A virtual livestock modeling method and device based on digital twinning and a medium

Abstract

The present application relates to a kind of virtual livestock modeling method based on digital twinning, the method comprises: collecting the real data of livestock, including the body shape data and behavior characteristics of the livestock, including the environmental conditions, breeding information, physiological performance and production performance of the livestock;Based on the real data, the virtual livestock model of the livestock is constructed, including geometric mapping entity and heat production and heat dissipation model, the geometric mapping entity is used to simulate the appearance and behavior of the livestock based on the body shape data and the behavior characteristics;The heat production and heat dissipation model is obtained based on the training of the environmental conditions, the breeding information, the physiological performance and the production performance;Based on the virtual livestock model, simulation is carried out under the set scene, and simulation result is obtained.The technical scheme of the present application, by modeling and simulation to real livestock, realize the management, monitoring and optimization to livestock, so as to provide fine management for livestock production.

Description

Technical Field

[0001] This invention relates to the field of intelligent livestock and poultry farming technology, and in particular to a virtual livestock and poultry modeling method, device and medium based on digital twins. Background Technology

[0002] Traditional livestock farming often relies on experience and intuition for management, making it difficult to achieve refined management, resulting in low production efficiency and serious resource waste. For example, livestock are often kept in crowded, unsanitary, and uncomfortable environments, failing to receive sufficient attention and protection, and diseases are difficult to diagnose and treat in a timely manner. Furthermore, traditional farming requires a large investment of human and material resources and cannot accurately measure the comfort level of each individual pig. In addition, experiments involving livestock in extreme environmental conditions often cannot be conducted if animal welfare requirements are not met. Summary of the Invention

[0003] To address the aforementioned problems, the present invention aims to provide a method, apparatus, and computer-readable storage medium for virtual livestock and poultry modeling based on digital twins. By modeling and simulating real livestock and poultry, the invention enables the management, monitoring, and optimization of livestock and poultry, thereby providing refined management and efficient decision support for livestock and poultry production. At the same time, it reduces damage and costs to real livestock and poultry, and has high economic benefits and social significance.

[0004] To achieve the above objectives, the present invention adopts the following technical solution:

[0005] In a first aspect, this application provides a virtual livestock and poultry modeling method based on digital twins, the method comprising:

[0006] Collect real data on livestock and poultry, including the size data and behavioral characteristics of the livestock and poultry, as well as the environmental conditions, breeding information, physiological performance and production performance of the livestock and poultry;

[0007] Based on the real data, a virtual livestock and poultry model is constructed. The virtual livestock and poultry model includes a geometric mapping entity and a heat production and heat dissipation model. The geometric mapping entity is used to simulate the appearance and behavior of the livestock and poultry based on the body size data and behavioral characteristics. The heat production and heat dissipation model is trained based on the environmental conditions, the breeding information, the physiological performance, and the production performance.

[0008] Based on the virtual livestock model, a simulation was performed in a set scenario, and the simulation results were obtained.

[0009] In one implementation of this application, the collection of real livestock and poultry data includes:

[0010] Real data of the livestock and poultry is collected by pre-set sensors and transmitted through the Internet of Things.

[0011] The method also includes preprocessing the collected data, including data cleaning, data integration, and data transformation.

[0012] In one implementation of this application, the heat production and heat dissipation model is used as input, with the environmental conditions and aquaculture information as input, and the physiological performance and production performance as output, to construct a dataset for training.

[0013] In one implementation of this application, the step of performing simulation based on the virtual livestock model in a set scenario and obtaining simulation results includes:

[0014] Receive test data corresponding to the set scenario, the test data including environmental conditions and aquaculture information of the scenario to be tested;

[0015] The test data is input into the heat generation and dissipation model to predict the physiological and production performance corresponding to the test data.

[0016] In one implementation of this application, the step of performing simulation based on the virtual livestock model in a set scenario and obtaining simulation results further includes:

[0017] The geometrically mapped entity displays the appearance and behavior of livestock and poultry based on the test data and the output of the heat generation and dissipation model; the test data also includes the body size data and behavioral characteristics of the livestock and poultry.

[0018] In one implementation of this application, the test data includes real data of livestock and poultry collected in the set environment, or twin data described by the virtual livestock and poultry model.

[0019] Secondly, this application provides a virtual livestock and poultry modeling device based on digital twins, the device comprising:

[0020] The data acquisition module is used to collect real data on livestock and poultry. The real data includes the body size data and behavioral characteristics of the livestock and poultry, as well as the environmental conditions, breeding information, physiological performance and production performance of the livestock and poultry.

[0021] The model building module is used to construct a virtual livestock and poultry model based on the real data; the virtual livestock and poultry model includes a geometric mapping entity and a heat production and heat dissipation model; the geometric modeling module is used to simulate the appearance and behavior of the livestock and poultry based on the body size data and the behavioral characteristics; the heat production and heat dissipation model is trained based on the environmental conditions, the breeding information, the physiological performance, and the production performance;

[0022] The scenario testing module is used to perform simulations based on the virtual livestock and poultry model in a set scenario and obtain simulation results.

[0023] In one implementation of this application, the data acquisition module collects real data of the livestock and poultry through pre-set sensors and transmits the real data through the Internet of Things; the data acquisition module also preprocesses the collected data, including: data cleaning, data integration and data conversion.

[0024] In one implementation of this application, the heat generation and dissipation are carried out by taking the environmental conditions and the aquaculture information as inputs, and the physiological performance and the production performance as outputs, and constructing a dataset for training.

[0025] The scenario testing module receives test data corresponding to the set scenario. The test data includes the environmental conditions and aquaculture information of the scenario to be tested. The test data is input into the heat production and heat dissipation model to predict the physiological performance and production performance corresponding to the test data.

[0026] The scenario testing module also displays the appearance and behavior of livestock and poultry through the geometric mapping entity based on the test data and the output of the heat generation and dissipation model; the test data also includes the body size data and behavioral characteristics of the livestock and poultry.

[0027] Thirdly, this application provides a computer-readable storage medium storing a computer program, wherein the computer program, when running, controls the device where the computer-readable storage medium is located to execute the virtual livestock and poultry modeling method based on digital twins described in the first aspect.

[0028] Fourthly, this application provides a computer device, including: a processor and a memory, wherein the memory stores a computer program, and the processor executes the computer program to implement the virtual livestock and poultry modeling method based on digital twins described in the first aspect.

[0029] The present invention, by adopting the above technical solution, has the following advantages: In the present invention, real data of livestock and poultry is collected, and based on the body shape data and behavioral characteristics in the real data, a geometric mapping entity of livestock and poultry is constructed to simulate the appearance and behavior of livestock and poultry; then, based on the environmental conditions, breeding information, physiological performance and production performance in the real data, a virtual livestock and poultry model corresponding to the livestock and poultry is trained; based on the trained virtual livestock and poultry model, simulation is carried out in a set scenario, and simulation results are obtained. Thus, by modeling and simulating real livestock and poultry, the management, monitoring and optimization of livestock and poultry can be realized, thereby providing refined management and efficient decision support for livestock and poultry production, while reducing the damage and cost to real livestock and poultry, which has high economic benefits and social significance. Attached Figure Description

[0030] Figure 1 This is a flowchart illustrating a virtual livestock and poultry modeling method based on digital twins provided in an embodiment of this application;

[0031] Figure 2 This is a schematic diagram of the module functions of a virtual livestock and poultry modeling device based on digital twins in an embodiment of this application;

[0032] Figure 3 This is a schematic diagram of the structure of a computer device according to an embodiment of this application. Detailed Implementation

[0033] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the described embodiments of the present invention are within the scope of protection of the present invention.

[0034] To address the problem of low production efficiency caused by the difficulty in achieving refined management in traditional animal husbandry, this application provides a method, apparatus, and computer-readable storage medium for virtual livestock and poultry modeling based on digital twins. The method includes: collecting real data on livestock and poultry, including body size data and behavioral characteristics, as well as environmental conditions, breeding information, physiological performance, and production performance; constructing a virtual livestock and poultry model based on the real data, the virtual model including a geometric mapping entity and a heat production and dissipation model, the geometric mapping entity being used to simulate the appearance and behavior of the livestock and poultry based on the body size data and behavioral characteristics; the heat production and dissipation model being trained based on the environmental conditions, breeding information, physiological performance, and production performance; and conducting simulations based on the virtual livestock and poultry model in a set scenario to obtain simulation results. This application provides refined management for livestock and poultry production.

[0035] See Figure 1 In one aspect of the embodiments of this application, a virtual livestock and poultry modeling method based on digital twins is provided.

[0036] The method includes:

[0037] S11, collect real data on livestock and poultry.

[0038] Specifically, the real data includes the body size and behavioral characteristics of the livestock and poultry, as well as their environmental conditions, breeding information, physiological performance, and production performance.

[0039] Body size data may include, but is not limited to, body dimensions and body structure, such as body length, weight, shoulder height, body height, chest depth, body cavity depth, skeletal structure, and fur color.

[0040] Behavioral characteristics, such as standing, squatting, lying down, walking, running, jumping, foraging, resting, and information such as frequency, duration, speed, and posture of the behavior.

[0041] Environmental conditions can include environmental parameters such as temperature, humidity, oxygen concentration, carbon dioxide concentration, and lighting intensity.

[0042] Aquaculture information includes feed type and dosage, water consumption, cleanliness, and vaccination status.

[0043] Physiological performance can include physiological indicators such as heart rate, respiratory rate, digestion and absorption, and energy consumption.

[0044] Production performance includes indicators such as egg production, meat yield, reproduction rate, and growth rate.

[0045] In this embodiment, different breeds of livestock and poultry should have their corresponding data collected according to their characteristics. Real-world livestock and poultry data is acquired by deploying various intelligent sensing devices (including sensors, cameras, RFID readers, etc.) within the farm. These devices wirelessly transmit the collected data to an IoT platform, enabling real-time monitoring and collection. Simultaneously, the IoT platform can store, process, and analyze this data. Device selection must be based on the actual conditions and needs of the livestock and poultry farm, choosing different types and specifications of intelligent sensing devices and deploying them in key locations and areas to effectively collect real-world livestock and poultry data. Data preprocessing during acquisition includes: data cleaning, data integration, and data transformation. Data cleaning addresses issues such as missing values, outliers, duplicates, and errors in the data to ensure its integrity and accuracy. Data integration involves combining data from different data sources into a single dataset, resolving issues such as naming conflicts and inconsistent data types. Data transformation converts the data into a format suitable for model use; for example, converting categorical data to numerical data or performing feature scaling.

[0046] S12, Based on the real data, construct a virtual livestock model of the livestock.

[0047] The virtual livestock model includes a geometrically mapped entity and a heat generation and dissipation model.

[0048] The geometric mapping entity is used to simulate the appearance and behavior of the livestock and poultry based on the body size data and the behavioral characteristics.

[0049] Specifically, when establishing geometrically mapped entities, key features are extracted from body shape and behavioral characteristic data, such as the body size, center of gravity, and movement trajectory of livestock and poultry. Using 3D modeling software, a geometric model of the livestock and poultry is built based on the extracted feature data. This model can be constructed using polygonal meshes or parametric surfaces. The established geometric model is then optimized in detail, such as adjusting model details, textures, and materials to make the model more realistic. After completion, the established geometric model is compared with real livestock and poultry to verify its accuracy. Different livestock and poultry correspond to different geometrically mapped entities. For the same type of livestock and poultry, multiple different geometrically mapped entities can be established to showcase the typical appearance and behavioral information of livestock and poultry under different growth conditions.

[0050] The heat production and dissipation model is obtained by training based on the environmental conditions, the aquaculture information, the physiological performance, and the production performance.

[0051] Specifically, based on the constructed geometrically mapped entity, a heat production and dissipation model is trained using intelligent algorithms based on environmental conditions, physiological performance, and production performance data. This model simulates the behavior of virtual livestock and poultry, their responses to the external environment, and their health status. In establishing this heat production and dissipation model, environmental conditions and breeding information are used as inputs, and physiological and production performance data are used as outputs. Deep learning and machine learning techniques, such as convolutional neural networks, are used to correlate the environmental conditions, breeding information, physiological performance, and production performance data of livestock and poultry, and a dataset is constructed to train the model. Based on the collected real data and the virtual livestock and poultry model, this model can predict and simulate the physiological and production performance results of virtual livestock and poultry, such as growth rate, feed conversion rate, and disease incidence rate. Simultaneously, the virtual livestock and poultry model can also be used to simulate and monitor the behavior, environmental responses, and health status of livestock and poultry. The geometrically constructed entity determines its display content based on the model input data and prediction results. When new environmental conditions, breeding information, and other data are input, the virtual livestock and poultry model calculates the corresponding physiological and production performance results based on these data, and then applies these results to the geometrically constructed entity to update the display content of the virtual livestock and poultry. This process can be repeated to ensure that the prediction and simulation effects of the virtual livestock and poultry model become more and more accurate.

[0052] S13. Based on the virtual livestock and poultry model, a simulation is performed in a set scenario, and the simulation results are obtained.

[0053] Specifically, virtual livestock models are dynamically trained by continuously receiving livestock data to improve their predictive and simulation accuracy. This data can then be used for various applications, including research, design, and testing. For example, virtual livestock models can be used to design and optimize breeding environments, study the effects of different feed combinations, and test new breeding programs. These applications can help the livestock industry better adapt to market demands and environmental changes, improving breeding efficiency and the sustainability of livestock farming. The received data can be real data collected in actual livestock scenarios or digital twin data generated when using virtual livestock models.

[0054] The aforementioned methods can be applied to livestock and poultry breeding, livestock and poultry health care, disease prevention, and environmental protection. In livestock and poultry breeding, virtual livestock and poultry systems can achieve precise management and optimization of the livestock and poultry production process, improving production efficiency and health levels. In livestock and poultry health care, virtual livestock and poultry systems can achieve real-time monitoring and early warning of livestock and poultry health status, enabling timely detection and treatment of diseases. In environmental protection, virtual livestock and poultry systems can assess and optimize the environmental impact of livestock and poultry farms, reducing pollution and damage to the environment caused by livestock and poultry breeding. Compared with existing technologies, virtual livestock and poultry systems can provide real-time monitoring and control, helping managers better understand the health status, growth, and dietary habits of livestock and poultry on the farm. Simultaneously, it can monitor and control factors such as the environment, feed, and lighting, thereby maximizing production efficiency, reducing resource waste, ensuring animal welfare, reducing environmental pollution, and improving the economic and social benefits of the farm.

[0055] In another aspect of this application, a virtual livestock and poultry modeling device based on digital twins is also provided. This device can be implemented in a computer device in hardware or software.

[0056] like Figure 2 As shown in the embodiment of this application, a virtual livestock and poultry modeling device 200 based on digital twins is provided. The device includes:

[0057] The data acquisition module 201 is used to collect real data of livestock and poultry. The real data includes the body size data and behavioral characteristics of the livestock and poultry, as well as the environmental conditions, breeding information, physiological performance and production performance of the livestock and poultry.

[0058] The model building module 202 is used to construct a virtual livestock and poultry model based on the real data; the virtual livestock and poultry model includes a geometric mapping entity and a heat production and heat dissipation model; the geometric modeling module is used to simulate the appearance and behavior of the livestock and poultry based on the body size data and the behavioral characteristics; the heat production and heat dissipation model is trained based on the environmental conditions, the breeding information, the physiological performance, and the production performance;

[0059] The scenario testing module 203 is used to perform simulations based on the virtual livestock and poultry model in a set scenario and obtain simulation results.

[0060] The apparatus provided in the above embodiments collects real data on livestock and poultry, constructs geometric mapping entities of livestock and poultry based on body size data and behavioral characteristics in the real data, and uses them to simulate the appearance and behavior of livestock and poultry; then, based on environmental conditions, breeding information, physiological performance and production performance in the real data, it trains virtual livestock and poultry models corresponding to the livestock and poultry; based on the trained virtual livestock and poultry models, it performs simulations in a set scenario and obtains simulation results, thereby realizing the management, monitoring and optimization of livestock and poultry by modeling and simulating real livestock and poultry, thus providing refined management for livestock and poultry production.

[0061] The above-mentioned device can be implemented in a computer device in hardware or software, so that the computer device can implement the equivalent frequency response modeling method of offshore oilfield cluster power grid in the embodiments of this application. The specific method can be referred to the description of the foregoing embodiments, and will not be repeated here.

[0062] In this application embodiment, a computer-readable storage medium is also provided, which stores a computer program. When a computer device executes the computer program, it implements the virtual livestock and poultry modeling method based on digital twins in this application embodiment.

[0063] The implemented virtual livestock and poultry modeling method based on digital twins includes the following steps:

[0064] Collect real data on livestock and poultry, including the size data and behavioral characteristics of the livestock and poultry, as well as the environmental conditions, breeding information, physiological performance and production performance of the livestock and poultry;

[0065] Based on the real data, a virtual livestock and poultry model is constructed. The virtual livestock and poultry model includes a geometric mapping entity and a heat production and heat dissipation model. The geometric mapping entity is used to simulate the appearance and behavior of the livestock and poultry based on the body size data and behavioral characteristics. The heat production and heat dissipation model is trained based on the environmental conditions, the breeding information, the physiological performance, and the production performance.

[0066] Based on the virtual livestock model, a simulation was performed in a set scenario, and the simulation results were obtained.

[0067] Reference Figure 3A computer device 600 is provided. This embodiment of the computer device 600 includes a processor 601, a memory 602, and a computer program 603 stored in the memory and executable on the processor 601. When the processor 601 executes the computer program 603, it implements the virtual livestock and poultry modeling method based on digital twins in this embodiment; to avoid repetition, details are omitted here. Alternatively, when the computer program is executed by the processor 601, it implements the functions of each model / unit in the virtual livestock and poultry modeling device based on digital twins in this embodiment; to avoid repetition, details are omitted here.

[0068] The computer device may include, but is not limited to, processor 601 and memory 602. Those skilled in the art will understand that FIG6 is merely an example of computer device 600 and does not constitute a limitation on computer device 600. It may include more or fewer components than shown, or combine certain components, or different components. For example, computer device may also include input / output devices, network access devices, buses, etc.

[0069] The processor 601 may be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor.

[0070] The memory 602 can be an internal storage unit of the computer device 600, such as a hard disk or RAM of the computer device 600. The memory 602 can also be an external storage device of the computer device 600, such as a plug-in hard disk, Smart Media Card (SMC), Secure Digital (SD) card, or Flash Card equipped on the computer device 600. Furthermore, the memory 602 can include both internal and external storage units of the computer device 600. The memory 602 is used to store computer programs and other programs and data required by the computer device. The memory 602 can also be used to temporarily store data that has been output or will be output.

[0071] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0072] In the embodiments provided by this invention, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of the units described above is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection between devices or units through some interfaces, and may be electrical, mechanical, or other forms.

[0073] The integrated units implemented as software functional units described above can be stored in a computer-readable storage medium. These software functional units, stored in a storage medium, include several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) or processor to execute some steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0074] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A virtual livestock and poultry modeling method based on digital twins, characterized in that, The method includes: Collect real data on livestock and poultry, including the size data and behavioral characteristics of the livestock and poultry, as well as the environmental conditions, breeding information, physiological performance and production performance of the livestock and poultry; Based on the real data, a virtual livestock and poultry model is constructed. The virtual livestock and poultry model includes a geometric mapping entity and a heat production and heat dissipation model. The geometric mapping entity is used to simulate the appearance and behavior of the livestock and poultry based on the body size data and behavioral characteristics. The heat production and heat dissipation model is trained based on the environmental conditions, the breeding information, the physiological performance, and the production performance. Based on the virtual livestock and poultry model, a simulation was performed in a set scenario, and the simulation results were obtained. Based on the heat production and heat dissipation model, the environmental conditions and the aquaculture information are used as inputs, and the physiological performance and the production performance are used as outputs to construct a dataset for training. The step of simulating a virtual livestock model under a set scenario and obtaining simulation results includes: receiving test data corresponding to the set scenario, the test data including environmental conditions and breeding information of the scenario to be tested; inputting the test data into the heat production and heat dissipation model to predict the physiological and production performance corresponding to the test data; The process of simulating based on the virtual livestock model in a set scenario and obtaining simulation results also includes: the geometric mapping entity displaying the appearance and behavior of livestock based on the test data and the output of the heat generation and dissipation model; the test data also includes the body size data and behavioral characteristics of the livestock.

2. The virtual livestock and poultry modeling method based on digital twins according to claim 1, characterized in that, The collected real data on livestock and poultry includes: Real data of the livestock and poultry is collected by pre-set sensors and transmitted through the Internet of Things. The method also includes preprocessing the collected data, including data cleaning, data integration, and data transformation.

3. The virtual livestock and poultry modeling method based on digital twins according to claim 1, characterized in that, The test data includes real data of livestock and poultry collected in the set environment, or twin data described by the virtual livestock and poultry model.

4. A virtual livestock and poultry modeling device based on digital twins, characterized in that, The device includes: The data acquisition module is used to collect real data on livestock and poultry. The real data includes the body size data and behavioral characteristics of the livestock and poultry, as well as the environmental conditions, breeding information, physiological performance and production performance of the livestock and poultry. The model building module is used to construct a virtual livestock and poultry model based on the real data; the virtual livestock and poultry model includes a geometric mapping entity and a heat production and heat dissipation model; the geometric mapping entity is used to simulate the appearance and behavior of the livestock and poultry based on the body size data and the behavioral characteristics; the heat production and heat dissipation model is trained based on the environmental conditions, the breeding information, the physiological performance, and the production performance. The scenario testing module is used to perform simulations based on the virtual livestock and poultry model in a set scenario and obtain simulation results. The heat generation and dissipation process uses the environmental conditions and aquaculture information as inputs, and the physiological performance and production performance as outputs to construct a dataset for training. The scenario testing module receives test data corresponding to the set scenario. The test data includes the environmental conditions and aquaculture information of the scenario to be tested. The test data is input into the heat production and heat dissipation model to predict the physiological performance and production performance corresponding to the test data. The scenario testing module also displays the appearance and behavior of livestock and poultry through the geometric mapping entity based on the test data and the output of the heat generation and dissipation model; the test data also includes the body size data and behavioral characteristics of the livestock and poultry.

5. The virtual livestock and poultry modeling device based on digital twins according to claim 4, characterized in that, The data acquisition module collects real data of the livestock and poultry through pre-set sensors and transmits the real data through the Internet of Things. The data acquisition module also preprocesses the acquired data, including data cleaning, data integration, and data transformation.

6. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, which, when executed, controls the device containing the computer-readable storage medium to perform the virtual livestock and poultry modeling method based on digital twins as described in any one of claims 1 to 3.

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