An electronic collar for monitoring the behavior of cows

Abstract

This utility model relates to the field of electronic collar technology and discloses an electronic collar for monitoring the behavior of cows. It includes a fixing block with a mounting groove on its top. A control system component is fixedly installed on the inner bottom wall of the mounting groove, and an annular groove is formed on the outer surface of the fixing block. This electronic collar for monitoring the behavior of cows engages with a fixing strap via the annular groove of the fixing block, allowing for detachable connection. A limiting frame laterally limits the fixing strap, and the fixing frame is further reinforced by the engagement of the locking block and the locking groove, effectively preventing the collar from falling off. The flexible fixing strap reduces pressure on the cow's neck and lowers stress response. By integrating multiple sensors to continuously collect behavioral data and combining it with a behavioral pattern library trained on a large number of samples, a machine learning algorithm combining decision trees and neural networks is used to accurately classify and judge the cow's behavioral states such as estrus and health, reducing false alarm and false negative rates and solving the problem of poor adaptability of traditional threshold judgment methods.

Description

Technical Field

[0001] This utility model relates to the field of electronic collar technology, specifically an electronic collar for monitoring the behavior of cows. Background Technology

[0002] As the livestock industry develops towards large-scale and intensive operations, the requirements for the precision of cow breeding management are increasing. Key information such as the identification of the estrus cycle, health status assessment, and activity monitoring of cows directly affect reproductive efficiency and economic benefits of breeding.

[0003] However, existing technologies have the following problems in practical use:

[0004] Existing monitoring equipment has functional limitations. Some devices can only collect single behavioral parameters, and some collar-type devices have unreasonable structural designs that make them easy to fall off when worn. In terms of data transmission, due to the complex environment of farms, existing equipment often suffers from unstable signals and high latency, which cannot meet the needs of remote real-time monitoring. At the same time, in terms of behavioral analysis algorithms, traditional equipment mostly uses simple threshold judgments, which are difficult to adapt to the behavioral differences of cows of different breeds and ages, resulting in high false alarm and false negative rates. Utility Model Content

[0005] (a) Technical problems to be solved

[0006] To overcome the aforementioned shortcomings of the prior art, this utility model provides an electronic collar for monitoring the behavior of cows, which solves the problems in the prior art:

[0007] Existing monitoring equipment has functional limitations. Some devices can only collect single behavioral parameters, and some collar-type devices have unreasonable structural designs that make them easy to fall off when worn. In terms of data transmission, due to the complex environment of farms, existing equipment often suffers from unstable signals and high latency, which cannot meet the needs of remote real-time monitoring. At the same time, in terms of behavioral analysis algorithms, traditional equipment mostly uses simple threshold judgments, which are difficult to adapt to the behavioral differences of cows of different breeds and ages, resulting in high false alarm and false negative rates.

[0008] (II) Technical Solution

[0009] To achieve the above objectives, this utility model is implemented through the following technical solution: an electronic collar for monitoring the behavior of cows, including a fixing block, a mounting groove is provided on the top of the fixing block, a control system element is fixedly installed on the inner bottom wall of the mounting groove, an annular groove is provided on the outer surface of the fixing block, a fixing strap is snapped into the inner wall of the annular groove, the two ends of the fixing strap are detachably connected, and a fixing frame is detachably connected to one side of the outer surface of the fixing block.

[0010] Optionally, a sealing cover plate for sealing is fixedly installed on the inner wall of the mounting groove.

[0011] Optionally, limit frames are fixedly installed on both sides of the fixing block, and are located on the outside of the fixing belt.

[0012] Optionally, the top and bottom of the fixing frame are threaded with fixing bolts, and the top and bottom of the fixing block are provided with threaded holes that are compatible with the fixing bolts.

[0013] Optionally, a positioning post is fixedly installed on the surface of one end of the fixing band, and a positioning hole adapted to the positioning post is opened on the surface of the other end of the fixing band, and a limit ring is sleeved on the surface of one end of the fixing band.

[0014] Optionally, a locking block is fixedly installed on the inner side wall of the fixing frame, and a slot adapted to the locking block is opened on the surface of the fixing belt.

[0015] Optional features include: data acquisition and initialization, where the electronic collar installed around the cow's neck is powered on and the control system components perform self-checks, verifying the proper functioning of sensors and data transmission modules, while simultaneously acquiring the cow's initial position information through the positioning module and recording the monitoring start time; behavior monitoring, where sensors within the fixed block continuously monitor cow behavior data, reading and storing data at preset time intervals and performing preliminary processing; behavior analysis and judgment, where the processed data is compared with a pre-stored behavior pattern library, and machine learning algorithms are used for analysis and classification to determine the cow's behavioral state; data transmission and remote monitoring, where the analyzed cow behavior information is sent to a remote ranch monitoring center server via the data transmission module within the fixed frame, allowing managers to view it via a terminal; feedback and alarm, where the control system components trigger an alarm device within the fixed frame to emit an audible and visual alarm signal when abnormal cow behavior is detected, while the remote monitoring center receives the alarm information and displays a pop-up notification window; and energy management and system maintenance, where the power management module within the control system components monitors battery power, automatically adjusts the operating mode to reduce power consumption, and receives system update commands from the remote monitoring center to update and upgrade the system.

[0016] Optionally, in the behavior analysis and judgment step, the behavior pattern library is obtained by collecting a large amount of normal and abnormal behavior data of cows and training it, and the machine learning algorithm adopts a combination of decision trees and neural networks.

[0017] Optionally, in the data transmission and remote monitoring steps, the data transmission module adopts 4G / 5G wireless communication technology, and the remote ranch monitoring center server can simultaneously receive and store data sent by multiple cow electronic collars.

[0018] Optionally, in the feedback and alarm step, the alarm device includes a buzzer and an indicator light, and the alarm information includes detailed information such as the cow's number, location, and type of abnormal behavior.

[0019] (III) Beneficial Effects

[0020] This utility model provides an electronic collar for monitoring the behavior of cows, which has the following beneficial effects:

[0021] This electronic collar for monitoring cow behavior uses a locking mechanism where a ring groove on a fixing block engages with a fixing strap, allowing for detachable connection. A limiting frame laterally restricts the strap, and the frame is further reinforced by the interlocking blocks and grooves, effectively preventing the collar from detaching. The flexible fixing strap reduces pressure on the cow's neck, minimizing stress. By integrating multiple sensors to continuously collect behavioral data and combining it with a behavior pattern library trained on a large sample size, a machine learning algorithm combining decision trees and neural networks is employed to accurately classify and judge the cow's estrus, health, and other behavioral states, reducing false alarm and false negative rates and addressing the poor adaptability of traditional threshold-based methods. A 4G / 5G data transmission module within the fixing frame ensures stable signal even in complex farm environments, enabling real-time transmission of analysis results to a remote monitoring center. It supports simultaneous data reception and storage from multiple devices, meeting the remote management needs of large-scale farming. When abnormal behavior occurs, local audible and visual alarms and remote terminal notifications are triggered simultaneously. Alarm information includes the cow's number, location, and type of abnormality, facilitating rapid location and handling by management personnel and minimizing losses. Attached Figure Description

[0022] Figure 1 This is a schematic diagram of the structure of this utility model;

[0023] Figure 2 This is a schematic diagram of the fixed frame structure of this utility model;

[0024] Figure 3 This is the control flowchart of this utility model.

[0025] In the diagram: 1. Fixing block; 2. Mounting groove; 3. Control system component; 4. Annular groove; 5. Fixing belt; 6. Positioning post; 7. Limiting ring; 8. Positioning hole; 9. Limiting frame; 10. Fixing frame; 11. Fixing bolt; 12. Clamping block; 13. Sealing cover plate. Detailed Implementation

[0026] The technical solutions of the present utility model will be clearly and completely described below with reference to the accompanying drawings of the embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present utility model without creative effort are within the scope of protection of the present utility model.

[0027] Please see Figures 1 to 3 This utility model provides a technical solution: an electronic collar for monitoring the behavior of cows.

[0028] I. Structural Components and Assembly Implementation

[0029] 1. Fixed block structure

[0030] The fixing block is injection molded from ABS engineering plastic. It is arc-shaped to fit the curve of the cow's neck. It is 8cm long, 5cm wide, and 3cm thick. The top mounting groove is 6cm×4cm×2cm. The inner bottom wall is fixed with control system components, including an STM32H743 microprocessor, an MPU6050 six-axis accelerometer, a DS18B20 temperature sensor, and a Beidou positioning module. The opening of the mounting groove is sealed to the sealing cover plate with a silicone sealing ring. The sealing cover plate is made of PC transparent material and is fastened to the fixing block with 4 M3 self-tapping screws.

[0031] 2. Fixing strap and connecting structure

[0032] The fixing strap is made of food-grade silicone with a width of 2.5cm and a thickness of 3mm. The surface is frosted to enhance the anti-slip properties. One end of the fixing strap has three cylindrical positioning posts with a diameter of 8mm, made of nylon, spaced 3cm apart. The other end has three sets of positioning holes with a diameter of 8.2mm. Five slots with a depth of 2mm and a width of 5mm are evenly distributed within a 10cm range at the end. One end of the fixing strap is fitted with an ABS limiting ring with an inner diameter of 2.6cm. During assembly, the free end of the fixing strap is passed through the limiting ring and then folded back so that the positioning posts are engaged with the corresponding positioning holes to achieve length adjustment. The adjustment range is 30-50cm.

[0033] 3. Fixed frame and limiting structure

[0034] The fixing frame has a U-shaped structure, is made of ABS material, and is 6cm long. Two elastic blocks made of rubber are symmetrically set on the inner side wall to fit the slot. M4 threaded holes are reserved at the top and bottom. The fixing blocks are connected to the fixing blocks by two 15mm long stainless steel fixing bolts. The limiting frames on both sides of the fixing blocks are made of PVC material, are 2cm high, and have a 0.5cm gap between the inner side and the fixing band to prevent the fixing band from shifting laterally.

[0035] II. Implementation Steps of Control Methods

[0036] 1. Data Acquisition and Initialization

[0037] The electronic collar has a built-in 3.7V lithium battery with a capacity of 2000mAh. After being powered on, the control system components start a self-test, which takes about 10 seconds. It detects the sensor communication status through the I2C bus and the data transmission module through AT commands. It uses the SIM8200CE5G module for network connectivity. The positioning module is BDS / GPS dual-mode to obtain the initial position with an accuracy of ≤10m. It also records the start time with accuracy to the second through the RTC module.

[0038] 2. Behavior monitoring parameter settings

[0039] The sensor sampling frequency is set to 10Hz, and a set of data is stored every 5 minutes, including triaxial acceleration, body surface temperature, and cumulative activity value. The data is temporarily stored in a 4GB SD card. The preliminary processing includes removing outliers, such as considering temperatures >42℃ or <36℃ as invalid, and calculating the acceleration variance within 1 minute.

[0040] 3. Behavioral analysis model training

[0041] The behavioral pattern database contains behavioral data from 500 cows, collected from each cow for 3 months. The data is divided into three categories: normal activity, feeding, rumination, resting, estrus behavior, mounting, frequent walking, and abnormal conditions, as well as elevated body temperature and sudden drop in activity. The machine learning model uses a C4.5 decision tree for coarse classification, and then uses a 3-layer BP neural network with 8 features in the input layer and 16 neurons in the hidden layer to optimize the classification results. The model accuracy was tested and reached 92%.

[0042] 4. Data transmission and alarm mechanism

[0043] Data transmission uses 5GCat.1 communication. Under normal conditions, summary data is uploaded once per hour, and when an abnormal condition is triggered, it is uploaded immediately with a delay of ≤3 seconds. The remote monitoring center uses Alibaba Cloud servers and supports simultaneous access to 1000 devices. Administrators can view real-time data through WeChat mini-programs or PCs, with a refresh rate of 1 minute.

[0044] Alarm thresholds are set to trigger when body temperature exceeds 39.5℃, activity level changes by ±50% from the previous day's average, or estrus characteristics persist for more than 15 minutes. The local alarm device is a 5V buzzer with a loudness of 85dB and a red LED light with a flashing frequency of 1Hz. Remote alarm information is pushed via SMS and mini-program, including cow number C0123, location 38.5°N 116.2°E, and abnormality type such as elevated body temperature of 39.8℃.

[0045] 5. Energy Management Strategies

[0046] The power management module detects the battery voltage via ADC. When the battery level is less than 20%, it automatically switches to low-power mode, extends the sampling interval to 10 minutes, and disables the 5G module, retaining only the Bluetooth wake-up function. The battery life can reach 30 days on a full charge. The system supports OTA remote upgrades. The upgrade package is transmitted via 5G, and the firmware is automatically replaced after verification, which takes about 2 minutes.

[0047] III. Assembly and Usage Instructions

[0048] 1. During assembly, insert the fixing strap 5 into the annular groove 4 of the fixing block 1, adjust the length and fix it with the positioning post 6, then attach the fixing frame 10 to the groove of the fixing strap 5, and tighten the fixing bolt 11 to complete the assembly.

[0049] 2. Before use, the collar must be connected via Bluetooth, and the cow's basic information, such as its number, age, and breed, must be entered into the local storage module to ensure that it matches the number in the remote system.

[0050] 3. It is recommended to check the wear of the fixing strap 5 monthly, and charge it through the reserved charging port of the sealing cover 13 to avoid disassembly affecting the sealing performance.

[0051] Although embodiments of the present invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the present invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. An electronic collar for monitoring the behavior of cows, comprising a fixing block (1), characterized in that: The top of the fixing block (1) is provided with an installation groove (2), and the inner bottom wall of the installation groove (2) is fixedly installed with a control system element (3). The outer surface of the fixing block (1) is provided with an annular groove (4), and the inner wall of the annular groove (4) is fitted with a fixing strap (5). The two ends of the fixing strap (5) are detachably connected, and a fixing frame (10) is detachably connected to one side of the outer surface of the fixing block (1).

2. The electronic collar for monitoring cow behavior according to claim 1, characterized in that: The inner wall of the mounting groove (2) is fixedly installed with a sealing cover plate (13) for sealing.

3. The electronic collar for monitoring cow behavior according to claim 1, characterized in that: Limit frames (9) are fixedly installed on both sides of the fixing block (1) and are located outside the fixing belt (5).

4. The electronic collar for monitoring cow behavior according to claim 1, characterized in that: The top and bottom of the fixed frame (10) are threaded with fixing bolts (11), and the top and bottom of the fixed block (1) are threaded with threaded holes that are compatible with the fixing bolts (11).

5. The electronic collar for monitoring cow behavior according to claim 1, characterized in that: A positioning post (6) is fixedly installed on the surface of one end of the fixing band (5), and a positioning hole (8) adapted to the positioning post (6) is opened on the surface of the other end of the fixing band (5). A limit ring (7) is sleeved on the surface of one end of the fixing band (5).

6. The electronic collar for monitoring cow behavior according to claim 1, characterized in that: The inner wall of the fixed frame (10) is fixedly installed with a card block (12), and the surface of the fixed belt (5) is provided with a card groove that is compatible with the card block (12).

Images