Breeding management method and system for breeding chickens

Abstract

The embodiment of the invention relates to the technical field of breeding management, and discloses a breeding chicken breeding management method, which comprises the following steps: acquiring a temperature detection image group of each breeding area in a chicken house; acquiring position information of each infrared detection pixel point in the temperature detection image, and performing segmentation processing on the temperature detection image according to the position information to obtain a segmented infrared image; inputting the segmented infrared image into a pre-constructed breeding hen temperature identification model for identification so as to obtain an identification temperature set of each monitored breeding hen in the temperature detection image; and matching the temperature identification set with a set temperature condition, and if the temperature identification set is not matched with the set temperature condition, performing early warning according to the position of the breeding hen to remind corresponding management personnel. According to the scheme, the body temperature of the breeding hens is monitored in real time, and possible health problems such as fever can be found in time, so that preventive measures are taken, and occurrence and diffusion of diseases are avoided. The survival rate of the breeding hens is increased, and the breeding cost is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of breeding management, and in particular to a breeding management method and system for breeding chickens. Background Art

[0002] In livestock and poultry farming, various parameters of animal bodies are one of the key growth indicators. However, due to differences between individual animals and differences in the environment, it is not possible to efficiently measure various parameters of animals. The existing methods generally use manual monitoring, which is highly subjective and cannot achieve refined measurements. Moreover, this method cannot timely and efficiently feedback the actual status of each breeder chicken in the entire chicken house, and cannot achieve refined breeding monitoring and management. Therefore, designing a solution that can perform refined breeding management has become a technical problem that needs to be solved urgently by those skilled in the art. Summary of the invention

[0003] In response to the above-mentioned defects, an embodiment of the present invention discloses a breeding management method for breeder chickens, which can achieve efficient breeding monitoring of breeder chickens, improve the breeding management level of the entire chicken house, and promptly detect abnormal conditions of the monitored breeder chickens.

[0004] The first aspect of the embodiment of the present invention discloses a breeding management method for breeder chickens, comprising:

[0005] A temperature detection image group of each breeding area in the chicken house is obtained by an infrared camera group arranged in the chicken house, wherein the temperature image detection group includes a plurality of temperature detection images, the infrared camera group includes a plurality of infrared cameras, and each breeding area corresponds to an infrared camera;

[0006] Acquire the position information of each infrared detection pixel point in the temperature detection image, and segment the temperature detection image according to the position information to obtain a segmented infrared image associated with each monitored breeder chicken;

[0007] Inputting the obtained segmented infrared images associated with each monitored breeder chicken into a pre-built breeder chicken temperature recognition model for recognition to obtain a recognition temperature set of each monitored breeder chicken in the temperature detection image;

[0008] The temperature identification set is matched with the set temperature condition. If there is a mismatch, an early warning is issued according to the location of the breeder chickens to remind the corresponding management personnel.

[0009] As an optional implementation, in the first aspect of the embodiment of the present invention, the temperature detection image group of the breeding area in the chicken house is obtained by using an infrared camera group arranged in the chicken house, including:

[0010] The infrared camera group arranged in the hatching hen house is used to obtain the temperature detection images of each breeding area in the hen house, wherein the temperature detection images include the temperature images of the breeder chickens to be hatched;

[0011] Acquire temperature detection images of various breeding areas in the chicken house by using an infrared camera group arranged in the brooding and rearing chicken house, wherein the temperature detection images include temperature images of brooding and rearing breeder chickens;

[0012] The temperature detection images of each breeding area in the chicken house are obtained by an infrared camera arranged in the laying hen house, wherein the temperature detection images include the temperature images of laying breeder chickens; the infrared camera includes first position information and second position information, wherein the first position information is used to represent the installation position of the infrared camera, and the second position information is used to represent the position number information of the infrared camera in the corresponding chicken house;

[0013] The step of inputting the obtained segmented infrared images associated with each monitored breeder chicken into a pre-built breeder chicken temperature recognition model for recognition includes:

[0014] Determine a corresponding breeder chicken temperature recognition model according to the first position information, wherein the breeder chicken temperature recognition model includes a hatching breeder chicken temperature model, a brooding and rearing breeder chicken temperature model, and a laying breeder chicken temperature model;

[0015] The segmented infrared images associated with each monitored breeder chicken are input into a pre-built breeder chicken temperature recognition model for recognition.

[0016] As an optional implementation, in the first aspect of the embodiment of the present invention, the step of inputting the segmented infrared image associated with each monitored breeder chicken into a pre-built breeder chicken temperature recognition model for recognition to obtain a recognition temperature set of each monitored breeder chicken in the temperature detection image includes:

[0017] Input the obtained segmented infrared images associated with each monitored breeder chicken into a pre-built breeder chicken temperature recognition model to obtain a first region of interest, a second region of interest, a third region of interest, and a fourth region of interest; obtain parameters of each pixel point associated with the first region of interest, the second region of interest, the third region of interest, and the fourth region of interest;

[0018] Performing temperature statistics on each pixel point data associated with the first region of interest, the second region of interest, the third region of interest, and the fourth region of interest according to a pre-constructed temperature calibration mapping table to determine average temperature information, maximum temperature information, and minimum temperature information of each region of interest;

[0019] The identification temperature set of each monitored breeder chicken is obtained according to the average temperature information, the maximum temperature information and the minimum temperature information of each area of ​​interest.

[0020] As an optional implementation, in the first aspect of the embodiment of the present invention, before the segmented infrared image associated with each monitored breeder chicken is input into a pre-built breeder chicken temperature recognition model, the method further includes:

[0021] Performing recognition processing on the segmented infrared image according to a set grayscale threshold to determine the position information of each fence in the segmented infrared image, and removing the fence image in the segmented infrared image;

[0022] The pixel parameters on the left and right sides of the position information of each fence are obtained, and the corresponding segmented infrared image is color filled according to the pixel parameters on the left and right sides of the position information of each fence to obtain the filled segmented infrared image.

[0023] As an optional implementation, in the first aspect of the embodiment of the present invention, the breeder chicken temperature recognition model is obtained by the following steps:

[0024] Acquire a sample training set, the sample training set comprising breeder chicken sample images; and divide the sample training set into a training set, a validation set, and a test set;

[0025] Performing a preprocessing operation on the breeder chicken sample image;

[0026] Input the preprocessed breeder chicken sample images into the breeder chicken temperature recognition model with completed parameter configuration for training and parameter configuration adjustment until the corresponding breeder chicken temperature recognition model meets the training requirements, and save the current optimal model parameters;

[0027] Use the trained breeder chicken temperature recognition model to predict the breeder chicken test images in the test set to obtain images of various parts in each breeder chicken test image;

[0028] Generate a part confusion matrix according to the prediction results and true annotations of the breeder chicken temperature recognition model; the rows of the part confusion matrix represent the true parts, and the columns represent the predicted parts;

[0029] Calculating the overall performance index of the breeder chicken temperature recognition model according to the part confusion matrix, wherein the overall performance index includes accuracy, precision, recall rate and F1 score;

[0030] And according to the analysis results of the part confusion matrix, the breeder chicken temperature recognition model is adjusted and optimized.

[0031] As an optional implementation, in the first aspect of the embodiment of the present invention, after obtaining the identification temperature set of each monitored breeder chicken in the temperature detection image, the method further includes:

[0032] Performing a data update operation on a corresponding breeder temperature table according to all the identified temperature sets obtained, wherein the breeder temperature table performs position mapping according to the positions of each breeder in the chicken house;

[0033] The breeding management method further comprises:

[0034] The temperature information in the corresponding chicken house is determined by a temperature sensor arranged in the chicken house; and the set temperature condition is updated according to the temperature information.

[0035] As an optional implementation manner, in the first aspect of the embodiment of the present invention, the breeding management method further includes:

[0036] At set intervals, the infrared camera set in the chicken house is used to obtain temperature monitoring images of each breeding area in the chicken house;

[0037] Acquire the position information of each infrared detection pixel point in the temperature monitoring image, and segment the temperature detection image according to the position information to obtain a segmented infrared image associated with each monitored breeder chicken;

[0038] The segmented infrared images associated with each monitored breeder chicken are input into a pre-built breeder chicken temperature recognition model to obtain the head and neck area, the leg and foot area, and the wing area;

[0039] According to the pre-built temperature calibration mapping table, temperature statistics are performed on the pixel data associated with the head and neck area, the leg and foot area, and the wing area to determine the average temperature information of each area of ​​interest;

[0040] The temperature difference information between the two is determined based on the average temperature information of each area of ​​interest obtained from adjacent detection images, and the movement state of the breeder chicken is determined based on the temperature difference information; if the movement state of the breeder chicken does not match the set movement state, an early warning operation is performed.

[0041] A second aspect of an embodiment of the present invention discloses a breeding management method for breeder chickens, comprising:

[0042] The first acquisition module is used to acquire a temperature detection image group of each breeding area in the chicken house through an infrared camera group arranged in the chicken house, wherein the temperature image detection group includes a plurality of temperature detection images, the infrared camera group includes a plurality of infrared cameras, and each breeding area corresponds to an infrared camera;

[0043] The second acquisition module is used to acquire the position information of each infrared detection pixel point in the temperature detection image, and segment the temperature detection image according to the position information to obtain a segmented infrared image associated with each monitored breeder chicken;

[0044] Identification module: used for inputting the segmented infrared images associated with each monitored breeder chicken into a pre-built breeder chicken temperature identification model for identification to obtain an identification temperature set of each monitored breeder chicken in the temperature detection image;

[0045] Early warning module: used to match the temperature identification set with the set temperature conditions. If there is a mismatch, an early warning is issued based on the location of the breeder chickens to remind the corresponding management personnel.

[0046] The third aspect of an embodiment of the present invention discloses an electronic device, comprising: a memory storing executable program code; a processor coupled to the memory; the processor calls the executable program code stored in the memory to execute the breeding and management method for breeding chickens disclosed in the first aspect of the embodiment of the present invention.

[0047] A fourth aspect of an embodiment of the present invention discloses a computer-readable storage medium storing a computer program, wherein the computer program enables a computer to execute the breeding and management method for breeding chickens disclosed in the first aspect of an embodiment of the present invention.

[0048] Compared with the prior art, the embodiments of the present invention have the following beneficial effects:

[0049] In the embodiment of the present invention, by obtaining the position information of each infrared detection pixel in the temperature detection image and performing image segmentation processing on the image, the segmented infrared image associated with each monitored breeder chicken can be accurately obtained. These images are input into the pre-built breeder chicken temperature recognition model for recognition, and the actual body temperature of each breeder chicken can be quickly obtained. This intelligent processing method not only improves management efficiency, but also can timely warn when abnormal temperature is found, reminding management personnel to take corresponding measures.

[0050] By monitoring the body temperature of breeder chickens in real time, possible health problems such as fever can be detected in time, so that preventive measures can be taken to avoid the occurrence and spread of diseases. This helps to improve the survival rate of breeder chickens and reduce breeding costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0052] Figure 1 It is a flow chart of the breeding management method of breeder chickens disclosed in an embodiment of the present invention;

[0053] Figure 2It is a schematic diagram of a specific temperature detection process disclosed in an embodiment of the present invention;

[0054] Figure 3 It is a schematic diagram of a process for detecting the movement status of breeder chickens disclosed in an embodiment of the present invention;

[0055] Figure 4 It is a structural schematic diagram of a breeding management system for breeder chickens provided by an embodiment of the present invention;

[0056] Figure 5 It is a structural schematic diagram of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0057] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0058] It should be noted that the terms "first", "second", "third", "fourth", etc. in the specification and claims of the present invention are used to distinguish different objects rather than to describe a specific order. The terms "including" and "having" in the embodiments of the present invention and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device including 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.

[0059] In livestock and poultry farming, various parameters of animal bodies are one of the key growth indicators. However, due to differences between individual animals and differences in the environment, it is not possible to efficiently measure various parameters of animals. The existing methods generally adopt manual monitoring, which is highly subjective; it is not possible to achieve refined measurement, and this method cannot timely and efficiently feedback the actual status of each breeder in the entire chicken house, and cannot achieve refined breeding monitoring and management. Based on this, the embodiment of the present invention discloses a breeding management method, system, electronic device and storage medium for breeders. By obtaining the position information of each infrared detection pixel point in the temperature detection image and performing image segmentation processing on the image, the segmented infrared image associated with each monitored breeder can be accurately obtained. These images are input into a pre-constructed breeder temperature recognition model for recognition, and the actual body temperature of each breeder can be quickly obtained. This intelligent processing method not only improves management efficiency, but also can timely warn when abnormal temperature is found, reminding managers to take corresponding measures. By real-time monitoring of the body temperature of breeders, possible health problems, such as fever, can be discovered in time, so that preventive measures can be taken to avoid the occurrence and spread of diseases. This helps to improve the survival rate of breeders and reduce breeding costs.

[0060] Embodiment 1

[0061] See also Figure 1 , Figure 1 It is a flow chart of the breeding management method of breeder chickens disclosed in the embodiment of the present invention. Among them, the execution subject of the method described in the embodiment of the present invention is an execution subject composed of software and / or hardware, and the execution subject can receive relevant information by wired or / and wireless means, and can send certain instructions. Of course, it can also have certain processing functions and storage functions. The execution subject can control multiple devices, such as a remote physical server or cloud server and related software, or it can be a local host or server and related software that performs related operations on a device placed somewhere. In some scenarios, multiple storage devices can also be controlled, and the storage devices can be placed in the same place or different places as the devices.

[0062] like Figure 1 As shown, the breeding management method based on breeder chickens includes the following steps:

[0063] S101: obtaining a temperature detection image group of each breeding area in the chicken house by means of an infrared camera group arranged in the chicken house, wherein the temperature image detection group includes a plurality of temperature detection images, the infrared camera group includes a plurality of infrared cameras, and each breeding area corresponds to an infrared camera;

[0064] S102: Acquire position information of each infrared detection pixel point in the temperature detection image, and segment the temperature detection image according to the position information to obtain a segmented infrared image associated with each monitored breeder chicken;

[0065] S103: inputting the obtained segmented infrared images associated with each monitored breeder chicken into a pre-built breeder chicken temperature recognition model for recognition to obtain a recognition temperature set of each monitored breeder chicken in the temperature detection image;

[0066] S104: Match the temperature identification set with the set temperature condition. If there is a mismatch, issue an early warning based on the location of the breeder chickens to alert the corresponding management personnel.

[0067] Generally, the area of ​​a chicken house is large, and the area that each infrared camera can cover is limited, so multiple cameras need to be set up to achieve comprehensive monitoring of the entire chicken house; when each infrared camera acquires infrared images, it is not just for one breeding chicken, but for all breeding chickens in an area.

[0068] The solution of the embodiment of the present invention can capture the temperature information of each breeding area in real time and form a temperature detection image group by means of an infrared camera group arranged in the chicken house. Compared with traditional manual temperature measurement or fixed-point temperature measurement, this method has higher efficiency and accuracy, and can realize comprehensive and real-time monitoring of the temperature in the entire chicken house. Before measurement, the temperature of the measurement environment should be ensured to be stable to avoid the influence of fluctuations in ambient temperature on the measurement results. The stability of ambient temperature can be achieved by adjusting the ventilation and heating equipment of the chicken house. When measuring, external interference factors such as direct sunlight, strong wind, etc. should be minimized. These interference factors may cause errors in the measurement results of the infrared thermal imager. The measurement is performed when the breeder chickens are in a stationary state to avoid the influence of heat generated by movement on the measurement results. It is usually possible to choose to measure in the morning or evening. When measuring, the measurement distance between the infrared thermal imager and the breeder chickens should be kept consistent to ensure the accuracy of the measurement results. Different measurement distances may cause differences in the temperature information captured by the infrared thermal imager.

[0069] This method can also help managers better understand the temperature distribution in the chicken house, so as to adjust the breeding environment according to the actual situation, such as ventilation and warmth, to provide a more suitable living environment for the breeder chickens and promote their healthy growth. When implementing it, further breeding environment control can be achieved by detecting the temperature distribution.

[0070] When configuring specific temperature conditions, there are multiple configuration methods. One is to use a single temperature range, and the other is to set different threshold ranges for different parts. In this way, when performing subsequent matching, all parts must meet the conditions before no warning is issued; if there is a part that does not meet the range, a warning will be issued.

[0071] And when conducting specific temperature identification, it is also necessary to combine it with the specific behavior patterns of the breeder chickens for identification. If the breeder chickens have just exercised, it means that their overall temperature will be higher. If the overall temperature is not at a high level, an early warning will be issued. In other words, the temperature can be comprehensively evaluated in combination with the exercise status of the breeder chickens in the future.

[0072] More preferably, the method of obtaining a temperature detection image group of the breeding area in the chicken house by using an infrared camera group arranged in the chicken house includes:

[0073] S1011: acquiring temperature detection images of various breeding areas in the chicken house by means of an infrared camera group arranged in the hatchery house, wherein the temperature detection images include temperature images of the breeder chickens to be hatched;

[0074] S1012: Acquire temperature detection images of various breeding areas in the chicken house by using an infrared camera group arranged in the brooding and rearing chicken house, wherein the temperature detection images include temperature images of the brooding and rearing breeder chickens;

[0075] S1013: obtaining temperature detection images of various breeding areas in the chicken house by means of an infrared camera arranged in the laying hen house, wherein the temperature detection images include temperature images of laying breeder chickens; the infrared camera includes first position information and second position information, wherein the first position information is used to represent the installation position of the infrared camera, and the second position information is used to represent the position number information of the infrared camera in the corresponding chicken house;

[0076] The step of inputting the obtained segmented infrared images associated with each monitored breeder chicken into a pre-built breeder chicken temperature recognition model for recognition includes:

[0077] Determine a corresponding breeder chicken temperature recognition model according to the first position information, wherein the breeder chicken temperature recognition model includes a hatching breeder chicken temperature model, a brooding and rearing breeder chicken temperature model, and a laying breeder chicken temperature model;

[0078] The segmented infrared images associated with each monitored breeder chicken are input into a pre-built breeder chicken temperature recognition model for recognition.

[0079] By setting up infrared camera groups in the hatchery house, brooding and rearing house, and laying hen house, accurate temperature monitoring can be performed for breeder chickens at different growth stages. This phased management method is more in line with the actual needs of breeder chicken growth and helps to ensure that the environmental conditions at each growth stage are optimal. The temperature parameters of breeder chickens at different stages are actually different, so corresponding parameter updates need to be made for each stage. During the incubation stage, temperature is a key factor affecting embryonic development. The incubation temperature of breeding eggs is generally controlled at around 37.8°C (incubation 1 to 19 days), while during the hatching period (19 to 21 days), the temperature will drop slightly, usually between 36.9°C and 37.2°C. At the same time, factors such as relative humidity and ventilation in the incubation environment will also affect the precise control of temperature. The ambient temperature during the incubation stage should be maintained between 22°C and 26°C, and good ventilation is required. The brooding stage is a critical period for the growth and development of chicks. In the early stage of brooding (1 to 3 days), the temperature of the brooding room needs to be maintained between 40°C and 35°C, and then the temperature is gradually reduced as the chicks age. For example, when the chicks are 4 to 7 days old, the temperature in the brooding room is reduced to 34°C to 33°C; when they are 2 weeks old, it is reduced to 33°C to 32°C; when they are 3 weeks old, it is reduced to 32°C to 30°C; when they are 4 weeks old, it is reduced to 30°C to 28°C. After that, the temperature in the brooding room can be gradually reduced to normal temperature. In addition, the relative humidity during the brooding stage should be maintained at about 65%.

[0080] During the growth stage, the temperature requirements of breeder chickens are relatively low, but they still need to maintain a suitable temperature to promote their normal growth and development. Generally, the temperature of the chicken house during the growth stage is more suitable to be controlled between 20℃ and 25℃. At this time, the chicken house should maintain appropriate ventilation and relative humidity to provide a comfortable living environment.

[0081] During the egg-laying stage, breeder hens need a stable and suitable temperature to maintain their high production performance. The temperature of the chicken house during the egg-laying period is generally controlled between 18°C ​​and 25°C, among which the egg production rate is higher at 13°C to 16°C, and the feed conversion rate is higher at 15°C to 20°C. However, there is also a view that the temperature of the laying hen house should not exceed 28°C, and 22°C to 28°C is the best. At the same time, the minimum temperature of the laying hen house should be kept at no less than 13°C and the maximum temperature should be kept at no more than 30°C to avoid adverse effects of excessive or low temperatures on the egg production rate. At different stages, due to different environments, it is necessary to adjust the corresponding detection and recognition model in combination with the specific environment to improve the accuracy of recognition.

[0082] The corresponding breeder chicken temperature recognition model (hatching breeder chicken temperature model, brooding and rearing breeder chicken temperature model, laying breeder chicken temperature model) is determined based on the first position information (installation position) of the infrared camera. This design makes the temperature recognition model more in line with the actual application scenario and can more accurately identify the actual body temperature of breeder chickens at different growth stages.

[0083] Through the second location information (the location number information of the infrared camera in the corresponding chicken house), the specific location and coverage of each infrared camera can be clearly known, so that the camera resources can be arranged and managed more reasonably. This helps to avoid overlapping coverage and blind spots between cameras and improve monitoring efficiency.

[0084] By inputting the segmented infrared image into the corresponding breeder temperature recognition model for recognition, the body temperature data of each monitored breeder can be quickly obtained. This automated processing method greatly reduces the frequency and intensity of manual intervention and improves management efficiency.

[0085] Accurate temperature monitoring and identification can help to detect abnormal changes in the body temperature of breeder chickens in a timely manner, so as to take preventive measures to avoid the occurrence and spread of diseases. At the same time, the optimized breeding environment can help improve the production performance of breeder chickens, such as improving hatching rate, survival rate, egg production rate, etc.

[0086] Through intelligent temperature monitoring and management, we can reduce the disease and death of breeder chickens caused by unsuitable environment, thereby reducing breeding costs. In addition, reasonable resource allocation and optimization can also reduce energy consumption and labor costs. Another aspect that can be achieved through the above method is the ability to accurately predict the corresponding egg production and the number of breeder chickens that can be supplied.

[0087] More preferably, Figure 2 As shown, the segmented infrared images associated with each monitored breeder chicken are input into a pre-built breeder chicken temperature recognition model for recognition to obtain a recognition temperature set of each monitored breeder chicken in the temperature detection image, including:

[0088] S1031: inputting the obtained segmented infrared images associated with each monitored breeder chicken into a pre-built breeder chicken temperature recognition model to obtain a first region of interest, a second region of interest, a third region of interest, and a fourth region of interest; obtaining parameters of each pixel point associated with the first region of interest, the second region of interest, the third region of interest, and the fourth region of interest;

[0089] S1032: performing temperature statistics on each pixel point data associated with the first region of interest, the second region of interest, the third region of interest, and the fourth region of interest according to a pre-constructed temperature calibration mapping table to determine average temperature information, maximum temperature information, and minimum temperature information of each region of interest;

[0090] S1033: Obtain the identification temperature set of each monitored breeder chicken according to the average temperature information, the maximum temperature information and the minimum temperature information of each area of ​​interest.

[0091] By inputting the segmented infrared image into the breeder temperature recognition model, it is possible to identify the first region of interest, the second region of interest, the third region of interest and the fourth region of interest associated with each monitored breeder. These regions of interest may correspond to different body parts of the breeder (such as the head, chest, wings, legs, etc.), thereby allowing a more refined analysis of the breeder's temperature.

[0092] By obtaining the pixel parameters associated with each region of interest and performing temperature statistics on these pixel data according to the pre-built temperature calibration mapping table, the average temperature, maximum temperature and minimum temperature of each region of interest can be accurately calculated. This processing method improves the accuracy of temperature recognition and helps to more accurately assess the health status of breeder chickens.

[0093] By counting the temperature information of each area of ​​interest, we can get the identification temperature set of each monitored breeder chicken, which contains the temperature data of different parts of the breeder chicken. This comprehensive temperature monitoring method helps to detect small changes in the body temperature of the breeder chicken and take preventive measures in time to prevent the occurrence of diseases.

[0094] Accurate temperature data provides an important reference for breeding management. Based on the identified temperature set of each monitored breeder chicken, more scientific and reasonable breeding plans and management measures can be formulated, such as adjusting breeding density, improving feeding environment, optimizing feed formula, etc., thereby improving the growth performance and health level of breeder chickens.

[0095] The above technical process realizes the automation and intelligence of temperature monitoring of breeder chickens, reduces the frequency and intensity of manual intervention, and improves the efficiency and accuracy of breeding management. At the same time, this intelligent temperature monitoring method also helps to improve the overall intelligence level of the breeding industry and promote the transformation and upgrading of the breeding industry.

[0096] The above methods can achieve comprehensive and refined management, especially if diseases occur in the later stage, so that the corresponding chicken house managers can detect abnormalities earlier. The maximum temperature and the minimum temperature are sensitive indicators that can reflect abnormal changes in the body temperature of breeder chickens earlier. When breeder chickens are infected with diseases or are in a state of stress, their body temperatures tend to fluctuate significantly. By monitoring these sensitive indicators in real time, potential disease risks can be discovered in time. Combining temperature data with preset threshold ranges, an abnormal early warning mechanism can be established. When the temperature data exceeds the normal range, the system will automatically issue a warning signal to remind chicken house managers to take timely countermeasures. This early warning mechanism helps to achieve early detection and early intervention of diseases.

[0097] More preferably, before inputting the obtained segmented infrared images associated with each monitored breeder chicken into a pre-built breeder chicken temperature recognition model, the method further includes:

[0098] Performing recognition processing on the segmented infrared image according to a set grayscale threshold to determine the position information of each fence in the segmented infrared image, and removing the fence image in the segmented infrared image;

[0099] The pixel parameters on the left and right sides of the position information of each fence are obtained, and the corresponding segmented infrared image is color filled according to the pixel parameters on the left and right sides of the position information of each fence to obtain the filled segmented infrared image.

[0100] By setting the grayscale threshold to identify and remove the fence image in the segmented infrared image, the interference factors in the image can be effectively reduced. Fences are common elements in the breeding environment, and their presence may block or affect the temperature monitoring of breeder chickens. After removing the fence image, the subsequent temperature recognition model can focus more on the temperature characteristics of the breeder chickens themselves, thereby improving the image quality and the accuracy of temperature recognition.

[0101] After removing the fence image, the pixel parameters on the left and right sides of the fence position information are obtained, and a color filling operation is performed to fill the image gaps caused by the fence removal. This color filling not only helps to maintain the integrity of the image, but also makes the temperature recognition model smoother when processing the image, avoiding recognition errors caused by image discontinuity.

[0102] By preprocessing the segmented infrared images to identify, remove and fill in fences, the temperature recognition model for breeder chickens can be more adaptable to image inputs in different breeding environments and conditions. This enhanced adaptability helps the model maintain stable performance in complex and changing breeding environments and improves the reliability and accuracy of temperature recognition.

[0103] The automation of the pretreatment steps can significantly reduce the frequency and intensity of manual intervention and improve the efficiency of aquaculture management. At the same time, through the optimization of the pretreatment steps, the temperature monitoring and analysis process can be made faster and more accurate, providing timely and effective support for aquaculture decision-making.

[0104] The above technical requirements reflect the trend of the breeding industry towards intelligence and automation. By introducing image processing technology and machine learning algorithms, real-time monitoring and analysis of the temperature of breeding chickens can be achieved, providing strong support for the intelligent management of the breeding industry. This intelligent development not only helps to improve breeding efficiency and quality, but also reduces labor costs and environmental pressure.

[0105] More preferably, the breeder chicken temperature recognition model is obtained through the following steps:

[0106] Acquire a sample training set, the sample training set comprising breeder chicken sample images; and divide the sample training set into a training set, a validation set, and a test set;

[0107] Performing a preprocessing operation on the breeder chicken sample image;

[0108] Input the preprocessed breeder chicken sample images into the breeder chicken temperature recognition model with completed parameter configuration for training and parameter configuration adjustment until the corresponding breeder chicken temperature recognition model meets the training requirements, and save the current optimal model parameters;

[0109] Use the trained breeder chicken temperature recognition model to predict the breeder chicken test images in the test set, and obtain images of various parts in each breeder chicken test image;

[0110] Generate a part confusion matrix according to the prediction results and true annotations of the breeder chicken temperature recognition model; the rows of the part confusion matrix represent the true parts, and the columns represent the predicted parts;

[0111] Calculating the overall performance index of the breeder chicken temperature recognition model according to the part confusion matrix, wherein the overall performance index includes accuracy, precision, recall rate and F1 score;

[0112] And according to the analysis results of the part confusion matrix, the breeder chicken temperature recognition model is adjusted and optimized.

[0113] During the specific implementation, the sample image and the later recognition detection image must be consistent. For example, if an image with a fence is used in the early training, it is also required in the later input, and the parameter adjustment parameters must be kept consistent during preprocessing to avoid recognition errors introduced by the intervention of image processing.

[0114] Through clear steps, a complete and repeatable process is formed from sample collection to model training, verification, testing, and performance evaluation and optimization. This helps ensure the stability and reliability of the model, while facilitating subsequent model updates and maintenance. Dividing the sample training set into training set, verification set, and test set can make more efficient use of data. The training set is used to learn the model, the verification set is used to adjust the model parameters to prevent overfitting, and the test set is used to evaluate the final performance of the model. This division method helps ensure the generalization ability of the model.

[0115] Preprocessing the images of the breeder chicken samples (such as denoising, enhancement, normalization, etc.) can significantly improve the training efficiency and recognition accuracy of the model. Preprocessing helps to reduce noise and redundant information in the data, making it easier for the model to learn useful features.

[0116] By inputting the preprocessed images into the temperature recognition model of the breeder chickens with complete parameter configuration for training, and adjusting the model parameters according to the results of the validation set, it is possible to ensure that the model is continuously optimized during the training process. At the same time, saving the current best model parameters helps to obtain the best performance model after the training is completed.

[0117] The trained model is predicted using the breeder test images in the test set, and the part confusion matrix is ​​generated to comprehensively evaluate the performance of the model. Indicators such as accuracy, precision, recall, and F1 score in the confusion matrix can intuitively reflect the performance of the model in different aspects, such as recognition accuracy, recognition accuracy for a certain category, and recall ability.

[0118] Based on the analysis results of the confusion matrix, the model’s performance on specific categories can be adjusted and optimized. For example, if the model performs poorly in identifying a certain category, the recognition accuracy can be improved by increasing the number of samples in that category, adjusting model parameters, or improving feature extraction methods.

[0119] More preferably, after obtaining the identification temperature set of each monitored breeder chicken in the temperature detection image, the method further includes:

[0120] Performing a data update operation on a corresponding breeder temperature table according to all the identified temperature sets obtained, wherein the breeder temperature table performs position mapping according to the positions of each breeder in the chicken house;

[0121] The breeding management method further comprises:

[0122] The temperature information in the corresponding chicken house is determined by a temperature sensor arranged in the chicken house; and the set temperature condition is updated according to the temperature information.

[0123] By associating the identified temperature set with the breeder temperature table and mapping the positions of each breeder in the chicken house, the temperature of the breeder can be updated and tracked in real time. This data update mechanism helps managers to understand the health status of the breeder chickens in a timely manner and provide data support for precision breeding.

[0124] By setting up temperature sensors in the chicken house to determine the temperature information in the chicken house and updating the set temperature conditions based on this information, precise control of the breeding environment can be achieved. This environmental control strategy helps to provide a suitable growth environment for breeder chickens and improve production performance and health levels. In addition, due to the different indoor temperatures, the accuracy of infrared detection will be affected to a certain extent. In high temperature environments and low temperature environments, the surface temperature of breeder chickens detected by infrared image detection is different, so it is necessary to combine specific environmental temperature parameters for subsequent comparison and correction.

[0125] The real-time updated temperature chart of breeder chickens and the temperature information of chicken houses provide a scientific basis for breeding decisions. Managers can formulate more reasonable breeding plans and management measures based on these data, such as adjusting stocking density, improving ventilation conditions, optimizing feed formula, etc., so as to improve breeding efficiency and economic benefits.

[0126] The breeder temperature table here refers to the temperature parameters of each breeder. When performing specific real-time monitoring, all detected temperature parameters are stored for easy subsequent analysis. For example, when a breeder in a chicken house becomes ill, it is reflected in the change in the detected temperature. Then, since a large amount of data is obtained, the spread can be predicted in combination with the temperature change position. The approximate path of disease spread can be predicted, allowing users to provide early warning feedback. And when implementing it, if an illness occurs, the detection accuracy can be improved by reducing the temperature threshold, and the user can be reminded of the risk of transmission.

[0127] More preferably, Figure 3 As shown, the breeding management method also includes:

[0128] S105: acquiring temperature monitoring images of each breeding area in the chicken house through an infrared camera group arranged in the chicken house at set intervals;

[0129] S106: Acquire position information of each infrared detection pixel point in the temperature monitoring image, and segment the temperature detection image according to the position information to obtain a segmented infrared image associated with each monitored breeder chicken;

[0130] S107: inputting the obtained segmented infrared images associated with each monitored breeder chicken into a pre-built breeder chicken temperature recognition model to obtain the head and neck area, the leg and foot area, and the wing area;

[0131] S108: performing temperature statistics on each pixel point data associated with the head and neck region, the leg and foot region, and the wing region according to a pre-constructed temperature calibration mapping table to determine average temperature information of each region of interest;

[0132] S109: Determine the temperature difference information between the two regions based on the average temperature information of each region of interest obtained from adjacent detection images, and determine the movement state of the breeder chicken based on the temperature difference information; if the movement state of the breeder chicken does not match the set movement state, perform an early warning operation.

[0133] The existing methods generally use images to detect action behaviors. In the embodiments of the present invention, the temperature difference detection method is innovatively used as a standard for measuring actions, so that its parameters can better characterize the corresponding functions of the breeder chickens. The embodiments of the present invention use image segmentation and region recognition technology to accurately segment the temperature monitoring image into segmented infrared images associated with each monitored breeder chicken, and further identify regions of interest such as the head and neck area, leg and foot area, and wing area. This precise region recognition helps to achieve independent statistics and analysis of the temperature of different parts of the breeder chickens, and improves the accuracy and reliability of temperature recognition.

[0134] By comparing the average temperature information of each area of ​​interest in adjacent detection images, the temperature difference information can be determined, and then the movement status of the breeder chickens can be judged. This kind of movement status monitoring not only helps to understand the activity of the breeder chickens, but also serves as an important basis for health assessment. When the movement status of the breeder chickens does not match the set movement status, timely warnings can remind managers to take corresponding measures to prevent potential health problems.

[0135] The specific principle of the embodiment of the present invention is leg movement recognition: when the breeder chicken walks, runs or stands, its leg muscles will generate heat and radiate to the body surface. Through infrared image recognition technology, this temperature change can be captured, and the leg movement state of the breeder chicken can be analyzed accordingly. For example, when the leg muscles of the breeder chicken are active frequently, the temperature of the corresponding area in the infrared image will rise, thereby reflecting the activity level of the breeder chicken. Wing flapping recognition: when the wings are flapping, the chest muscles of the breeder chicken will generate heat and dissipate the heat into the air through the flapping of the wings. Through infrared image recognition technology, this heat dissipation process can be captured, and the flapping of the wings of the breeder chicken can be judged accordingly. When carrying out specific implementation, the corresponding movement state can also be determined by the change in the coverage area of ​​the wing area, and the corresponding movement state recognition can be realized by combining the change in the coverage area of ​​the wing area with the temperature change of the chicken chest. Through high-precision infrared image recognition technology and appropriate image processing algorithms, the recognition of this movement state can be realized. Head turning and pecking behavior recognition: head turning and pecking behavior will cause temperature changes in the head area of ​​the breeder chicken. For example, when a breeder turns its head, the neck muscles generate heat; when a breeder pecks, the temperature around its mouth also changes. Through infrared image recognition technology, these subtle temperature changes can be captured, and the head turning and pecking behavior of the breeder can be analyzed accordingly. Different detection thresholds are set for different temperature change intervals to determine the movement state of the breeder; these changes in movement state will cause subtle differences in the temperature distribution of the breeder's body surface. By capturing these differences and processing and analyzing them, the movement state of the breeder can be identified. The above-mentioned temperature detection method can better realize the monitoring of animal behavior, and then provide a variety of breeding status information to the corresponding users.

[0136] The embodiment of the present invention can also detect the ambient temperature by installing infrared cameras in key areas of the chicken house (such as the entrance, exit, central area, corners, etc.) to ensure that the entire chicken house can be fully covered. The setting can also be combined with the above-mentioned infrared temperature detection method to realize the overall chicken house airtightness detection; to evaluate the construction of the chicken house.

[0137] In the embodiment of the present invention, by obtaining the position information of each infrared detection pixel in the temperature detection image and performing image segmentation processing on the image, the segmented infrared image associated with each monitored breeder chicken can be accurately obtained. These images are input into the pre-built breeder chicken temperature recognition model for recognition, and the actual body temperature of each breeder chicken can be quickly obtained. This intelligent processing method not only improves management efficiency, but also can timely warn when abnormal temperature is found, reminding management personnel to take corresponding measures.

[0138] By monitoring the body temperature of breeder chickens in real time, possible health problems such as fever can be detected in time, so that preventive measures can be taken to avoid the occurrence and spread of diseases. This helps to improve the survival rate of breeder chickens and reduce breeding costs.

[0139] Embodiment 2

[0140] See also Figure 4 , Figure 4 Schematic diagram of the structure of the breeding management system for breeder chickens disclosed in the embodiment of the present invention. Figure 4 As shown, the breeding management system of the breeder chicken may include:

[0141] The first acquisition module 21 is used to acquire a temperature detection image group of each breeding area in the chicken house through an infrared camera group arranged in the chicken house, wherein the temperature image detection group includes a plurality of temperature detection images, the infrared camera group includes a plurality of infrared cameras, and each breeding area corresponds to an infrared camera;

[0142] The second acquisition module 22 is used to acquire the position information of each infrared detection pixel point in the temperature detection image, and segment the temperature detection image according to the position information to obtain a segmented infrared image associated with each monitored breeder chicken;

[0143] Identification module 23: used for inputting the segmented infrared images associated with each monitored breeder chicken into a pre-built breeder chicken temperature identification model for identification to obtain an identification temperature set of each monitored breeder chicken in the temperature detection image;

[0144] The early warning module 24 is used to match the temperature identification set with the set temperature conditions. If there is a mismatch, an early warning is issued according to the location of the breeder chickens to remind the corresponding management personnel.

[0145] In the embodiment of the present invention, by obtaining the position information of each infrared detection pixel in the temperature detection image and performing image segmentation processing on the image, the segmented infrared image associated with each monitored breeder chicken can be accurately obtained. These images are input into the pre-built breeder chicken temperature recognition model for recognition, and the actual body temperature of each breeder chicken can be quickly obtained. This intelligent processing method not only improves management efficiency, but also can timely warn when abnormal temperature is found, reminding management personnel to take corresponding measures.

[0146] By monitoring the body temperature of breeder chickens in real time, possible health problems such as fever can be detected in time, so that preventive measures can be taken to avoid the occurrence and spread of diseases. This helps to improve the survival rate of breeder chickens and reduce breeding costs.

[0147] Embodiment 3

[0148] See also Figure 5 , Figure 5 Schematic diagram of the structure of an electronic device disclosed in an embodiment of the present invention. The electronic device may be a computer, a server, etc. Of course, in certain circumstances, it may also be a smart device such as a mobile phone, a tablet computer, a monitoring terminal, and an image acquisition device with processing functions. Figure 5 As shown, the electronic device may include:

[0149] A memory 510 storing executable program codes;

[0150] a processor 520 coupled to the memory 510;

[0151] The processor 520 calls the executable program code stored in the memory 510 to execute part or all of the steps in the breeding and management method for breeder chickens in the first embodiment.

[0152] An embodiment of the present invention discloses a computer-readable storage medium storing a computer program, wherein the computer program enables a computer to execute part or all of the steps in the breeding and management method for breeding chickens in Embodiment 1.

[0153] The embodiment of the present invention further discloses a computer program product, wherein when the computer program product is run on a computer, the computer is enabled to execute part or all of the steps in the breeding and management method for breeding chickens in the first embodiment.

[0154] An embodiment of the present invention further discloses an application publishing platform, wherein the application publishing platform is used to publish a computer program product, wherein when the computer program product runs on a computer, the computer executes part or all of the steps in the breeding and management method for breeding chickens in embodiment one.

[0155] In various embodiments of the present invention, it should be understood that the size of the serial numbers of the processes does not necessarily mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0156] 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, i.e., they may be located in one place or distributed over multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0157] In addition, each functional unit in each embodiment of the present invention 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 integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0158] 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-accessible memory. Based on this understanding, the technical solution of the present invention, in essence, 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, which is stored in a memory and includes several requests for a computer device (which can be a personal computer, a server or a network device, etc., specifically a processor in a computer device) to perform some or all of the steps of the method described in each embodiment of the present invention.

[0159] In the embodiments provided by the present invention, it should be understood that "B corresponding to A" means that B is associated with A, and B can be determined according to A. However, it should also be understood that determining B according to A does not mean determining B only according to A, and B can also be determined according to A and / or other information.

[0160] A person of ordinary skill in the art can understand that some or all of the steps in the various methods of the embodiments can be completed by instructing related hardware through a program, and the program can be stored in a computer-readable storage medium, and the storage medium includes a read-only memory (ROM), a random access memory (RAM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), a one-time programmable read-only memory (OTPROM), an electronically erasable rewritable read-only memory (EEPROM), a compact disc (CD-ROM) or other optical disc storage, magnetic disk storage, magnetic tape storage, or any other computer-readable medium that can be used to carry or store data.

[0161] The breeding and management method, system, electronic device and storage medium for breeding chickens disclosed in the embodiments of the present invention are introduced in detail above. Specific examples are used in this article to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea; at the same time, for general technical personnel in this field, according to the idea of ​​the present invention, there will be changes in the specific implementation method and application scope. In summary, the content of this specification should not be understood as a limitation on the present invention.

Claims

1. A breeding and management method for breeder chickens, characterized in that: include: A temperature detection image group of each breeding area in the chicken house is obtained by an infrared camera group arranged in the chicken house, wherein the temperature image detection group includes a plurality of temperature detection images, the infrared camera group includes a plurality of infrared cameras, and each breeding area corresponds to an infrared camera; Acquire the position information of each infrared detection pixel point in the temperature detection image, and segment the temperature detection image according to the position information to obtain a segmented infrared image associated with each monitored breeder chicken; Inputting the obtained segmented infrared images associated with each monitored breeder chicken into a pre-built breeder chicken temperature recognition model for recognition to obtain a recognition temperature set of each monitored breeder chicken in the temperature detection image; The temperature identification set is matched with the set temperature condition. If there is a mismatch, an early warning is issued according to the location of the breeder chickens to remind the corresponding management personnel.

2. The breeding and management method for breeder chickens according to claim 1, characterized in that: The method of obtaining a temperature detection image group of the breeding area in the chicken house by using an infrared camera group arranged in the chicken house includes: The infrared camera group arranged in the hatching hen house is used to obtain the temperature detection images of each breeding area in the hen house, wherein the temperature detection images include the temperature images of the breeder chickens to be hatched; Acquire temperature detection images of various breeding areas in the chicken house by using an infrared camera group arranged in the brooding and rearing chicken house, wherein the temperature detection images include temperature images of brooding and rearing breeder chickens; The temperature detection images of each breeding area in the chicken house are obtained by an infrared camera arranged in the laying hen house, wherein the temperature detection images include the temperature images of laying breeder chickens; the infrared camera includes first position information and second position information, wherein the first position information is used to represent the installation position of the infrared camera, and the second position information is used to represent the position number information of the infrared camera in the corresponding chicken house; The step of inputting the obtained segmented infrared images associated with each monitored breeder chicken into a pre-built breeder chicken temperature recognition model for recognition includes: Determine a corresponding breeder chicken temperature recognition model according to the first position information, wherein the breeder chicken temperature recognition model includes a hatching breeder chicken temperature model, a brooding and rearing breeder chicken temperature model, and a laying breeder chicken temperature model; The segmented infrared images associated with each monitored breeder chicken are input into a pre-built breeder chicken temperature recognition model for recognition.

3. The breeding and management method for breeder chickens according to claim 1, characterized in that: The step of inputting the obtained segmented infrared images associated with each monitored breeder chicken into a pre-built breeder chicken temperature recognition model for recognition to obtain a recognition temperature set of each monitored breeder chicken in the temperature detection image includes: Input the obtained segmented infrared images associated with each monitored breeder chicken into a pre-built breeder chicken temperature recognition model to obtain a first region of interest, a second region of interest, a third region of interest, and a fourth region of interest; obtain parameters of each pixel point associated with the first region of interest, the second region of interest, the third region of interest, and the fourth region of interest; Performing temperature statistics on each pixel point data associated with the first region of interest, the second region of interest, the third region of interest, and the fourth region of interest according to a pre-constructed temperature calibration mapping table to determine average temperature information, maximum temperature information, and minimum temperature information of each region of interest; The identification temperature set of each monitored breeder chicken is obtained according to the average temperature information, the maximum temperature information and the minimum temperature information of each area of ​​interest.

4. The breeding and management method for breeder chickens according to claim 3, characterized in that: Before the segmented infrared images associated with each monitored breeder chicken are input into a pre-built breeder chicken temperature recognition model, the method further includes: Performing recognition processing on the segmented infrared image according to a set grayscale threshold to determine the position information of each fence in the segmented infrared image, and removing the fence image in the segmented infrared image; The pixel parameters on the left and right sides of the position information of each fence are obtained, and the corresponding segmented infrared image is color filled according to the pixel parameters on the left and right sides of the position information of each fence to obtain the filled segmented infrared image.

5. The breeding and management method for breeder chickens according to claim 1, characterized in that: The breeder chicken temperature recognition model is obtained through the following steps: Acquire a sample training set, the sample training set comprising breeder chicken sample images; and divide the sample training set into a training set, a validation set, and a test set; Performing a preprocessing operation on the breeder chicken sample image; Input the preprocessed breeder chicken sample images into the breeder chicken temperature recognition model with completed parameter configuration for training and parameter configuration adjustment until the corresponding breeder chicken temperature recognition model meets the training requirements, and save the current optimal model parameters; Use the trained breeder chicken temperature recognition model to predict the breeder chicken test images in the test set, and obtain images of various parts in each breeder chicken test image; Generate a part confusion matrix according to the prediction results and true annotations of the breeder chicken temperature recognition model; the rows of the part confusion matrix represent the true parts, and the columns represent the predicted parts; Calculating the overall performance index of the breeder chicken temperature recognition model according to the part confusion matrix, wherein the overall performance index includes accuracy, precision, recall rate and F1 score; And according to the analysis results of the part confusion matrix, the breeder chicken temperature recognition model is adjusted and optimized.

6. The breeding and management method for breeder chickens according to claim 1, characterized in that: After obtaining the identification temperature set of each monitored breeder chicken in the temperature detection image, the method further includes: Performing a data update operation on a corresponding breeder temperature table according to all the identified temperature sets obtained, wherein the breeder temperature table performs position mapping according to the positions of each breeder in the chicken house; The breeding management method further comprises: The temperature information in the corresponding chicken house is determined by a temperature sensor arranged in the chicken house; and the set temperature condition is updated according to the temperature information.

7. The breeding and management method for breeder chickens according to claim 1, characterized in that: The breeding management method also includes: At set intervals, the infrared camera set in the chicken house is used to obtain temperature monitoring images of each breeding area in the chicken house; Acquire the position information of each infrared detection pixel point in the temperature monitoring image, and segment the temperature detection image according to the position information to obtain a segmented infrared image associated with each monitored breeder chicken; The segmented infrared images associated with each monitored breeder chicken are input into a pre-built breeder chicken temperature recognition model to obtain the head and neck area, the leg and foot area, and the wing area; According to the pre-built temperature calibration mapping table, temperature statistics are performed on the pixel data associated with the head and neck area, the leg and foot area, and the wing area to determine the average temperature information of each area of ​​interest; The temperature difference information between the two is determined based on the average temperature information of each area of ​​interest obtained from adjacent detection images, and the movement state of the breeder chicken is determined based on the temperature difference information; if the movement state of the breeder chicken does not match the set movement state, an early warning operation is performed.

8. A breeding and management method for breeder chickens, characterized in that: include: The first acquisition module is used to acquire a temperature detection image group of each breeding area in the chicken house through an infrared camera group arranged in the chicken house, wherein the temperature image detection group includes a plurality of temperature detection images, the infrared camera group includes a plurality of infrared cameras, and each breeding area corresponds to an infrared camera; The second acquisition module is used to acquire the position information of each infrared detection pixel point in the temperature detection image, and segment the temperature detection image according to the position information to obtain a segmented infrared image associated with each monitored breeder chicken; Identification module: used for inputting the segmented infrared images associated with each monitored breeder chicken into a pre-built breeder chicken temperature identification model for identification to obtain an identification temperature set of each monitored breeder chicken in the temperature detection image; Early warning module: used to match the temperature identification set with the set temperature conditions. If there is a mismatch, an early warning is issued based on the location of the breeder chickens to remind the corresponding management personnel.

9. An electronic device, characterized in that: include: A memory storing executable program code; a processor coupled to the memory; The processor calls the executable program code stored in the memory to execute the breeding and management method for breeding chickens as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, wherein the computer program enables a computer to execute the breeding and management method for breeder chickens as described in any one of claims 1 to 7.

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