Intelligent environment regulation and control method, device and system for fish breeding

Abstract

The invention relates to an intelligent environment regulation and control method, device and system for fish breeding. The method comprises the following steps: acquiring environmental parameters and historical environmental parameters of an environment where to-be-bred fishes are located, and fish behavior information of the to-be-bred fishes; inputting the historical environmental parameters and the environmental parameters into the trained environmental parameter prediction model to obtain an environmental parameter prediction value in a future target time period; identifying target behavior characteristics of the to-be-bred fishes from the fish behavior information; selecting a target environment parameter value matched with the target behavior characteristic and the target time period based on a preset fish breeding knowledge graph; and controlling an environment regulation and control device associated with the target environment parameter value to regulate and control the environment of the to-be-bred fish based on the target environment parameter. According to the scheme, the fish breeding success rate is effectively increased.

Description

Technical Field

[0001] The present disclosure relates to the field of environmental control technologies, and particularly to an intelligent environmental control method, device, and system for fish breeding. Background Art

[0002] In related technologies, in order to effectively breed various fish, it is necessary to control the breeding environment of fish (such as temperature, water quality, etc.). However, the existing constant temperature circulation system only maintains a fixed water temperature through a heating rod and a water pump, and cannot adapt to the temperature difference between day and night, resulting in frequent stress responses of fry. In addition, existing technologies mostly focus on the adjustment of a single parameter (such as dissolved oxygen or pH value) and lack comprehensive control capabilities. Moreover, at present, manual intervention is still relied on to control environmental parameters. A large amount of human intervention is required in links such as broodstock domestication, induced spawning and hatching, etc., with low efficiency and high costs. Summary of the Invention

[0003] To overcome the problems existing in related technologies, the present disclosure provides an intelligent environmental control method, device, and system for fish breeding.

[0004] According to the first aspect of the embodiments of the present disclosure, an intelligent environmental control method for fish breeding is provided, including:

[0005] Obtaining environmental parameters and historical environmental parameters of the environment where the fish to be bred is located, as well as the fish behavior information of the fish to be bred;

[0006] Inputting the historical environmental parameters and the environmental parameters into a trained environmental parameter prediction model to obtain predicted values of environmental parameters within a future target time period;

[0007] Identifying target behavior characteristics of the fish to be bred from the fish behavior information;

[0008] Based on a preset fish breeding knowledge graph, selecting target environmental parameter values that match the target behavior characteristics and the target time period;

[0009] Controlling environmental control devices associated with the target environmental parameter values to regulate the environment where the fish to be bred is located based on the target environmental parameters.

[0010] In some embodiments of the present disclosure, the fish behavior information includes images of the fish to be bred;

[0011] The identifying target behavior characteristics of the fish to be bred from the fish behavior information includes:

[0012] Inputting the image of the fish to be bred into a pre-trained convolutional neural network model to obtain target behavior characteristics output by the convolutional neural network model after fish behavior recognition of the image of the fish to be bred.

[0013] In some embodiments of the present disclosure, controlling the environmental regulation device associated with the target environmental parameter value to regulate the environment where the fish to be bred is located based on the target environmental parameter includes:

[0014] For each target environmental parameter, selecting the actual environmental parameter corresponding to the target environmental parameter from the environmental parameters;

[0015] Calculating the difference between the target environmental parameter and the corresponding actual environmental parameter to obtain a difference value;

[0016] Controlling the environmental regulation device associated with the target environmental parameter value to regulate the environment where the fish to be bred is located based on the difference value.

[0017] In some embodiments of the present disclosure, the target environmental parameter value includes a first environmental parameter and a second environmental parameter;

[0018] Selecting the target environmental parameter value that matches the target behavior feature and the target time period based on the preset fish breeding knowledge graph includes:

[0019] Based on the fish breeding knowledge graph and the target behavior feature, determining the behavior type of the fish to be bred and the first environmental parameter that matches the behavior type;

[0020] Determining the second environmental parameter required by the fish to be bred during the target time period from the fish breeding knowledge graph.

[0021] In some embodiments of the present disclosure, the method further includes:

[0022] Inputting the environmental parameters and the fish behavior information into the trained spawning plan prediction model to obtain the predicted spawning time of the fish to be bred predicted by the spawning plan prediction model based on the environmental parameters and the fish behavior information and the resource allocation information for spawning.

[0023] In some embodiments of the present disclosure, there are multiple types of fish to be bred, and the method further includes:

[0024] Performing fish type recognition using the image of the fish to be bred to obtain the type to which the fish to be bred belongs;

[0025] Selecting a target breeding mode from the preset breeding mode set according to the type; the target breeding mode includes breeding environmental parameters suitable for the fish to be bred;

[0026] Controlling the environmental regulation device associated with the breeding environmental parameters to regulate the environment where the fish to be bred is located based on the breeding environmental parameters.

[0027] According to a second aspect of the embodiments of the present disclosure, there is provided an intelligent environment control device for fish breeding, including:

[0028] An acquisition unit, configured to acquire environmental parameters and historical environmental parameters of the environment where the fish to be bred is located, as well as fish behavior information of the fish to be bred;

[0029] A prediction unit, configured to input the historical environmental parameters and the environmental parameters into a trained environmental parameter prediction model to obtain predicted values of environmental parameters within a future target time period;

[0030] An identification unit, configured to identify target behavior characteristics of the fish to be bred from the fish behavior information;

[0031] A selection unit, configured to select target environmental parameter values that match the target behavior characteristics and the target time period based on a preset fish breeding knowledge graph;

[0032] A control unit, configured to control an environmental control device associated with the target environmental parameter value to regulate the environment where the fish to be bred is located based on the target environmental parameter.

[0033] According to a third aspect of the embodiments of the present disclosure, an electronic device includes: a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the computer program, the method described in any one of the first aspects is implemented.

[0034] According to a fourth aspect of the embodiments of the present disclosure, there is provided a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the method described in any one of the first aspects is implemented.

[0035] According to a fifth aspect of the embodiments of the present disclosure, there is provided a computer program product, including a computer program. When the computer program is executed by a processor, the method described in any one of the first aspects is implemented.

[0036] The technical solutions provided by the embodiments of the present disclosure may include the following beneficial effects: By obtaining the environmental parameters and historical environmental parameters of the environment where the fish to be bred is located, as well as the fish behavior information of the fish to be bred; inputting the historical environmental parameters and environmental parameters into the trained environmental parameter prediction model to obtain the predicted values of the environmental parameters in the future target time period; identifying the target behavior characteristics of the fish to be bred from the fish behavior information; based on the preset fish breeding knowledge graph, selecting the target environmental parameter values that match the target behavior characteristics and the target time period; controlling the environmental regulation device associated with the target environmental parameter values to regulate the environment where the fish to be bred is located based on the target environmental parameters. Thus, it is possible to flexibly adjust the environmental parameters according to the changes in the environment where the fish is located, so that the fish can continuously be in an environment suitable for breeding, effectively improving the success rate of fish breeding. In addition, this application can automatically adjust the breeding environmental parameters of the fish throughout the process, improving the efficiency and accuracy of environmental parameter regulation and reducing the labor cost.

[0037] It should be understood that the above general description and the following detailed description are only exemplary and explanatory, and cannot limit the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] The accompanying drawings herein are incorporated into the specification and constitute a part of this specification, showing embodiments consistent with the present invention and used together with the specification to explain the principles of the present invention.

[0039] Figure 1 is a flowchart of an intelligent environmental regulation method for fish breeding shown according to an exemplary embodiment.

[0040] Figure 2 is a block diagram of an intelligent environmental regulation device for fish breeding shown according to an exemplary embodiment.

[0041] Figure 3 is a block diagram of a device for an intelligent environmental regulation method for fish breeding shown according to an exemplary embodiment. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0042] Here, the exemplary embodiments will be described in detail, and the examples are shown in the accompanying drawings. When the following description refers to the accompanying drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present invention. On the contrary, they are merely examples of devices and methods consistent with some aspects of the present invention as detailed in the appended claims.

[0043] The terms used in the embodiments of the present disclosure are for the purpose of describing specific embodiments only and are not intended to limit the embodiments of the present disclosure. The singular forms "a" and "the" used in the embodiments of the present disclosure and the appended claims are also intended to include the plural forms unless the context clearly dictates otherwise.

[0044] It should be understood that although the terms first, second, third, etc. may be used in the embodiments of the present disclosure to describe various information, such information should not be limited to these terms. These terms are only used to distinguish information of the same type from each other. For example, without departing from the scope of the embodiments of the present disclosure, the first information may also be referred to as the second information, and similarly, the second information may also be referred to as the first information. Depending on the context, the words "if" and "when" as used herein may be interpreted as "when" or "while" or "in response to determining".

[0045] In addition, various forms of processes shown in the embodiments of the present disclosure may be used, reordering, adding or deleting steps. For example, the steps described in this application can be executed in parallel, sequentially, or in a different order, as long as the desired results of the technical solutions disclosed in the present disclosure can be achieved, and no limitations are imposed herein.

[0046] In the related art, in order to effectively breed various fish species, it is necessary to regulate the breeding environment of fish (such as temperature, water quality, etc.). However, the existing constant temperature circulation system only maintains a fixed water temperature through a heating rod and a water pump, and cannot adapt to the temperature difference between day and night, resulting in frequent stress responses of fry. In addition, the existing technology mostly focuses on the regulation of a single parameter (such as dissolved oxygen or pH value) and lacks comprehensive regulation ability. In addition, manual control of environmental parameters is still relied on at present. A large amount of human intervention is required in links such as broodstock domestication, induced spawning and hatching, which is inefficient and costly.

[0047] To solve the above problems, the present disclosure provides an intelligent environment regulation method, device, and system for fish breeding. By obtaining the environmental parameters and historical environmental parameters of the environment where the fish to be bred is located, as well as the fish behavior information of the fish to be bred; inputting the historical environmental parameters and environmental parameters into the trained environmental parameter prediction model to obtain the predicted environmental parameter values within the future target time period; identifying the target behavior characteristics of the fish to be bred from the fish behavior information; selecting the target environmental parameter values that match the target behavior characteristics and the target time period based on the preset fish breeding knowledge graph; controlling the environmental regulation device associated with the target environmental parameter values to regulate the environment where the fish to be bred is located based on the target environmental parameters. Thus, it is possible to flexibly adjust the environmental parameters according to the changes in the environment where the fish is located, and further enable the fish to continuously be in an environment suitable for breeding, effectively improving the success rate of fish breeding. In addition, this application can automatically adjust the breeding environmental parameters of the fish throughout the process, improving the efficiency and accuracy of environmental parameter regulation and reducing the labor cost.

[0048] Figure 1 is a flowchart of an intelligent environment regulation method for fish breeding shown according to an exemplary embodiment, as Figure 1 shown. It should be noted that the intelligent environment regulation method for fish breeding in the embodiments of the present disclosure is applied to an intelligent environment regulation device for fish breeding. As Figure 1 shown, the method may include the following steps:

[0049] Step 101, obtain the environmental parameters and historical environmental parameters of the environment where the fish to be bred is located, as well as the fish behavior information of the fish to be bred.

[0050] In one embodiment, the above environmental parameters may include any multiple parameters among water temperature, dissolved oxygen content, pH value, conductivity, and water flow velocity data. The above environmental parameters can be collected by corresponding sensors. The above sensors can be arranged in an array form in the hatching pond, nursery pond, and water circulation pipeline.

[0051] In one embodiment, the above fish behavior information may include fish videos or images collected by an underwater camera or an infrared sensor. The fish behavior information can be used to track the fish egg hatching rate (such as the embryonic development stage) and the activity intensity of fry (such as feeding behavior, swimming speed) of the fish to be bred.

[0052] Step 102, input the historical environmental parameters and environmental parameters into the trained environmental parameter prediction model to obtain the predicted environmental parameter values within the future target time period.

[0053] As a possible example, the above environmental parameter prediction model can adopt an LSTM (Long Short-Term Memory) model, which is trained by using the historical environmental parameters and historical breeding data of fish of the same species as the fish to be bred above as training samples.

[0054] In one embodiment, the historical environmental parameters and environmental parameters can be input into the trained environmental parameter prediction model, and the environmental parameter prediction model predicts the environmental parameters within the future target time period based on the historical environmental parameters and environmental parameters, so as to obtain the above environmental parameter prediction values.

[0055] As an example, the 10-year historical hatching records (including historical hatching environment data) and the real-time collected environmental parameters can be input into the trained environmental parameter prediction model to obtain the best water temperature curve (accuracy ±0.3°C) and dissolved oxygen threshold (>7mg / L) within the next 2 hours output by the environmental parameter prediction model.

[0056] Step 103, identify the target behavior characteristics of the fish to be bred from the fish behavior information.

[0057] In one embodiment, in order to identify fish behavior in a timely manner, the target behavior characteristics of the fish to be bred can be identified from the fish behavior information (i.e., fish images or videos).

[0058] As an example, the target behavior characteristics can be the spawning activity of fish, the fish egg hatching rate, or the fry activity intensity.

[0059] In some embodiments of the present application, the fish behavior information includes images of the fish to be bred, and step 103 can specifically include: inputting the images of the fish to be bred into a pre-trained convolutional neural network model, and obtaining the target behavior characteristics output by the convolutional neural network model after identifying the fish behavior of the images of the fish to be bred.

[0060] In one embodiment, the above convolutional neural network model can be trained by using the historical images of fish of the same type as the fish to be bred above.

[0061] In one embodiment, the images of the fish to be bred can be input into a pre-trained convolutional neural network model, and the convolutional neural network model identifies the fish behavior of the images of the fish to be bred and outputs the target behavior characteristics, so that the required fish behavior characteristics can be quickly obtained by using the images, effectively improving the efficiency and accuracy of identifying fish behavior.

[0062] Step 104, based on the preset fish breeding knowledge graph, select the target environmental parameter values that match the target behavior characteristics and the target time period.

[0063] In some embodiments of the present application, the above-mentioned fish breeding knowledge graph can be obtained by integrating multi-source data such as environmental parameters, fish group behavior, breeding results (such as hatching rate, deformity rate), etc.

[0064] In some embodiments of the present application, the target environmental parameter value includes a first environmental parameter and a second environmental parameter. Step 104 may specifically include:

[0065] Based on the fish breeding knowledge graph and the target behavior characteristics, determine the behavior type of the fish to be bred and the first environmental parameter matching the behavior type;

[0066] Determine the second environmental parameter required by the fish to be bred during the target time period from the fish breeding knowledge graph.

[0067] In one embodiment, the fish breeding knowledge graph stores the behavior characteristics, behavior types, and suitable optimal environmental parameters of different fish. Therefore, based on the above-mentioned target behavior characteristics, the behavior type of the corresponding fish to be bred and the first environmental parameter matching the behavior type can be found from the fish breeding knowledge graph. Thus, based on the fish breeding knowledge graph, the most suitable environmental parameters for the current fish to be bred can be quickly determined for environmental regulation, improving the efficiency and accuracy of environmental regulation.

[0068] For example, by analyzing historical data, it is found that the spawning success rate of Schizothorax nukiangensis is the highest when the dissolved oxygen content is 7.5 mg / L, and this dissolved oxygen threshold can be automatically locked.

[0069] In another embodiment, the fish breeding knowledge graph stores the optimal environmental parameters of different fish at different time periods. Therefore, based on the type of the fish to be bred above, the optimal second environmental parameter of the fish to be bred during the target time period can be found from the fish breeding knowledge graph. Thus, based on the fish breeding knowledge graph, the most suitable environmental parameters for the current fish to be bred in the future time period can be quickly determined for environmental regulation, improving the efficiency and accuracy of environmental regulation.

[0070] For example, when it is predicted that the night temperature drops suddenly, the intelligent temperature control box is started in advance for heating to prevent the fish eggs from dying due to temperature difference stress.

[0071] Step 105, control the environmental regulation device associated with the target environmental parameter value to regulate the environment where the fish to be bred is located based on the target environmental parameter.

[0072] In one embodiment, the above environmental control device may include an intelligent temperature control and water circulation system and an automatic execution unit. The intelligent temperature control and water circulation system adopts PWM (pulse width modulation) temperature control technology to heat / cool in time periods according to predicted demands; UV sterilization and biological filtration are integrated in the water circulation purification module to reduce the frequency of water replacement (from once a day to once a week). In the automatic execution unit, the variable frequency water pump group adjusts the water flow rate (0.1 - 0.5 m / s) according to AI instructions to avoid energy waste caused by a constant high flow rate. The nano aeration disk is only started when the dissolved oxygen content is lower than the threshold value to reduce no-load energy consumption.

[0073] For example, the environmental parameter prediction model generates device control instructions (such as water pump speed and aeration volume) within a future target time period according to the requirements of different fish species (for example, Schizothorax nukiangensis prefers slow water flow).

[0074] It should be noted that by real-time monitoring of environmental parameters and fish behavior information, dynamically adjusting the environment according to the actual situation effectively improves the environmental control effect and flexibility, and avoids situations that are not conducive to fish breeding, such as fluctuations in egg hatching rate, caused by fish's maladaptation to the environment.

[0075] In some embodiments of the present application, step 105 may specifically include:

[0076] For each target environmental parameter, select the corresponding actual environmental parameter from the environmental parameters;

[0077] Calculate the difference between the target environmental parameter and the corresponding actual environmental parameter to obtain a difference value;

[0078] Control the environmental control device associated with the target environmental parameter value, and adjust the environment where the fish to be bred is located based on the difference value.

[0079] In some embodiments of the present application, the method may further include:

[0080] Input the environmental parameters and fish behavior information into the trained spawning plan prediction model to obtain the predicted spawning time of the fish to be bred predicted by the spawning plan prediction model based on the environmental parameters and fish behavior information and the resource allocation information for spawning.

[0081] In one embodiment, the above spawning plan prediction model may be obtained by training a machine learning model with historical behavior information, historical environmental parameters, and historical spawning plans of different fish species.

[0082] As an example, the predicted spawning time of the fish to be bred may be a spawning time suggestion, that is, a time suitable for fish spawning given in combination with the actual environmental situation (such as when the water temperature is stable at the beginning of the rainy season), so as to guide artificial induced spawning operations.

[0083] For example, the above resource allocation information for spawning can be to dynamically adjust the water body replacement frequency according to the fry density.

[0084] In some embodiments of the present application, there are multiple types of fish to be bred, and the method may further include:

[0085] Using the image of the fish to be bred to identify the type of the fish, and obtaining the type to which the fish to be bred belongs;

[0086] Selecting a target breeding mode from a preset set of breeding modes according to the type; the target breeding mode includes breeding environment parameters adapted to the fish to be bred;

[0087] Controlling the environmental regulation device associated with the breeding environment parameters, and regulating the environment where the fish to be bred is located based on the breeding environment parameters.

[0088] It should be noted that different types of fish have different environmental requirements. Therefore, it is necessary to set suitable breeding modes according to the types of different fish, so as to quickly configure a suitable growth and breeding environment for different fish, and improve the configuration efficiency.

[0089] In one example, according to the actual requirements of different indigenous fish in the current environment, breeding modes (such as "Schizothorax lissolabiatus mode": water flow speed 0.2 m / s, water temperature 18 - 20 °C; "Schizothorax lancangensis mode": water flow 0.5 m / s, water temperature 16 - 18 °C) and other parameter packages can be preset. Users can switch modes with one key through the man-machine interaction interface, and the system automatically adjusts the parameters of the variable frequency water pump and the temperature control device.

[0090] According to the intelligent environmental regulation method for fish breeding proposed by the embodiments of the present disclosure, by obtaining the environmental parameters and historical environmental parameters of the environment where the fish to be bred is located, as well as the fish behavior information of the fish to be bred; inputting the historical environmental parameters and environmental parameters into the trained environmental parameter prediction model to obtain the predicted value of the environmental parameters in the future target time period; identifying the target behavior characteristics of the fish to be bred from the fish behavior information; based on the preset fish breeding knowledge graph, selecting the target environmental parameter value that matches the target behavior characteristics and the target time period; controlling the environmental regulation device associated with the target environmental parameter value to regulate the environment where the fish to be bred is located based on the target environmental parameters. Thus, it is possible to flexibly adjust the environmental parameters according to the changes in the environment where the fish is located, and further enable the fish to continuously be in a suitable environment for breeding, effectively improving the success rate of fish breeding. In addition, the present application can automatically adjust the breeding environmental parameters of the fish throughout the process, improving the efficiency and accuracy of environmental parameter regulation and reducing the labor cost.

[0091] Figure 2It is a block diagram of an intelligent environment control device for fish breeding shown according to an exemplary embodiment. Refer to Figure 2 , the device includes an acquisition unit 201, a prediction unit 202, an identification unit 203, a selection unit 204, and a control unit 205.

[0092] Among them, the acquisition unit 201 is used to acquire the environmental parameters and historical environmental parameters of the environment where the fish to be bred is located, as well as the fish behavior information of the fish to be bred;

[0093] The prediction unit 202 is used to input the historical environmental parameters and environmental parameters into the trained environmental parameter prediction model to obtain the predicted value of the environmental parameters in the future target time period;

[0094] The identification unit 203 is used to identify the target behavior characteristics of the fish to be bred from the fish behavior information;

[0095] The selection unit 204 is used to select the target environmental parameter value that matches the target behavior characteristics and the target time period based on the preset fish breeding knowledge graph;

[0096] The control unit 205 is used to control the environmental regulation equipment associated with the target environmental parameter value to regulate the environment where the fish to be bred is located based on the target environmental parameter.

[0097] In some embodiments of the present application, the fish behavior information includes the image of the fish to be bred, and the identification unit 203 can specifically be used for:

[0098] Input the image of the fish to be bred into the pre-trained convolutional neural network model, and obtain the target behavior characteristics output by the convolutional neural network model after identifying the fish behavior of the image of the fish to be bred.

[0099] In some embodiments of the present application, the control unit 205 can specifically be used for:

[0100] For each target environmental parameter, select the actual environmental parameter corresponding to the target environmental parameter from the environmental parameters;

[0101] Calculate the difference between the target environmental parameter and the corresponding actual environmental parameter to obtain the difference value;

[0102] Control the environmental regulation equipment associated with the target environmental parameter value to regulate the environment where the fish to be bred is located based on the difference value.

[0103] In some embodiments of the present application, the target environmental parameter value includes a first environmental parameter and a second environmental parameter, and the selection unit 204 can specifically be used for:

[0104] Based on the fish breeding knowledge graph and the target behavior characteristics, determine the behavior type of the fish to be bred and the first environmental parameters matching the behavior type;

[0105] Determine the second environmental parameters required by the fish to be bred during the target time period from the fish breeding knowledge graph.

[0106] In some embodiments of the present application, the device may further include:

[0107] The scheme prediction unit is configured to input the environmental parameters and fish behavior information into the trained spawning scheme prediction model, and obtain the predicted spawning time of the fish to be bred predicted by the spawning scheme prediction model based on the environmental parameters and fish behavior information, as well as the resource allocation information for spawning.

[0108] In some embodiments of the present application, there are multiple types of fish to be bred, and the device may further include:

[0109] The recognition unit is further configured to perform fish type recognition using the image of the fish to be bred to obtain the type to which the fish to be bred belongs;

[0110] The selection unit is further configured to select a target breeding mode from a preset set of breeding modes according to the belonging type; the target breeding mode includes breeding environmental parameters adapted to the fish to be bred;

[0111] The regulation unit is further configured to control the environmental regulation device associated with the breeding environmental parameters, and regulate the environment where the fish to be bred is located based on the breeding environmental parameters.

[0112] Regarding the device in the above embodiments, the specific manners in which each module performs operations have been described in detail in the embodiments related to the method, and will not be elaborated here.

[0113] According to the intelligent environmental regulation device for fish breeding proposed in the embodiments of the present disclosure, by acquiring the environmental parameters and historical environmental parameters of the environment where the fish to be bred is located, as well as the fish behavior information of the fish to be bred; inputting the historical environmental parameters and environmental parameters into the trained environmental parameter prediction model to obtain the predicted value of the environmental parameters in the future target time period; identifying the target behavior characteristics of the fish to be bred from the fish behavior information; based on the preset fish breeding knowledge graph, selecting the target environmental parameter value matching the target behavior characteristics and the target time period; controlling the environmental regulation device associated with the target environmental parameter value to regulate the environment where the fish to be bred is located based on the target environmental parameters. Thus, it is possible to flexibly adjust the environmental parameters according to the changes in the environment where the fish is located, and further enable the fish to continuously be in an environment suitable for breeding, effectively improving the success rate of fish breeding. In addition, the present application can automatically adjust the breeding environmental parameters of the fish throughout the process, improving the efficiency and accuracy of environmental parameter regulation and reducing the labor cost.

[0114] Figure 3 It is a block diagram of a device for an intelligent environment control method for fish breeding shown according to an exemplary embodiment. For example, the device 300 can be an electronic device, such as a mobile phone, a computer, a digital broadcast terminal, a messaging device, a game console, a tablet device, a medical device, a fitness device, a personal digital assistant, etc.

[0115] Referring to Figure 3 , the device 300 can include one or more of the following components: a processing component 302, a memory 304, a power supply component 306, a multimedia component 308, an audio component 310, an input / output (I / O) interface 312, a sensor component 314, and a communication component 316.

[0116] The processing component 302 generally controls the overall operation of the device 300, such as operations associated with display, telephone calls, data communication, camera operations, and recording operations. The processing component 302 can include one or more processors 320 to execute instructions to complete all or part of the steps of the above method. In addition, the processing component 302 can include one or more modules to facilitate the interaction between the processing component 302 and other components. For example, the processing component 302 can include a multimedia module to facilitate the interaction between the multimedia component 308 and the processing component 302.

[0117] The memory 304 is configured to store various types of data to support the operation of the device 300. Examples of such data include instructions for any application or method operating on the device 300, contact data, phone book data, messages, pictures, videos, etc. The memory 304 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, a magnetic disk, or an optical disk.

[0118] The power supply component 306 provides power to various components of the device 300. The power supply component 306 can include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power for the device 300.

[0119] The multimedia component 308 includes a screen that provides an output interface between the device 300 and the user. In some embodiments, the screen may include a liquid crystal display (LCD) and a touch panel (TP). If the screen includes a touch panel, the screen can be implemented as a touch screen to receive input signals from the user. The touch panel includes one or more touch sensors to sense touches, swipes, and gestures on the touch panel. The touch sensors can sense not only the boundaries of the touch or swipe actions, but also detect the duration and pressure associated with the touch or swipe operation. In some embodiments, the multimedia component 308 includes a front camera and / or a rear camera. When the device 300 is in an operating mode, such as a shooting mode or a video mode, the front camera and / or the rear camera can receive external multimedia data. Each of the front camera and the rear camera can be a fixed optical lens system or have a focal length and optical zoom capabilities.

[0120] The audio component 310 is configured to output and / or input audio signals. For example, the audio component 310 includes a microphone (MIC) that is configured to receive external audio signals when the device 300 is in an operating mode, such as a call mode, a recording mode, and a voice recognition mode. The received audio signals can be further stored in the memory 304 or transmitted via the communication component 316. In some embodiments, the audio component 310 further includes a speaker for outputting audio signals.

[0121] The I / O interface 312 provides an interface between the processing component 302 and a peripheral interface module, which can be a keyboard, a click wheel, buttons, etc. These buttons can include, but are not limited to: a home button, a volume button, a power button, and a lock button.

[0122] The sensor component 314 includes one or more sensors for providing a status assessment of various aspects of the device 300. For example, the sensor component 314 can detect the on / off state of the device 300, the relative positioning of components, such as the display and keypad of the device 300. The sensor component 314 can also detect a change in the position of the device 300 or a component of the device 300, the presence or absence of user contact with the device 300, the orientation or acceleration / deceleration of the device 300, and the temperature change of the device 300. The sensor component 314 can include a proximity sensor configured to detect the presence of nearby objects without any physical contact. The sensor component 314 can also include a light sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, the sensor component 314 can further include an acceleration sensor, a gyroscope sensor, a magnetic sensor, a pressure sensor, or a temperature sensor.

[0123] The communication component 316 is configured to facilitate communication between the device 300 and other devices in a wired or wireless manner. The device 300 can access a communication standard-based wireless network, such as WiFi, 2G, or 3G, or a combination thereof. In an exemplary embodiment, the communication component 316 receives a broadcast signal or broadcast-related information from an external broadcast management system via a broadcast channel. In an exemplary embodiment, the communication component 316 further includes a Near Field Communication (NFC) module to facilitate short-range communication. For example, the NFC module can be implemented based on Radio Frequency Identification (RFID) technology, Infrared Data Association (IrDA) technology, Ultra Wideband (UWB) technology, Bluetooth (BT) technology, and other technologies.

[0124] In an exemplary embodiment, the device 300 can be implemented by one or more Application Specific Integrated Circuits (ASICs), Digital Signal Processors (DSPs), Digital Signal Processing Devices (DSPDs), Programmable Logic Devices (PLDs), Field Programmable Gate Arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components for performing the above method.

[0125] In an exemplary embodiment, a non-transitory computer-readable storage medium including instructions is also provided, such as a memory 304 including instructions, and the above instructions can be executed by a processor 320 of the device 300 to complete the above method. For example, the non-transitory computer-readable storage medium can be a ROM, Random Access Memory (RAM), CD-ROM, magnetic tape, floppy disk, and optical data storage device, etc.

[0126] In an exemplary embodiment, a computer program product is also provided, including a computer program, and the computer program implements the above method when executed by a processor 320 of the device 300.

[0127] Those skilled in the art will readily conceive of other embodiments of the present invention after considering the specification and practicing the invention disclosed herein. This disclosure is intended to cover any variations, uses, or adaptations of the present invention that follow the general principles of the present invention and include common general knowledge or conventional technical means in the technical field not disclosed herein. The specification and embodiments are only to be considered exemplary, and the true scope and spirit of the present invention are pointed out by the following claims.

[0128] It should be understood that the present invention is not limited to the exact structures described above and shown in the drawings, and various modifications and changes can be made without departing from its scope. The scope of the present invention is only limited by the appended claims.

Claims

1. An intelligent environment regulation method for fish breeding, characterized in that, Including: Obtain the environmental parameters and historical environmental parameters of the environment where the fish to be bred is located, as well as the fish behavior information of the fish to be bred; Input the historical environmental parameters and the environmental parameters into the trained environmental parameter prediction model to obtain the predicted environmental parameter values within the future target time period; Identify the target behavior characteristics of the fish to be bred from the fish behavior information; Based on the preset fish breeding knowledge graph, select the target environmental parameter values that match the target behavior characteristics and the target time period; Control the environmental regulation device associated with the target environmental parameter value to regulate the environment where the fish to be bred is located based on the target environmental parameter; 2. The intelligent environment regulation method for fish breeding according to claim 1, wherein The fish behavior information includes images of the fish to be bred; The identifying the target behavior characteristics of the fish to be bred from the fish behavior information includes: Input the image of the fish to be bred into the pre-trained convolutional neural network model to obtain the target behavior characteristics output by the convolutional neural network model after identifying the fish behavior of the image of the fish to be bred; 3. The intelligent environment regulation method for fish breeding according to claim 1, wherein The controlling the environmental regulation device associated with the target environmental parameter value to regulate the environment where the fish to be bred is located based on the target environmental parameter includes: For each target environmental parameter, select the actual environmental parameter corresponding to the target environmental parameter from the environmental parameters; Calculate the difference between the target environmental parameter and the corresponding actual environmental parameter to obtain a difference value; Control the environmental regulation device associated with the target environmental parameter value to regulate the environment where the fish to be bred is located based on the difference value; 4. The intelligent environment regulation method for fish breeding according to claim 1, characterized in that The target environmental parameter values include a first environmental parameter and a second environmental parameter; The selecting the target environmental parameter values that match the target behavior characteristics and the target time period based on the preset fish breeding knowledge graph includes: Based on the fish breeding knowledge graph and the target behavior characteristics, determine the behavior type of the fish to be bred and the first environmental parameter that matches the behavior type; Determine the second environmental parameter required by the fish to be bred during the target time period from the fish breeding knowledge graph; 5. The intelligent environment regulation method for fish breeding according to claim 1, wherein Also including: Input the environmental parameters and the fish behavior information into the trained spawning plan prediction model to obtain the predicted spawning time of the fish to be bred predicted by the spawning plan prediction model based on the environmental parameters and the fish behavior information and the resource allocation information for spawning; 6. The intelligent environment regulation method for fish breeding according to claim 2, wherein There are multiple types of the fish to be bred, and the method further includes: Use the image of the fish to be bred to perform fish type identification to obtain the type to which the fish to be bred belongs; Select a target breeding mode from the preset breeding mode set according to the type; the target breeding mode includes breeding environmental parameters suitable for the fish to be bred; Control the environmental regulation device associated with the breeding environmental parameter to regulate the environment where the fish to be bred is located based on the breeding environmental parameter; 7. An intelligent environment control device for fish breeding, characterized in that, Including: An acquisition unit for acquiring the environmental parameters and historical environmental parameters of the environment where the fish to be bred is located, as well as the fish behavior information of the fish to be bred; A prediction unit, configured to input the historical environment parameters and the environment parameters into a trained environment parameter prediction model to obtain predicted values of environment parameters within a future target time period; An identification unit, configured to identify target behavioral characteristics of fish to be bred from the fish behavior information; A selection unit, configured to select target environment parameter values that match the target behavioral characteristics and the target time period based on a preset fish breeding knowledge graph; A control unit, configured to control an environment regulation device associated with the target environment parameter values to regulate the environment where the fish to be bred is located based on the target environment parameters.

8. An electronic device, characterized in that, Comprising: A memory, a processor, and a computer program stored on the memory and executable on the processor, wherein when the processor executes the computer program, the method according to any one of claims 1 to 6 is implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, the method according to any one of claims 1 to 6 is implemented.

10. A computer program product comprising a computer program, characterized in that, When the computer program is executed by the processor, the method according to any one of claims 1 to 6 is implemented.

Images