Fish culture optimization method, system, equipment and medium

Abstract

The invention discloses an optimization method, system and equipment for fish culture and a medium. The method comprises the following steps: acquiring current environment parameters of a culture area and parameters of fishes of each variety; according to the current environment parameters and the parameters of the fishes of each variety, the culture density of the fishes of each variety is calculated; calculating the optimal culture density of the culture area according to the culture density of the fishes of each variety; according to the current environment parameters of the breeding area, ideal environment parameters of the breeding area are calculated based on the optimal breeding density; in response to the culture equipment in the culture area, the culture parameters of the culture equipment are adjusted in real time according to the ideal environment parameters, the optimal culture density can be determined according to the culture environment and the fish data, and the culture environment can be dynamically adjusted in real time in combination with the culture environment data and the fish data, so that the fish culture survival rate and the culture yield are improved. The breeding efficiency and the economic benefit are improved.

Description

Technical Field

[0001] The present application relates to the field of aquaculture technology, and in particular to an optimization method, system, equipment and medium for fish farming. Background Art

[0002] Traditional fish farming relies mainly on the experience of farmers when setting stocking density. However, due to differences in pond size, fish species, breeding environment and water quality, it is often difficult to accurately control based on experience alone, which affects the growth status and survival rate of fish.

[0003] However, existing intelligent farming technology only calculates ideal farming data based on environmental data, and lacks reference to the growth of different fish species. As a result, it is not only impossible to dynamically adjust the existing farming control equipment according to real-time environmental data, but also impossible to determine the optimal fish farming density in the pond based on the size of different ponds, the species of fish raised, the farming environment and the differences in water quality conditions. This affects the farming efficiency and leads to low farming output and low survival rate. Summary of the invention

[0004] The following is a summary of the subject matter described in detail herein. This summary is not intended to limit the scope of the claims.

[0005] The main purpose of the embodiments of the present disclosure is to propose a method, system, device and storage medium that can improve the survival rate and aquaculture output of fish, and improve aquaculture efficiency and economic benefits.

[0006] A first aspect of an embodiment of the present application provides a method for optimizing fish farming, which is used in a central controller. The method comprises:

[0007] Obtain current environmental parameters of the breeding area and fish parameters of each species;

[0008] Calculating the fish breeding density of each species according to the current environmental parameters and the fish parameters of each species;

[0009] Calculate the optimal stocking density in the aquaculture area according to the stocking density of each species of fish;

[0010] According to the current environmental parameters of the breeding area, the ideal environmental parameters of the breeding area are calculated based on the optimal breeding density;

[0011] Respond to the farming equipment in the farming area to adjust the farming parameters of the farming equipment in real time according to the ideal environmental parameters.

[0012] The embodiment of the present application provides a method for optimizing fish farming, by obtaining the current environmental parameters of a farming area and the parameters of each species of fish; calculating the fish farming density of each species according to the current environmental parameters and the parameters of each species of fish; calculating the optimal farming density of the farming area according to the fish farming density of each species; calculating the ideal environmental parameters of the farming area based on the optimal farming density according to the current environmental parameters of the farming area; responding to the farming equipment in the farming area to adjust the farming parameters of the farming equipment in real time according to the ideal environmental parameters, the optimal farming density can be determined according to the farming environment and fish data, and the farming environment can be dynamically adjusted in real time in combination with the farming environment data and the fish data, thereby improving the survival rate and farming yield of fish farming, and improving the farming efficiency and economic benefits.

[0013] In some embodiments of the present application, the step of calculating the fish breeding density of each species according to the current environmental parameters and the fish parameters of each species includes:

[0014] Calculating the oxygen supply in the breeding area according to the current environmental parameters;

[0015] Calculating the oxygen demand of each species of fish according to the current environmental parameters and the parameters of each species of fish;

[0016] The fish breeding density of each species is calculated according to the oxygen supply in the breeding area and the oxygen demand of each species of fish.

[0017] In some embodiments of the present application, the fish parameter includes fish species, the current environmental parameter includes multiple environmental factor data in the breeding area,

[0018] The calculation formula for calculating the oxygen supply in the breeding area includes:

[0019] O s =C o ×V;

[0020] V = L × W × D;

[0021] Among them, O s is the oxygen supply in the breeding area, C o is the oxygen concentration per unit volume of water, V is the volume of water in the aquaculture area, L is the length of water in the aquaculture area, W is the width of water in the aquaculture area, and D is the average depth of water in the aquaculture area;

[0022] The calculation formula for calculating the oxygen requirement of each species of fish includes:

[0023] O d =K×W×(T+273);

[0024] Among them, O d is the oxygen requirement of a single fish of a single fish, K is the fish species, W is the average weight of a single fish, and T is the culture temperature of the culture area.

[0025] In some embodiments of the present application, the calculation formula for calculating the fish farming density of each species includes:

[0026]

[0027] f(T,pH)=α(T-T0)+β(pH-pH0);

[0028] Wherein, N is the fish farming density of a single fish, f(T, pH) is the correction coefficient of farming temperature and pH, α is the influence coefficient of preset water temperature on oxygen demand, β is the influence coefficient of preset pH on oxygen demand, T0 is the preset ideal farming temperature, pH is the pH of the farming area, and pH0 is the preset ideal pH.

[0029] In some embodiments of the present application, the formula for calculating the optimal breeding density of the breeding area includes:

[0030]

[0031] Among them, N is the optimal breeding density, A is the area of ​​the breeding area, D is the average depth of the water body in the breeding area, and E is env is the influencing factor of the current environmental parameters, F load is the fish load factor per unit water body.

[0032] In some embodiments of the present application, the ideal environmental parameters of the breeding area include:

[0033] Q feed =N×F(W,T,O e ,D,α);

[0034] Among them, Q feed is the feeding amount for breeding, N is the optimal breeding density, W is the weight of a single fish, T is the water temperature in the breeding area, O2 is the dissolved oxygen content in the breeding area, D is the fish growth stage coefficient, and α is the unit water load coefficient.

[0035] In some embodiments of the present application, the responding to the farming equipment in the farming area to adjust the farming parameters of the farming equipment in real time according to the ideal environmental parameters includes:

[0036] Real-time monitoring of real-time environmental parameters of the breeding area;

[0037] Based on the ideal environmental parameters, the breeding parameters of the breeding equipment are adjusted according to the real-time environmental parameters.

[0038] To achieve the above object, a second aspect of an embodiment of the present invention provides an optimization system for fish farming, the system comprising:

[0039] A data acquisition module is used to obtain the current environmental parameters of the breeding area and the parameters of each species of fish;

[0040] A first calculation module, used for calculating the fish breeding density of each species according to the current environmental parameters and the preset fish parameters;

[0041] A second calculation module is used to calculate the optimal breeding density of the breeding area according to the breeding density of each species of fish;

[0042] A third calculation module is used to calculate the ideal environmental parameters of the breeding area based on the optimal breeding density according to the current environmental parameters of the breeding area;

[0043] The data adjustment module is used to respond to the breeding equipment in the breeding area to adjust the breeding parameters of the breeding equipment in real time according to the ideal environmental parameters.

[0044] To achieve the above-mentioned purpose, the third aspect of an embodiment of the present invention provides an electronic device, comprising: at least one control processor and a memory for communicating with the at least one control processor; the memory stores instructions that can be executed by the at least one control processor, and the instructions are executed by the at least one control processor so that the at least one control processor can execute the above-mentioned fish farming optimization method.

[0045] To achieve the above-mentioned purpose, a fourth aspect of an embodiment of the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer-executable instructions, and the computer-executable instructions are used to enable a computer to execute the above-mentioned method for optimizing fish farming.

[0046] It can be understood that the beneficial effects of the second to fourth aspects compared with the related art are the same as the beneficial effects of the first aspect compared with the related art. Please refer to the relevant description in the first aspect, and no further details will be given here. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] The above and / or additional aspects and advantages of the present application will become apparent and easily understood from the description of the embodiments in conjunction with the following drawings, in which:

[0048] Figure 1 It is a schematic diagram of a flow chart of a method for optimizing fish farming provided in an embodiment of the present application;

[0049] Figure 2 It is a structural schematic diagram of an optimization system for fish farming provided in an embodiment of the present application;

[0050] Figure 3 It is a schematic diagram of the hardware structure of the electronic device provided in the embodiment of the present application. DETAILED DESCRIPTION

[0051] The embodiments of the present application are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present application, and cannot be understood as limiting the present application.

[0052] In the description of this application, if there is a description of first, second, etc., it is only for the purpose of distinguishing technical features, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features or implicitly indicating the order of the indicated technical features.

[0053] In the description of the present application, it should be understood that the descriptions involving orientation, such as the orientation or positional relationship indicated as up, down, etc., are based on the orientation or positional relationship shown in the drawings, and are only for the convenience of describing the present application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as a limitation on the present application.

[0054] In the description of this application, it should be noted that, unless otherwise clearly defined, terms such as setting, installing, connecting, etc. should be understood in a broad sense, and technicians in the relevant technical field can reasonably determine the specific meaning of the above terms in this application based on the specific content of the technical solution.

[0055] Traditional fish farming relies mainly on the experience of farmers when setting stocking density. However, due to differences in pond size, fish species, breeding environment and water quality, it is often difficult to accurately control based on experience alone, which affects the growth status and survival rate of fish.

[0056] With the advancement of intelligent farming technology, systems based on environmental monitoring and data analysis are gradually being applied to the aquaculture industry. However, how to effectively combine pond size, environmental parameters and fish demand to calculate the optimal fish farming density is still a technical difficulty in current aquaculture.

[0057] Existing methods lack an accurate scientific basis for calculating the optimal fish farming density in ponds, making it difficult to ensure the aquaculture goals of high yield, low cost and high survival rate. As a result, common oxygenation equipment cannot be dynamically adjusted according to real-time environmental data, resulting in excessive or insufficient oxygenation, affecting farming efficiency.

[0058] Therefore, the existing intelligent farming technology only calculates ideal farming data based on environmental data, lacks reference to the growth of different fish, and thus not only cannot dynamically adjust the existing farming control equipment according to real-time environmental data, but also cannot determine the optimal fish farming density in the pond according to the size of different ponds, the species of fish raised, the farming environment and the water quality conditions. This leads to suboptimal farming in the farming area, affects the farming efficiency, and results in low farming output and low survival rate.

[0059] Based on this, the embodiments of the present application provide a method, system, electronic device and medium for optimizing fish farming, aiming to improve the survival rate and yield of fish farming, and improve farming efficiency and economic benefits.

[0060] The optimization method, system, electronic device and medium for fish farming provided in the embodiments of the present application are specifically illustrated through the following embodiments. First, the optimization method for fish farming in the embodiments of the present application is described.

[0061] The embodiments of the present application can acquire and process relevant data based on artificial intelligence technology. Among them, artificial intelligence (AI) is the theory, method, technology and application system that uses digital computers or machines controlled by digital computers to simulate, extend and expand human intelligence, perceive the environment, acquire knowledge and use knowledge to obtain the best results.

[0062] AI basic technologies generally include sensors, dedicated AI chips, cloud computing, distributed storage, big data processing technology, operation / interaction systems, mechatronics, etc. AI software technologies mainly include computer vision technology, robotics technology, biometrics technology, speech processing technology, natural language processing technology, and machine learning / deep learning.

[0063] An optimization method for fish farming provided in an embodiment of the present application relates to the field of intelligent farming technology. The optimization method for fish farming provided in an embodiment of the present application can be applied to a terminal, can be applied to a server side, or can be software running in a terminal or a server side. In some embodiments, the terminal can be a smart phone, a tablet computer, a laptop computer, a desktop computer, etc.; the server side can be configured as an independent physical server, or can be configured as a server cluster or a distributed system composed of multiple physical servers, or can be configured as a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms; the software can be an application for implementing the optimization method for fish farming, etc., but is not limited to the above forms.

[0064] The present application can be used in many general or special computer system environments or configurations. For example: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, distributed computing environments including any of the above systems or devices, etc. The present application can be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform specific tasks or implement specific abstract data types. The present application can also be practiced in distributed computing environments, in which tasks are performed by remote processing devices connected through a communication network. In a distributed computing environment, program modules can be located in local and remote computer storage media including storage devices.

[0065] It should be noted that in each specific implementation of the present application, when it comes to the need to perform relevant processing based on data related to user identity or characteristics such as user information, user behavior data, user historical data, and user location information, the user's permission or consent will be obtained first, and the collection, use, and processing of these data will comply with relevant laws, regulations, and standards. In addition, when the embodiment of the present application needs to obtain the user's sensitive personal information, the user's separate permission or consent will be obtained through a pop-up window or by jumping to a confirmation page. After clearly obtaining the user's separate permission or consent, the necessary user-related data for the normal operation of the embodiment of the present application will be obtained.

[0066] For this purpose, refer to Figure 1The embodiment of the present application provides a method for optimizing fish farming. The method is applied to a central controller. The controller can be a server, an electronic device, or a mobile terminal, etc., which is not specifically limited here. The method includes the following steps S110 to S150.

[0067] Step S110, obtaining the current environmental parameters of the breeding area and the parameters of each species of fish.

[0068] In aquaculture, environmental factors do have a direct and significant impact on the growth of fish. Specific influencing factors include water temperature, dissolved oxygen level, pH value, ammonia nitrogen and nitrite concentration, etc., which together determine the health status, growth rate and survival rate of fish. Therefore, obtaining the current environmental parameters of the breeding area is crucial for the optimization of fish breeding.

[0069] In this step, the current environmental parameters of the breeding area are first collected in real time, including water volume, dissolved oxygen content, water temperature, pH value, etc.

[0070] Specifically, the environmental parameters of the breeding area can be accurately obtained by using methods such as laser ranging and sound wave measurement, and then the environmental parameters of the breeding area can be used as important input parameters for the subsequent calculation of the optimal breeding density. For example, sensor modules are installed in the pond and the surrounding environment to monitor environmental parameters in real time, such as water temperature, dissolved oxygen, pH value, ammonia nitrogen concentration and other environmental data. Among them, the metabolic rate of fish is directly related to water temperature, and the oxygen demand of fish is different at different temperatures. The actual supply of oxygen in the water body is a key indicator for determining fish density. Water quality factors such as pH value, ammonia nitrogen, and nitrite will affect the water quality and the growth environment of fish.

[0071] It can also include monitoring and obtaining basic physical data such as pond size and depth, and then transmitting the data collected by the sensor to the central control system via a wireless network or wired connection for subsequent calculation and decision-making processes to ensure the real-time and accuracy of the data.

[0072] Furthermore, the environmental parameters of the breeding area are determined according to the basic physical parameters of the breeding area. For example, the water volume (length, width, depth) of the pond is calculated to obtain the pond capacity.

[0073] In addition, different fish have different requirements for oxygen and living space, so it is necessary to obtain the fish parameters of each species, and then based on the real-time monitoring data, combined with the fish species and their growth needs, calculate the current optimal breeding density in the breeding area through intelligent algorithms.

[0074] Specifically, the fish parameters for each species refer to the various biological and ecological characteristics that need to be considered during the farming process of a specific fish species, which are essential for ensuring the healthy growth of fish, optimizing the stocking density, and maintaining good water quality conditions. Among them, the fish species constant reflects the intensity of each fish's demand for oxygen and is used to calculate the oxygen demand of a single fish. The average weight of the fish directly affects its oxygen demand and other physiological needs. As the fish grows, its weight will change, so it needs to be updated or predicted regularly.

[0075] Secondly, each type of fish has its most suitable water temperature range, within which their metabolism is most active and their growth rate is fastest. For example, cold-water fish such as salmon are suitable for lower temperatures, while tropical fish such as tilapia require higher water temperatures. In addition, the pH of the water will also affect the health of fish. Most freshwater fish prefer neutral to slightly alkaline water (pH 6.5-8.5), but some special species may have a narrower or different pH tolerance range.

[0076] Moreover, different fish have different requirements for dissolved oxygen. High oxygen-consuming fish such as trout require higher dissolved oxygen levels, while some bottom fish can tolerate lower dissolved oxygen concentrations. It is also possible to combine the maximum individual length and the reproductive cycle. Since different fish have different maximum growth potentials, combining the maximum individual length can avoid affecting the spatial utilization efficiency of the pond, and by understanding the reproductive habits of fish, it helps to plan the breeding cycle and avoid overcrowding or waste of resources.

[0077] Therefore, by accurately grasping the fish parameters of each species of fish and applying them to the optimization method of fish farming, more scientific and reasonable aquaculture practices can be achieved, farming efficiency and economic benefits can be improved, and the healthy growth of fish can be ensured.

[0078] Step S120: Calculate the fish breeding density of each species according to the current environmental parameters and the parameters of each species of fish.

[0079] In this step, the fish breeding density of each species is calculated according to the current environmental parameters and the parameters of each species of fish, which specifically includes calculating the oxygen supply in the breeding area according to the current environmental parameters, and then calculating the oxygen demand of each species of fish according to the current environmental parameters and the parameters of each species of fish, and finally calculating the fish breeding density of each species according to the oxygen supply in the breeding area and the oxygen demand of each species of fish.

[0080] Specifically, it is first necessary to calculate the oxygen supply in the breeding area based on the current environmental parameters of the breeding area obtained, specifically including calculating the water volume of the breeding area, and then calculating the oxygen supply in the breeding area based on the water volume of the breeding area and the dissolved oxygen content per unit water volume.

[0081] Furthermore, the fish species constant, average body weight, ideal water temperature and environmental correction factor of each species are determined, and then the oxygen requirement of each species of fish is calculated based on the current environmental parameters and the parameters of each species of fish.

[0082] Finally, based on the oxygen supply in the breeding area and the oxygen demand of each species of fish, the breeding density of each species of fish is calculated to obtain the maximum breeding number of a certain species of fish without causing hypoxia, and then the optimal breeding density recommendation for each species of fish is given based on the calculation results.

[0083] In this embodiment, the optimal breeding density is dynamically calculated based on the physical characteristics of the breeding area (such as area and depth) and real-time environmental factors (such as water temperature, dissolved oxygen, and pH value), so as to determine the optimal fish density through scientific calculation, avoid overstocking or insufficient breeding density, ensure the rational use of breeding resources, thereby increasing fish production per unit area and maximizing economic benefits. At the same time, it can also be improved by combining machine learning and regression analysis to improve prediction accuracy and decision-making efficiency.

[0084] In some embodiments, in step S120, the fish breeding density of each species is calculated according to the current environmental parameters and the parameters of each species of fish, including the following steps:

[0085] Calculate oxygen supply in the breeding area based on current environmental parameters;

[0086] Calculate the oxygen requirement of each fish species based on the current environmental parameters and the parameters of each fish species;

[0087] Calculate the fish stocking density for each species based on the oxygen supply in the culture area and the oxygen demand of each species of fish.

[0088] In this embodiment, fish parameters include fish species, and current environmental parameters include multiple environmental factor data in the breeding area. First, the oxygen supply in the breeding area is calculated, where the dissolved oxygen content represents the concentration of oxygen in the water body, which can be obtained through real-time monitoring by a dissolved oxygen sensor.

[0089] Specifically, the formula for calculating the oxygen supply in the breeding area includes:

[0090] O s =C o ×V;

[0091] V = L × W × D;

[0092] Among them, O s is the oxygen supply in the breeding area, C ois the oxygen concentration per unit volume of water, V is the water volume of the aquaculture area, L is the length of the water in the aquaculture area, W is the width of the water in the aquaculture area, and D is the average depth of the water in the aquaculture area.

[0093] In this embodiment, the oxygen supply in the breeding area refers to the total amount of oxygen that can be provided to fish and other organisms in the water body of the breeding area within a specific period of time. The oxygen supply in the breeding area is crucial to ensure the healthy growth of fish, because sufficient dissolved oxygen is one of the key factors in maintaining high-density breeding and good water quality. Therefore, it is necessary to determine the optimal breeding density of the breeding area by calculating the oxygen supply in the breeding area to ensure that there is no lack of oxygen during the fish breeding process.

[0094] Specifically, the water volume of the breeding area is calculated through the three dimensions of length, width and depth of the breeding area, which is used as the basic parameter in the calculation of the optimal breeding density, and then the oxygen supply of the breeding area is calculated according to the water volume of the breeding area and the dissolved oxygen content of the breeding area.

[0095] In some embodiments, the pond volume is calculated by the length, width and average depth of the pond. Specifically, the pond volume V is calculated as V=L×W×D, where L is the length of the pond (unit: meter), W is the width of the pond (unit: meter), and D is the average depth of the pond (unit: meter).

[0096] In addition, C o It is the oxygen concentration per unit volume of water, which is mainly obtained through real-time monitoring of dissolved oxygen sensors. It reflects the amount of oxygen contained in each unit volume of water. In addition, the oxygen concentration will be affected by many factors, including natural light (to promote photosynthesis), temperature, wind stirring, operation of artificial oxygenation equipment, etc. Therefore, real-time monitoring of dissolved oxygen content can reduce the impact of other environmental factors on fish farming. Calculating the total oxygen supply in the breeding area will help decide when to start the oxygenation equipment or adjust the feeding amount to avoid fish death or poor growth due to lack of oxygen.

[0097] Furthermore, the formula for calculating the oxygen requirement of each species of fish includes:

[0098] O d =K×W×(T+273);

[0099] Among them, O d is the oxygen requirement of a single fish of a single fish, K is the fish species, W is the average weight of a single fish, and T is the culture temperature of the culture area.

[0100] In this embodiment, water temperature affects the metabolism of fish and is therefore an important parameter for calculating oxygen demand. Furthermore, the weight of fish at different growth stages will change, and the average weight of fish will directly affect their oxygen demand. Therefore, it is necessary to dynamically update the weight of fish of different qualities at different growth stages.

[0101] Specifically, it is preferred to calculate the average weight of the fish by regular sampling measurements, or predict the change of the fish weight by a growth model, wherein the unit of the fish weight W is gram (g) or kilogram (kg). In addition, different fish species have different requirements for oxygen, and the fish species constant K is used to represent the oxygen demand intensity of each fish. It can be obtained based on the experimental data of specific fish at different water temperatures and growth stages, and is an inherent constant of each fish. Specifically, different constant values ​​are set for each fish according to the experimental data.

[0102] Furthermore, the oxygen requirements of different types of fish can be calculated based on the parameters of different types of fish, and then the dissolved oxygen content of the breeding environment can be changed through natural dissolution and artificial oxygenation, thereby improving the survival rate of fish.

[0103] Furthermore, the calculation formula for the fish farming density of each species includes:

[0104]

[0105] f(T,pH)=α(T-T0)+β(pH-pH0);

[0106] Wherein, N is the fish farming density of a single fish, f(T, pH) is the correction coefficient of farming temperature and pH, α is the influence coefficient of preset water temperature on oxygen demand, β is the influence coefficient of preset pH on oxygen demand, T0 is the preset ideal farming temperature, pH is the pH of the farming area, and pH0 is the preset ideal pH.

[0107] In this embodiment, the environmental correction coefficient f(T, pH) is used to correct the oxygen demand of fish in a specific environment, which is specifically determined based on environmental parameters such as water temperature and pH. Among them, the influence of water temperature T in the calculation of f(T, pH) can be determined by experimental data. For example, for every 1°C increase in temperature, the metabolism of fish increases by a certain percentage, thereby affecting the oxygen demand. By introducing environmental parameter influencing factors, the calculation of breeding density can be made more precise. Considering the specific effects of different environmental conditions on fish growth, the accuracy of breeding density calculation can be significantly improved, and the uncertainty caused by environmental fluctuations can be reduced, thereby dynamically adjusting the oxygen demand forecast of fish, thereby optimizing breeding strategies.

[0108] In addition, since changes in pH have a certain impact on the growth of fish, it is preferred to pre-set a series of ideal environmental parameter ranges based on experimental and empirical data and according to the needs of different fish species to make the data more referenceable, and then consider the oxygen consumption rate of individual fish and the impact of environmental conditions on oxygen demand to ensure that the pond space is maximized for fish farming without causing hypoxia.

[0109] Step S130: Calculate the optimal breeding density of the breeding area according to the breeding density of each species of fish.

[0110] In this step, the optimal stocking density for fish of different qualities in the breeding area can be determined based on the stocking density of different species of fish and the environmental parameters of the breeding area, thereby ensuring the best growth environment for fish, reducing fish deaths caused by environmental changes, and improving breeding efficiency and economic benefits.

[0111] In some embodiments, the formula for calculating the optimal breeding density in the breeding area includes:

[0112]

[0113] Among them, N is the optimal breeding density, A is the area of ​​the breeding area, D is the average depth of the water body in the breeding area, and E is env is the influencing factor of the current environmental parameters, F load is the fish load factor per unit water body.

[0114] In this embodiment, the optimal fish density is determined through scientific calculations, which avoids overstocking or insufficient breeding density, ensures the rational use of breeding resources, and thus increases the fish yield per unit area and maximizes economic benefits.

[0115] Specifically, the influencing factors of environmental parameters in calculating the optimal breeding density in the breeding area are preferably obtained through real-time monitoring of environmental conditions such as water temperature, dissolved oxygen, pH value, etc., which mainly affect the growth and survival of fish. The fish load coefficient per unit water body is preferably obtained by comprehensive calculation of water body volume, oxygen demand, fish species and environmental data, and is used to represent the maximum number of fish that can be cultured per unit water body.

[0116] Step S140: Calculate ideal environmental parameters of the breeding area based on the current environmental parameters of the breeding area and the optimal breeding density.

[0117] In this step, the ideal environmental parameters of the breeding area are calculated by combining the optimal breeding density of different species of fish and the current environmental parameters of the breeding area. The breeding plan is then adjusted according to the ideal environmental parameters, and suggestions are given for releasing or reducing the number of fish, providing an intelligent breeding plan.

[0118] In some embodiments, a sensor network can be deployed to monitor the real-time environmental parameters of the aquaculture area in real time. Specifically, multiple types of sensors can be installed to monitor key environmental parameters, such as: Water temperature sensor: used to measure water temperature. Dissolved oxygen sensor: detects oxygen concentration in water. pH sensor: measures water acidity. Ammonia nitrogen and nitrite sensors: monitor the content of harmful substances. Turbidity sensor: evaluates water transparency.

[0119] Furthermore, the data collected by the sensors are transmitted to the central control system through a wireless or wired network to realize data collection and transmission, ensuring the stability and real-time performance of data transmission so as to quickly respond to environmental changes.

[0120] Furthermore, the central control system analyzes and processes the received data, generates intuitive charts and reports, and realizes the visualization of data analysis. It can also provide a user interface so that managers can view the status of each monitoring point in real time.

[0121] In some embodiments, ideal environmental parameters for the farming area include:

[0122] Q feed =N×F(W,T,O2,D,α);

[0123] Among them, Q feed is the feeding amount for breeding, N is the optimal breeding density, W is the weight of a single fish, T is the water temperature in the breeding area, O2 is the dissolved oxygen content in the breeding area, D is the fish growth stage coefficient, and α is the unit water load coefficient.

[0124] In this embodiment, the stocking density is closely related to the stocking feeding amount. Reasonable stocking density can directly affect the growth rate and health status of fish, while the stocking feeding amount needs to be adjusted according to the stocking density, fish species, growth stage and environmental factors. Therefore, it is necessary to calculate the ideal environmental parameters of the stocking area based on the optimal stocking density according to the current environmental parameters of the stocking area.

[0125] Specifically, in calculating the ideal environmental parameters of the breeding area, N is the optimal breeding density, the number of fish in the pond. As the number of fish increases, the feeding amount will also increase accordingly; W is the weight of a single fish. The heavier the fish, the more food it requires. Therefore, when calculating the feeding amount, the weight of a single fish needs to be taken into consideration.

[0126] Furthermore, T is the water temperature, which affects the appetite and metabolic rate of fish. Usually when the temperature is higher, the metabolism and appetite of fish are stronger, so they need more food. O2 is dissolved oxygen, which directly affects the growth of fish. When there is sufficient oxygen, the digestive system of fish can work better, thus requiring more food.

[0127] Furthermore, D is the fish growth stage coefficient. The growth stage of fish determines its metabolic needs and food intake. For example, in the juvenile stage, the fish's feeding needs are usually high, while in the mature stage, the feeding needs will decrease; α is the unit water load coefficient, which is closely related to the carrying capacity of the water body in the breeding area. The higher the load coefficient, the more fish the unit water body can support, and the corresponding feeding amount will also increase.

[0128] Furthermore, F(W,T,O2,D,α) represents a comprehensive consideration of the weight of a single fish, the water temperature of the breeding area, the dissolved oxygen content in the breeding area, the fish growth stage coefficient and the unit water load coefficient. It is used to calculate the feeding amount of a single fish based on a variety of environmental and biological factors. The calculation can ensure that under different environmental conditions, the fish can obtain the right amount of food to maintain their healthy growth and optimal production performance.

[0129] Step S150, responding to the breeding equipment in the breeding area to adjust the breeding parameters of the breeding equipment in real time according to the ideal environmental parameters.

[0130] In this step, by responding to the breeding equipment in the breeding area and adjusting the breeding parameters of the breeding equipment in real time according to the ideal environmental parameters, it is possible to calculate and adjust the breeding density in time according to the real-time environmental parameters (such as water temperature, dissolved oxygen, pH value, etc.), to ensure that the fish are always in the best growth conditions, reduce the stress response of fish caused by environmental changes, and improve the success rate of breeding. In addition, intelligent monitoring and control equipment can be used to achieve automatic oxygenation, automatic feeding and other operations, reducing the complexity and cost of manual management.

[0131] Specifically, by real-time monitoring of the real-time environmental parameters of the breeding area, and then based on the ideal environmental parameters, adjusting the breeding parameters of the breeding equipment according to the real-time environmental parameters, and then dynamically adjusting the breeding quantity or controlling the oxygenation equipment according to the breeding parameters, ensure that the dissolved oxygen and other parameters in the pond are maintained at the optimal level.

[0132] In some embodiments, the aquaculture equipment includes oxygenation equipment, feeding equipment, etc., which are specifically controlled according to ideal environmental parameters and real-time environmental parameters. For example, when it is detected that there is insufficient oxygen in the water or the temperature is too high, the adjustment equipment is automatically started to maintain the best growth environment for fish. By continuously monitoring the water quality and adjusting the oxygenation equipment, feeding amount, etc., the disease and death of fish caused by water quality deterioration (such as hypoxia or excessive ammonia nitrogen) are reduced, and the stability of the ecological environment of the water body is guaranteed. Then, as the environmental parameters such as water temperature and oxygen concentration change, the aquaculture density is continuously adjusted to maintain the best aquaculture conditions in the aquaculture environment.

[0133] In some embodiments, in step S150, responding to the farming equipment in the farming area to adjust the farming parameters of the farming equipment in real time according to the ideal environmental parameters includes the following steps:

[0134] Real-time monitoring of real-time environmental parameters in the breeding area;

[0135] Based on the ideal environmental parameters, the breeding parameters of the breeding equipment are adjusted according to the real-time environmental parameters.

[0136] In this embodiment, by continuously monitoring water quality and adjusting oxygenation equipment, feeding amount, etc., fish diseases and deaths caused by water quality deterioration (such as lack of oxygen or excessive ammonia nitrogen) are reduced, ensuring the stability of the water ecological environment.

[0137] In some embodiments, environmental data is first collected, and the water temperature, dissolved oxygen, pH value and other parameters in the pond are collected in real time through the environmental monitoring module and transmitted to the control center. Then, the sensor module is installed in the pond and the surrounding environment to monitor the environmental parameters in real time, such as water temperature, dissolved oxygen, pH value, ammonia nitrogen concentration, etc. In addition, it also includes detecting basic physical data such as the size and depth of the pond, and then the data collected by the sensor is transmitted to the central control system through the wireless network through the data collection and transmission system for calculation and decision-making.

[0138] Furthermore, the central control algorithm module uses a computational model and algorithm to dynamically calculate the optimal breeding density based on the physical characteristics of the pond and real-time environmental factors, and then uses a feedback control system to control feeding, oxygenation or other breeding equipment according to the algorithm calculation results to keep the fish in the best growth state.

[0139] Furthermore, the stocking density is calculated, specifically by combining the pond size and fish species to calculate the optimal fish stocking density data. If the current number of fish is too high or too low, a corresponding prompt is generated, and oxygenation control or the number of fish released is adjusted through automated equipment to ensure the health and stability of the water body. At the same time, as environmental parameters such as water temperature and oxygen concentration change, the stocking density can be continuously adjusted to maintain the optimal stocking conditions, which not only improves the stocking efficiency, but also reduces manual intervention, reduces management costs, and achieves more scientific and reasonable aquaculture management.

[0140] In some embodiments, the breeding parameters of the breeding equipment are adjusted in real time according to the ideal environmental parameters. For example, for the oxygenation equipment, when the dissolved oxygen is detected to be lower than the ideal value, the oxygenation pump is automatically started to increase the oxygen supply; conversely, when the dissolved oxygen is too high, the amount of oxygenation is reduced. For the heating / cooling system: according to the degree to which the water temperature deviates from the ideal value, the heater or cooling device is activated to maintain a suitable water temperature. For the pH adjustment system: adjust the pH value of the water in the breeding area to the ideal range by adding an appropriate amount of acid or alkali. For the filtration and purification system: when ammonia nitrogen or nitrite exceeds the standard, enhance the filtration and purification process to remove harmful substances. For the feeding system: optimize the feeding frequency and amount according to the feeding behavior of the fish and environmental conditions to avoid water quality deterioration caused by excessive feeding.

[0141] In addition, by adopting optimization methods such as machine learning and regression analysis, the density calculation method can be continuously optimized through historical data to improve prediction accuracy and decision-making efficiency, so that the entire fish farming optimization method can be self-perfected and improved in practical applications, so as to be applied to a variety of farming scenarios, such as fresh water, seawater or circulating water bodies, etc., to enhance adaptability and meet the needs of different aquaculture conditions. It has broad application prospects and will ultimately not only significantly improve the economic benefits of fish farming, but also ensure ecological sustainability and the automation and intelligent management of the farming process, and have strong market competitiveness and technological innovation.

[0142] In this embodiment, the current environmental parameters of the breeding area and the parameters of each species of fish are obtained; the breeding density of each species of fish is calculated according to the current environmental parameters and the parameters of each species of fish; the optimal breeding density of the breeding area is calculated according to the breeding density of each species of fish; the ideal environmental parameters of the breeding area are calculated based on the optimal breeding density according to the current environmental parameters of the breeding area; the breeding parameters of the breeding equipment in the breeding area are adjusted in real time according to the ideal environmental parameters in response to the breeding equipment, the optimal breeding density can be determined according to the breeding environment and fish data, and the breeding environment can be dynamically adjusted in real time in combination with the breeding environment data and the fish data, thereby improving the survival rate and breeding yield of fish breeding, and improving the breeding efficiency and economic benefits.

[0143] Therefore, the implementation method of this embodiment not only takes into account the physical characteristics of the pond (such as size and depth), but also comprehensively considers the effects of various environmental factors (such as water temperature, dissolved oxygen, pH value, etc.) on fish growth, and realizes intelligent management of breeding density by constructing an accurate mathematical calculation method. Moreover, through the adaptability and continuous optimization capabilities of the overall method, as well as its wide applicability in different breeding environments, it not only improves the efficiency of aquaculture, but also promotes ecological sustainable development, provides new ideas and technical support for modern aquaculture, and helps promote the transformation of the industry towards a more efficient and environmentally friendly direction.

[0144] like Figure 2 As shown, some embodiments of the present application provide a fish farming optimization system, the system includes a data acquisition module 210, a first calculation module 220, a second calculation module 230, a third calculation module 240, and a data adjustment module 250. Specifically:

[0145] The data acquisition module 210 is used to obtain the current environmental parameters of the breeding area and the parameters of each species of fish.

[0146] The first calculation module 220 is used to calculate the fish breeding density of each species according to the current environmental parameters and the preset fish parameters.

[0147] The second calculation module 230 is used to calculate the optimal breeding density of the breeding area according to the breeding density of each fish species.

[0148] The third calculation module 240 is used to calculate the ideal environmental parameters of the breeding area based on the current environmental parameters of the breeding area and the optimal breeding density.

[0149] The data adjustment module 250 is used to respond to the farming equipment in the farming area to adjust the farming parameters of the farming equipment in real time according to the ideal environmental parameters.

[0150] In some embodiments, the first calculation module 220 may include: calculating the oxygen supply of the breeding area according to the current environmental parameters;

[0151] In some embodiments, the first calculation module 220 may include: calculating the oxygen demand of each species of fish according to the current environmental parameters and the parameters of each species of fish.

[0152] In some embodiments, the first calculation module 220 may include: calculating the fish farming density of each species according to the oxygen supply in the farming area and the oxygen demand of each species of fish.

[0153] In some implementations, the first calculation module 220 may include:

[0154] O s =C o ×V;

[0155] V = L × W × D;

[0156] Among them, O s is the oxygen supply in the breeding area, C o is the oxygen concentration per unit volume of water, V is the water volume of the aquaculture area, L is the length of the water in the aquaculture area, W is the width of the water in the aquaculture area, and D is the average depth of the water in the aquaculture area.

[0157] In some implementations, the first calculation module 220 may include:

[0158] O d =K×W×(T+273);

[0159] Among them, O d is the oxygen requirement of a single fish of a single fish, K is the fish species, W is the average weight of a single fish, and T is the culture temperature of the culture area.

[0160] In some implementations, the first calculation module 220 may include:

[0161]

[0162] f(T,pH)=α(T-T0)+β(pH-pH0);

[0163] Wherein, N is the fish farming density of a single fish, f(T, pH) is the correction coefficient of farming temperature and pH, α is the influence coefficient of preset water temperature on oxygen demand, β is the influence coefficient of preset pH on oxygen demand, T0 is the preset ideal farming temperature, pH is the pH of the farming area, and pH0 is the preset ideal pH.

[0164] In some implementations, the second calculation module 230 may include:

[0165]

[0166] Among them, N is the optimal breeding density, A is the area of ​​the breeding area, D is the average depth of the water body in the breeding area, and E is env is the influencing factor of the current environmental parameters, F load is the fish load factor per unit water body.

[0167] In some implementations, the third calculation module 240 may include:

[0168] Q feed =N×F(W,T,O2,D,α);

[0169] Among them, Q feed is the feeding amount for breeding, W is the weight of a single preset fish, T is the water temperature of the breeding area, O2 is the dissolved oxygen content in the breeding area, D is the fish growth stage coefficient, and α is the unit water load coefficient.

[0170] In some embodiments, the data adjustment module 250 may include: real-time monitoring of real-time environmental parameters of the breeding area.

[0171] In some embodiments, the data adjustment module 250 may include: adjusting the farming parameters of the farming equipment according to the real-time environmental parameters based on the ideal environmental parameters.

[0172] It should be noted that the fish farming optimization system provided in this embodiment and the above-mentioned fish farming optimization method are based on the same inventive concept, so the relevant content of the above-mentioned fish farming optimization method is also applicable to the content of the fish farming optimization system, and therefore, it will not be repeated here.

[0173] In order to solve the technical problems of low aquaculture output and low survival rate, the system obtains the current environmental parameters of the aquaculture area and the parameters of each species of fish; calculates the fish farming density of each species based on the current environmental parameters and the parameters of each species of fish; calculates the optimal farming density of the aquaculture area based on the fish farming density of each species; calculates the ideal environmental parameters of the aquaculture area based on the current environmental parameters of the aquaculture area and the optimal farming density; responds to the aquaculture equipment in the aquaculture area to adjust the aquaculture parameters of the aquaculture equipment in real time according to the ideal environmental parameters. In this way, the optimal aquaculture density can be determined based on the aquaculture environment and fish data, and the aquaculture environment can be dynamically adjusted in real time in combination with the aquaculture environment data and fish data, thereby improving the survival rate and aquaculture output of fish aquaculture, and improving aquaculture efficiency and economic benefits.

[0174] An embodiment of the present application also provides an electronic device, which includes a memory and a processor. The memory stores a computer program, and the processor implements the above-mentioned fish farming optimization method when executing the computer program.

[0175] like Figure 3 , Figure 3 A schematic diagram of the hardware structure of an electronic device provided in an embodiment of the present application, wherein the electronic device includes:

[0176] At least one battery;

[0177] at least one memory;

[0178] at least one processor;

[0179] at least one program;

[0180] The programs are stored in the memory, and the processor executes at least one program to implement the above-mentioned optimization method for fish farming implemented in the present disclosure.

[0181] The electronic device may be any intelligent terminal including a mobile phone, a tablet computer, a personal digital assistant (PDA), a vehicle-mounted computer, etc.

[0182] The electronic device according to the embodiment of the present application is described in detail below.

[0183] The processor 1600 may be implemented by a general-purpose central processing unit (CPU), a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of the present disclosure;

[0184] The memory 1700 can be implemented in the form of a read-only memory (ROM), a static storage device, a dynamic storage device, or a random access memory (RAM). The memory 1700 can store an operating system and other application programs. When the technical solution provided in the embodiments of this specification is implemented by software or firmware, the relevant program code is stored in the memory 1700, and the processor 1600 calls and executes a method for optimizing fish farming in the embodiments of the present disclosure.

[0185] Input / output interface 1800, used to implement information input and output;

[0186] The communication interface 1900 is used to realize the communication interaction between the device and other devices. The communication can be realized through a wired manner (such as USB, network cable, etc.) or a wireless manner (such as mobile network, WIFI, Bluetooth, etc.);

[0187] Bus 2000 , which transmits information between various components of the device (e.g., processor 1600 , memory 1700 , input / output interface 1800 , and communication interface 1900 );

[0188] The processor 1600 , the memory 1700 , the input / output interface 1800 , and the communication interface 1900 are connected to each other in communication within the device via the bus 2000 .

[0189] The embodiment of the present disclosure also provides a storage medium, which is a computer-readable storage medium. The computer-readable storage medium stores computer-executable instructions, and the computer-executable instructions are used to enable a computer to execute the above-mentioned fish farming optimization method.

[0190] The memory, as a non-transient computer-readable storage medium, can be used to store non-transient software programs and non-transient computer executable programs. In addition, the memory may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some embodiments, the memory may optionally include a memory remotely disposed relative to the processor, and these remote memories may be connected to the processor via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0191] The embodiments described in the embodiments of the present disclosure are intended to more clearly illustrate the technical solutions of the embodiments of the present disclosure and do not constitute a limitation on the technical solutions provided by the embodiments of the present disclosure. Those skilled in the art will appreciate that with the evolution of technology and the emergence of new application scenarios, the technical solutions provided by the embodiments of the present disclosure are also applicable to similar technical problems.

[0192] Those skilled in the art will appreciate that the technical solutions shown in the figures do not limit the embodiments of the present disclosure and may include more or fewer steps than shown in the figures, or a combination of certain steps, or different steps.

[0193] The device embodiments described above are merely illustrative, and the units described as separate components may or may not be physically separated, that is, they may be located in one place or distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0194] Those skilled in the art will appreciate that all or some of the steps in the methods disclosed above, and the functional modules / units in the systems and devices may be implemented as software, firmware, hardware, or a suitable combination thereof.

[0195] The terms "first", "second", "third", "fourth", etc. (if any) in the specification of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0196] It should be understood that in the present application, "at least one (item)" means one or more, and "plurality" means two or more. "And / or" is used to describe the association relationship of associated objects, indicating that three relationships may exist. For example, "A and / or B" can mean: only A exists, only B exists, and A and B exist at the same time, where A and B can be singular or plural. The character " / " generally indicates that the objects associated before and after are in an "or" relationship. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single or plural items. For example, at least one of a, b or c can mean: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, c can be single or multiple.

[0197] In the several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0198] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0199] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0200] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including multiple instructions to enable an electronic device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of each embodiment method of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (Read-Only Memory, ROM), random access memory (Random Access Memory, RAM), disk or optical disk and other media that can store programs.

[0201] The above is a specific description of the preferred implementation of the embodiments of the present application, but the embodiments of the present application are not limited to the above-mentioned implementation methods. Technical personnel familiar with the field can also make various equivalent modifications or substitutions without violating the spirit of the embodiments of the present application. These equivalent modifications or substitutions are all included in the scope defined by the claims of the embodiments of the present application.

[0202] The embodiments of the present application are described in detail above in conjunction with the accompanying drawings, but the present application is not limited to the above embodiments. Various changes can be made within the knowledge scope of ordinary technicians in the relevant technical field without departing from the purpose of the present application.

Claims

1. A method for optimizing fish farming, characterized in that: The method comprises: Obtain current environmental parameters of the breeding area and fish parameters of each species; Calculating the fish breeding density of each species according to the current environmental parameters and the fish parameters of each species; Calculate the optimal stocking density in the aquaculture area according to the stocking density of each species of fish; According to the current environmental parameters of the breeding area, the ideal environmental parameters of the breeding area are calculated based on the optimal breeding density; Respond to the farming equipment in the farming area to adjust the farming parameters of the farming equipment in real time according to the ideal environmental parameters.

2. The method for optimizing fish farming according to claim 1, characterized in that: The step of calculating the fish breeding density of each species according to the current environmental parameters and the fish parameters of each species includes: Calculating the oxygen supply in the breeding area according to the current environmental parameters; Calculating the oxygen demand of each species of fish according to the current environmental parameters and the parameters of each species of fish; The fish breeding density of each species is calculated according to the oxygen supply in the breeding area and the oxygen demand of each species of fish.

3. The method for optimizing fish farming according to claim 2, characterized in that: The fish parameters include fish species, and the current environmental parameters include multiple environmental factor data in the breeding area. The calculation formula for calculating the oxygen supply in the breeding area includes: O s =C o ×V; V = L × W × D; Among them, O s is the oxygen supply in the breeding area, C o is the oxygen concentration per unit volume of water, V is the volume of water in the aquaculture area, L is the length of water in the aquaculture area, W is the width of water in the aquaculture area, and D is the average depth of water in the aquaculture area; The calculation formula for calculating the oxygen requirement of each species of fish includes: O d =K×W×(T+273); Among them, O d is the oxygen requirement of a single fish of a single fish, K is the fish species, W is the average weight of a single fish, and T is the culture temperature of the culture area.

4. The method for optimizing fish farming according to claim 3, characterized in that: The calculation formula for calculating the fish farming density of each species includes: f(T,pH)=α(T-T0)+β(pH-pH0); Wherein, N is the fish farming density of a single fish, f(T, pH) is the correction coefficient of farming temperature and pH, α is the influence coefficient of preset water temperature on oxygen demand, β is the influence coefficient of preset pH on oxygen demand, T0 is the preset ideal farming temperature, pH is the pH of the farming area, and pH0 is the preset ideal pH.

5. The method for optimizing fish farming according to claim 1, characterized in that: The formula for calculating the optimal breeding density in the breeding area includes: Among them, N is the optimal breeding density, A is the area of ​​the breeding area, D is the average depth of the water body in the breeding area, and E is the average depth of the water body in the breeding area. env is the influencing factor of the current environmental parameters, F load is the fish load factor per unit water body.

6. The method for optimizing fish farming according to claim 1, characterized in that: The ideal environmental parameters of the breeding area include: Q feed =N×F(W,T,O2,D,α); Among them, Q feed is the feeding amount for breeding, N is the optimal breeding density, W is the weight of a single fish, T is the water temperature in the breeding area, O2 is the dissolved oxygen content in the breeding area, D is the fish growth stage coefficient, and α is the unit water load coefficient.

7. The method for optimizing fish farming according to claim 1, characterized in that: The responding to the breeding equipment in the breeding area to adjust the breeding parameters of the breeding equipment in real time according to the ideal environmental parameters includes: Real-time monitoring of real-time environmental parameters of the breeding area; Based on the ideal environmental parameters, the breeding parameters of the breeding equipment are adjusted according to the real-time environmental parameters.

8. An optimization system for fish farming, characterized in that: The system comprises: A data acquisition module is used to obtain the current environmental parameters of the breeding area and the parameters of each species of fish; A first calculation module, used for calculating the fish breeding density of each species according to the current environmental parameters and the preset fish parameters; A second calculation module is used to calculate the optimal breeding density of the breeding area according to the breeding density of each species of fish; A third calculation module is used to calculate the ideal environmental parameters of the breeding area based on the optimal breeding density according to the current environmental parameters of the breeding area; The data adjustment module is used to respond to the breeding equipment in the breeding area to adjust the breeding parameters of the breeding equipment in real time according to the ideal environmental parameters.

9. An electronic device, characterized in that: It comprises at least one control processor and a memory for communicating with the at least one control processor; the memory stores instructions executable by the at least one control processor, and the instructions are executed by the at least one control processor so that the at least one control processor can execute the fish farming optimization method described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions, and the computer-executable instructions are used to enable a computer to execute the fish farming optimization method according to any one of claims 1 to 7.

Images