Intelligent water quality monitoring and adjusting device based on Internet of Things

Abstract

The invention belongs to the technical field of aquaculture intelligent monitoring, and particularly discloses an intelligent water quality monitoring and adjusting device based on Internet of Things, which comprises a multi-parameter water quality monitoring unit, an intelligent adjusting unit and a remote control unit. According to the intelligent water quality monitoring and adjusting device based on the Internet of Things, modular design is adopted, the device is suitable for various scenes such as shrimp and crab industrial aquaculture and rare fish aquaculture, intelligent integration of water quality monitoring, adjusting and early warning is achieved, all-dimensional intelligent monitoring and accurate adjusting of aquaculture water quality are achieved, and the water quality monitoring and adjusting device is suitable for popularization and application. And a new technical scheme is provided for accurate management of aquaculture.

Description

Technical Field

[0001] The present invention belongs to the technical field of intelligent monitoring of aquaculture, and in particular relates to an intelligent water quality monitoring and regulating device based on the Internet of Things. Background Art

[0002] With the expansion and intensive development of aquaculture, water quality monitoring and regulation have become critical for ensuring profitability. Existing water quality monitoring technologies primarily rely on manual monitoring based on the experience of aquaculture personnel. This traditional approach is not only subjective and lacks standardization, but also, due to limited human resources, it is difficult to implement 24-hour continuous monitoring, which can easily lead to missed opportunities for optimal adjustments. Currently available automatic monitoring equipment suffers from general shortcomings in monitoring accuracy, particularly in complex water quality environments, where data reliability is poor. Most of these devices monitor a single parameter and lack the ability to analyze and adjust multiple parameters in a coordinated manner. Unable to predict water quality trends, these devices often detect and address problems only after they occur. Their simple adjustment methods also fail to achieve precise water quality balance. Regarding the application of IoT technology, existing systems still need to improve the reliability of data collection and transmission. Furthermore, they lack intelligent data analysis and early warning mechanisms, and their limited remote control capabilities fail to meet the demands of complex operating conditions. These technical bottlenecks severely hinder the development of intelligent aquaculture.

[0003] Therefore, there is a need in the art to develop an intelligent water quality monitoring and regulation device based on the Internet of Things that can effectively solve the above problems. Summary of the Invention

[0004] The purpose of the present invention is to provide an intelligent water quality monitoring and regulation device based on the Internet of Things. The device adopts a modular design and is suitable for various scenarios such as factory farming of shrimp and crabs and farming of precious fish. It realizes the intelligent integration of water quality monitoring, regulation, and early warning, thereby realizing all-round intelligent monitoring and precise regulation of aquaculture water quality, providing a new technical solution for the precise management of aquaculture.

[0005] To achieve the above objectives, the present invention provides an intelligent water quality monitoring and regulation device based on the Internet of Things, comprising a multi-parameter water quality monitoring unit, an intelligent regulation unit, and a remote control unit. The multi-parameter water quality monitoring unit uses a new composite sensor that can monitor more than 10 indicators of aquaculture water in real time, including temperature, pH value, dissolved oxygen, ammonia nitrogen, and nitrite, 24 hours a day. The new composite sensor adopts a distributed layout scheme and uses a built-in data calibration algorithm to ensure the accuracy and reliability of the monitoring data.

[0006] The intelligent regulation unit adopts a multi-parameter linkage control algorithm. Based on the relationship between various water quality parameters, it configures an independent regulation execution system to make real-time corrections to detected abnormal indicators, thus achieving precise balance and dynamic regulation of water quality.

[0007] The remote control unit is built based on Internet of Things 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 to automatically trigger the adjustment program when an anomaly is detected.

[0008] The device adopts a modular design and is suitable for various scenarios such as factory farming of shrimp and crabs and farming of rare fish. It has the functions of collecting, storing, analyzing, warning and adjusting water quality data, and can realize remote monitoring and intelligent management through the Internet of Things platform, thereby realizing all-round monitoring and adjustment of aquaculture water quality.

[0009] Preferably, the novel composite sensor is composed of a temperature sensor array, a pH composite electrode, an optical dissolved oxygen sensor, an ion selective electrode, and a spectrum analyzer; wherein the temperature sensor array uses a platinum resistance temperature measuring element with a measurement accuracy of ±0.1°C and a measurement range of 0-50°C; 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 principle of fluorescence quenching, 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 spectrum analyzer uses visible light-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 layout scheme adopts a "3+1" four-group sensor layout structure. A new set of composite sensors is placed at the water inlet, middle, and outlet of the aquaculture pond. A detection point is set at 0.5 meters, 1.5 meters, and 2.5 meters below the water surface. At the same time, a standard sensor group is added in the center of the aquaculture pond for data calibration. Data is transmitted between sensors via the RS485 bus, and the sampling frequency is automatically adjusted between 1 and 10 minutes.

[0011] The data calibration algorithm includes three steps: signal preprocessing, drift correction, and data fusion, to ensure the accuracy and reliability of monitoring data. Signal preprocessing uses wavelet transform to remove high-frequency noise. Drift correction establishes a dynamic compensation model based on the measurement values ​​of a standard sensor group. Data fusion uses a Kalman filter algorithm based on an adaptive noise covariance matrix to perform weighted averaging on multi-point measurement data. This algorithm dynamically adjusts the weight coefficient based on the measurement accuracy of each sensor and the stability of historical data. It also introduces an outlier detection mechanism to automatically remove abnormal data points when it detects that the sensor data deviation exceeds a set threshold.

[0012] The multi-parameter water quality monitoring unit also includes an automatic cleaning system, which uses compressed air and a mechanical brush to clean the sensor probe. The cleaning cycle is automatically adjusted within the range of 2-24 hours according to the water quality conditions. Data collection is automatically suspended during the cleaning process. Data calibration is performed after cleaning is completed 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 water quality parameters based on the Pearson correlation coefficient and establishes 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 algorithm, with water quality stability and energy consumption as optimization goals, to calculate the optimal operating parameters of each regulating equipment in real time;

[0014] The intelligent regulation unit includes an independent regulation execution system, a real-time correction mechanism, and an energy management system; the independent regulation execution system includes a temperature monitoring and regulation system, a pH monitoring and regulation system, an oxygenation system, and a water purification system. The temperature monitoring and regulation system consists of a variable frequency water pump, a heat exchanger, and a temperature control valve, with an adjustment accuracy of ±0.5°C; the pH monitoring and regulation system is equipped with a two-way injection device for alkali and acid, and the dosage is precisely controlled by a peristaltic pump with an adjustment accuracy of ±0.1; the oxygenation system uses a micro-nano bubble generator combined with jet aeration, with a dissolved oxygen adjustment accuracy of ±0.2mg / L; the water purification system integrates a biological filter and a microfiltration device, with a purification capacity of not less than 100m 3 / h;

[0015] The real-time correction mechanism is based on the proportional-integral-derivative (PID) control algorithm. An independent control loop is set for each execution system, with a proportional coefficient (Kp) range of 0.5-2.0, an integral time (Ti) range of 60-300 seconds, a derivative time (Td) range of 0-60 seconds, and a control cycle of 1 minute. The proportional-integral-derivative control algorithm parameters are automatically adjusted according to the changing trends of water quality parameters.

[0016] The energy management system monitors the operating status and energy consumption data of each executive device in real time, and automatically selects the optimal equipment combination and operation plan based on water quality regulation requirements, thereby minimizing energy consumption while ensuring stable water quality. It also has equipment fault diagnosis and backup switching functions to ensure the reliability of the regulation system.

[0017] Preferably, the IoT technology architecture adopts an edge computing model, including a field control layer, an edge computing layer, and a cloud platform layer. Data is transmitted through the MQTT protocol to achieve real-time communication and control between devices. The water quality change trend model uses the LSTM deep learning algorithm and combines historical data to predict changes in water quality parameters. The prediction time window is 12-24 hours, which can provide early warning of water quality anomalies.

[0018] The remote control unit is equipped with an automatic adjustment mechanism, which adopts corresponding adjustment strategies according to abnormal conditions of different water quality parameters: when the temperature is abnormal, the frequency conversion water pump adjusts the circulating water volume and controls the working status of the refrigeration unit or heater at the same time; when the pH value is abnormal, the precision dosing system is activated, and the dosage of acid-base regulator is accurately controlled through multi-point detection combined with flow calculation; when the dissolved oxygen is insufficient, the power of the micro-nano aeration system is first increased, and the backup jet aerator is activated if necessary, and the water flow rate is adjusted by the water pump to increase the reoxygenation efficiency; when the ammonia nitrogen or nitrite exceeds the standard, the biological filter backwash program is activated, the circulating water volume is increased, and the water quality is adjusted through the microbial agent dosing system.

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

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

[0021] a. For the water temperature indicator, three levels of warning thresholds are set: when the temperature deviates from the set value by ±1°C, a level one warning is triggered, and the variable frequency water pump adjustment is started; when it deviates by ±2°C, a level two warning is triggered, and the temperature control equipment is started; when it deviates by ±3°C, a level three warning is triggered, and the water circulation system and temperature control system are started at the same time;

[0022] b. For the pH value indicator, set three levels of warning thresholds: when the pH value deviates from the set value by ±0.3, it triggers the first level warning and starts the weak injection pump; when it deviates by ±0.5, it triggers the second level warning and increases the injection volume; when it deviates by ±0.8, it triggers the third level warning and starts the emergency dosing system;

[0023] c. For the dissolved oxygen index, three levels of warning thresholds are set: when the dissolved oxygen level is lower than 5mg / L, a level one warning is triggered, increasing the aeration intensity; when it is lower than 4mg / L, a level two warning is triggered, activating the backup aeration equipment; when it is lower than 3mg / L, a level three warning is triggered, activating all aeration systems;

[0024] d. For the ammonia nitrogen index, three levels of warning thresholds are set: when the ammonia nitrogen exceeds 1 mg / L, a level one warning is triggered, and the flow rate of the biofilter 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;

[0025] e. For the nitrite indicator, three levels of warning thresholds are set: when nitrite exceeds 0.5mg / L, a level one warning is triggered, increasing the circulating water volume; when it exceeds 1mg / L, a level two warning is triggered, starting the denitrification system; when it exceeds 1.5mg / L, a level three warning is triggered, adding a special degradation agent;

[0026] The parameter threshold setting and adjustment trigger 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 trigger time, parameter value and adjustment measures are automatically recorded, and an early 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.

[0027] Preferably, the water temperature monitoring and regulation system adopts different regulation mechanisms according to the warning level, including the first-level warning regulation mechanism, the second-level warning regulation mechanism and the third-level warning regulation mechanism; among them, the first-level warning regulation mechanism is triggered when the water temperature deviates from the set value by ±1°C. The mechanism is equipped 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 uses the Siemens S7-200 series PLC controller to automatically adjust the pump frequency, gradually adjusting the pump operating frequency from the initial 30Hz to 20-50Hz in an adjustment step of 2Hz / min. After each adjustment, the system automatically waits for 5 minutes to observe the temperature change trend and determines the direction and amplitude of further adjustment based on the trend;

[0028] The secondary warning adjustment mechanism is triggered when the water temperature deviates from the set value by ±2℃. The mechanism is equipped with a temperature control device consisting of a refrigeration unit and a heater. The refrigeration unit has a cooling capacity of 60,000 kcal / h and a heat exchange area of ​​20m 2 The titanium tube heat exchanger uses R410A as the refrigerant. The heater uses a 12kW titanium alloy heating tube and the surface temperature is controlled within the range of 60±5°C. When the temperature exceeds the threshold, the system automatically activates the corresponding temperature control device based on the temperature deviation direction. The refrigeration 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 optimization of the adjustment strategy.

[0029] The three-level early warning adjustment mechanism is triggered when it detects that the water temperature deviates from the set value by ±3°C. 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. It is powered by a 7.5kW variable frequency water pump. The temperature control equipment includes a refrigeration unit with a cooling capacity of 60,000kcal / h and a heater with a power of 12kW. When the system enters the three-level early warning state, the controller automatically adjusts the frequency of the variable frequency water pump to 45Hz to achieve a circulating water volume of 100m3. 3 / h, and simultaneously start the refrigeration unit to run at 100% load or the heater to run at full power of 12KW, and open all branch pipe valves through the electric valve controller to achieve rapid circulation of the entire pool water. The system continues to operate until the water temperature returns to the set range;

[0030] 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, automatic frequency reduction protection when the water pump motor temperature exceeds 60°C, and automatic pressure relief protection when the system pipeline pressure exceeds 0.5MPa. At the same time, the system uploads the equipment operating status, protection action records and regulation effect data to the remote control unit in real time, providing data support for system maintenance management and optimization upgrades.

[0031] Preferably, the pH monitoring and adjustment system adopts different adjustment mechanisms according to the warning level, including a first-level warning adjustment mechanism, a second-level warning adjustment mechanism and a third-level warning adjustment mechanism; wherein, the first-level warning adjustment mechanism is triggered when the pH value deviates from the set value by ±0.3. The mechanism is equipped with a magnetically driven diaphragm metering pump as a weak injection pump. The metering pump adopts a polytetrafluoroethylene diaphragm, has a maximum flow rate of 2L / h, a head of 50 meters, and an injection accuracy of ±1%. The injection amount is controlled by a 4-20mA analog signal. The system automatically selects an acidic or alkaline regulator according to the direction of pH deviation, and adds it through a peristaltic pump at an initial flow rate of 0.5L / h. After each addition, wait for 3 minutes to observe the pH value change trend;

[0032] The secondary warning adjustment mechanism is triggered when it detects that the pH value deviates from the set value by ±0.5. The mechanism is equipped with a dual-head metering pump system, including a main pump and a backup pump. The metering pump uses a 316L stainless steel pump head with a maximum flow rate of 5L / h and an injection accuracy of ±0.5%. The system increases the injection rate to 1.5L / h through the PLC controller and simultaneously starts the water circulation system to increase the mixing efficiency of the regulator. The circulation system uses a 2.2KW vertical centrifugal pump with a flow rate of 30m 3 / h, collect pH value every 5 minutes and automatically adjust the injection amount according to the change trend;

[0033] The three-level early warning adjustment 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 group, and a rapid mixing device. The storage tank is made of PE material and equipped with a liquid level gauge and metering scale. The metering pump group consists of three metering pumps connected in series, with a maximum flow rate of 10L / h per unit. The multi-pump coordinated operation is achieved through a PLC controller. The rapid mixing device uses a 4kW jet pump with four injection points set at different locations on the tank body to ensure rapid and uniform mixing of the regulator.

[0034] The pH monitoring and adjustment system is also equipped with a chemical safety protection mechanism, including liquid level monitoring of the reagent storage tank, pipeline pressure monitoring and reagent concentration monitoring. When the liquid level of the storage tank is lower than 20%, it will automatically alarm, and when the pipeline pressure exceeds 0.4MPa, the pump will automatically stop for protection. At the same time, the system records the pH value change every 30 seconds through the online pH meter. When the pH value changes by more than 0.3 due to a single drug addition, the injection volume will be automatically reduced to ensure the safety and controllability of the adjustment process. The system will upload real-time data of the adjustment process to the remote control unit for optimizing the adjustment strategy and predictive maintenance.

[0035] Preferably, the ammonia nitrogen monitoring and regulation system adopts different regulation mechanisms according to the warning level, including a first-level warning regulation mechanism, a second-level warning regulation mechanism and a third-level warning regulation mechanism; wherein, the first-level warning regulation mechanism is triggered when the ammonia nitrogen concentration is detected to be greater than 1 mg / L. The mechanism is configured with a biological filter system, including a multi-layer filter bed and a variable frequency water pump group, wherein the total volume of the filter bed is 15% of the aquaculture water body, and a three-layer structure design is adopted, which is a quartz sand layer, a volcanic rock layer and a biological filler layer from top to bottom, and the filter material particle sizes are 2-3mm, 15-25mm and 35-50mm respectively. The variable frequency water pump group is composed of two 7.5KW water pumps in parallel. The system adjusts the filtration flow rate from the initial 60m3 / L to the maximum through the PLC controller. 3 / h increased to 100m 3 / h, and simultaneously start the backwash program to clean the filter media, with a backwash intensity of 12L / m2·s and a duration of 180 seconds;

[0036] The secondary early warning adjustment mechanism is triggered when the ammonia nitrogen concentration exceeds 2mg / L. The 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. The speed can be adjusted within the range of 0-120rpm. The maximum flow rate of the metering pump is 5L / h with an accuracy of ±0.5%. The distributed dosing device is equipped with 8 dosing points at different locations in the breeding pond. The system is based on a 100m 3 The biological agent was added to the water body at a ratio of 5L, and the trend of ammonia nitrogen changes within 12 hours after each addition was monitored;

[0037] The three-level early warning adjustment mechanism is triggered when the ammonia nitrogen concentration is detected to be over 3mg / L. The mechanism is equipped with an emergency water exchange system, including a water treatment unit, a drainage unit and a water quality adjustment unit. The water treatment unit is equipped with a mechanical filter and an ultraviolet disinfection device with a filtration accuracy of 20μm and an ultraviolet dose of ≥30mJ / cm2. The drainage unit adopts a 200m 3 / h high-flow submersible pump, the water quality adjustment unit is equipped with a temperature regulator and an automatic pH adjustment device. The system changes water at a rate of 30% per hour. During the replacement process, the inlet water quality is continuously monitored by an online monitor to ensure that the replaced water meets the aquaculture requirements;

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

[0039] Preferably, the nitrite monitoring and regulation system adopts different regulation mechanisms according to the warning level, including the first-level warning regulation mechanism, the second-level warning regulation mechanism and the third-level warning regulation mechanism; wherein, the first-level warning regulation mechanism is triggered when the nitrite concentration exceeds 0.5 mg / L. The mechanism is equipped with a circulating oxygenation system, including a main circulation pump group and an aeration device, wherein the main circulation pump group is composed of two 11KW variable frequency water pumps in parallel, and the maximum flow of a single water pump is 150m 3 / h, made of 316L stainless steel, the aeration device uses a nano bubble generator, the bubble particle size is 50-100nm, and the air supply volume is 120m 3 / h, the system changes the circulating water volume from the initial 80m 3 / h increased to 150m 3 / h, and at the same time, the nano aeration system is turned on to increase the dissolved oxygen content, and the dissolved oxygen level is maintained at 6-7mg / L;

[0040] The secondary warning regulation mechanism is triggered when the nitrite concentration exceeds 1 mg / L. The mechanism is equipped 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 ​​800m 2 / m 3The designed hydraulic retention time is 40 minutes. The carbon source dosing device is equipped with a 500L storage tank and a high-precision metering pump. The metering pump flow rate is adjustable from 0 to 10L / h with an accuracy of ±0.1%. The dissolved oxygen monitoring unit uses a fluorescence dissolved oxygen meter with a measurement range of 0-20mg / L. The system adjusts the carbon source dosage through an intelligent controller to maintain a C / N ratio between 4 and 6.

[0041] The three-level early warning adjustment mechanism is triggered when the nitrite concentration exceeds 1.5mg / L. The mechanism is equipped with a special degradation bacterial agent dosing system, including a bacterial agent cultivation device, an automatic dosing device and a water quality monitoring module. The bacterial agent cultivation device consists of a 300L fermentation tank, equipped with a temperature control system and a pH monitoring and adjustment system. The fermentation temperature is controlled at 28±1℃. The automatic dosing device uses a peristaltic pump with a flow meter to accurately control the dosage, with a dosing accuracy of ±2%. The water quality monitoring module includes a nitrite online analyzer and an ammonia nitrogen online analyzer. The system is based on every 100m 3 The water body is treated by adding 10L of active bacterial solution;

[0042] The nitrite monitoring and regulation system is also equipped with a full-process monitoring mechanism, including water pump operation status monitoring, denitrification efficiency evaluation and bacterial agent activity detection. The water pump operation parameters are recorded every 5 minutes, the denitrification efficiency is calculated by the difference in nitrite concentration between the inlet and outlet water, and the bacterial agent activity is detected every 4 hours using an ATP fluorescence detector. The system uploads various parameters of the regulation process to the remote control unit and automatically optimizes the regulation strategy based on the treatment effect.

[0043] The IoT-based intelligent water quality monitoring and regulation device achieves precise monitoring and intelligent regulation of aquaculture water quality through the organic combination of a multi-parameter water quality monitoring unit, an intelligent regulation unit, and a remote control unit. A novel composite sensor and distributed layout ensure the accuracy of monitoring data; a multi-parameter linkage control algorithm and an independent regulation execution system achieve precise water quality balance; and IoT technology and deep learning algorithms provide early warning of water quality anomalies. This approach significantly improves the intelligence level and management efficiency of aquaculture, providing reliable technical support for precise aquaculture management.

[0044] The present invention adopts the above-mentioned intelligent water quality monitoring and regulation device based on the Internet of Things, and the beneficial effects are as follows:

[0045] (1) This invention achieves technological breakthroughs and application benefits by organically combining novel composite sensor technology, a multi-parameter linkage control algorithm, and Internet of Things technology. The novel composite sensor employed in this invention features high measurement accuracy and excellent stability. Its distributed layout and built-in data calibration algorithm effectively eliminate the effects of environmental interference and sensor drift, significantly improving the reliability of water quality monitoring data.

[0046] (2) The system in the present invention innovatively adopts a multi-parameter linkage control algorithm. Based on an in-depth analysis of the complex correlation between water quality parameters, it achieves precise regulation of water quality. Compared with the traditional single-parameter adjustment method, the fluctuation range of key indicators can be controlled within a smaller range.

[0047] (3) By integrating a water quality early warning model based on deep learning, the present invention can detect potential water quality anomalies 12-24 hours in advance, reserving sufficient processing time for aquaculture managers and effectively reducing the adverse effects of water quality fluctuations on aquaculture organisms.

[0048] (4) The modular design concept of the present invention makes the system versatile and scalable. It can be widely applied to various scenarios such as shrimp and crab factory farming and rare fish farming, and can flexibly adjust monitoring parameters and control strategies according to specific needs. The Internet of Things architecture adopted by the device enables real-time transmission and remote management of water quality data, significantly improving the efficiency and scientific nature of aquaculture management.

[0049] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

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

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

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

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

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

[0055] The technical solution of the present invention is further described below with reference to the accompanying drawings and embodiments.

[0056] Unless otherwise defined, technical or scientific terms used in the present invention shall have the same meaning as commonly understood by one of ordinary skill in the art to which the present invention belongs.

[0057] Example

[0058] like Figure 1 Figure 1 shows an IoT-based intelligent water quality monitoring and regulation device, comprising a multi-parameter water quality monitoring unit, an intelligent regulation unit, and a remote control unit. The multi-parameter water quality monitoring unit utilizes a novel composite sensor array, enabling comprehensive monitoring of aquaculture water bodies through a distributed layout. The intelligent regulation unit includes an independent regulation execution system that enables real-time correction of abnormal indicators. The remote control unit integrates a water quality early warning model to provide early warning of water quality anomalies.

[0059] The specific method is as follows: during the aquaculture process, the multi-parameter water quality monitoring unit continuously collects water quality data through a composite sensor group distributed at different locations in the aquaculture pond. The data is transmitted to the data processing module via the RS485 bus for calibration processing. The intelligent adjustment unit calculates the optimal adjustment parameters based on the processed data and drives the corresponding execution equipment. The remote control unit (3) is responsible for the overall scheduling and early warning of the system.

[0060] like Figure 2 As shown, the multi-parameter water quality monitoring unit's new composite sensor assembly consists of a temperature sensor array, a pH composite electrode, an optical dissolved oxygen sensor, an ion-selective electrode, and a spectrum analyzer. The sensors are deployed in a "3+1" distributed configuration, with one group each located at the inlet, center, and outlet of the aquaculture pond. A standard sensor group is located in the center of the pond for data calibration. The system is equipped with automatic cleaning devices, including a compressed air system and a mechanical cleaning system.

[0061] Specifically, each sensor group has detection points at 0.5 meters, 1.5 meters, and 2.5 meters below the water surface. The sampling frequency is automatically adjusted within a range of 1 to 10 minutes. The automatic cleaning system automatically adjusts the cleaning cycle within a range of 2 to 24 hours based on water quality. Data collection is suspended during the cleaning process and data calibration is performed after the cleaning is completed.

[0062] like Figure 3 As shown in the figure, the intelligent regulation unit consists of a multi-parameter linkage control system and an independent regulation 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 regulation execution system includes a temperature monitoring and regulation system, a pH monitoring and regulation system, an oxygenation system, and a water purification system, each equipped with an independent PID controller.

[0063] The specific method is as follows: the water quality parameter correlation analysis module establishes a parameter correlation matrix through Pearson correlation coefficient calculation, and the multi-objective optimization control module uses water quality stability and energy consumption as optimization targets to calculate the optimal operating parameters of each regulating equipment in real time. The temperature monitoring and regulation system uses a variable frequency water pump, heat exchanger and temperature control valve to achieve precise regulation of ±0.5℃; the pH monitoring and regulation system uses a bidirectional injection device for alkali and acid solutions, and achieves precise regulation of ±0.1 through a peristaltic pump; the oxygenation system combines a micro-nano bubble generator and jet aeration to achieve a dissolved oxygen regulation accuracy of ±0.2mg / L; the water purification system has a purification capacity of 100m 3 / h or more.

[0064] like Figure 4 As shown in the figure, the remote control unit utilizes an edge computing architecture, consisting of 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 includes a water quality early warning model and device management module; and the cloud platform layer provides data storage and remote access. The system uses the MQTT protocol for data transmission, enabling real-time communication and control between devices.

[0065] Specifically, the water quality early warning model, based on the LSTM deep learning algorithm, provides 12-24 hour advance predictions of water quality parameter changes. The device management module monitors system operating status and conducts fault diagnosis. The cloud platform caches the last seven days of data and automatically synchronizes it upon network recovery.

[0066] like Figure 5 The system's early warning and adjustment flow chart, shown in Figure 2, illustrates the three-level early warning mechanism and corresponding adjustment strategies for each water quality parameter. Taking water temperature adjustment as an example, a temperature deviation of ±1°C from the set point triggers a level one warning, activating the variable frequency water pump. A deviation of ±2°C triggers a level two warning, activating the temperature control equipment. A deviation of ±3°C triggers a level three warning, activating both the water circulation system and the temperature control system.

[0067] Specifically, when any warning threshold is triggered, the system automatically records the trigger time, parameter values, and adjustment measures, and sends an alert to management via a remote control unit. Each adjustment execution system is equipped with an independent PID control loop, with a proportional coefficient Kp range of 0.5-2.0, an integral time Ti range of 60-300 seconds, a differential time Td range of 0-60 seconds, and a control cycle of 1 minute. When water quality parameters return to normal range, the system automatically records the recovery time and adjustment results for subsequent optimization of the adjustment strategy.

[0068] Through the implementation of the technical solution of this embodiment, intelligent monitoring and precise regulation of aquaculture water quality are achieved, which significantly improves the automation level and work efficiency of aquaculture management.

[0069] Therefore, the present invention adopts the above-mentioned intelligent water quality monitoring and regulation device based on the Internet of Things. The device adopts a modular design and is suitable for various scenarios such as factory farming of shrimps and crabs, farming of precious fish, etc. It realizes the intelligent integration of water quality monitoring, regulation, and early warning, and thus realizes all-round intelligent monitoring and precise regulation of aquaculture water quality, providing a new technical solution for the precise management of aquaculture.

[0070] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit the same. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that they can still modify or replace the technical solutions of the present invention with equivalents, and these modifications or equivalent replacements cannot cause the modified technical solutions to deviate from the spirit and scope of the technical solutions of the present invention.

Claims

1. An intelligent water quality monitoring and regulation device based on the Internet of Things, characterized by: 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 uses a new composite sensor with a distributed layout. The built-in data calibration algorithm ensures the accuracy and reliability of the monitoring data. The intelligent regulation unit adopts a multi-parameter linkage control algorithm. Based on the relationship between various water quality parameters, it configures an independent regulation execution system to make real-time corrections to detected abnormal indicators, thus achieving precise balance and dynamic regulation of water quality. The remote control unit is built based on Internet of Things 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 to automatically trigger the adjustment program when an anomaly is detected.

2. An intelligent water quality monitoring and regulation device based on the Internet of Things according to claim 1, characterized in that: The new composite sensor consists of a temperature sensor array, a pH composite electrode, an optical dissolved oxygen sensor, an ion-selective electrode, and a spectrum analyzer. The temperature sensor array uses a platinum resistance temperature measuring element with a measurement accuracy of ±0.1°C and a measurement range of 0-50°C. 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 principle of fluorescence quenching, 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 spectrum analyzer uses visible-near-infrared spectroscopy to measure nitrite with a measurement accuracy of ±0.005mg / L and a measurement range of 0-5mg / L. The distributed layout scheme uses a four-group sensor layout structure. A new type of composite sensor is placed at the water inlet, middle, and outlet of the aquaculture pond. A detection point is set at 0.5 meters, 1.5 meters, and 2.5 meters below the water surface. At the same time, a standard sensor group is added in the center of the aquaculture pond for data calibration. Data is transmitted between sensors via the RS485 bus, and the sampling frequency is automatically adjusted between 1 and 10 minutes. The data calibration algorithm includes three steps: 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 the measurements of a standard sensor group. Data fusion uses a Kalman filter algorithm based on an adaptive noise covariance matrix to perform weighted averaging on multi-point measurement data. This algorithm dynamically adjusts the weight coefficient based on the measurement accuracy of each sensor and the stability of historical data. It also introduces an outlier detection mechanism to automatically remove abnormal data points when sensor data deviation exceeds a set threshold. The multi-parameter water quality monitoring unit also includes an automatic cleaning system, which uses compressed air and a mechanical brush to clean the sensor probe. The cleaning cycle is automatically adjusted within 2-24 hours according to the water quality conditions. Data collection is automatically suspended during the cleaning process. Data calibration is performed after cleaning is completed to ensure the continuity and reliability of the monitoring data.

3. An intelligent water quality monitoring and regulation device based on the Internet of Things according to claim 1, characterized in that: The multi-parameter linkage control algorithm adopts a fuzzy neural network structure and includes a water quality parameter correlation analysis module and a multi-objective optimization control module. The correlation analysis module calculates the coupling relationship between water quality parameters based on the Pearson correlation coefficient and establishes a parameter correlation matrix including temperature-dissolved oxygen, pH-ammonia nitrogen, and ammonia nitrogen-nitrite. The multi-objective optimization control module uses an improved particle swarm algorithm, with water quality stability and energy consumption as the optimization goals, to calculate the optimal operating parameters of each regulating device in real time. The intelligent regulation unit includes an independent regulation execution system, a real-time correction mechanism, and an energy management system; the independent regulation execution system includes a temperature monitoring and regulation system, a pH monitoring and regulation system, an oxygenation system, and a water purification system. The temperature monitoring and regulation system consists of a variable frequency water pump, a heat exchanger, and a temperature control valve, with an adjustment accuracy of ±0.5°C; the pH monitoring and regulation system is equipped with a two-way injection device for alkali and acid, and the dosage is precisely controlled by a peristaltic pump with an adjustment accuracy of ±0.1; the oxygenation system uses a micro-nano bubble generator combined with jet aeration, with a dissolved oxygen adjustment accuracy of ±0.2mg / L; the water purification system integrates a biological filter and a microfiltration device, with a purification capacity of ≥100m 3 / h; The real-time correction mechanism is based on the proportional-integral-differential control algorithm, with an independent control loop set for each execution system. The proportional coefficient range is 0.5-2.0, the integral time range is 60-300 seconds, the differential time range is 0-60 seconds, and the control cycle is 1 minute. The proportional-integral-differential control algorithm parameters are automatically adjusted according to the changing trends of water quality parameters. The energy management system monitors the operating status and energy consumption data of each executive device in real time, and automatically selects the optimal equipment combination and operation plan based on water quality regulation requirements, thereby minimizing energy consumption while ensuring stable water quality. It also has equipment fault diagnosis and backup switching functions.

4. An intelligent 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, enabling real-time communication and control between devices. The water quality trend model uses the LSTM deep learning algorithm and combines historical data to predict changes in water quality parameters. The prediction time window is 12-24 hours. The remote control unit is equipped with an automatic adjustment mechanism, which adopts corresponding adjustment strategies according to abnormal conditions of different water quality parameters: when the temperature is abnormal, the frequency conversion water pump adjusts the circulating water volume and controls the working status of the refrigeration unit or heater at the same time; when the pH value is abnormal, the precision dosing system is activated, and the dosage of acid-base regulator is accurately controlled through multi-point detection combined with flow calculation; when the dissolved oxygen is insufficient, the power of the micro-nano aeration system is first increased, and the backup jet aerator is activated if necessary, and the water flow rate is adjusted by the water pump to increase the reoxygenation efficiency; when the ammonia nitrogen or nitrite exceeds the standard, the biological filter backwash program is activated, the circulating water volume is increased, and the water quality is adjusted through the microbial agent dosing system. Among them, the remote control unit has data storage and system recovery functions, maintains data cache for the last 7 days, and automatically synchronizes to the cloud platform after the network is restored.

5. An intelligent water quality monitoring and regulation device based on the Internet of Things according to claim 1, characterized in that: The device's parameter threshold settings and adjustment trigger mechanisms include: a. For the water temperature indicator, three levels of warning thresholds are set: when the temperature deviates from the set value by ±1°C, a level one warning is triggered, and the variable frequency water pump adjustment is started; when it deviates by ±2°C, a level two warning is triggered, and the temperature control equipment is started; when it deviates by ±3°C, a level three warning is triggered, and the water circulation system and temperature control system are started at the same time; b. For the pH value indicator, set three levels of warning thresholds: when the pH value deviates from the set value by ±0.3, it triggers the first level warning and starts the weak injection pump; when it deviates by ±0.5, it triggers the second level warning and increases the injection volume; when it deviates by ±0.8, it triggers the third level warning and starts the emergency dosing system; c. For the dissolved oxygen index, three levels of warning thresholds are set: when the dissolved oxygen level is lower than 5mg / L, a level one warning is triggered, increasing the aeration intensity; when it is lower than 4mg / L, a level two warning is triggered, activating the backup aeration equipment; when it is lower than 3mg / L, a level three warning is triggered, activating all aeration systems; d. For the ammonia nitrogen index, three levels of warning thresholds are set: when the ammonia nitrogen exceeds 1 mg / L, a level one warning is triggered, and the flow rate of the biofilter 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 the nitrite indicator, three levels of warning thresholds are set: when nitrite exceeds 0.5mg / L, a level one warning is triggered, increasing the circulating water volume; when it exceeds 1mg / L, a level two warning is triggered, starting the denitrification system; when it exceeds 1.5mg / L, a level three warning is triggered, adding a special degradation agent; The parameter threshold setting and adjustment trigger 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 trigger time, parameter value and adjustment measures are automatically recorded, and an early 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.

6. An intelligent water quality monitoring and regulation device based on the Internet of Things according to claim 5, characterized in that: The water temperature monitoring and regulation system adopts different regulation mechanisms according to the warning level, including the first-level warning regulation mechanism, the second-level warning regulation mechanism and the third-level warning regulation mechanism. Among them, the first-level warning regulation mechanism is triggered when the water temperature deviates from the set value by ±1°C. The mechanism is equipped 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 uses the Siemens S7-200 series PLC controller to automatically adjust the water pump frequency, gradually adjusting the water pump operating frequency from the initial 30Hz to 20-50Hz in steps of 2Hz / min. After each adjustment, the system automatically waits for 5 minutes to observe the temperature change trend and determines the direction and amplitude of further adjustment based on the trend; The secondary warning adjustment mechanism is triggered when the water temperature deviates from the set value by ±2℃. The mechanism is equipped with a temperature control device consisting of a refrigeration unit and a heater. The refrigeration unit has a cooling capacity of 60,000 kcal / h and a heat exchange area of ​​20m 2 The titanium tube heat exchanger uses R410A as the refrigerant. The heater uses a 12kW titanium alloy heating tube with a surface temperature controlled at 60±5°C. When the temperature exceeds the threshold, the system automatically activates the corresponding temperature control device based on the temperature deviation direction. The refrigeration 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 optimization of the adjustment strategy. The three-level early warning adjustment mechanism is triggered when it detects that the water temperature deviates from the set value by ±3°C. 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. It is powered by a 7.5kW variable frequency water pump. The temperature control equipment includes a refrigeration unit with a cooling capacity of 60,000kcal / h and a heater with a power of 12kW. When the system enters the three-level early warning state, the controller automatically adjusts the frequency of the variable frequency water pump to 45Hz to achieve a circulating water volume of 100m3. 3 / h, and simultaneously start the refrigeration unit to run at 100% load or the heater to run at full power of 12KW, and open all branch pipe valves through the electric valve controller to achieve rapid circulation of the entire pool water. The system continues to operate 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, automatic frequency reduction protection when the water pump motor temperature exceeds 60°C, and automatic pressure relief protection when the system pipeline pressure exceeds 0.5MPa. At the same time, the system uploads the equipment operating status, protection action records and regulation effect data to the remote control unit in real time, providing data support for system maintenance management and optimization upgrades.

7. An intelligent water quality monitoring and regulation device based on the Internet of Things according to claim 5, characterized in that: The pH value adjustment monitoring and system adopts different adjustment mechanisms according to the warning level, including the first-level warning adjustment mechanism, the second-level warning adjustment mechanism, and the third-level warning adjustment mechanism. Among them, 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, has a maximum flow rate of 2L / h, a head of 50 meters, and an injection accuracy of ±1%. The injection volume is controlled by a 4-20mA analog signal. The system automatically selects acidic or alkaline regulator according to the direction of pH deviation and adds it through a peristaltic pump at an initial flow rate of 0.5L / h. After each addition, wait for 3 minutes to observe the pH value change trend. The secondary warning adjustment mechanism is triggered when it detects that the pH value deviates from the set value by ±0.

5. The mechanism is equipped with a dual-head metering pump system, including a main pump and a backup pump. The metering pump uses a 316L stainless steel pump head with a maximum flow rate of 5L / h and an injection accuracy of ±0.5%. The system increases the injection rate to 1.5L / h through the PLC controller and simultaneously starts the water circulation system to increase the mixing efficiency of the regulator. The circulation system uses a 2.2KW vertical centrifugal pump with a flow rate of 30m 3 / h, collect pH value every 5 minutes and automatically adjust the injection amount according to the change trend; The three-level early warning adjustment 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 group, and a rapid mixing device. The storage tank is made of PE material and equipped with a liquid level gauge and metering scale. The metering pump group consists of three metering pumps connected in series, with a maximum flow rate of 10L / h per unit. The multi-pump coordinated operation is achieved through a PLC controller. The rapid mixing device uses a 4kW jet pump with four injection points set at different locations on the tank body to ensure rapid and uniform mixing of the regulator. The pH value monitoring and adjustment system is also equipped with a chemical safety protection mechanism, including liquid level monitoring of the reagent storage tank, pipeline pressure monitoring and reagent concentration monitoring. When the liquid level of the storage tank is lower than 20%, it will automatically alarm, and when the pipeline pressure exceeds 0.4MPa, the pump will automatically stop for protection. At the same time, the system records the pH value change every 30 seconds through the online pH meter. When the pH value changes by more than 0.3 due to a single addition of medicine, the injection amount will be automatically reduced to ensure the safety and controllability of the adjustment process. The system will upload the real-time data of the adjustment process to the remote control unit for optimizing the adjustment strategy and predictive maintenance.

8. An intelligent water quality monitoring and regulation device based on the Internet of Things according to claim 1, characterized in that: The ammonia nitrogen monitoring and regulation system adopts different regulation mechanisms according to the warning level, including the first-level warning regulation mechanism, the second-level warning regulation mechanism and the third-level warning regulation mechanism; among them, the first-level warning regulation mechanism is triggered when the ammonia nitrogen concentration exceeds 1mg / L. The mechanism is equipped with a biological filter system, including a multi-layer filter bed and a variable frequency water pump group. The total volume of the filter bed is 15% of the aquaculture water body. It adopts a three-layer structure design, which is a quartz sand layer, a volcanic rock layer and a biological filler layer from top to bottom. The filter material particle sizes are 2-3mm, 15-25mm and 35-50mm respectively. The variable frequency water pump group consists of two 7.5KW water pumps in parallel. The system uses a PLC controller to adjust the filtration flow rate from the initial 60m 3 / h increased to 100m 3 / h, and start the backwash program to clean the filter material at the same time, with a backwash intensity of 12L / m 2 s, duration 180 seconds; The secondary early warning adjustment mechanism is triggered when the ammonia nitrogen concentration exceeds 2mg / L. The 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. The speed is adjustable within the range of 0-120rpm. The maximum flow rate of the metering pump is 5L / h with an accuracy of ±0.5%. The distributed dosing device is equipped with 8 dosing points at different locations in the breeding pond. The system is based on a 100m 3 The biological agent was added to the water body at a ratio of 5L, and the trend of ammonia nitrogen changes within 12 hours after each addition was monitored; The three-level early warning adjustment mechanism is triggered when the ammonia nitrogen concentration is detected to be over 3mg / L. The mechanism is equipped with an emergency water exchange system, including a water treatment unit, a drainage unit and a water quality adjustment unit. The water treatment unit is equipped with a mechanical filter and an ultraviolet disinfection device with a filtration accuracy of 20μm and an ultraviolet dose of ≥30mJ / cm2. The drainage unit adopts a 200m 3 / h high-flow submersible pump, the water quality adjustment unit is equipped with a temperature regulator and an automatic pH adjustment device. The system changes water at a rate of 30% per hour. During the replacement process, the inlet water quality is continuously monitored by an online monitor to ensure that the replaced water meets the aquaculture requirements; The ammonia nitrogen monitoring and regulation system is also equipped with process monitoring and safety protection mechanisms, including biofilter backwash pressure monitoring, biological agent addition recording and water quality monitoring during water exchange. When the filter pressure difference exceeds 0.05MPa, backwash is automatically started. The total amount of biological agent added within 24 hours does not exceed the set threshold. If the inlet water quality is found to be abnormal during the water exchange process, the backup water source will be automatically switched. The system will upload the key parameters of the regulation process to the remote control unit in real time for equipment maintenance and process optimization.

9. An intelligent water quality monitoring and regulation device based on the Internet of Things according to claim 1, characterized in that: The nitrite monitoring and regulation system adopts different regulation mechanisms according to the warning level, including the first-level warning regulation mechanism, the second-level warning regulation mechanism and the third-level warning regulation mechanism. Among them, the first-level warning regulation mechanism is triggered when the nitrite concentration exceeds 0.5mg / L. The mechanism is equipped with a circulating oxygenation system, including a main circulation pump group and an aeration device. The main circulation pump group consists of two 11KW variable frequency water pumps in parallel, and the maximum flow of a single water pump is 150m 3 / h, made of 316L stainless steel, the aeration device uses a nano bubble generator, the bubble particle size is 50-100nm, and the air supply volume is 120m 3 / h, the system changes the circulating water volume from the initial 80m 3 / h increased to 150m 3 / h, and at the same time, the nano aeration system is turned on to increase the dissolved oxygen content, and the dissolved oxygen level is maintained at 6-7mg / L; The secondary warning regulation mechanism is triggered when the nitrite concentration exceeds 1 mg / L. The mechanism is equipped 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 ​​800m 2 / m 3 The designed hydraulic retention time is 40 minutes. The carbon source dosing device is equipped with a 500L storage tank and a high-precision metering pump. The metering pump flow rate is adjustable from 0 to 10L / h with an accuracy of ±0.1%. The dissolved oxygen monitoring unit uses a fluorescence dissolved oxygen meter with a measurement range of 0-20mg / L. The system adjusts the carbon source dosage through an intelligent controller to maintain a C / N ratio of 4-6. The three-level early warning adjustment mechanism is triggered when the nitrite concentration exceeds 1.5mg / L. The mechanism is equipped with a special degradation bacterial agent dosing system, including a bacterial agent cultivation device, an automatic dosing device and a water quality monitoring module. The bacterial agent cultivation device consists of a 300L fermentation tank, equipped with a temperature control system and a pH monitoring and adjustment system. The fermentation temperature is controlled at 28±1℃. The automatic dosing device uses a peristaltic pump with a flow meter to accurately control the dosage, with a dosing accuracy of ±2%. The water quality monitoring module includes a nitrite online analyzer and an ammonia nitrogen online analyzer. The system is based on every 100m 3 The water body is treated by adding 10L of active bacterial solution; The nitrite monitoring and regulation system is also equipped with a full-process monitoring mechanism, including water pump operation status monitoring, denitrification efficiency evaluation and bacterial agent activity detection. The water pump operation parameters are recorded every 5 minutes, the denitrification efficiency is calculated by the difference in nitrite concentration between the inlet and outlet water, and the bacterial agent activity is detected every 4 hours using an ATP fluorescence detector. The system uploads various 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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