Automatic monitoring device for weight and feed intake of beef cattle

Abstract

The present invention discloses an automatic monitoring device for the weight and feed intake of beef cattle, which belongs to the technical field of automated monitoring in animal husbandry, and includes: a data acquisition system, a data processing system, a feed delivery system and an intelligent analysis system; wherein the data acquisition system is used to collect the weight data and feed intake data of beef cattle in real time; the data processing system is used to analyze and process the collected weight data and feed intake data to obtain analysis results; the feed delivery system is used to adjust the feed delivery amount based on the analysis results; the intelligent analysis system is used to predict and evaluate the feed conversion efficiency and daily weight gain of beef cattle. The present invention can monitor the weight, feeding time and single feed intake of each cattle before and after feeding in real time, and calculate the daily weight, daily feed intake, daily weight gain and feed conversion rate at the same time.

Description

Technical Field

[0001] The invention belongs to the technical field of animal husbandry automatic monitoring, and in particular relates to an automatic monitoring device for the weight and feed intake of beef cattle. Background Art

[0002] Accurate measurement of cattle weight is a key indicator for assessing their health and growth status, and is also an indispensable part of achieving refined farming. Regular weight monitoring of cattle is the basic work to ensure that they get appropriate nutrition and promote their healthy development. Precision feeding technology plays a vital role in the refined farming of beef cattle. Its core lies in the ability to track the changes in cattle weight in real time, so as to provide them with customized feed formulas and accurate feed intake. At the same time, the monitoring of beef cattle weight and feed intake has important production significance for beef cattle breeding, while the traditional manual monitoring of feed intake is more stressful to beef cattle and requires a large amount of manual work. Therefore, a device that can accurately monitor the weight and feed intake of beef cattle is designed. Through the automatic monitoring of this indicator, beef cattle with high feed conversion efficiency and high daily weight gain are selected. At the same time, it can be used for real-time evaluation of feed effects. This technology is of great significance for the breeding and production performance monitoring of beef cattle. Summary of the invention

[0003] In order to solve the above technical problems, the present invention proposes an automatic monitoring device for the weight and feed intake of beef cattle to solve the problems existing in the above prior art.

[0004] To achieve the above-mentioned purpose, the present invention provides an automatic monitoring device for the weight and feed intake of beef cattle, comprising: a data acquisition system, a data processing system, a feed delivery system and an intelligent analysis system;

[0005] Wherein, the data acquisition system is used to collect the weight data and feeding data of beef cattle in real time;

[0006] The data processing system is used to analyze and process the collected body weight data and food intake data to obtain analysis results;

[0007] The feed delivery system is used to adjust the feed delivery amount based on the analysis result;

[0008] The intelligent analysis system is used to predict and evaluate the feed conversion efficiency and daily weight gain of beef cattle.

[0009] Optionally, the data collection system includes: a weight collection device, a food intake detection device and an identity recognition device;

[0010] Wherein, the weight collection device is used to record the daily feed intake and daily weight of beef cattle;

[0011] The feeding detection device is used to detect the amount of feed in the feeding trough;

[0012] The identity recognition device is used to identify the identity of beef cattle based on RFID.

[0013] Optionally, the weight collection device includes a weight scale that is larger than the length and width of the beef cattle, a manure baffle and a manure scraper, and railings on both sides;

[0014] The manure baffles are fixed on the four sides of the scale, the front baffles and the left and right baffles are fixed baffles, and the rear baffles are flippable baffles.

[0015] The manure scraper is moved forward and backward by rotating spiral rods fixed on both sides of the scale. When the cattle eat and leave, the manure scraper turns flat to scrape out the manure. After the manure scraping is completed, the manure scraper returns to the initial position.

[0016] Optionally, the feeding detection device includes a photoelectric sensor arranged above the feeding trough, and the photoelectric sensor is used to detect the change in the feed amount in the feeding trough.

[0017] Optionally, the data processing system includes a data storage module, a data calculation module and a data transmission module;

[0018] Wherein, the data storage module is used to store the collected data and build a daily management database for each beef cattle;

[0019] The data calculation module is used to calculate the feed intake and weight changes of beef cattle;

[0020] The data transmission module is used to transmit the calculation result of the calculation unit to the intelligent analysis system.

[0021] Optionally, the feed delivery system includes a feed bin, a controller and a conveying device;

[0022] Wherein, the feed bin is used to store feed;

[0023] The controller is used to issue a feed delivery instruction based on the analysis result of the data processing system and the instruction of the intelligent analysis system;

[0024] The conveying device is used to take out feed from the feed bin and put it into the trough.

[0025] Optionally, the intelligent analysis system includes an artificial intelligence model training module and a prediction and evaluation module;

[0026] Wherein, the artificial intelligence model training module is used to construct and train a beef cattle feeding-weight prediction model;

[0027] The prediction and evaluation unit is used to predict and evaluate the daily management of beef cattle based on the beef cattle feeding-weight prediction model and real-time data.

[0028] Optionally, the device further comprises a user interaction interface; the user interaction interface is used to display parameters such as the weight, feed intake, feed conversion efficiency, daily weight gain, etc. of the beef cattle, and to provide an interface for operating and controlling the device.

[0029] Optionally, the device is integrated with a pasture management system to achieve data exchange and sharing.

[0030] Compared with the prior art, the present invention has the following advantages and technical effects:

[0031] The automatic monitoring device for the weight and feed intake of beef cattle disclosed in the present invention can monitor the weight and feed intake of beef cattle in real time, and predict and evaluate the feed conversion efficiency and daily weight gain of beef cattle based on these data. Through personalized feeding management, beef cattle with high feed conversion efficiency and high daily weight gain can be screened out to improve breeding efficiency. At the same time, the device can also be used for real-time evaluation of feed effects, providing data support for the research and development and improvement of feed. In addition, the device can also be integrated with a pasture management system to realize data sharing and exchange, and improve the efficiency and accuracy of pasture management. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] The drawings constituting a part of the present application are used to provide a further understanding of the present application. The illustrative embodiments and descriptions of the present application are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0033] Figure 1 This is a schematic diagram of an automatic monitoring device for beef cattle weight and feed intake according to an embodiment of the present invention;

[0034] Figure 2 This is a schematic diagram of the initial state of the device according to an embodiment of the present invention;

[0035] Figure 3 This is a schematic diagram of a beef cattle entering the equipment according to an embodiment of the present invention;

[0036] Figure 4 This is a schematic diagram of a beef cattle eating and leaving with a manure scraper opened in an embodiment of the present invention;

[0037] Figure 5 A top view of a manure scraper cleaning according to an embodiment of the present invention;

[0038] Figure 6 This is a schematic diagram of the equipment after manure and sewage are cleaned according to an embodiment of the present invention. DETAILED DESCRIPTION

[0039] It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of the present application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0040] It should be noted that the steps shown in the flowcharts of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and that, although a logical order is shown in the flowcharts, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0041] Embodiment 1

[0042] In the present embodiment, a device for automatically monitoring the weight and feed intake of beef cattle is provided, which is used to record the daily weight, feed intake, and feed conversion rate of beef cattle, and realize contactless and simultaneous recording of relevant indicators. In the present embodiment, a weighing scale with a length greater than the body length of the beef cattle is set in each feeding stall. There are RFID identification systems on both sides of the scale. There are manure baffles all around, and the rear baffle is flippable. There is a manure scraper on the bottom plate. There are railings on the front and sides of the equipment, and the front railing is a railing that can be used to feed through the head of the cattle. The equipment is installed in all places where cattle can feed in the cowshed to ensure that data is recorded every time the cattle feed.

[0043] Before each feeding, the scale is automatically reset to zero, the cow enters the stall, and the rear ground baffle is closed (to prevent the excretion of feces and urine during the feeding process from interfering with the feeding amount record. The cow number is identified by the RFID device on the side of the equipment through the pedometer worn on the cow's ear tag or neck, and the weight of the cow when it enters is recorded. After feeding, the weight of the cow before leaving the stall is recorded. The difference in weight is the weight of a single feeding amount. The total amount of feeding each time throughout the day is recorded as the daily feeding amount. The weight before the first feeding of the day is recorded as the weight of the day. After each feeding, the cow exits, the rear baffle is flattened, and the feces and dirt inside are cleaned by the dung scraper. The next cow's feeding and weight are recorded. This equipment can realize real-time monitoring of the weight, feeding time, and single feeding amount of each cow before and after feeding. At the same time, it calculates the daily weight, daily feed intake, daily weight gain, and feed conversion rate.

[0044] As a preferred solution of this embodiment, the process of weighing beef cattle includes: placing a weighing device at the feeding position of beef cattle, each device has railings on both sides, weighing the cattle each time they feed, and weighing the cattle again when they leave after feeding. The difference between the two weights is the single feed intake, and the feed intake of a single cattle calculated cumulatively for one day is the daily feed intake. Each cattle has RFID identification. In order to avoid interference from feces and urine each time they feed. The weighing floor is made of stainless steel. A baffle is installed at the back. It is closed when the cattle enter and opened to discharge feces and urine after leaving. At the same time, the corresponding scraper is installed when leaving. The power is fixed on both sides by a rotating spiral rod. This ensures that each discharge of feces is counted. After leaving, the feces is scraped out, which can effectively avoid interference from feces and sewage.

[0045] like Figure 1As shown, in this embodiment, a device for automatically monitoring the weight and feed intake of beef cattle is provided, including: a data acquisition system, a data processing system, a feed delivery system and an intelligent analysis system;

[0046] Among them, the data acquisition system is used to collect the weight data and feeding data of beef cattle in real time; the data processing system is connected to the data acquisition system, and is used to analyze and process the collected weight data and feeding data to obtain analysis results; the feed delivery system is connected to the data processing system, and is used to judge the feed content in the trough based on the analysis results; the intelligent analysis system is connected to the feed delivery system, and is used to predict and evaluate the feed conversion efficiency and daily weight gain of beef cattle, and issue feed delivery instructions to the feed delivery system based on the prediction and evaluation results, and adjust the feed delivery amount at the same time.

[0047] As a preferred solution of this embodiment, the data collection system includes: a weight collection device, a feeding detection device and an identity recognition device; wherein the weight collection device is used to record the daily feed intake and daily weight of beef cattle; the feeding detection device is used to detect the amount of feed in the trough; and the identity recognition device is used to identify the identity of beef cattle based on RFID. The weight collection device includes a weight scale, a manure baffle and a manure scraper that are larger than the length and width of the beef cattle; wherein the manure baffles are fixed on all sides of the weight scale, the front and left and right baffles are fixed baffles, and the rear baffle is a flippable baffle; the manure scraper is moved back and forth by a rotating spiral rod fixed on both sides of the weight scale. When the beef cattle eat and leave, the manure scraper turns flat and scrapes out the manure. After the manure scraping is completed, the manure scraper returns to its original position.

[0048] like Figure 2 As shown in the figure, it is the initial state before the beef cattle enter the equipment. After the cattle enter the equipment, the rear door is closed, the board is closed, and the RFID reader can quickly identify the identity of the cattle and associate the collected weight and feeding data with its identity, as shown in the figure. Figure 3 As shown. Before the first meal of the day, the weight of the cattle is measured as the weight of the day. After the cattle finish eating, the weight of the cattle is measured. The difference between the two weights is the single feed intake. The feed intake of a single cattle in one day is calculated cumulatively as the daily feed intake. After the cattle leave, the weight sensor in the weight collection device senses the weight. When the cattle leave completely, the weight sensor in the weight collection device and the sensor in the manure baffle on the open side send a measurement completion signal to the manure scraper. The manure scraper starts based on the signal to clean the manure in the weight collection device. That is, when the beef cattle are eating, the rear baffle is tightly closed to ensure that the feces of the beef cattle are stored in the weight trough when eating. As shown Figure 4 , Figure 5 , Figure 6 As shown in the figure, after the cattle finish eating, the manure is cleaned up, which reduces the impact of cattle manure on the feed intake calculation.

[0049] Furthermore, the feed intake of beef cattle is recorded by recording the weight before feeding each time the beef cattle enter the scale. Usually, the weight of the first feeding of the day is the daily fasting weight. When the beef cattle are feeding, the weight changes are recorded in real time. When the feeding is finished and the beef cattle leave the scale, the weight of the beef cattle before leaving and the total weight of the feces and urine on the scale are recorded. The difference in weight before and after feeding is calculated as the single feed intake of the beef cattle, and the total amount of each cattle feeding every day is calculated as the daily feed intake.

[0050] When there are multiple feeding devices in the same pen, the feed intake and body weight are calculated by summarizing the data.

[0051] This embodiment also installs a precise photoelectric sensor inside the trough. The design purpose of this sensor is to monitor the stock change of feed in the trough in real time.

[0052] As a preferred solution of this embodiment, the data processing system includes a data storage module, a data calculation module and a data transmission module; wherein the data storage module is used to store the collected data and build a daily management database for each beef cattle; the data calculation module is used to calculate the feed intake and weight changes of the beef cattle; and the data transmission module is used to transmit the calculation results of the calculation unit to the intelligent analysis system.

[0053] The data storage module uses a distributed database system to support the storage and management of large-scale data. The data storage module includes data tags, which add tags to each data record to facilitate the classification and retrieval of data for specific cattle or time periods, and the data storage module uses a time series database to optimize the storage and query efficiency of timestamp data. The data calculation module allows users to customize calculation rules and parameters according to breeding needs, and performs real-time data processing based on statistical analysis methods to quickly respond to cattle behavior and environmental changes. The data transmission module supports a variety of data transmission protocols, such as MQTT, HTTP, and WebSocket, to adapt to different network environments and application scenarios, and applies data compression technology in the data transmission process to reduce transmission time and save bandwidth.

[0054] As a preferred solution of this embodiment, the feed delivery system includes a feed bin, a controller and a conveying device; wherein the feed bin is used to store feed; the controller is used to issue feed delivery amount instructions based on the analysis results of the data processing system and the instructions of the intelligent analysis system; the conveying device is used to take out the feed from the feed bin and deliver it to the trough.

[0055] The feed bin monitors the feed inventory in the bin in real time to ensure the continuity of feed supply. The feed bin is also designed with multifunctional compartments to allow different types of feed to be stored at the same time to meet the nutritional needs of different cattle. When the feed inventory drops to the preset threshold, the filling mechanism is automatically triggered to reduce manual intervention. The controller has powerful data processing capabilities and can receive and analyze information from the data calculation module in real time. Based on the intelligent scheduling algorithm, the controller intelligently calculates and schedules the feed delivery amount according to the weight, feed intake and growth stage of the cattle, and continuously optimizes the feed delivery strategy based on historical data. The conveying device delivers the calculated feed delivery amount to multiple troughs.

[0056] The controller intelligently calculates and schedules the feed delivery amount based on the weight, feed intake and growth stage of the cattle based on the intelligent scheduling algorithm. The process includes: first, starting with the collection of data such as the weight, feed intake and growth stage of the cattle, and then cleaning and standardizing the data to eliminate the influence of different dimensions. Then, feature selection is performed to identify the key indicators that affect the growth of cattle, including the weight change rate and feeding frequency. On this basis, a cattle growth model is established using random forests, and historical data is used for training and verification to ensure the accuracy and generalization ability of the model. The feed intake of each cow is calculated based on the model prediction results and real-time data, while considering the dynamic adjustment of time series and environmental adaptability. Finally, this method is integrated into the controller to achieve automatic control, and the user interface enables the farmer to monitor the system status, adjust parameters, and manually override the automatic control when necessary.

[0057] As a preferred solution of this embodiment, the intelligent analysis system includes an artificial intelligence model training module and a prediction and evaluation module; wherein the artificial intelligence model training module is used to construct and train a beef cattle feeding-weight prediction model; the prediction and evaluation unit is used to predict and evaluate the daily management of beef cattle based on the beef cattle feeding-weight prediction model and real-time data.

[0058] This embodiment performs intelligent analysis based on a generative adversarial network. When designing a GAN, the generator network is responsible for taking food intake requirements as input and generating corresponding weight predictions, while the discriminator network evaluates whether these predictions are consistent with the real data. The generator network may contain fully connected layers or convolutional layers, which generate prediction results through a series of transformations. The discriminator network uses a binary classification structure, inputs real and generated weight data, and outputs the probability of consistency between the two.

[0059] During the model training phase, it is crucial to define the loss functions of the generator and the discriminator. The goal of the generator is to generate data that is realistic enough to mislead the discriminator, while the discriminator needs to distinguish between real and generated data. By training the two networks alternately, the accuracy of the weight data generated by the generator and the discriminator's ability to distinguish can be gradually improved. The specific implementation process includes: before starting training, randomly initialize the parameters of the generator and discriminator networks; for the discriminator, use the binary cross entropy loss function to measure its ability to distinguish between real and generated data; for the generator, use the inverse loss related to the discriminator loss, that is, hope that the discriminator will misjudge the generated data as real. Set up a training cycle, and in each training batch, use the generator network to generate fake weight data based on random noise or food intake requirements. Input the real data and the generated fake data into the discriminator together. Calculate the loss of the discriminator in distinguishing between real and fake data. Update the parameters of the discriminator through backpropagation to reduce the loss. Use the generator to generate new fake data and input it into the discriminator. Calculate the loss of the generator, that is, the probability that the discriminator will misjudge the fake data as real data. Update the parameters of the generator to reduce the loss and improve the quality of the generated data. Alternately train the generator and the discriminator, and apply gradient penalties or regularization techniques in the feature space to prevent the generator network from generating overly smooth or repetitive outputs. After each epoch, use the validation set to evaluate the quality of the weight data generated by the generator. Adjust the learning rate, network structure, or other hyperparameters based on the evaluation results.

[0060] The above are only preferred specific implementations of the present application, but the protection scope of the present application is not limited thereto. Any changes or substitutions that can be easily thought of by a person skilled in the art within the technical scope disclosed in the present application should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. An automatic monitoring device for beef cattle weight and feed intake, characterized in that: include: Data collection system, data processing system, feed delivery system and intelligent analysis system; Wherein, the data acquisition system is used to collect the weight data and feeding data of beef cattle in real time; The data collection system includes: a weight collection device, a feeding detection device and an identity recognition device; wherein the weight collection device is used to record the daily feed intake and daily weight of beef cattle; the feeding detection device is used to detect the amount of feed in the trough; the identity recognition device is used to identify the identity of beef cattle based on RFID; The weight collection device includes a weight scale that is larger than the length and width of the beef cattle, a manure baffle and a manure scraper, and railings on both sides; wherein the manure baffles are fixed on all sides of the weight scale, the front and left and right baffles are fixed baffles, and the rear baffle is a flippable baffle; the manure scraper is moved forward and backward by a rotating spiral rod fixed on both sides of the weight scale, and when the beef cattle eat and leave, the manure scraper turns flat to scrape out the manure, and after the manure scraping is completed, the manure scraper returns to the initial position; The feeding detection device includes a photoelectric sensor arranged above the feeding trough, and the photoelectric sensor is used to detect the change in the feed amount in the feeding trough to ensure sufficient feed supply during the feeding process of the cattle; The data processing system is used to analyze and process the collected body weight data and food intake data to obtain analysis results; The feed delivery system is used to adjust the feed delivery amount based on the analysis result; The intelligent analysis system is used to predict and evaluate the feed conversion efficiency and daily weight gain of beef cattle; the intelligent analysis system includes an artificial intelligence model training module and a prediction and evaluation module; wherein the artificial intelligence model training module is used to construct and train a beef cattle feeding-weight prediction model; the prediction and evaluation unit is used to predict and evaluate the daily management of beef cattle based on the beef cattle feeding-weight prediction model and real-time data.

2. The automatic monitoring device for beef cattle weight and feed intake according to claim 1, characterized in that: The data processing system includes a data storage module, a data calculation module and a data transmission module; Wherein, the data storage module is used to store the collected data and build a daily management database for each beef cattle; The data calculation module is used to calculate the feed intake and weight changes of beef cattle; The data transmission module is used to transmit the calculation result of the calculation unit to the intelligent analysis system.

3. The automatic monitoring device for beef cattle weight and feed intake according to claim 2, characterized in that: The feed delivery system includes a feed bin, a controller and a conveying device; Wherein, the feed bin is used to store feed; The controller is used to issue a feed delivery amount instruction based on the analysis result of the data processing system and the instruction of the intelligent analysis system; The conveying device is used to take out feed from the feed bin and put it into the feeding trough.

4. The automatic monitoring device for beef cattle weight and feed intake according to claim 1, characterized in that: The device also includes a user interaction interface; the user interaction interface is used to display parameters such as the weight, feed intake, feeding time, feed conversion efficiency, daily weight gain, etc. of the beef cattle, and provides an interface for operating and controlling the device.

5. The automatic monitoring device for beef cattle weight and feed intake according to claim 1, characterized in that: The equipment is integrated with the pasture management system to realize data exchange and sharing.

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