Factory-scale intelligent aquaculture systems, methods, equipment, media and products

Abstract

The present application discloses a factory-based intelligent aquaculture system, method, equipment, medium and product, which relate to the field of recirculating aquaculture technology. The system includes: recirculating aquaculture infrastructure, a programmable logic controller (PLC), a data transmission unit (DTU), a network video recorder, and a server; a water quality sensor group, an environmental sensor group, a working condition sensor group, an underwater camera and an above-water camera. The data acquisition equipment therein collects on-site data of the aquaculture system and sends the collected data to the PLC. After the PLC receives the data, it sends it to the server via the DTU. The server determines the control decision, such as whether to change the operating status of each infrastructure and how to change it, and sends it to the PLC via the DTU. The PLC controls the operating status of each device, thereby automatically controlling the operating status of each device, thereby improving the aquaculture efficiency of the recirculating aquaculture system.

Description

Technical Field

[0001] The present application relates to the technical field of recirculating aquaculture, and in particular to a factory-based intelligent aquaculture system, method, equipment, medium and product. Background Art

[0002] Recirculating aquaculture (RCA) is an intensive and efficient farming model, a key area of ​​transformation, upgrading, and green development for my country's aquaculture sector. RCA encompasses production processes such as physical filtration, biochemical reactions, oxygenation and temperature control, and disinfection and sterilization. It requires the integrated use of interdisciplinary technologies, including aquaculture, facility agriculture equipment, and artificial intelligence, to achieve digital characterization and intelligent management of the water quality environment, cultured fish, operational equipment, and energy and power.

[0003] Currently, recirculating aquaculture systems include infrastructure such as aquaculture ponds, vertical flow sedimentation tanks, microfiltration machines, nitrification tanks, and buffer tanks, as well as auxiliary equipment installed on these infrastructures, such as centrifugal pumps, submersible pumps, oxygen generators, and air pumps. Each device is connected by pipes or other devices; valves are also installed on the pipes to control the opening and closing of the pipes. When the aquaculture system is in operation, water is first injected into the aquaculture pond via a submersible pump. The water in the aquaculture pond then passes through the vertical flow sedimentation tanks, microfiltration machines, nitrification tanks, and buffer tanks in sequence before returning to the aquaculture pond, achieving the recycling of aquaculture water. If a device in the aquaculture system malfunctions, causing the aquaculture system to stop operating normally, staff will shut down the equipment and perform maintenance.

[0004] From the above content, it can be seen that although the existing technology has achieved the recycling of aquaculture water, the control of the entire aquaculture process still requires too much manual participation and has a low degree of intelligence, which leads to low aquaculture efficiency. Summary of the Invention

[0005] The purpose of this application is to provide a factory-based intelligent aquaculture system, method, equipment, medium and product to solve the problem of low aquaculture efficiency described in the background technology.

[0006] To achieve the above objectives, this application provides the following solutions:

[0007] In a first aspect, the present application provides a factory-based intelligent aquaculture system, comprising: a recirculating aquaculture infrastructure, a programmable logic controller (PLC), a data transmission unit (DTU), a network video recorder, and a server;

[0008] The circulating aquaculture infrastructure includes: aquaculture ponds, vertical flow sedimentation tanks, microfiltration machines, ultraviolet sterilization lamps, nitrification tanks, air source heat pumps and buffer tanks connected in sequence according to the flow direction of the aquaculture circulating water, forming a closed loop;

[0009] The infrastructures are connected via pipelines, and electric valves are installed at predetermined positions of the pipelines;

[0010] A centrifugal pump is arranged between the ultraviolet germicidal lamp and the nitrification tank;

[0011] An air pump connected to the nitrification tank is installed outside the nitrification tank; an oxygen generator connected to the buffer tank is installed outside the buffer tank;

[0012] A water quality sensor group and an underwater camera are installed in the aquaculture water of the aquaculture pond, and an above-water camera is installed above the surface of the aquaculture water;

[0013] An environmental sensor group is installed in the air of the area where the breeding pond is located;

[0014] The microfiltration machine, ultraviolet germicidal lamp, air source heat pump, centrifugal pump, air pump and oxygen generator are equipped with a working condition sensor group;

[0015] The water quality sensor group, the environmental sensor group, the working condition sensor group, the microfiltration machine, the ultraviolet sterilization lamp, the air source heat pump, the centrifugal pump, the air pump, the oxygen generator and the electric valve are connected to the PLC signal, the PLC is connected to the DTU signal, and the DTU is connected to the server signal;

[0016] The above-water camera and the underwater camera are connected to the network video recorder by signal, and the network video recorder is connected to the server by signal;

[0017] The server is used to analyze the timing data sent by the DTU and the image data sent by the network video recorder to generate a control decision, and the control decision is used to control the operating status of each device.

[0018] Optionally, the water quality sensor group includes: a dissolved oxygen sensor, a temperature sensor, a pH sensor, a COD sensor, an ORP sensor, a conductivity sensor, a turbidity sensor, an ammonia nitrogen sensor, a nitrate sensor, a nitrite sensor, a residual chlorine sensor and a liquid level sensor, and each sensor included in the water quality sensor group is connected to the PLC signal.

[0019] Optionally, the environmental sensor group includes: a temperature sensor, a humidity sensor, a carbon dioxide sensor, a sound sensor, and a light sensor, and the temperature sensor, humidity sensor, carbon dioxide sensor, sound sensor, and light sensor are connected to the PLC signal.

[0020] Optionally, the operating condition sensor group includes a smart meter, a current sensor and a vibration frequency sensor, and the smart meter, current sensor and vibration frequency sensor are connected to the PLC signal.

[0021] Optionally, suspended matter sensors are installed at the water inlet of the vertical flow sedimentator, the water inlet of the microfiltration machine, and the water outlet of the microfiltration machine, and the suspended matter sensors are connected to the PLC signal.

[0022] Optionally, the aquaculture system further comprises a water reservoir and a sewage tank; the water reservoir is connected to the aquaculture pool; the sewage tank is connected to the sewage outlet of the aquaculture pool, the sewage outlet of the vertical flow sedimentation device, the sewage outlet of the microfiltration machine, the sewage outlet of the nitrification tank, and the sewage outlet of the buffer tank;

[0023] Fluid flow meters are installed at the water outlet of the water reservoir, the water inlet of the sewage tank, the water outlet of the breeding tank, and the water outlet of the nitrification tank, and the fluid flow meters are connected to the PLC signal.

[0024] In a second aspect, the present application provides a factory-based intelligent aquaculture method, which is applied to the factory-based intelligent aquaculture system described in any one of the first aspects and is executed by a server, comprising:

[0025] Acquire time series data, which is used to characterize water quality, environmental conditions, and operating conditions of various devices in the recirculating aquaculture system;

[0026] Acquiring image data, wherein the image data is used to reflect the status of the aquaculture group above the aquaculture pond water and the status of the aquaculture objects under the aquaculture pond water;

[0027] Sending the time series data and the image data to a pre-trained intelligent decision model, so that the intelligent decision model performs a comprehensive decision analysis based on the time series data and the image data, outputs a decision result, and returns the decision result to the intelligent management and control platform;

[0028] The decision result is sent to each device.

[0029] In a third aspect, the present application provides a computer device comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the method described in the second aspect above.

[0030] In a fourth aspect, the present application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method described in the second aspect above.

[0031] In a fifth aspect, the present application provides a computer program product, comprising a computer program, which, when executed by a processor, implements the steps of the method described in the second aspect above.

[0032] According to the specific embodiments provided in this application, this application discloses the following technical effects:

[0033] The embodiment of the present application provides a factory-based intelligent aquaculture system. The embodiment of the present application provides the above-mentioned factory-based intelligent aquaculture system, which includes a water quality sensor group, an environmental sensor group, an operating condition sensor group, an underwater camera and an above-water camera. The data acquisition equipment therein collects on-site data of the aquaculture system and sends the collected data to the PLC. After the PLC receives the data, it sends it to the server through the DTU. The server determines the control decision, such as whether to change the operating status of each infrastructure and how to change it, and sends it to the PLC through the DTU. The PLC controls the operating status of each device, thereby automatically controlling the operating status of each device, thereby improving the aquaculture efficiency of the recirculating aquaculture system. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0035] Figure 1 A schematic diagram of a factory-scale intelligent aquaculture system provided in one embodiment of the present application;

[0036] Figure 2 A schematic diagram of another factory-scale intelligent aquaculture system provided in one embodiment of the present application;

[0037] Figure 3 A schematic diagram of another factory-scale intelligent aquaculture system provided in one embodiment of the present application;

[0038] Figure 4 A schematic diagram of a process flow of a factory-based intelligent aquaculture method provided in another embodiment of the present application;

[0039] Figure 5 A schematic diagram of the structure of a computer device provided in one embodiment of the present application.

[0040] Among them, there are aquaculture pond 1; vertical flow sedimentation tank 2; microfiltration machine 3; ultraviolet sterilization lamp 4; nitrification tank 5; air source heat pump 6; buffer tank 7; fluid flow meter 8; electric valve 9; centrifugal pump 10; suspended matter sensor 11; environmental sensor group 12; overflow port 13; above-water camera 14; underwater camera 15; water quality sensor group 16; bottom outlet 17; submersible pump 18; air pump 19; PC terminal 20; mobile terminal 21; intelligent decision model 22; intelligent management and control platform 23; working condition sensor 24; oxygen generator 25; programmable logic controller PLC 26; data transmission unit DTU 27; network video recorder 28; server 29; and mobile terminal 30. DETAILED DESCRIPTION

[0041] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0042] In order to make the above-mentioned purposes, features and advantages of the present application more obvious and easy to understand, the present application is further described in detail below with reference to the accompanying drawings and specific implementation methods.

[0043] Glossary:

[0044] A programmable logic controller (PLC) is a digital computer designed for industrial environments to control machinery or production processes. It implements functions such as logic control, sequence control, timing, counting, and arithmetic operations through programming.

[0045] A Data Transfer Unit (DTU) is a device used for remote data transmission and is widely used in the Internet of Things (IoT), industrial automation, and remote monitoring. DTUs transmit data from field devices to a central control system or cloud platform via wireless or wired means.

[0046] A Network Video Recorder (NVR) is a device used in video surveillance systems to receive, store, and manage video data from network cameras. Unlike traditional digital video recorders (DVRs), NVRs specialize in processing digital video streams transmitted over the network.

[0047] The embodiment of the present application provides a factory-based intelligent aquaculture system, such as Figure 1 As shown, combined with Figure 3 The system includes: recirculating aquaculture infrastructure, programmable logic controller PLC26, data transmission unit DTU27, network video recorder 28, and server 29.

[0048] The circulating aquaculture infrastructure includes: a culture pond 1, a vertical flow sedimentation device 2, a microfiltration machine 3, an ultraviolet sterilization lamp 4, a nitrification tank 5, an air source heat pump 6 and a buffer tank 7 connected in sequence according to the flow direction of the aquaculture circulating water, and forming a closed loop;

[0049] Each of the infrastructures is connected by a pipeline, and an electric valve 9 is installed at a predetermined position of each pipeline;

[0050] A centrifugal pump 10 is arranged between the ultraviolet germicidal lamp 4 and the nitrification tank 5;

[0051] An air pump 19 connected to the nitrification tank 5 is installed outside the nitrification tank 5; an oxygen generator 25 connected to the buffer tank 7 is installed outside the buffer tank 7;

[0052] A water quality sensor group 16 and an underwater camera 15 are installed in the aquaculture water of the aquaculture pond 1, and an above-water camera 14 is installed above the surface of the aquaculture water;

[0053] An environmental sensor group 12 is installed in the air of the area where the breeding pond 1 is located;

[0054] The microfiltration machine 3, ultraviolet germicidal lamp 4, air source heat pump 6, centrifugal pump 10, air pump 19 and oxygen generator 25 are equipped with a group of working condition sensors 24;

[0055] The water quality sensor group 16, the environmental sensor group 12, the working condition sensor group 24, the microfiltration machine 3, the ultraviolet sterilization lamp 4, the air source heat pump 6, the centrifugal pump 10, the air pump 19, the oxygen generator 25 and the electric valve 9 are connected to the PLC signal connection, the PLC is connected to the DTU signal connection, and the DTU is connected to the server 29 signal connection;

[0056] The above-water camera 14 and the underwater camera 15 are connected to the network video recorder 28 by signal, and the network video recorder 28 is connected to the server 29 by signal.

[0057] Among them, the formation of a closed loop can be understood as: the breeding pond 1, the vertical flow sedimentation tank 2, the microfiltration machine 3, the ultraviolet sterilization lamp 4, the nitrification tank 5, the air source heat pump 6 and the buffer tank 7 are connected in sequence, and the water outlet of the buffer tank 7 is connected to the water inlet of the breeding pond 1.

[0058] The electric valve 9 is used to control the opening and closing of the pipeline in which it is located. Further, the predetermined locations for installing the electric valve 9 include: the water inlet of the breeding pool 1, the water outlet of the breeding pool 1, the water inlet of the centrifugal pump 10, the water outlet of the nitrification pool 5, etc.

[0059] The aquaculture pond 1 is used to raise aquacultured animals, and the aquacultured animals are placed in the aquaculture pond 1 for aquaculture. Furthermore, the aquaculture pond 1 adopts a split-way sewage discharge technology. A surface discharge port is provided at the center of the upper surface of the aquaculture pond 1, a bottom discharge port 17 is provided at the center of the lower surface, and an overflow port 13 is provided on the side of the aquaculture pond 1. The surface discharge port is used to separate the surface oil film and floating leftover bait, and the bottom discharge port 17 is used to separate feces and particulate matter such as leftover bait that sinks to the bottom. The overflow port 13 is used to control the water level of the aquaculture pond 1 to prevent the water level from being too high and causing water overflow.

[0060] The vertical flow precipitator 2 is used to separate large suspended solids from the aquaculture tailwater. The aquaculture tailwater enters the vertical flow precipitator 2 from top to bottom, slowly rises along the vertical flow precipitator 2, and after the suspended solids settle, they are discharged through the sewage outlet at the bottom of the vertical flow precipitator 2. The filtered water overflows from the upper outlet.

[0061] Microfilter 3 is used to separate tiny suspended solids from aquaculture tailwater, achieving solid-liquid separation. Microfilter 3 can intercept suspended solids in the water. Furthermore, microfilter 3 is equipped with an external high-pressure flushing pump, which regularly backwashes the screen and discharges wastewater through the drain outlet.

[0062] The ultraviolet germicidal lamp 4 is used for physical ultraviolet sterilization of aquaculture tail water, destroying the nucleic acid and protein of microorganisms, thereby making them lose their reproductive function and causing their death. The centrifugal pump 10 is used to pressurize the low-level water body treated by the ultraviolet germicidal lamp 4 to the high-level nitrification tank 5.

[0063] The nitrification tank 5 is used for biological filtration. The biological filtration process can be briefly summarized as follows: nitrifying bacteria are cultivated; the nitrifying bacteria convert ammonia nitrogen and nitrite in the water into nitrate, thereby reducing the ammonia nitrogen and nitrite in the water, thereby reducing the harm of ammonia nitrogen and nitrite to the growth of the aquaculture plants.

[0064] The air pump 19 is used to blow air into the nitrification tank 5 to promote the tumbling of the biological filler and provide sufficient oxygen for the nitrification reaction.

[0065] The air source heat pump 6 is used to heat the aquaculture water flowing through it to control the temperature of the aquaculture water.

[0066] The buffer tank 7 is used to regulate the water quality of the aquaculture water.

[0067] Among them, the oxygen generator 25 is used to provide high-concentration oxygen to the buffer tank 7. After the high-concentration oxygen is evenly mixed with the aquaculture water in the buffer tank 7, the buffer tank 7 then transports the evenly mixed aquaculture water to the aquaculture pond 1. In this way, the water obtained by the aquaculture pond 1 is aquaculture water in which oxygen has been evenly mixed, thereby increasing the aquaculture density.

[0068] The water quality sensor group 16 is used to measure the water quality parameters in the breeding pond 1 and send the measured data to the PLC, which then sends the data to the DTU, which then transmits it to the server 29.

[0069] The environmental sensor group 12 is used to measure the air parameters in the area where the breeding pond 1 is located, and send the measured data to the PLC, which then sends the data to the DTU, which then transmits it to the server 29.

[0070] Among them, the operating condition sensor group 24 is used to measure the operating conditions of the microfiltration machine 3, ultraviolet sterilization lamp 4, air source heat pump 6, centrifugal pump 10, air pump 19, and oxygen generator 25, and send the measurement data to the PLC, which then sends the data to the DTU, and then the DTU transmits it to the server 29.

[0071] Among them, the water camera 14 is used to obtain group characteristics such as spatial distribution, movement trajectory, aggregation, and feeding status of the aquaculture objects.

[0072] The underwater camera 15 is used to obtain individual characteristics of the cultured object, such as body length, body width, body thickness, and fin distribution.

[0073] The image data collected by the above-water camera 14 and the underwater camera 15 are transmitted to the server 29 via the network video recorder 28 .

[0074] Among them, the server 29 is installed with an intelligent decision-making model 22 and an intelligent management and control platform 23. The intelligent decision-making model 22 is used to analyze the decision results and send them to the intelligent management and control platform 23. The intelligent management and control platform 23 is used to manage the operating status of the infrastructure, such as performing management operations on each device included in the recirculating aquaculture system through the interface displayed on the platform.

[0075] The working process of the above-mentioned circulating aquaculture system is as follows:

[0076] The water quality sensor group 16 collects water quality parameters in the breeding pond 1 and sends them to the PLC;

[0077] The environmental sensor group 12 collects the air parameters of the area and sends them to the PLC;

[0078] 24 groups of working condition sensors collect the operating parameters of each device and send them to the PLC;

[0079] The above-water camera 14 collects above-water images of the aquaculture pond 1 and sends them to the network video recorder 28 , and the underwater camera 15 collects underwater images of the aquaculture pond 1 and sends them to the network video recorder 28 ;

[0080] The PLC sends the received water quality parameters, air parameters and operating parameters to the server 29, and the network video recorder 28 sends the received above-water images and underwater images to the server 29;

[0081] The server 29 generates control instructions based on water quality parameters, air parameters, operating parameters, above-water images and underwater images. The control instructions are transmitted to the PLC through the DTU. The control instructions include switching quantities and analog quantities. The PLC controls the start and stop of the microfiltration machine 3, ultraviolet sterilization lamp 4, air source heat pump 6, centrifugal pump 10, air pump 19, and oxygen generator 25 through switching quantities. The PLC controls the opening size of the electric valve 9 and the motor speed of the centrifugal pump 10 through analog quantities, thereby forming a factory-based intelligent aquaculture control system.

[0082] An embodiment of the present application provides the above-mentioned factory-based intelligent aquaculture system, which includes a water quality sensor group 16, an environmental sensor group 12, a working condition sensor group 24, an above-water camera 14, and an underwater camera 15. These devices collect on-site data of the aquaculture system and send the collected data to the PLC. After the PLC receives the data, it sends it to the server 29 via the DTU. The server 29 determines the control decision, such as whether to change the operating status of each infrastructure and how to change it, and sends it to the PLC via the DTU. The PLC controls the operating status of each device, thereby automatically controlling the operating status of each device, thereby improving the aquaculture efficiency of the recirculating aquaculture system.

[0083] In addition, compared with the existing technology, this application also sets up an above-water camera 14 and an underwater camera 15 to collect the biological characteristics of the aquaculture objects in real time, so as to understand the growth status of the aquaculture objects in real time, so as to take corresponding measures when the growth status is poor; further, a water quality sensor group 16, an environmental sensor group 12 and a working condition sensor group 24 are set up to monitor the aquaculture water quality parameters, air environment parameters and equipment operation status in real time. In this application, the parameters of various equipment at the aquaculture system site, water quality, environment, working conditions and other multi-factor data are collected to provide the system with complete aquaculture site data, and an intelligent aquaculture algorithm is constructed based on the coupling interaction relationship between the water quality environment, the air environment and the equipment operation, so that the server 29 can provide a more reasonable control plan, realize the precise regulation of water quality and the intelligent management and control of equipment, and thus improve the aquaculture efficiency of the recirculating aquaculture system.

[0084] In addition, in this application, an electric valve 9 is also provided. The opening size of the electric valve 9 can be controlled by the analog signal of the intelligent decision-making model 22, thereby controlling the opening and closing of the pipelines and the flow size of the breeding system, thereby realizing the intelligent and unmanned breeding of the circulating water breeding system.

[0085] Alternatively, see Figure 2 The factory-scale aquaculture intelligent breeding system also includes a water reservoir, which is equipped with a submersible pump 18. The water outlet of the submersible pump 18 is connected to the water inlet of the breeding pond 1, and the submersible pump 18 is connected to the PLC signal.

[0086] The water reservoir is used to store water and supply water to the breeding pond 1.

[0087] The submersible pump 18 is used to transfer the water in the reservoir to the breeding pond 1 .

[0088] Optionally, the factory-scale aquaculture intelligent breeding system further includes a sewage drainage pool, which is connected to the sewage outlet of the breeding pond 1, the sewage outlet of the vertical flow sedimentator 2, the sewage outlet of the microfiltration machine 3, the sewage outlet of the nitrification tank 5 and the sewage outlet of the buffer tank 7.

[0089] Among them, the sewage tank is used to discharge the aquaculture water from the system when the system water is changed.

[0090] Furthermore, the PLC will also receive the switch quantity sent by the intelligent control platform 23, and control the start and stop of the submersible pump 18 through the switch quantity.

[0091] Optionally, the predetermined positions for installing the electric valve 9 also include: the drain outlet of the breeding pond 1, the drain outlet of the vertical flow sedimentator 2, the drain outlet of the microfiltration machine 3, the drain outlet of the nitrification tank 5, the drain outlet of the buffer tank 7, the water outlet of the reservoir, etc.

[0092] Optionally, the microfilter 3 may be a drum-type microfilter 3 or a laminated microfilter 3;

[0093] Optionally, the water quality sensor group 16 includes: a dissolved oxygen sensor, a temperature sensor, a pH sensor, a COD sensor, an ORP sensor, a conductivity sensor, a turbidity sensor, an ammonia nitrogen sensor, a nitrate sensor, a nitrite sensor, a residual chlorine sensor and a liquid level sensor, and each sensor included in the water quality sensor group 16 is connected to the PLC signal.

[0094] The water quality sensor group 16 is installed in the aquaculture pond 1 to monitor dissolved oxygen, temperature, pH, COD, ORP, conductivity, turbidity, ammonia nitrogen concentration, nitrate concentration, nitrite concentration, residual chlorine concentration and liquid level, and sends the monitored data to the PLC.

[0095] Optionally, the environmental sensor group 12 includes: a temperature sensor, a humidity sensor, a carbon dioxide sensor, a sound sensor, and a light sensor, and the temperature sensor, humidity sensor, carbon dioxide sensor, sound sensor, and light sensor are connected to the PLC signal.

[0096] The environmental sensor group 12 is used to monitor air temperature, air humidity, carbon dioxide concentration, sound intensity, and light intensity, and send the monitored data to the PLC.

[0097] Optionally, the operating condition sensor group 24 includes a smart meter, a current sensor and a vibration frequency sensor, and the smart meter, current sensor and vibration frequency sensor are connected to the PLC signal.

[0098] Among them, the smart meter and the current sensor can be called an electrical sensor group.

[0099] Furthermore, an electrical sensor group is installed in the control cabinet to monitor the system's voltage, current, instantaneous power, total power, and operating current of each device, and send the monitored data to the PLC.

[0100] The vibration frequency sensor is installed on the equipment to be detected, such as the centrifugal pump 10, the air pump 19, and the oxygen generator 25, to monitor the vibration frequency of the equipment and send the monitored data to the PLC.

[0101] Optionally, a suspended matter sensor 11 is installed at the water inlet of the vertical flow sedimentator 2, the water inlet of the microfilter 3 and the water outlet of the microfilter 3, and the suspended matter sensor 11 is connected to the PLC signal.

[0102] The suspended matter sensor 11 is used to monitor the suspended matter concentration, thereby quantifying the operating conditions of the vertical flow precipitator 2 and the microfiltration machine 3, and sending the monitored data to the PLC.

[0103] Optionally, a fluid flow meter 8 is installed at the water outlet of the water reservoir, the water inlet of the sewage tank, the water outlet of the breeding pond 1, and the water outlet of the nitrification tank 5, and the fluid flow meter 8 is connected to the PLC signal.

[0104] The fluid flow meter 8 is used to monitor the total amount of water inflow, the total amount of water outflow, the instantaneous flow rate, the flow percentage and the water conductivity ratio, and send the monitored data to the PLC.

[0105] Optionally, two centrifugal pumps 10 are provided, one of which is used as a backup so that when one of the centrifugal pumps fails, the other can be activated in time to ensure the smooth operation of the aquaculture system.

[0106] Optionally, the factory-scale aquaculture intelligent farming system further includes a mobile terminal 30 , which is signal-connected to the server 29 .

[0107] An application corresponding to the intelligent management and control platform 23 is installed in the mobile terminal 30, and the staff can send control instructions to each infrastructure by opening the application.

[0108] The mobile terminal 30 may be, but is not limited to, various desktop computers, laptops, smartphones, tablet computers, IoT devices, and portable wearable devices. IoT devices may be smart speakers, smart TVs, smart air conditioners, smart car devices, etc. Portable wearable devices may be smart watches, smart bracelets, head-mounted devices, etc.

[0109] The server 29 may be implemented as an independent server 29 or a server 29 cluster composed of multiple servers 29 , or may be a cloud server 29 .

[0110] In addition, Figure 3 In this paper, each device in the factory aquaculture intelligent farming system is presented through the perception layer, transmission layer, data processing layer, and application layer. The application layer also includes control devices and mobile terminals 30. For the specific devices and connection relationships of each layer, please refer to Figure 3 and related descriptions.

[0111] In addition, other relevant contents of the system embodiment can be found in the following method embodiment and will not be described in detail here.

[0112] In an exemplary embodiment, Figure 4 As shown, a method for intelligent aquaculture in a factory is provided. The method is executed by a computer device, specifically a computer device such as a server 29, or a terminal and a server 29. In the embodiment of the present application, the method is applied to Figure 1 and Figure 2 Taking the server 29 in FIG. 1 as an example, the method includes the following steps 201 to 204:

[0113] Step 201: Acquire time series data, which is used to characterize the water quality, environmental conditions, and operating conditions of various devices in the recirculating aquaculture system.

[0114] Among them, the time series data is collected by the time series data acquisition device and sent to the programmable logic controller PLC26, then sent to the server 29 by the PLC through the DTU, and finally stored by the server 29.

[0115] Among them, the time series data acquisition equipment includes one or more of the water quality sensor group 16, the environmental sensor group 12, the working condition sensor group 24, the suspended matter sensor 11, and the fluid flow meter 8 mentioned in the system embodiment.

[0116] After the timing data acquisition device collects the timing data, it transmits it to the PLC through the RS485 interface and the Modbus protocol; the PLC transmits the timing data to the DTU through the serial port communication method of the RS485 interface and the Modbus RTU protocol, or through the Ethernet communication method of the RJ45 interface and the Modbus TCP protocol; the DTU transmits the timing data to the intelligent management and control platform 23 through the 4G / 5G protocol and the MQTT protocol, and the intelligent management and control platform 23 stores the timing data.

[0117] Step 202: Acquire image data, wherein the image data is used to reflect the status of the aquaculture group above the aquaculture pond water and the status of the aquaculture objects under the aquaculture pond water.

[0118] The above-mentioned above-water camera 14 and underwater camera 15 are used to collect image data in the breeding pond 1. The above-water camera 14 and underwater camera 15 transmit the collected image data to the network video recorder 28 through the RJ45 interface and the ONVIF protocol; the network video recorder 28 transmits the image data collected from the above-water camera 14 and the underwater camera 15 to the intelligent management and control platform 23 through the TCP / UDP protocol and the RTSP protocol, and the image data is stored by the intelligent management and control platform 23.

[0119] In step 203, the time series data and the image data are sent to a pre-trained intelligent decision model, so that the intelligent decision model performs a comprehensive decision analysis based on the time series data and the image data, outputs a decision result, and returns the decision result to the intelligent management and control platform.

[0120] The decision result is used to control the operating status of each device in the circulating aquaculture system.

[0121] Among them, the equipment whose operating status needs to be controlled includes: electric valve 9, centrifugal pump 10, microfiltration machine 3, air source heat pump 6, submersible pump 18, air pump 19, ultraviolet sterilization lamp 4 and oxygen generator 25.

[0122] Furthermore, the operating status of each device includes start and pause. Furthermore, for the electric valve 9, its operating status also includes the valve opening. By varying the opening size, the amount of water flowing into the corresponding device is limited, achieving precise control to improve the efficiency of recirculating aquaculture. For the centrifugal pump 10, the operating status also includes the motor speed. By precisely controlling the motor speed of the centrifugal pump 10, the precise control of the water volume is improved, thereby improving the efficiency of recirculating aquaculture.

[0123] For example, if the time series data detects that the water quality of the aquaculture water is too poor, the intelligent decision-making model 22 analyzes that all the aquaculture water needs to be replaced, then the decision result is to start the submersible pump 18, and open the electric valve 9 at the drain outlet of the aquaculture pond 1 and the water outlet of the reservoir. If it is detected that the aquaculture water has been replaced, the decision result is to suspend the submersible pump 18 and close the electric valve 9 at the drain outlet of the aquaculture pond 1 and the water outlet of the reservoir.

[0124] The intelligent management and control platform 23 opens the stored time series data and image data to the intelligent decision model 22 through the application programming interface API. The intelligent decision model 22 obtains data from the intelligent management and control platform 23 through the application programming interface API and returns the decision result to the intelligent management and control platform 23.

[0125] Furthermore, the intelligent decision-making model 22 extracts data features based on machine learning or deep learning methods, quantitatively analyzes the coupling interaction mechanism of water quality environment-farmed fish-operating equipment, and returns the intelligent decision-making results to the intelligent management and control platform 23 through the application programming interface API.

[0126] Optionally, the intelligent decision-making model 22 includes a water quality prediction model based on LSTM, an environment prediction model based on RNN, a working condition control model based on fuzzy control, a fish feeding behavior analysis model based on ResNet, and an underwater fish detection model based on YOLOv8.

[0127] Among them, the role of the LSTM-based water quality prediction model is to receive water quality parameters such as dissolved oxygen, temperature, pH, etc. collected by the water quality sensor group 16, and predict their long-term and short-term change trends based on the water quality parameters to ensure timely regulation and stabilization of water quality.

[0128] Furthermore, the LSTM-based water quality prediction model introduces a spatiotemporal attention mechanism to enhance the feature extraction of the spatial and temporal dimensions of water quality parameters, so as to better meet the long-term and short-term prediction needs of water quality parameters.

[0129] The RNN-based environment prediction model is used to receive environmental parameters such as temperature, humidity, and carbon dioxide concentration collected by the environmental sensor group 12, and predict their long-term change trends based on the environmental parameters to ensure environmental stability.

[0130] Among them, the function of the working condition control model based on fuzzy control is to receive working condition parameters such as working current and vibration frequency collected by 24 groups of working condition sensors, and adjust the operating status of the equipment according to the working condition parameters to ensure stable operation of the equipment.

[0131] Among them, the function of the fish feeding behavior analysis model based on ResNet is to receive the fish feeding images collected by the underwater camera 14, analyze the feeding status characteristics of the fish according to the feeding images, and divide the results into four categories: strong feeding, medium feeding, weak feeding, and no feeding.

[0132] Furthermore, the ResNet-based fish feeding behavior analysis model introduces an attention mechanism module to enhance attention to the feeding characteristics of fish schools and improve the analysis accuracy of fish feeding status.

[0133] Among them, the function of the underwater fish detection model based on YOLOv8 is to receive images captured by the underwater camera 15, detect individual fish according to the underwater images, and monitor the growth status of the fish.

[0134] Step 204: Send the decision result to each device.

[0135] The intelligent management and control platform 23 transmits the intelligent decision results to the DTU via the 4G / 5G protocol and the MQTT protocol. The DTU transmits the intelligent decision results to the PLC via the aforementioned serial communication or Ethernet communication. The PLC converts the intelligent decision results into control instructions and issues control instructions to the electric valve 9, centrifugal pump 10, microfiltration machine 3, air source heat pump 6, air pump 19, ultraviolet germicidal lamp 4, and oxygen concentrator 25 in the infrastructure via the RS485 interface and the Modbus protocol. In other words, the equipment in step 204 is the electric valve 9, centrifugal pump 10, microfiltration machine 3, air source heat pump 6, air pump 19, ultraviolet germicidal lamp 4, and oxygen concentrator 25.

[0136] Optionally, the decision result is sent to the mobile terminal 30 so that the mobile terminal 30 can remotely control the operating status of each device in the recirculating aquaculture system.

[0137] The mobile terminal 30 can be a PC 20 or a mobile terminal 21 (smartphone). The intelligent management and control platform 23 is connected to the mobile terminal 30 via a 4G / 5G protocol to achieve remote control of the factory-scale intelligent aquaculture system.

[0138] The present embodiment provides the aforementioned factory-scale intelligent aquaculture method, which includes acquiring time series data and image data, and sending the time series data and image data to an intelligent decision model 22. The intelligent decision model 22 outputs a decision result, such as whether to change the operating status of each infrastructure and how to change it, and sends the result to the PLC via the DTU. The PLC then controls the operating status of each device. Therefore, the present application can automatically control the operating status of each device, thereby improving the aquaculture efficiency of the recirculating aquaculture system.

[0139] In addition, the embodiment of the method provides complete aquaculture site data, so that the intelligent management and control platform 23 can provide a more reasonable control solution, thereby improving the aquaculture efficiency of the recirculating aquaculture system.

[0140] In addition, other relevant contents of the method embodiment can be found in the above-mentioned system embodiment and will not be described in detail here.

[0141] In an exemplary embodiment, a computer device is provided. The computer device may be a server or a terminal. The internal structure diagram thereof may be as follows: Figure 5As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, abbreviated as I / O) and a communication interface. The processor, memory and input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and computer program in the non-volatile storage medium. The database of the computer device is used to store data related to factory-scale intelligent aquaculture. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a method for factory-scale intelligent aquaculture can be implemented.

[0142] Those skilled in the art will understand that Figure 5 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0143] In an exemplary embodiment, a computer device is further provided, including a memory and a processor. The memory stores a computer program, and the processor implements the steps in the above method embodiments when executing the computer program.

[0144] In an exemplary embodiment, a computer-readable storage medium is provided, storing a computer program. When the computer program is executed by a processor, the steps in the above-mentioned method embodiments are implemented.

[0145] In an exemplary embodiment, a computer program product is provided, including a computer program. When the computer program is executed by a processor, the steps in the above method embodiments are implemented.

[0146] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0147] Those skilled in the art will appreciate that all or part of the processes in the above-described method embodiments can be implemented by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the above-described method embodiments. In the embodiments provided in this application, any reference to a memory, database, or other medium can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM may be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

[0148] The databases involved in the various embodiments provided herein may include at least one of a relational database and a non-relational database. Non-relational databases may include, but are not limited to, distributed databases based on blockchains. The processors involved in the various embodiments provided herein may include, but are not limited to, general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic units, data processing logic units based on quantum computing, and the like.

[0149] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0150] This document uses specific examples to illustrate the principles and implementation methods of this application. The description of the above examples is only intended to help understand the method and core concept of this application. At the same time, for those skilled in the art, based on the concept of this application, there may be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting this application.

Claims

1. A factory-scale intelligent aquaculture system, characterized in that: include: Recirculating aquaculture infrastructure, programmable logic controller PLC, data transmission unit DTU, network video recorder, server; The circulating aquaculture infrastructure includes: aquaculture ponds, vertical flow sedimentation tanks, microfiltration machines, ultraviolet sterilization lamps, nitrification tanks, air source heat pumps and buffer tanks connected in sequence according to the flow direction of the aquaculture circulating water, forming a closed loop; The infrastructures are connected via pipelines, and electric valves are installed at predetermined positions of the pipelines; A centrifugal pump is arranged between the ultraviolet germicidal lamp and the nitrification tank; An air pump connected to the nitrification tank is installed outside the nitrification tank; an oxygen generator connected to the buffer tank is installed outside the buffer tank; A water quality sensor group and an underwater camera are installed in the aquaculture water of the aquaculture pond, and an above-water camera is installed above the surface of the aquaculture water; An environmental sensor group is installed in the air of the area where the breeding pond is located; The microfiltration machine, ultraviolet germicidal lamp, air source heat pump, centrifugal pump, air pump and oxygen generator are equipped with a working condition sensor group; The water quality sensor group, the environmental sensor group, the working condition sensor group, the microfiltration machine, the ultraviolet sterilization lamp, the air source heat pump, the centrifugal pump, the air pump, the oxygen generator and the electric valve are connected to the PLC signal, the PLC is connected to the DTU signal, and the DTU is connected to the server signal; The above-water camera and the underwater camera are signal-connected to the network video recorder, and the network video recorder is signal-connected to the server; the server is used to analyze the timing data sent by the DTU and the image data sent by the network video recorder to generate a control decision, and the control decision is used to control the operating status of each device; The server is equipped with an intelligent decision-making model and an intelligent management and control platform. The intelligent management and control platform is used to receive the time series data sent by the DTU and the image data sent by the network video recorder; and forward the time series data and image data to the intelligent decision-making model. The intelligent decision-making model is used to generate a decision result and send it to the intelligent management and control platform. The intelligent management and control platform receives the decision result and converts it into a control instruction, which is sent to the DTU. The DTU sends it to the PLC, and the PLC sends it to each device that needs to be controlled to manage the operating status of each device. The intelligent decision-making model includes a water quality prediction model based on LSTM, an environment prediction model based on RNN, a working condition control model based on fuzzy control, a fish feeding behavior analysis model based on ResNet, and an underwater fish detection model based on YOLOv8; The intelligent decision-making model is used to extract data features of time series data and image data, and quantitatively analyze the coupling interaction mechanism of water quality environment-farmed fish-operating equipment. The decision result includes the coupling interaction mechanism of water quality environment-farmed fish-operating equipment; The control instructions include switching quantities and analog quantities. The PLC controls the start and stop of the microfiltration machine, ultraviolet sterilization lamp, air source heat pump, centrifugal pump, air pump, and oxygen generator through the switching quantities. The PLC controls the opening size of the electric valve and the motor speed of the centrifugal pump through the analog quantities. Among them, the operating condition sensor group includes a vibration frequency sensor and is connected to the PLC signal; the vibration frequency sensor is installed on the centrifugal pump, air pump, and oxygen concentrator to monitor the vibration frequency of the centrifugal pump, air pump, and oxygen concentrator, and send the monitored data to the PLC.

2. The factory-scale intelligent aquaculture system according to claim 1, characterized in that: The water quality sensor group includes: a dissolved oxygen sensor, a temperature sensor, a pH sensor, a COD sensor, an ORP sensor, a conductivity sensor, a turbidity sensor, an ammonia nitrogen sensor, a nitrate sensor, a nitrite sensor, a residual chlorine sensor and a liquid level sensor, and each sensor included in the water quality sensor group is connected to the PLC signal.

3. The factory-scale intelligent aquaculture system according to claim 1, characterized in that: The environmental sensor group includes: a temperature sensor, a humidity sensor, a carbon dioxide sensor, a sound sensor, and a light sensor. The temperature sensor, humidity sensor, carbon dioxide sensor, sound sensor, and light sensor are connected to the PLC signal.

4. The factory-scale intelligent aquaculture system according to claim 1, characterized in that: The operating condition sensor group further includes a smart meter and a current sensor, and the smart meter and the current sensor are connected to the PLC signal.

5. The factory-scale intelligent aquaculture system according to any one of claims 1 to 4, characterized in that: Suspended matter sensors are installed at the water inlet of the vertical flow sedimentator, the water inlet of the microfiltration machine and the water outlet of the microfiltration machine, and the suspended matter sensors are connected to the PLC signal.

6. The factory-scale intelligent aquaculture system according to any one of claims 1 to 4, characterized in that: The aquaculture system further comprises a water reservoir and a sewage tank; the water reservoir is connected to the aquaculture pool; the sewage tank is connected to the sewage outlet of the aquaculture pool, the sewage outlet of the vertical flow sedimentation device, the sewage outlet of the microfiltration machine, the sewage outlet of the nitrification tank and the sewage outlet of the buffer tank; Fluid flow meters are installed at the water outlet of the water reservoir, the water inlet of the sewage tank, the water outlet of the breeding tank, and the water outlet of the nitrification tank, and the fluid flow meters are connected to the PLC signal.

7. A factory-scale intelligent aquaculture method, characterized in that: Applied to the factory-scale intelligent aquaculture system according to any one of claims 1 to 6 and executed by the intelligent management and control platform in the server, comprising: Acquire time series data, which is used to characterize water quality, environmental conditions, and operating conditions of various devices in the recirculating aquaculture system; Acquiring image data, wherein the image data is used to reflect the status of the aquaculture group above the aquaculture pond water and the status of the aquaculture objects under the aquaculture pond water; Sending the time series data and the image data to a pre-trained intelligent decision model, so that the intelligent decision model performs a comprehensive decision analysis based on the time series data and the image data, outputs a decision result, and returns the decision result to the intelligent management and control platform; The intelligent management and control platform converts the decision results into control instructions and controls the operating status of each device through DTU and PLC.

8. A computer device comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the factory-scale intelligent aquaculture method according to claim 7.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the factory-scale intelligent aquaculture method according to claim 7 is implemented.

10. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the factory-scale intelligent aquaculture method according to claim 7 is implemented.

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