CN105091938A - Poultry health monitoring method and system - Google Patents
Poultry health monitoring method and system Download PDFInfo
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Abstract
The invention provides a poultry health monitoring method and a system. The method comprises the following steps. Step 1: a tri-axial acceleration transducer of a data acquiring unit, based on pre-set acquired sample frequency, obtains data concerning tri-axial acceleration of N poultry, wherein N is an integer greater than zero; step 2: a data processing unit utilizes a cluster computing method to conduct cluster analysis on the obtained data concerning tri-axial acceleration so as to obtain time-series data concerning the basic behavior of each of the poultry; and step 3; the data processing unit compares and analyzes the time-series data with a pre-set threshold value parameter to obtain the health information of each of the poultry. The system provided by the invention comprises a data acquiring unit, a micro-storing unit, a wireless transmission unit and a data processing unit. According to the embodiments of the invention, the system is fairly adaptive, is less affected by an external environment, and can provide high accurate monitoring results. The method and the system also play a favorable role in judging behaviors of poultry, monitoring the health of poultry, breeding poultry according to the classification of poultry and achieving quality supervision throughout a whole process.
Description
Technical field
The present invention relates to the application of information network technique at livestock and poultry cultivation management domain, particularly livestock birds health condition monitoring method and system.
Background technology
Along with the development of information network technique, information network technique is used for traditional livestock and poultry cultivation management and is day by day subject to the people's attention.Livestock and poultry cultivation management is advanced towards robotization, informationization and intelligentized direction.In recent years, the requirement of China to livestock birds health cultivation and omnidistance quality monitoring is very strict, so just require to utilize advanced sensor technology and information network technique to carry out digital safety monitoring to livestock and poultry cultivation whole process, and carries out Classified optimization cultivation to it.
Disclosed a kind of scheme realizing livestock birds health condition monitoring mainly relies on the physiological parameters such as the electrocardio of Real-Time Monitoring livestock and poultry, brain electricity, body temperature and blood pressure and measures the behavioral parameters such as livestock and poultry travel distance, motion frequency and the speed of travel at present, then determine behavior and the health status of measured livestock and poultry according to the comparative result of parameters obtained and parameter preset, carry out classification cultivation.
Because the motion state similarity in the daily activity in production of livestock and poultry is larger, livestock and poultry behavior is made and health status judgement can exist very big error by means of only said method, the accuracy rate of classification cultivation is unsatisfactory, and judged result affects by factors such as external environment situation and livestock and poultry individual differences.Therefore, existing technical matters how to provide a kind of applicability strong, little by environmental conditions and the livestock birds health condition monitoring method that accuracy rate is high.
Summary of the invention
In order to solve the problems of the technologies described above, one aspect of the present invention proposes a kind of livestock birds health condition monitoring method, comprises the following steps:
S1: the 3-axis acceleration sensor in data acquisition unit gathers the 3-axis acceleration data of N number of livestock and poultry according to presetting sample frequency, wherein N be greater than 0 integer;
S2: data processing unit carries out cluster analysis by clustering algorithm to described 3-axis acceleration data, obtains the time series data of all kinds of basic act of each livestock and poultry;
S3: described time series data and the threshold parameter preset are compared analysis by data processing unit, draw the health information of each livestock and poultry.
Preferably, while data processing unit draws the health information of each livestock and poultry described in described step S3, indicate the identity information of each livestock and poultry;
Wherein, described identity information is the information of the electronic tag that the identity recognizing unit in described data acquisition unit identifies; Described electronic tag is positioned on the outside surface of each livestock and poultry health.
Preferably, in described step S2, described data processing unit carries out cluster analysis by clustering algorithm to described behavior acceleration information, specifically comprises the following steps:
S21: all kinds of basic acts of described N number of livestock and poultry are divided into K classification, presets the cluster centre of a described K classification, wherein K be greater than 0 integer;
S22: calculate the behavior acceleration information of each livestock and poultry in described N number of livestock and poultry and the Euclidean distance of a described K cluster centre respectively, the behavior acceleration information of described each livestock and poultry is assigned in the classification representated by the cluster centre minimum with its Euclidean distance;
S23: respectively all behavior acceleration informations that each classification in a described K classification comprises are averaged, using described average as the new cluster centre of this classification, calculate all behavior acceleration informations in this classification to the square distance of cluster centre new described in such other and;
S24: judge cluster centre and described square distance and value whether change, if do not change, then cluster terminates; If change, then repeat step S22.
Preferably, in described step S21, all kinds of basic acts of described N number of livestock and poultry are divided into K classification to be specially:
All kinds of basic acts of described N number of livestock and poultry are divided into K=4 classification, described 4 classifications comprise lying behaviour, behavior of standing or be careful, foraging behaviour and across slip a line for.
Preferably, the cluster centre presetting a described K classification in described step S21 is specially: the cluster centre presetting a described K classification according to ambient data;
Wherein, described ambient data is the temperature of the surrounding environment at the livestock and poultry place that temperature sensor, baroceptor and relative humidity sensor in described data acquisition unit collect respectively, air pressure and relative humidity.
Preferably, described step S1 also comprises subminiature memory cells and stores the data message that described data acquisition unit acquires arrives.
Preferably, described step S1 also comprises and utilizes wireless transmission unit that the data message of described data acquisition unit acquires is transferred to described data processing unit through conversion process.
Preferably, the infrared video collecting device in described data acquisition unit gathers the complete monitoring video of each livestock and poultry behavior; Described monitor video is utilized to examine described health information.
Preferably, data processing unit provides managerial integration to each livestock and poultry according to the health information of described each livestock and poultry; Described managerial integration comprises and hives off, isolates or maintain former stable breeding mode.
The present invention proposes a kind of livestock birds health condition monitoring system on the other hand, comprises data acquisition unit, subminiature memory cells, wireless transmission unit and data processing unit;
Described data acquisition unit comprises: 3-axis acceleration sensor, identity recognizing unit, temperature sensor, baroceptor, relative humidity sensor and infrared video collecting device;
Described 3-axis acceleration sensor, temperature sensor, baroceptor and relative humidity sensor are integrated into microsensor unit, are arranged on the outside surface of each livestock and poultry health;
Described identity recognizing unit and described infrared video collecting device are separately positioned on the predeterminated position of livestock and poultry place environment;
Described 3-axis acceleration sensor is used for gathering the 3-axis acceleration data of N number of livestock and poultry according to presetting sample frequency, wherein N be greater than 0 integer;
Described identity recognizing unit is for identifying the information of electronic tag; Described electronic tag is positioned on the outside surface of each livestock and poultry health;
Described temperature sensor, baroceptor, relative humidity sensor are for gathering the temperature of the surrounding environment at livestock and poultry place, air pressure and relative humidity;
Described infrared video collecting device is for gathering the complete monitoring video of each livestock and poultry behavior;
Described subminiature memory cells is for the data that store described data acquisition unit acquires and arrive and information;
Described wireless transmission unit to be used for the data of described data acquisition unit acquires and information to transfer to described data processing unit through conversion process;
Described data processing unit, carries out cluster analysis by clustering algorithm to described 3-axis acceleration data, obtains the time series data of all kinds of basic act of each livestock and poultry; Described time series data and the threshold parameter preset are compared analysis, draws the health information of each livestock and poultry; The managerial integration to each livestock and poultry is provided according to the health information of described each livestock and poultry; Described managerial integration comprises and hives off, isolates or maintain former stable breeding mode.
The present invention carries out cluster analysis by the behavior acceleration information of clustering algorithm to livestock and poultry, combines, obtain the abnormal information of livestock and poultry behavior and health status with the electronic label identification information identified.Strong adaptability of the present invention, affect little by external environment situation, accuracy rate is high, to cultivate and omnidistance quality monitoring plays favourable effect judging that livestock and poultry behavior and health status, livestock and poultry are classified.
Accompanying drawing explanation
Can understanding the features and advantages of the present invention clearly by reference to accompanying drawing, accompanying drawing is schematic and should not be construed as and carry out any restriction to the present invention, in the accompanying drawings:
Fig. 1 shows the livestock birds health condition monitoring method process flow diagram that the embodiment of the present invention provides;
Fig. 2 shows the structural representation of the livestock birds health condition monitoring system that the embodiment of the present invention provides;
Fig. 3 shows the process flow diagram of step S2 in the livestock birds health condition monitoring method that the embodiment of the present invention provides;
Fig. 4 shows the 3-axis acceleration curve map of livestock and poultry 4 kinds of daily behaviors that the embodiment of the present invention provides.
Embodiment
Below in conjunction with drawings and Examples, the specific embodiment of the present invention is described in further detail.Following examples for illustration of the present invention, but are not used for limiting the scope of the invention.
Fig. 1 shows the livestock birds health condition monitoring method process flow diagram that the embodiment of the present invention provides.As shown in Figure 1, livestock birds health condition monitoring method provided by the present invention, specifically comprises the following steps:
S1: the 3-axis acceleration sensor in data acquisition unit gathers the 3-axis acceleration data of N number of livestock and poultry according to presetting sample frequency, wherein N be greater than 0 integer;
S2: data processing unit carries out cluster analysis by clustering algorithm to described 3-axis acceleration data, obtains the time series data of all kinds of basic act of each livestock and poultry;
S3: described time series data and the threshold parameter preset are compared analysis by data processing unit, draw the health information of each livestock and poultry.
Livestock birds health condition monitoring method provided by the present invention has strong adaptability, affects little by external environment situation, the feature that accuracy rate is high, can to cultivate and omnidistance quality monitoring plays favourable effect judging that livestock and poultry behavior and health status, livestock and poultry are classified, carrying out in the process of long-term Real-Time Monitoring to the behavior of livestock and poultry, do not affect the daily activity in production of livestock and poultry, basic non-stress.
Preferably, while data processing unit draws the health information of each livestock and poultry described in described step S3, indicate the identity information of each livestock and poultry; Wherein, described identity information is the information of the electronic tag that the identity recognizing unit in described data acquisition unit identifies; Described electronic tag is positioned on the outside surface of each livestock and poultry health, as being worn on the ear of livestock and poultry.
Fig. 3 shows the process flow diagram of step S2 in the livestock birds health condition monitoring method that the embodiment of the present invention provides.As shown in Figure 3, in described step S2, described data processing unit carries out cluster analysis by clustering algorithm to described behavior acceleration information, specifically comprises the following steps:
S21: all kinds of basic acts of described N number of livestock and poultry are divided into K classification, presets the cluster centre of a described K classification, wherein K be greater than 0 integer;
S22: calculate the behavior acceleration information of each livestock and poultry in described N number of livestock and poultry and the Euclidean distance of a described K cluster centre respectively, the behavior acceleration information of described each livestock and poultry is assigned in the classification representated by the cluster centre minimum with its Euclidean distance;
S23: respectively all behavior acceleration informations that each classification in a described K classification comprises are averaged, using described average as the new cluster centre of this classification, calculate all behavior acceleration informations in this classification to the square distance of cluster centre new described in such other and;
S24: judge cluster centre and described square distance and value whether change, if do not change, then cluster terminates; If change, then repeat step S22.
Preferably, in described step S21, all kinds of basic acts of described N number of livestock and poultry are divided into K classification to be specially:
All kinds of basic acts of described N number of livestock and poultry are divided into K=4 classification, described 4 classifications comprise lying behaviour, behavior of standing or be careful, foraging behaviour and across slip a line for.
Preferably, the cluster centre presetting a described K classification in described step S21 is specially: the cluster centre presetting a described K classification according to ambient data;
Wherein, described ambient data is the temperature of the surrounding environment at the livestock and poultry place that temperature sensor, baroceptor and relative humidity sensor in described data acquisition unit collect respectively, air pressure and relative humidity.Such as when Various Seasonal, the daily behavior duration of livestock and poultry can present different rules.Therefore, when judging livestock birds health state, the ambient data at livestock and poultry place should be taken into account, according to the difference of ambient data, for each classification presets different cluster centres.
Preferably, described step S1 also comprises subminiature memory cells and stores the data message that described data acquisition unit acquires arrives, data can be obtained to micro-storage unit by PC timed sending instruction like this, also can prevent the event of data loss that the accidents such as power-off cause.
Preferably, described step S1 also comprises and utilizes wireless transmission unit that the data message of described data acquisition unit acquires is transferred to described data processing unit through conversion process.
Preferably, the infrared video collecting device in described data acquisition unit gathers the complete monitoring video of each livestock and poultry behavior; Described monitor video is utilized to examine described health information.Such as, through conversion process by manually checking, the effect examining livestock birds health condition monitoring result further can be played, making the accuracy rate of monitoring higher after transferring to PC at the complete monitoring video of livestock and poultry behavior.
Preferably, data processing unit provides managerial integration to each livestock and poultry according to the health information of described each livestock and poultry; Described managerial integration comprises and hives off, isolates or maintain former stable breeding mode.
Below by citing, the specific works flow process of described livestock birds health condition monitoring method and system is described.
Fig. 2 shows the structural representation of the livestock birds health condition monitoring system that the embodiment of the present invention provides.As shown in Figure 2, described system comprises: data acquisition unit 10, subminiature memory cells 20, identity recognizing unit 30, wireless transmission unit 40, data processing unit 50.
In the present embodiment, data acquisition unit 10 comprises the 3-axis acceleration sensor 111 of the behavior acceleration signature data of collecting livestock and poultry (such as milk cow) and collects the microsensor unit 11 of the microsensor composition that the temperature sensor 112 of ambient data, baroceptor 113 and humidity sensor 114 form, this microsensor unit 11 is fixed on the leg of milk cow by stationary installation 15 (such as bandage), can not damage milk cow health and affect the daily activity in production of milk cow.Infrared video collecting device 12 is placed in the living environment of milk cow with predetermined angle, obtains the monitor video of livestock and poultry behavior.Power module 13 adopts battery to be that data acquisition unit 10 is powered.
Identity recognizing unit 30 is fixed on the predeterminated position in the living environment of milk cow, such as drinking water place, place etc. of milking, to reach the object obtaining milk cow specific behavior state.Identity recognizing unit 30 also comprises milk cow and carries electronic tag 31, the RFID read-write equipment 32 of (being such as worn on the ear of milk cow) and identify control module 33.The effect of electronic tag 31 is the identity informations identifying milk cow, identifies that control module 33 controls the electronic label identification information of RFID read-write equipment 32 reading electronic labels 31.Preferred as the present embodiment, the model of RFID read-write equipment 32 is that the EPC electronic tag of double antenna fixes read write line.
Data processing unit 50 can elect PC as, and itself and RFID read-write equipment 32 carry out data interaction by wireless transmission communication modes, realize the identification of the individual identity to milk cow.Clustering algorithm software is installed in data processing unit 50, described clustering algorithm software is utilized to carry out analyzing and processing to described second data set received, clustering algorithm by data mining repeatedly superposes training to described data set and obtains comparatively stable cluster centre, set up basic act pattern architecture, ultimate principle is as follows:
Given one is comprised to the data set X={x at n d dimension strong point
1, x
2..., x
i..., x
n, wherein x
i∈ R
d, and the number K of the data subset that will generate, by organize data objects be K and divide C={c
k, i=1,2 ... K}.Each division represents a class c
k, each class c
kthere is a class center μ
i.Choose Euclidean distance as similarity and Distance Judgment criterion, to calculate in such each point to cluster centre μ
isquare distance and
Cluster target be make all kinds of total square distance and
minimum.
Each data point, from an initial K category division, is then assigned in each classification by this algorithm, with reduce total square distance and.Total square distance and trend towards along with the increase of classification number K reduce (as K=n, J (c)=0).Be the process that iterates, object makes samples all in Clustering Domain minimum to the quadratic sum J (c) of cluster centre distance.
According to this clustering algorithm, the 3-axis acceleration data ACC=(ACC of livestock and poultry individuality
x, ACC
y, ACC
z) represent.
The concrete computation process being applied to the modeling of milk cow daily behavior is as follows:
First, assuming that need the object of cluster to have n, sample set is X={x
1, x
2..., x
n, the object of this algorithm is that n sample object is divided into K=4 bunch, and K here refers to four of milk cow main daily behavior classification, and the sample object in making bunch has higher similarity, and bunch between sample object similarity very low.
Such as, the daily behavior of milk cow is divided into K=4 class, namely lying behaviour, behavior, the foraging behaviour and overstating of standing or be careful slip a line into, divide describe as shown in table 1.
The daily behavior classification of table 1. milk cow
Generally, the milk cow time about 13.5 hour of every day for searching for food and ruminate; Couch about 7 hours time of having a rest; Standing, across jumping equal time about 3.5 hours of other.
Fig. 4 shows the 3-axis acceleration curve map of milk cow 4 kinds of daily behaviors that the embodiment of the present invention provides, wherein, scheme (a) ~ (d) and respectively illustrate the upper and lower across 3-axis acceleration curve when jumping, couch, search for food and stand or be careful of milk cow.From figure (a), when milk cow be in up and down across slip a line for time, the data and curves of 3-axis acceleration sensor record there will be to rise suddenly significantly and plunges, and irregular fluctuation; In figure (b), when milk cow couches, the acceleration information curve kept stable of 3-axis acceleration sensor record, and after mainly concentrating on foraging behaviour; In figure (c), when milk cow be in search for food the stage time, 3-axis acceleration data and curves fluctuation ratio is comparatively violent and acceleration information is significantly not regular; In figure (d), when milk cow is stood or be careful, acceleration information curve presents and fluctuates more regularly.Therefore utilize the response difference of 3-axis acceleration sensor axis of orientation, and in conjunction with cluster algorithm, cluster is carried out to the set of data samples gathered, can realize other classification of 4 kinds of main daily behavior feature classes.
Then, the clustering algorithm by data mining repeatedly superposes training to described data set and obtains comparatively stable cluster centre, and concrete operation flow process is as follows:
(1) the individual initial cluster centre of random selecting K=4: C
1, C
2..., C
k.
(2) during by the object in sample set X, according to minimal distance principle, to be assigned in K cluster some; Minimal distance principle: D
j=min ‖ X-C
j‖, X={x
1, x
2..., x
n, j=1,2 ..., k.
(3) new cluster centre position is recalculated, so that the average of each sample object in cluster is minimum to the distance sum of new cluster centre;
X＝{x
1，x
2，…，x
n}，j＝1,2，…，K。In formula: n
jit is the sample number comprised in this cluster.
(4) if cluster centre changes, then 2 are repeated), 3) step, until cluster centre no longer change location, namely make clustering criteria function convergence.
After completing the modeling of milk cow daily behavior, data processing unit generates the form milk cow individuality of exception being carried out to classification stable breeding according to the abnormal information generated, can promote management level accordingly, greatly improve the good and bad difference of milk cow individuality, detailed process is as follows:
PC is according to the milk cow behaviour classification analyzed and duration; in conjunction with data such as temperature, humidity, air pressure; the behavior obtaining current milk cow differentiates result; normal or abnormal; and automatically indicate the numbering of abnormal individuals, such as, under current certain environment temperature, humidity, air pressure conditions; behavior is for standing, and this discriminating data is normal information by PC.
Then differentiation result is exported with report form, then by category filter, generate abnormal information form, as shown in table 2, the sample ie breakdown IE wherein in remarks column is as shown in table 3, and the behavioral statistics example of milk cow is as shown in table 4.PC, according to the abnormal information form exported, provides milk cow Managed Solution targetedly, as hived off, divides circle or isolated rearing etc., output category stable breeding form in a tabular form, as shown in table 5; If differentiation milk cow health, then system does not provide anomaly management scheme, maintains former stable breeding mode.
Table 2.2015 year 06 month 01 day abnormal information form
Table 3.1434 sample ie breakdown IE
Table No. 4.1434 20150601 behavioral statistics examples
Normally in situation, the milk cow time about 13.5 hour of every day for searching for food and ruminate; Couch about 7 hours time of having a rest; Other stand, across jumping equal time about 3.5 hours, can judge that whether place's milk cow behavior is abnormal accordingly, if the time of often kind of behavior of milk cow, not in normal range, is judged as exception by its behavior.
Table 5. is classified stable breeding form
| Ear tag number | Temperature | Humidity | Air pressure | Behavior | Result | Scheme |
| 1434 | 30.7 | 40％ | 1004hPa | Stand | Healthy | Nothing |
| 1435 | 30.6 | 42％ | 1006hPa | Abnormal | Abnormal | Isolation |
| 1334 | 30.5 | 44％ | 1005hPa | Abnormal | Abnormal | Isolation |
| 1335 | 30.6 | 42％ | 1006hPa | Couch | Healthy | Nothing |
The livestock birds health condition monitoring method that the present embodiment provides does not affect the daily activity in production of livestock and poultry; long-term Real-Time Monitoring is carried out to livestock and poultry behavior; basic act pattern architecture is formed at data processing unit; itself and the threshold parameter preset are compared analysis; automatically indicate the identity information of the livestock and poultry of abnormal behavior or health status exception, reach the object of the livestock and poultry of exception being carried out to classification stable breeding.Livestock birds health condition monitoring method of the present invention is low to monitoring conditional request, and affect little by external environment situation, the basic non-stress of livestock and poultry body, for judging the individual daily behavior of livestock and poultry and disease relationship, animal welfare cultivate and the foundation of disease forecasting model provides the foundation.
Although describe embodiments of the present invention by reference to the accompanying drawings, but those skilled in the art can make various modifications and variations without departing from the spirit and scope of the present invention, such amendment and modification all fall into by within claims limited range.
Claims (10)
1. a livestock birds health condition monitoring method, is characterized in that, comprises the following steps:
S1: the 3-axis acceleration sensor in data acquisition unit gathers the 3-axis acceleration data of N number of livestock and poultry according to presetting sample frequency, wherein N be greater than 0 integer;
S2: data processing unit carries out cluster analysis by clustering algorithm to described 3-axis acceleration data, obtains the time series data of all kinds of basic act of each livestock and poultry;
S3: described time series data and the threshold parameter preset are compared analysis by data processing unit, draw the health information of each livestock and poultry.
2. livestock birds health condition monitoring method according to claim 1, is characterized in that, while data processing unit draws the health information of each livestock and poultry described in described step S3, indicates the identity information of each livestock and poultry;
Wherein, described identity information is the information of the electronic tag that the identity recognizing unit in described data acquisition unit identifies; Described electronic tag is positioned on the outside surface of each livestock and poultry health.
3. livestock birds health condition monitoring method according to claim 1, is characterized in that, in described step S2, described data processing unit carries out cluster analysis by clustering algorithm to described behavior acceleration information, specifically comprises the following steps:
S21: all kinds of basic acts of described N number of livestock and poultry are divided into K classification, presets the cluster centre of a described K classification, wherein K be greater than 0 integer;
S22: calculate the behavior acceleration information of each livestock and poultry in described N number of livestock and poultry and the Euclidean distance of a described K cluster centre respectively, the behavior acceleration information of described each livestock and poultry is assigned in the classification representated by the cluster centre minimum with its Euclidean distance;
S23: respectively all behavior acceleration informations that each classification in a described K classification comprises are averaged, using described average as the new cluster centre of this classification, calculate all behavior acceleration informations in this classification to the square distance of cluster centre new described in such other and;
S24: judge cluster centre and described square distance and value whether change, if do not change, then cluster terminates; If change, then repeat step S22.
4. livestock birds health condition monitoring method according to claim 3, is characterized in that, in described step S21, all kinds of basic acts of described N number of livestock and poultry is divided into K classification and is specially:
All kinds of basic acts of described N number of livestock and poultry are divided into K=4 classification, described 4 classifications comprise lying behaviour, behavior of standing or be careful, foraging behaviour and across slip a line for.
5. livestock birds health condition monitoring method according to claim 3, is characterized in that,
The cluster centre presetting a described K classification in described step S21 is specially: the cluster centre presetting a described K classification according to ambient data;
Wherein, described ambient data is the temperature of the surrounding environment at the livestock and poultry place that temperature sensor, baroceptor and relative humidity sensor in described data acquisition unit collect respectively, air pressure and relative humidity.
6. the livestock birds health condition monitoring method according to any one of claim 1,2,5, is characterized in that, described step S1 also comprises subminiature memory cells and stores the data message that described data acquisition unit acquires arrives.
7. livestock birds health condition monitoring method according to claim 1, is characterized in that, described step S1 also comprises and utilizes wireless transmission unit that the data message of described data acquisition unit acquires is transferred to described data processing unit through conversion process.
8. according to the livestock birds health condition monitoring method in claim 1-5 or 7 described in any one, it is characterized in that, the infrared video collecting device in described data acquisition unit gathers the complete monitoring video of each livestock and poultry behavior; Described monitor video is utilized to examine described health information.
9. livestock birds health condition monitoring method according to claim 1, is characterized in that, data processing unit provides the managerial integration to each livestock and poultry according to the health information of described each livestock and poultry; Described managerial integration comprises and hives off, isolates or maintain former stable breeding mode.
10. implement the claims a system for livestock birds health condition monitoring method any one of 1-9, it is characterized in that, comprise data acquisition unit, subminiature memory cells, wireless transmission unit and data processing unit;
Described data acquisition unit comprises: 3-axis acceleration sensor, identity recognizing unit, temperature sensor, baroceptor, relative humidity sensor and infrared video collecting device;
Described 3-axis acceleration sensor, temperature sensor, baroceptor and relative humidity sensor are integrated into microsensor unit, are arranged on the outside surface of each livestock and poultry health;
Described identity recognizing unit and described infrared video collecting device are separately positioned on the predeterminated position of livestock and poultry place environment;
Described 3-axis acceleration sensor is used for gathering the 3-axis acceleration data of N number of livestock and poultry according to presetting sample frequency, wherein N be greater than 0 integer;
Described identity recognizing unit is for identifying the information of electronic tag; Described electronic tag is positioned on the outside surface of each livestock and poultry health;
Described temperature sensor, baroceptor, relative humidity sensor are for gathering the temperature of the surrounding environment at livestock and poultry place, air pressure and relative humidity;
Described infrared video collecting device is for gathering the complete monitoring video of each livestock and poultry behavior;
Described subminiature memory cells is for the data that store described data acquisition unit acquires and arrive and information;
Described wireless transmission unit to be used for the data of described data acquisition unit acquires and information to transfer to described data processing unit through conversion process;
Described data processing unit, carries out cluster analysis by clustering algorithm to described 3-axis acceleration data, obtains the time series data of all kinds of basic act of each livestock and poultry; Described time series data and the threshold parameter preset are compared analysis, draws the health information of each livestock and poultry; The managerial integration to each livestock and poultry is provided according to the health information of described each livestock and poultry; Described managerial integration comprises and hives off, isolates or maintain former stable breeding mode.
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