CN117581809A - Cattle living body supervision and evaluation system - Google Patents
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- A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
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- A—HUMAN NECESSITIES
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Abstract
The invention is suitable for the field of animal husbandry management and animal health monitoring, and provides a living body supervision and assessment system for cattle, wherein the core equipment of the system is an intelligent necklace, an animal husbandry intelligent calculation core algorithm is built in the intelligent necklace, vital sign data such as heart rate, activity and the like of cattle are collected in real time, and the data are accurately analyzed to monitor and assess the health condition of the cattle. The biological health assessment algorithm and the group behavior analysis algorithm integrated by the system can process sensor data in real time through a deep learning technology, optimize a health assessment model to assess the health condition of the cattle group, and provide visual health reports and real-time alarms through a user-friendly interface. Compared with the prior art, the method has the advantages of improving the monitoring precision, improving the user interactivity, predicting the health trend and the like, provides powerful technical support for the intellectualization of the breeding industry and animal welfare, and brings higher economic benefit for farmers.
Description
Technical Field
The invention belongs to the field of animal husbandry management and animal health monitoring, and particularly relates to a living bovine supervision and evaluation system.
Background
In conventional beef cattle farming practice, monitoring of the health and productivity of cattle is often dependent on farmer experience and periodic manual checks. The method has the advantages of high labor intensity and low efficiency, and is difficult to realize real-time monitoring of the health condition and production behavior of the cattle. Particularly in large-scale farms, detailed monitoring of individual cattle is an almost impossible task, which can easily lead to delayed treatment of diseases and poor management efficiency.
While some animal health monitoring products, such as smart collars or ear tags, are currently available on the market that can provide some degree of monitoring of information such as activity, feeding behavior, etc., most existing solutions do not provide a comprehensive health assessment. These systems often ignore the impact of environmental factors on the health of cattle, such as temperature and humidity, climate change, etc., and the analysis and processing of data is often not deep enough to provide direct decision support for farmers.
Furthermore, while some advanced systems integrate more advanced algorithms for behavioral pattern analysis, they often lack adaptivity, and it is difficult to adjust the evaluation criteria according to specific conditions of individual farms and individual differences of cattle. Algorithms of the systems cannot be generally made to have high accuracy and high universality, so that a large improvement space is still reserved in universality and accuracy in practical application.
Disclosure of Invention
The invention aims to provide a living body supervision and evaluation system for cattle, which aims to solve the technical problems in the prior art determined in the background art.
The invention provides a comprehensive living body supervision method and a health assessment system of beef cattle, which aim to monitor and deeply analyze the health condition and behavior pattern of beef cattle groups in real time through a highly integrated module and an advanced data processing technology. The system is composed of a plurality of modules, and relates to intelligent hardware equipment, an environment sensing element, a data processing unit, a user interaction interface and the like. The core intelligent hardware of the system is a custom made intelligent collar equipped with a variety of sensors including heart rate monitors, activity trackers and thermometers that collect physiological data of the cow in real time. The method is matched with an original animal husbandry intelligent computation core (Livestock Intellect Core, LINC) algorithm, so that not only can the collected parameters be analyzed in real time, but also the health trend of the cattle can be predicted from historical data, and possible health problems can be found in time.
The intelligent necklace device is used as a core component of the invention, and is designed and integrated with a series of high-precision multi-parameter physiological sensors for comprehensively monitoring key physiological indexes of cattle. This includes an accurate heart rate sensor that monitors the heart rate of the cow in real time, providing critical data for cardiovascular health. The activity level sensor can then record the frequency and intensity of movements of the cattle, thereby assessing their daily activity level and possible behavioral anomalies. In addition, the temperature sensor on the collar monitors the change of the bovine body surface temperature, is beneficial to detecting health problems such as fever and the like, and can also be used as an index of environmental stress.
At the same time, the smart collar is also equipped with sound sensors specifically tailored to monitor chewing and ruminating activities. By analyzing the chewing sound frequency, intensity and mode of the cow, the sensor can help judge the feed intake of the cow, digest health status, discover tooth problems in time and the like. The data collected by the sound sensor is critical to assessing feed efficiency and overall welfare status of the cow.
The environmental monitoring unit of the system is a link which is important for the health assessment of the cattle in the invention. This unit is equipped with a plurality of sensors, including high-precision temperature and humidity sensors and specifically designed harmful gas detection sensors, which are capable of continuously monitoring and recording key parameters in the farming environment. The temperature and humidity sensor is important to ensure the comfort of the cow and prevent heat stress. They monitor the temperature and humidity levels of the breeding environment in real time, ensuring that these conditions remain within a range that is beneficial to the health of the cattle at all times. If the monitored environmental parameters exceed preset safety thresholds, the system will immediately alert farmers, allowing them to quickly take action, such as adjusting the ventilation system, or changing the layout of the farming area, to restore the appropriate farming environment. The harmful gas detection sensor can detect the concentration of ammonia gas and other gases possibly endangering the health of the cattle. These sensors are extremely important for preventing respiratory diseases and other health problems that may result from prolonged exposure to high concentrations of harmful gases.
In order to further improve the comprehensiveness and accuracy of the monitoring, the system can be optionally provided with a video monitoring device. The devices can monitor the behaviors and movements of the cow in real time, analyze the video data through a computer vision algorithm, and identify possible behavior patterns such as group movements, frame or other abnormal behaviors, so as to provide more information about the health and welfare of the cow.
The central data processing unit is the key of the invention, and is not only a junction for data collection and distribution, but also an execution platform of a livestock intelligent computing core (LINC) algorithm. The LINC algorithm integrates individual and group data through an integrated machine learning technology, and carries out accurate assessment and prediction on the health state of the cow; meanwhile, the algorithm also has group behavior analysis capability, and the behavior dynamics of the cattle group are analyzed through statistics and pattern recognition technology, and abnormal behaviors are monitored to early warn possible epidemic situations.
The user interaction interface aims to provide an intuitive operation platform for farmers, and the user can easily access the health status dashboard, receive early warning information, view production reports and acquire management suggestions through the interface. The data visualization technology adopted in the interface intuitively displays the complex data processing result in the form of a chart and an instrument panel, and greatly simplifies the operation process of a user.
The intelligent collar is tightly matched with the central processing unit, the high-efficiency data processing capacity of the LINC algorithm is utilized, continuous monitoring and real-time health evaluation of each cow are ensured, evaluation parameters can be adjusted according to environments of different farms and individual characteristics of the cows, and the adaptability and accuracy of the system are improved.
The beneficial effects of the invention are as follows: .
The invention realizes real-time monitoring of the health condition and the breeding environment of the cattle by utilizing the comprehensive data acquisition of the intelligent necklace and the environment monitoring unit. The physiological sensors of the intelligent collar equipment can continuously monitor the heart rate, the activity, the body temperature and the ruminant activity of the cow, and the heart rate, the activity, the body temperature and the ruminant activity are key physiological indexes for evaluating the health condition of the cow. For example, an abnormality in heart rate may be a sign of early disease, while a decrease in activity may indicate that the cow is only lack of activity or has a health problem. The traditional manual inspection mode is difficult to continuously and accurately capture the fine changes, and the invention can capture health risks in real time and send early warning in time through continuous monitoring.
In addition, the invention provides a data-driven decision support system by comprehensively analyzing the physiological data and the environmental data of the cattle. The animal intelligence core (LINC) algorithm not only processes a single data point, but also can identify correlations between multiple data, revealing complex interactions between health and environmental factors. This enables farmers to make more scientific and rational management decisions based on comprehensive analysis results. For example, if the analysis shows an increased incidence of certain diseases under certain environmental conditions, the farmer may adjust the cultivation strategy.
Finally, the system design provided by the invention considers the diversity of cultivation scale and conditions, and has good applicability and expandability. The system can be customized and expanded according to specific needs, whether it be a small-scale home farm or a large commercial farm. The design of the smart collar allows for use in different types and sizes of cattle, while the central data processing unit and user interface can be functionally expanded and customized according to the specific needs of the user.
Detailed Description
The present invention will be described in further detail with reference to the following examples in order to make the objects, technical solutions and advantages of the present invention more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
It will be understood that the terms "first," "second," and the like, as used herein, may be used to describe various elements, but these elements are not limited by these terms unless otherwise specified. These terms are only used to distinguish one element from another element. For example, a first xx script may be referred to as a second xx script, and similarly, a second xx script may be referred to as a first xx script, without departing from the scope of the present application.
A bovine living supervision evaluation system, the system comprising:
the intelligent necklace is provided with a heart rate sensor, an activity sensor, a temperature sensor and a position sensor which are used for collecting physiological data and behavior data of the cattle in real time;
the data processing unit is internally provided with a livestock intelligence calculation core algorithm and is used for carrying out multidimensional analysis on biological health scores and group behavior patterns of the cattle;
and a user interface for generating a visual chart and a custom report, displaying the comprehensive analysis result obtained from the animal intelligence core algorithm, and transmitting a health condition alarm based on a predetermined threshold set by a user.
In an embodiment of the present invention, the smart collar further includes:
the environment sensing sensor is used for monitoring environment data around the cattle, wherein the environment data comprise temperature, humidity and illumination intensity;
the environment data is combined with the physiological data through a weighted fusion algorithm and is used for acquiring an evaluation result of the welfare state of the cow, and the evaluation result is displayed in the welfare index of the user interface.
In the embodiment of the invention, the animal intelligence calculation core algorithm comprises a biological health assessment module, wherein the biological health assessment module comprises a nonlinear dynamic system and is used for analyzing heart rate variability and identifying stress state and early symptoms of diseases by utilizing a compound event processing technology in combination with environmental factors and behavior data.
In the embodiment of the invention, the animal husbandry intelligent computation core algorithm further comprises a group behavior analysis module, wherein the group behavior analysis module applies an unsupervised learning technology, performs high-dimensional data analysis of group dynamic change according to the movement mode and social interaction data of the cattle, optimizes the breeding management strategy and provides a group health map on a user interface.
In an embodiment of the present invention, the bovine living body supervision and evaluation system further includes:
the communication module is used for enabling the intelligent necklace to communicate with the data processing unit through a wireless network, supports 4G/LTE and NB-IoT communication standards, and supports remote data access and cloud-based real-time alarm notification.
In the embodiment of the invention, the user interface can be customized by a user, allows the user to adjust health and behavior monitoring parameters according to the requirements of a farm, learns user preferences by using a machine learning recommendation system to automatically adjust the parameters, and can derive data reports for long-term trend analysis and management decision support.
In the embodiment of the invention, the data processing unit adopts a time sequence analysis method to analyze and predict health trend and welfare trend, and stores the history in the form of time stamp.
In the embodiment of the invention, the data processing unit adopts a deep learning framework for identifying and predicting and analyzing the complex pattern.
In an embodiment of the present invention, the smart collar further includes:
and the energy management module dynamically adjusts the data transmission frequency and the sensor sampling rate through an algorithm to optimize energy consumption, and sends a device charging or replacement prompt to a user according to the use condition and the electric quantity level.
The core formula of the intelligent livestock calculation core algorithm combines the principles of biometry, machine learning and behavior science;
a comprehensive health index (Comprehensive Health Index, CHI) is defined that can integrate heart rate variability, activity, temperature and other relevant biological indicators of the cow to assess health status. The design of the integrated health index aims to provide a standardized health score for each cow so that breeders can quickly identify animals that need special attention. Furthermore, it allows for an effective comparison of the health status of cattle at different time points and under different environmental conditions.
Let HRV be heart rate variability score, a be activity score, T be temperature score, E be environmental factor score (including humidity, light, etc.), then CHI may be expressed as:
CHI＝ω 1 ·f(HRV)+ω 2 ·g(A)+ω 3 ·h(T)+ω 4 ·k(E)；
HRV (Heart Rate Variability) is heart rate variability, which is collected by a heart rate sensor of the intelligent necklace and represents natural fluctuation of heart rate, and the heart rate variability is an important physiological index and can reflect the stress state of animals and the activities of an autonomic nervous system;
f (HRV) is a transfer function of heart rate variability for converting the raw HRV values into a score suitable for the integrated health index;
the function may be adjusted according to the statistical properties of the heart rate variability data:
wherein μhrv is the target value of heart rate variability, i.e. the average HRV of healthy cattle, while σhrv is the allowed standard deviation, determining the extent to which HRV deviates from the average;
a (Activity Level) is activity, and the movement condition of the cattle is monitored by an activity sensor of the intelligent necklace, including the time proportion of walking, standing and lying;
g (A) is a conversion function of activity amount and is used for converting the activity data of the cattle into health scores, and different score levels are set based on activity threshold values;
where a is the actual observed activity amount and A0 is the desired activity level;
t (Temperature) is the cow body temperature or ambient temperature measured by the temperature sensor of the intelligent collar;
h (T) is a conversion function of temperature for converting body temperature data into health scores;
e (Environmental Factors) is an environmental parameter monitored by the intelligent collar or an external device, such as temperature, humidity, illumination intensity, etc.;
k (E) is a conversion function of environmental factors and is used for integrating various environmental indexes into an environmental benefit score;
ω 1 、ω 2 、ω 3 、ω 4 for the weight coefficients, the relative importance of heart rate variability, activity, body temperature and environmental factors in the integrated health index are defined, respectively. These weight coefficients need to be determined from experimental data to ensure that the CHI accurately reflects the health of the cow.
The living body supervision method and the health evaluation system for the beef cattle provided in the embodiment aim to solve a series of challenges in the traditional beef cattle cultivation field. The intelligent necklace equipment of system core part for an innovative design, this equipment has integrated multiple physiological parameter sensor, including heart rate sensor, activity sensor, body temperature sensor etc. can carry out accurate monitoring to the basic vital sign of ox only. The comprehensive monitoring means is designed aiming at the conditions that the traditional cultivation relies on manual observation, has large error and has extremely low efficiency, and can remarkably improve the accuracy and timeliness of monitoring data, so that a cultivation manager can timely master the health condition of cattle. By utilizing intelligent necklace equipment, the system not only can collect physiological parameters in real time, but also can capture tiny physiological changes which can cause health problems through high-frequency data acquisition. For example, when cattle are in oestrus or abnormal health, the heart rate and activity levels often change significantly. Through the real-time monitoring of the parameters, farmers can respond timely, and the breeding efficiency and the welfare of cattle can be effectively improved no matter the breeding is arranged or the treatment is carried out early. The data collected by the sensors are transmitted to a central data processing unit in real time through a wireless network and are processed and analyzed by an advanced data analysis algorithm, so that practical information and management advice are provided for farmers.
In this embodiment, the intelligent collar device worn by each cow is a multifunctional physiological monitoring tool, which has the capability of monitoring key physiological indexes such as heart rate, activity, body temperature, chewing frequency and the like in real time. The monitoring not only responds to the requirements of the prior art for real-time and continuous monitoring, but also improves the accuracy and reliability of the monitoring data. The intelligent collar built-in animal husbandry mental arithmetic core (LINC) algorithm is an advanced data processing algorithm designed specifically for understanding and interpreting these physiological indicators. The method can process a large number of data points, can identify abnormal health modes and trends from the data, and provides immediate disease early warning for farmers. The LINC algorithm can self-learn and adapt to the physiological characteristics of each head cow by utilizing a machine learning technology, thereby realizing individual monitoring. When the algorithm detects an abnormal mode, such as a continuous increase in heart rate or an abnormal change in activity, it automatically triggers an alarm system to prompt the farmer to take corresponding measures. Furthermore, by analyzing changes in body temperature and chewing frequency, algorithms can predict and identify estrus or digestive system problems earlier, which is critical to improving reproductive rate and reducing disease incidence.
Furthermore, the LINC algorithm also fuses the analysis of environmental factors, and combines physiological data measured by the intelligent necklace with environmental indexes such as temperature and humidity, ammonia concentration and the like collected by the environmental monitoring unit. Such a comprehensive analysis enables the algorithm to monitor not only the health status of the individual, but also to evaluate the health impact of the breeding environment in which the whole population is located. The comprehensive health management means makes LINC algorithm play a vital role in improving the cultivation efficiency and animal welfare. Through the advanced technical application, farmers can manage cattle groups more scientifically, and the beef cattle cultivation practice with higher efficiency and more intelligence is realized.
The data transmission mechanism of the intelligent necklace is realized through a wireless technology, and the design thought of the intelligent necklace is derived from the aim of reducing the manpower monitoring burden and improving the real-time performance of data. Through the mechanism, data are transmitted to the central data processing unit in real time, so that timeliness and accuracy of information are ensured, and efficiency of management decision making of farmers is directly affected.
The specific implementation steps are as follows:
a. the intelligent necklace is arranged on the neck of the cow, and physiological data and behavioral data of the cow are collected on the premise of not interfering with normal activities of the cow;
b. the environmental monitoring unit is installed in a suitable location and monitoring of the environmental conditions of the cowshed is started.
c. The collected data are transmitted to a central data processing unit in real time through a wireless network, and comprehensive analysis is carried out by a livestock intelligent computing core (LINC) algorithm.
d. When the system detects potential health risks or environmental problems, early warning is immediately sent to farmers through a user interface, and corresponding suggested measures are provided.
e. The farmer can check the dynamic data report through the user interface and monitor the health status of the cow and the real-time status of the breeding environment.
f. The system continuously optimizes the algorithm according to the feedback and the historical data of farmers, and improves the accuracy of evaluation and early warning.
The environmental monitoring unit of the system fuses the monitoring of temperature and humidity and harmful gas (such as ammonia gas), which expands the environmental perception capability mentioned in the claims, realizes the comprehensive monitoring of the environmental quality of the cowshed, combines with the physiological parameter monitoring mentioned above, and comprehensively improves the management efficiency of the cultivation environment.
The user interaction interface is a bridge of the invention, which not only reflects the requirements of the management system which is friendly to users and is proposed in the technical background, but also is an important tool for converting technical details into operation suggestions which can be directly used by farmers, thereby improving the practicability and usability of the system.
Those skilled in the art will appreciate that all or part of the processes in the methods of the above embodiments may be implemented by a computer program for instructing relevant hardware, where the program may be stored in a non-volatile computer readable storage medium, and where the program, when executed, may include processes in the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in the various embodiments provided herein may include non-volatile and/or volatile memory. The nonvolatile memory can include Read Only Memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double Data Rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous Link DRAM (SLDRAM), memory bus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), among others.
The technical features of the above-described embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above-described embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.
The foregoing examples illustrate only a few embodiments of the invention and are described in detail herein without thereby limiting the scope of the invention. It should be noted that it will be apparent to those skilled in the art that several variations and modifications can be made without departing from the spirit of the invention, which are all within the scope of the invention. Accordingly, the scope of protection of the present invention is to be determined by the appended claims.
The foregoing description of the preferred embodiments of the invention is not intended to be limiting, but rather is intended to cover all modifications, equivalents, and alternatives falling within the spirit and principles of the invention.
Claims (10)
1. A bovine living supervision and assessment system, the system comprising:
the intelligent necklace is provided with a heart rate sensor, an activity sensor, a temperature sensor and a position sensor which are used for collecting physiological data and behavior data of the cattle in real time;
the data processing unit is internally provided with a livestock intelligence calculation core algorithm and is used for carrying out multidimensional analysis on biological health scores and group behavior patterns of the cattle;
and a user interface for generating a visual chart and a custom report, displaying the comprehensive analysis result obtained from the animal intelligence core algorithm, and transmitting a health condition alarm based on a predetermined threshold set by a user.
2. The system of claim 1, wherein the smart collar further comprises:
the environment sensing sensor is used for monitoring environment data around the cattle, wherein the environment data comprise temperature, humidity and illumination intensity;
the environment data is combined with the physiological data through a weighted fusion algorithm and is used for acquiring an evaluation result of the welfare state of the cow, and the evaluation result is displayed in the welfare index of the user interface.
3. The system of claim 2, wherein the animal intelligence core algorithm includes a biological health assessment module, wherein the biological health assessment module includes a nonlinear dynamic system for analyzing heart rate variability and using compound event processing techniques to identify stress states and early signs of disease in combination with environmental factors and behavioral data.
4. A system according to claim 3, wherein the herding mental arithmetic core algorithm further comprises a group behavior analysis module, wherein the group performance is that the analysis module applies an unsupervised learning technology, performs high-dimensional data analysis of group dynamic change according to the movement mode and social interaction data of the cattle, optimizes the breeding management strategy and provides a group health map on a user interface.
5. The system of claim 1, wherein the bovine living supervision evaluation system further comprises:
the communication module is used for enabling the intelligent necklace to communicate with the data processing unit through a wireless network, supports 4G/LTE and NB-IoT communication standards, and supports remote data access and cloud-based real-time alarm notification.
6. The system of any one of claims 1 to 5, wherein the user interface is customizable by a user, allowing the user to adjust health and behavioral monitoring parameters according to farm needs, wherein the user interface learns user preferences using a machine learning recommendation system to automatically adjust parameters, and wherein data reports for long term trend analysis and management decision support can be derived.
7. The system of claim 6, wherein the data processing unit employs a time series analysis method to analyze and predict health trends and welfare trends and stores the history in the form of time stamps.
8. The system of claim 7, wherein the data processing unit employs a deep learning framework for recognition and predictive analysis of complex patterns.
9. The system of claim 8, wherein the smart collar further comprises:
and the energy management module dynamically adjusts the data transmission frequency and the sensor sampling rate through an algorithm to optimize energy consumption, and sends a device charging or replacement prompt to a user according to the use condition and the electric quantity level.
10. The system of claim 1, wherein the core formula of the animal intelligence core algorithm incorporates biometrics, machine learning, and behavioral science principles;
defining a comprehensive health index (Comprehensive Health Index, CHI) for estimating health status by integrating heart rate variability, activity, temperature and other related biological indicators of the cow;
let HRV be heart rate variability score, a be activity score, T be temperature score, E be environmental factor score (including humidity, light, etc.), then CHI may be expressed as:
CHI＝ω 1 ·f(HRV)+ω 2 ·g(A)+ω 3 ·h(T)+ω 4 ·k(E)；
wherein HRV (Heart Rate Variability) is heart rate variability, collected by heart rate sensors of the smart collar, representing natural fluctuations in heart rate;
f (HRV) is a transfer function of heart rate variability for converting the raw HRV values into a score suitable for the integrated health index;
the function may be adjusted according to the statistical properties of the heart rate variability data:
wherein μhrv is the target value of heart rate variability, i.e. the average HRV of healthy cattle, while σhrv is the allowed standard deviation, determining the extent to which HRV deviates from the average;
a (Activity Level) is activity, and the movement condition of the cattle is monitored by an activity sensor of the intelligent necklace, including the time proportion of walking, standing and lying;
g (A) is a conversion function of activity amount and is used for converting the activity data of the cattle into health scores, and different score levels are set based on activity threshold values;
where a is the actual observed activity amount and A0 is the desired activity level;
t (Temperature) is the cow body temperature or ambient temperature measured by the temperature sensor of the intelligent collar;
h (T) is a conversion function of temperature for converting body temperature data into health scores;
e (Environmental Factors) is an environmental parameter monitored by the smart collar or external device;
k (E) is a conversion function of environmental factors and is used for integrating various environmental indexes into an environmental benefit score;
ω 1 、ω 2 、ω 3 、ω 4 for the weight coefficients, the relative importance of heart rate variability, activity, body temperature and environmental factors in the integrated health index are defined, respectively.
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| CN117850601A (en) * | 2024-03-08 | 2024-04-09 | 南昌大学第二附属医院 | System and method for automatically detecting vital signs of handheld PDA |
| CN117850601B (en) * | 2024-03-08 | 2024-05-14 | 南昌大学第二附属医院 | System and method for automatically detecting vital signs of handheld PDA |
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