Intelligent beef cattle breeding and feed management monitoring system

Abstract

The invention discloses an intelligent beef cattle breeding and feed management monitoring system in the technical field of cattle breeding. Comprising an NFC label used for distinguishing cattle, a camera used for shooting the overall state of the cattle, a weighing instrument used for being placed on one side of a trough to weigh the cattle, a temperature and humidity sensor and an accurate feeding module. Calculating and preparing a feed formula and total amount; and the intelligent monitoring module is used for receiving the feed intake and the cattle state video data of the cattle identified and monitored by the camera, and automatically judging the overall state of the cattle according to the feed intake and the cattle state video data. The system is scientific and reasonable, the system makes a scientific and reasonable mating plan, and ensures that cattle can obtain appropriate nutrition supply through data sharing and cooperative work, and effective linkage of breeding and feed management is achieved.

Description

Technical Field

[0001] The invention belongs to the technical field of cattle breeding, and in particular is an intelligent beef cattle breeding and feed management monitoring system. Background Art

[0002] With the rapid development of animal husbandry and the continuous advancement of science and technology, traditional beef cattle breeding methods can no longer meet the needs of modern animal husbandry for efficiency, precision and environmental protection. The emergence of intelligent beef cattle management and monitoring systems is designed to solve this problem. The system integrates advanced technologies such as the Internet of Things, big data, and artificial intelligence, and realizes the intelligence and automation of the beef cattle breeding process through real-time monitoring, data analysis and optimization management.

[0003] However, there are still some problems with the traditional beef cattle management and monitoring system. Breeding data and feed management data are often processed separately, and there is no unified data platform. This leads to a lack of effective linkage between breeding decisions and feed formula adjustments, and it is impossible to accurately manage cattle according to their genetic characteristics and growth needs. Traditional monitoring systems usually rely on manual observation and experience judgment for disease warning, lacking scientific data support and intelligent analysis. This leads to untimely disease detection, which can easily lead to the spread of the epidemic and cause significant losses to farms.

[0004] In summary, the lack of effective linkage between breeding decisions and feed formula adjustment in traditional monitoring systems has become an urgent problem that technicians in this field need to solve. Therefore, it is necessary to propose an intelligent beef cattle breeding and feed management monitoring system. Summary of the invention

[0005] In order to solve the above problems, the purpose of the present invention is to provide an intelligent beef cattle breeding and feed management monitoring system, which can formulate a scientific and reasonable breeding plan according to the breeding potential and health status of cattle by optimizing the breeding module. At the same time, the precision feeding module will automatically calculate and configure the feed formula according to the growth stage and nutritional needs of the cattle to ensure that the cattle obtain the most suitable nutritional supply. Through data sharing and collaborative work between these two modules, effective linkage between breeding and feed management is achieved.

[0006] In order to achieve the above-mentioned purpose, the technical solution of the present invention is as follows: an intelligent beef cattle breeding and feed management monitoring system, comprising an NFC tag for distinguishing cattle, a plurality of cameras for photographing the overall status of cattle, a weighing instrument for weighing cattle, a plurality of temperature and humidity sensors for collecting temperature and humidity at various locations in the breeding farm, and the following modules:

[0007] Precision feeding module: used to receive data collected by cameras and weighing instruments and conduct comprehensive analysis, calculate and configure feed formula and total amount according to the weight, growth stage and nutritional requirements of the cattle.

[0008] Intelligent monitoring module: used to receive camera identification and monitor the feed intake and cattle status video data of cattle, and automatically determine the overall status of the cattle based on the feed intake and cattle status video data.

[0009] Tag identification module: used to input the NFC tag of each cow to generate an NFC database, which contains the breed, age, gender, health status and NFC tag sequence information of each cow;

[0010] Reproduction optimization module: used to receive data transmitted by the intelligent monitoring module, comprehensively analyze the breeding cycles of cows and bulls, and formulate breeding plans and feeding plans. The feeding plans are transmitted to the precision feeding module. After receiving the feeding plans, the precision feeding module calculates and changes the feed formula and total amount based on the feeding plans and the characteristics of the cattle herd's needs.

[0011] Disease prevention module: used to receive data transmitted by the intelligent monitoring module, intelligently adjust the temperature and humidity of the farm, and conduct comprehensive analysis to identify sick and unsuitable breeding cows and bulls, and promptly notify relevant personnel for isolation and treatment.

[0012] Furthermore, the camera has a night vision function and an integrated tag recognition module for clearly photographing cattle in low-light conditions and automatically identifying NFC tags, and distinguishing cattle through the information entered in the NFC database.

[0013] Furthermore, a feed management unit is provided in the precision feeding module, which is used to automatically record the inventory, usage and remaining amount of the feed, and automatically replenish and adjust the feed supply according to the instructions of the precision feeding module.

[0014] Furthermore, automatic judgment in the intelligent monitoring module refers to extracting the behavioral characteristics of cattle from the camera data. The behavioral characteristics include eating speed, frequency and posture changes. The collected data is trained and analyzed using machine learning algorithms to establish a cattle status judgment model. The cattle status judgment model is used to judge the development status, emotional status and estrus status of cattle.

[0015] Furthermore, an environmental feedback unit is integrated in the disease prevention module. After receiving the data collected by the temperature and humidity sensors, the module environmental feedback unit automatically adjusts the environmental parameters in the pen by intelligently controlling the ventilation equipment, heating / cooling equipment and humidity control equipment in the farm.

[0016] Furthermore, a genetic evaluation unit is provided in the optimized breeding module. The genetic evaluation unit evaluates the breeding potential and offspring quality of the cattle based on the breeding record of the cattle, and provides a reference for formulating a breeding plan.

[0017] Furthermore, the disease prevention module uses machine learning algorithms to analyze the behavioral patterns of cattle in video data and predict disease risks.

[0018] Furthermore, the disease prevention module is provided with a remote diagnosis and treatment unit, which is used for veterinary remote video diagnosis.

[0019] Furthermore, the intelligent monitoring module supports cloud storage and remote access for remote monitoring and management by farm managers.

[0020] Furthermore, the disease prevention module has a comprehensive report generation function for automatically generating a comprehensive report containing cattle growth, feed consumption, environmental parameters, breeding records and disease conditions.

[0021] The following principles and beneficial effects are achieved by adopting the above scheme:

[0022] 1. The optimized breeding module in the present invention formulates a breeding plan and a feeding plan based on the data provided by the intelligent monitoring module. These plans are then transmitted to the precision feeding module to achieve the linkage between breeding and feed management. At the same time, the system dynamically adjusts the feeding plan and breeding environment according to the actual growth of the cattle and environmental changes through a real-time feedback mechanism to ensure that the cattle are always in the best growth state. Through the coordinated work of the optimized breeding module and the precision feeding module, the system can screen out cattle with excellent genetic potential for breeding and provide them with scientific feeding management. This helps to improve the quality and market competitiveness of cattle.

[0023] 2. The present invention uses NFC tags, cameras, weighing instruments, temperature and humidity sensors and other equipment to collect data such as individual information, growth status, feed intake and environmental parameters of cattle in real time. These data are integrated into the system, and through data transmission, each module can obtain the required information in real time. Through intelligent management and precise feeding, the system can ensure that cattle obtain the most suitable nutritional supply, thereby promoting their rapid growth and reproduction. This greatly improves breeding efficiency and shortens the breeding cycle.

[0024] 3. The precision feeding module and intelligent monitoring module in the present invention use machine learning algorithms and data analysis technology to deeply mine and analyze the collected data. By extracting key features and building models, the system can automatically determine the growth stage, nutritional needs, health status and reproductive potential of cattle, and formulate scientific and reasonable feeding plans and breeding plans accordingly.

[0025] 4. The disease prevention module of the present invention can timely detect sick and unfit cattle for breeding by real-time monitoring of cattle behavior patterns and health conditions, and take effective isolation and treatment measures. This enhances the disease prevention and control capabilities of the farm and reduces the risk of disease transmission.

[0026] 5. The intelligent monitoring module in the present invention supports cloud storage and remote access functions, so that farm managers can access system data through the Internet anytime and anywhere for remote monitoring and management. This remote management capability not only improves management efficiency, but also reduces labor costs.

[0027] 6. The disease prevention module in the present invention has a comprehensive report generation function, which can automatically generate a comprehensive report containing cattle growth, feed consumption, environmental parameters, breeding records and disease conditions. This provides comprehensive data support for farm managers, helping them to better understand the operation of the farm and formulate scientific breeding strategies. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 is a flow chart of an embodiment of the present invention. DETAILED DESCRIPTION

[0029] The following is further described in detail through specific implementation methods:

[0030] The embodiment is basically as shown in the attached Figure 1 As shown: An intelligent beef cattle breeding and feed management monitoring system, including NFC tags for distinguishing cattle, several cameras for photographing the overall status of cattle, the cameras have night vision function and integrated tag recognition modules, which are used to clearly photograph cattle under low light conditions and automatically recognize NFC tags, and distinguish cattle through information entered in the NFC database; weighing instruments for weighing cattle, several temperature and humidity sensors for collecting temperature and humidity at various locations in the farm, and the following modules:

[0031] Precision feeding module: used to receive data collected by cameras and weighing instruments and conduct comprehensive analysis, calculate and configure feed formula and total amount according to the weight, growth stage and nutritional requirements of the cattle; the precision feeding module is equipped with a feed management unit, which is used to automatically record the inventory, usage and remaining amount of feed, and automatically replenish and adjust the feed supply according to the instructions of the precision feeding module.

[0032] Intelligent monitoring module: used to receive camera identification and monitor cattle's feed intake and cattle status video data, and extract cattle's behavioral characteristics based on feed intake and cattle status video data. Behavioral characteristics include eating speed, frequency and posture changes. Use machine learning algorithms to train and analyze the collected data to establish a cattle status judgment model. The cattle status judgment model is used to judge the development status, emotional status and estrus status of cattle.

[0033] Tag identification module: used to enter the NFC tag of each cow to generate an NFC database. The NFC database contains the breed, age, gender, health status and NFC tag sequence information of each cow.

[0034] Reproduction optimization module: used to receive data transmitted by the intelligent monitoring module, comprehensively analyze the breeding cycles of cows and bulls, and formulate breeding plans and feeding plans. The feeding plans are transmitted to the precision feeding module. After receiving the feeding plans, the precision feeding module calculates and changes the feed formula and total amount based on the feeding plans and the characteristics of the cattle herd's needs.

[0035] The optimized breeding module is equipped with a genetic evaluation unit, which evaluates the breeding potential and offspring quality of the cattle based on the breeding records of the cattle, and provides a reference for formulating breeding plans.

[0036] Disease prevention module: used to receive data transmitted by the intelligent monitoring module, use machine learning algorithms to analyze the behavior patterns of cattle in video data, and predict disease risks. Comprehensive analysis identifies sick and unsuitable cows and bulls, and promptly notifies relevant personnel for isolation and treatment.

[0037] The disease prevention module is integrated with an environmental feedback unit. After receiving the data collected by the temperature and humidity sensors, the environmental feedback unit automatically adjusts the environmental parameters in the pen by intelligently controlling the ventilation equipment, heating / cooling equipment and humidity control equipment in the farm.

[0038] It also has a comprehensive report generation function, which is used to automatically generate comprehensive reports including cattle growth, feed consumption, environmental parameters, breeding records and disease conditions.

[0039] Specific implementation steps:

[0040] Configure the system on the cloud or local server, set the camera monitoring area, weighing instrument parameters and temperature and humidity sensor thresholds. Then hang the NFC tag on the cow's ear and enter the basic information of each cow, including breed, age, gender, health status and NFC tag sequence information, to establish an NFC database for subsequent identification of cows.

[0041] When a cow enters the monitoring area or passes a specific point, the tag recognition module integrated in the camera will automatically scan and identify the NFC tag worn by the cow, obtain its unique NFC tag sequence, and find out the basic information corresponding to the cow by comparing it with the data entered in the NFC database. The high-definition camera monitors the overall status of the cow when eating, and uses the night vision function to ensure clear shooting even in low light conditions. The camera also captures videos of the cow's behavior, such as eating, resting, and activities. The weighing instrument placed on one side of the trough automatically measures the weight change data of each cow and uploads the data to the system.

[0042] The precision feeding module receives data from cameras and weighing instruments, comprehensively analyzes the weight, growth stage and nutritional needs of the cattle, and calculates the feed formula and total amount for the cattle. The feed management unit automatically monitors feed inventory and automatically replenishes and adjusts feed supply according to demand.

[0043] The intelligent monitoring module processes the video data captured by the camera and analyzes the behavioral characteristics of cattle such as feed intake, eating speed, frequency and posture changes through machine learning algorithms. A cattle status judgment model is established to evaluate the overall health status of cattle. The environmental feedback unit automatically adjusts ventilation, heating / cooling and humidity control equipment based on the data from the temperature and humidity sensors to maintain the best breeding environment.

[0044] The breeding optimization module integrates the data of the intelligent monitoring module to analyze the breeding cycle of cows and bulls and formulate breeding and feeding plans. The genetic evaluation unit evaluates the breeding potential and offspring quality of cattle based on breeding records, providing a scientific basis for breeding plans. The disease prevention module uses machine learning algorithms to analyze behavioral patterns in video data and predict disease risks. When sick or unsuitable cattle are identified, managers are notified in time for treatment and isolation.

[0045] The disease prevention module automatically generates a comprehensive report on cattle growth, feed consumption, environmental parameters, breeding records, and disease conditions. Managers can remotely monitor and understand the overall operation of the farm through cloud storage and remote access functions. Based on the generated comprehensive report, managers can make more scientific and reasonable decisions, such as adjusting feeding strategies, optimizing breeding plans, and improving the breeding environment, so as to improve breeding efficiency and economic benefits.

[0046] The above is only an embodiment of the present invention. The common sense such as the known specific structure and characteristics in the scheme is not described in detail here. The ordinary technicians in the relevant field know all the common technical knowledge in the technical field of the invention before the application date or priority date, can obtain all the existing technologies in the field, and have the ability to apply the conventional experimental means before that date. The ordinary technicians in the relevant field can improve and implement this scheme in combination with their own abilities under the enlightenment given by this application. Some typical known structures or known methods should not become obstacles for ordinary technicians in the relevant field to implement this application. It should be pointed out that for those skilled in the art, without departing from the structure of the present invention, several deformations and improvements can be made, which should also be regarded as the protection scope of the present invention, which will not affect the effect of the implementation of the present invention and the practicality of the patent. The protection scope required by this application shall be based on the content of its claims, and the specific implementation methods and other records in the specification can be used to interpret the content of the claims.

Claims

1. An intelligent beef cattle breeding and feed management monitoring system, characterized by: It includes NFC tags for distinguishing cattle, several cameras for photographing the overall status of cattle, several weighing instruments for weighing cattle, several temperature and humidity sensors for collecting temperature and humidity at various locations in the farm, and the following modules: Precision feeding module: used to receive and analyze the data collected by the camera and weighing instrument, calculate and configure the feed formula and total amount according to the weight, growth stage and nutritional requirements of the cattle; Intelligent monitoring module: used to receive camera recognition and monitor the feed intake and cattle status video data of cattle, and automatically determine the overall status of the cattle based on the feed intake and cattle status video data; Tag identification module: used to input the NFC tag of each cow to generate an NFC database, which contains the breed, age, gender, health status and NFC tag sequence information of each cow; Reproduction optimization module: used to receive data transmitted by the intelligent monitoring module, comprehensively analyze the reproductive cycles of cows and bulls, and formulate breeding plans and feeding plans. The feeding plans are transmitted to the precision feeding module. After receiving the feeding plans, the precision feeding module calculates and changes the feed formula and total amount based on the feeding plans and the characteristics of the cattle herd's needs; Disease prevention module: used to receive data transmitted by the intelligent monitoring module, intelligently adjust the temperature and humidity of the farm, and conduct comprehensive analysis to identify sick and unsuitable breeding cows and bulls, and promptly notify relevant personnel for isolation and treatment.

2. The intelligent beef cattle breeding and feed management monitoring system according to claim 1 is characterized by: The camera has night vision function and an integrated tag recognition module, which is used to clearly capture cattle in low-light conditions and automatically identify NFC tags, and distinguish cattle based on the information entered in the NFC database.

3. The intelligent beef cattle breeding and feed management monitoring system according to claim 2 is characterized in that: The precision feeding module is provided with a feed management unit, which is used to automatically record the inventory, usage and remaining amount of feed, and automatically replenish and adjust the feed supply according to the instructions of the precision feeding module.

4. The intelligent beef cattle breeding and feed management monitoring system according to claim 3 is characterized by: Automatic judgment in the intelligent monitoring module refers to extracting cattle's behavioral characteristics from camera data. Behavioral characteristics include eating speed, frequency and posture changes. The collected data is trained and analyzed using machine learning algorithms to establish a cattle status judgment model. The cattle status judgment model is used to judge the development status, emotional status and estrus status of cattle.

5. The intelligent beef cattle breeding and feed management monitoring system according to claim 4 is characterized in that: The disease prevention module is integrated with an environmental feedback unit. After receiving the data collected by the temperature and humidity sensors, the environmental feedback unit automatically adjusts the environmental parameters in the pen by intelligently controlling the ventilation equipment, heating / cooling equipment and humidity control equipment in the farm.

6. The intelligent beef cattle breeding and feed management monitoring system according to claim 5 is characterized by: The optimized breeding module is equipped with a genetic evaluation unit, which evaluates the breeding potential and offspring quality of the cattle based on the breeding records of the cattle, and provides a reference for formulating breeding plans.

7. The intelligent beef cattle breeding and feed management monitoring system according to claim 6 is characterized by: The disease prevention module uses machine learning algorithms to analyze the behavior patterns of cattle in video data and predict disease risks.

8. The intelligent beef cattle breeding and feed management monitoring system according to claim 7 is characterized by: The disease prevention module is equipped with a remote diagnosis and treatment unit, which is used for veterinary remote video diagnosis.

9. The intelligent beef cattle breeding and feed management monitoring system according to claim 8, characterized in that: The intelligent monitoring module supports cloud storage and remote access. The intelligent monitoring module is used for remote monitoring and management by farm managers.

10. The intelligent beef cattle breeding and feed management monitoring system according to claim 9, characterized in that: The disease prevention module has the function of generating comprehensive reports. The disease prevention module is used to automatically generate comprehensive reports including cattle growth, feed consumption, environmental parameters, breeding records and disease conditions.

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