. The primary warning regulation mechanism activates when the nitrite concentration exceeds 0.5... Triggered by time, this mechanism is equipped with a circulating oxygenation system, including a main circulating pump set and an aeration device. The main circulating pump set consists of two 11KW variable frequency water pumps connected in parallel, with a maximum flow rate of 150m³ / h for each pump. 3 / h, made of 316L stainless steel, the aeration device uses a nano bubble generator with a bubble particle size of 50-100nm, and an air supply of 120m³ / h. 3 / h, the system uses a PLC controller to adjust the circulating water volume from the initial 80m³ / h. 3 / h increased to 150m 3 / h, while simultaneously activating the nano-aeration system to increase dissolved oxygen levels, maintaining a dissolved oxygen level of 6-7. ; The secondary early warning and regulation mechanism detects nitrite concentrations exceeding 1 Triggered by time, this mechanism is equipped with a denitrification system, including a denitrifying biological filter, a carbon source dosing device, and a dissolved oxygen monitoring unit. The denitrifying biological filter adopts an upflow structure, with polyethylene carrier as the packing material and a specific surface area of ​​800 m². 2 / m 3 The design hydraulic retention time is 40 minutes. The carbon source dosing device is equipped with a 500L storage tank and a high-precision metering pump with a flow rate of 0-10 L / L. Adjustable, with a precision of The dissolved oxygen monitoring unit uses a fluorescence-based dissolved oxygen meter with a measurement range of 0-20%. The dissolved oxygen level is 0.1%. The system uses an intelligent controller to adjust the amount of carbon source added, maintaining a C / N ratio of 4-6. The three-tiered early warning and control mechanism responds when nitrite concentration exceeds 1.5%. Triggered by time, this mechanism is equipped with a dedicated degradation agent dosing system, including an agent cultivation device, an automatic dosing device, and a water quality monitoring module. The agent cultivation device consists of a 300L fermenter, equipped with a temperature control system and a pH monitoring and adjustment system, with the fermentation temperature controlled at 28°C. 1 The automatic dosing device uses a peristaltic pump in conjunction with a flow meter to precisely control the dosing amount, with a dosing accuracy of [missing information]. 2%, the water quality monitoring module includes an online nitrite analyzer and an online ammonia nitrogen analyzer, the system is configured for every 100m³ 3 The water body was treated by adding 10L of active bacterial solution. The nitrite monitoring and regulation system is also equipped with a full-process monitoring mechanism, including monitoring of water pump operation status, evaluation of denitrification efficiency, and detection of bacterial activity. The water pump operation parameters are recorded every 5 minutes, the denitrification efficiency is calculated by the difference in nitrite concentration between the influent and effluent, and the bacterial activity is detected every 4 hours by an ATP fluorescence detector. The system uploads all parameters of the regulation process to the remote control unit and automatically optimizes the regulation strategy based on the treatment effect.

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