CN105091938B - Livestock birds health condition monitoring method and system - Google Patents
Livestock birds health condition monitoring method and system Download PDFInfo
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Abstract
The invention discloses a kind of livestock birds health condition monitoring method and system, the described method includes：S1：3-axis acceleration sensor in data acquisition unit gathers the 3-axis acceleration data of N number of livestock and poultry according to preset sample frequency, and wherein N is the integer more than 0；S2：Data processing unit carries out cluster analysis by clustering algorithm to the 3-axis acceleration data, obtains the time series data of all kinds of basic acts of each livestock and poultry；S3：Data processing unit analyzes the time series data compared with default threshold parameter, draws the health information of each livestock and poultry.The system comprises：Data acquisition unit, subminiature memory cells, wireless transmission unit and data processing unit.The present invention it is adaptable it is strong, small, the characteristics of accuracy rate is high, the effect favourable with health status, livestock and poultry classification cultivation and whole quality monitoring performance to judging livestock and poultry behavior are influenced by external environment situation.
Description
Technical field
The present invention relates to information network technique livestock and poultry cultivation management domain application, more particularly to livestock birds health situation supervise
Survey method and system.
Background technology
With the continuous development of information network technique, by information network technique for traditional livestock and poultry cultivation management increasingly by
The attention of people is arrived.Livestock and poultry cultivation management is advanced towards automation, information-based and intelligentized direction.In recent years, China pair
The requirement of livestock birds health cultivation and whole quality monitoring is very strict, so requiring to utilize advanced sensor technology and information
Network technology is digitized livestock and poultry cultivation whole process security monitoring, and carries out Classified optimization cultivation to it.
A kind of presently disclosed scheme for realizing livestock birds health condition monitoring relies primarily on electrocardio, the brain of monitoring livestock and poultry in real time
The behavioral parameters such as the physiological parameters such as electricity, body temperature and blood pressure and measurement livestock and poultry travel distance, the motion frequency and speed of travel, then
The behavior of livestock and poultry and health status according to measured by determining the comparative result of parameters obtained and parameter preset, carry out classification cultivation.
Since the motion state similitude in the daily production activity of livestock and poultry is larger, livestock and poultry behavior is only made by the above method
And health status judges can there is very big error, the accuracy rate for cultivation of classifying is unsatisfactory, and judging result is by external environment
The factors such as situation and livestock and poultry individual difference influence.Therefore, the technical issues of existing is how to provide a kind of strong applicability, by environment
Situation influences small and high accuracy rate livestock birds health condition monitoring method.
The content of the invention
In order to solve the above-mentioned technical problem, one aspect of the present invention proposes a kind of livestock birds health condition monitoring method, including
Following steps：
S1：3-axis acceleration sensor in data acquisition unit gathers three axis of N number of livestock and poultry according to preset sample frequency
Acceleration information, wherein N are the integer more than 0；
S2：Data processing unit carries out cluster analysis by clustering algorithm to the 3-axis acceleration data, obtains each
The time series data of all kinds of basic acts of livestock and poultry；
S3：Data processing unit analyzes the time series data compared with default threshold parameter, draws each poultry
The health information of fowl.
Preferably, while data processing unit draws the health information of each livestock and poultry described in the step S3,
Indicate the identity information of each livestock and poultry；
Wherein, the electronic tag that the identity information identifies for the identity recognizing unit in the data acquisition unit
Information；The electronic tag is located on the outer surface of each livestock and poultry body.
Preferably, in the step S2, the data processing unit is by clustering algorithm to the behavior acceleration information
Cluster analysis is carried out, specifically includes following steps：
S21：All kinds of basic acts of N number of livestock and poultry are divided into K classification, in the cluster for presetting the K classification
The heart, wherein K are the integer more than 0；
S22：The behavior acceleration information of each livestock and poultry and the K cluster centre in N number of livestock and poultry are calculated respectively
Euclidean distance, by the behavior acceleration information of each livestock and poultry be assigned to representated by the cluster centre of its Euclidean distance minimum
Classification in；
S23：It averages respectively to all behavior acceleration informations that each classification includes in the K classification, by described in
The average cluster centre new as the category calculates all behavior acceleration informations in the category and gathers to the described new of the category
The square distance at class center and；
S24：Judge whether cluster centre and the value of the square distance sum change, if not changing, cluster
Terminate；If changing, repeatedly step S22.
Preferably, all kinds of basic acts of N number of livestock and poultry are divided into K classification in the step S21 is specially：
All kinds of basic acts of N number of livestock and poultry are divided into K=4 classification, 4 classifications include lying behaviour,
Stand or be careful behavior, foraging behaviour and across slip a line for.
Preferably, the cluster centre of the default K classification is specially in the step S21：According to ambient data
Preset the cluster centre of the K classification；
Wherein, the ambient data is temperature sensor, baroceptor and the phase in the data acquisition unit
Temperature, air pressure and the relative humidity of ambient enviroment where the livestock and poultry collected respectively to humidity sensor.
Preferably, the step S1 further includes subminiature memory cells and stores the data letter that the data acquisition unit collects
Breath.
Preferably, the step S1 is further included the data for being gathered the data acquisition unit using wireless transmission unit and believed
Breath is by conversion process and is transmitted to the data processing unit.
Preferably, the infrared video collecting device in the data acquisition unit gathers the complete monitoring of each livestock and poultry behavior
Video；The health information is verified using the monitor video.
Preferably, data processing unit provides the management to each livestock and poultry according to the health information of each livestock and poultry
It is recommended that；The managerial integration includes dividing group, isolation or maintains former stable breeding mode.
Another aspect of the present invention proposes a kind of livestock birds health condition monitoring system, including data acquisition unit, miniature deposits
Storage unit, wireless transmission unit and data processing unit；
The data acquisition unit includes：3-axis acceleration sensor, identity recognizing unit, temperature sensor, air pressure transmission
Sensor, relative humidity sensor and infrared video collecting device；
The 3-axis acceleration sensor, temperature sensor, baroceptor and relative humidity sensor are integrated into miniature
Sensor unit is arranged on the outer surface of each livestock and poultry body；
The default position of environment where the identity recognizing unit is separately positioned on livestock and poultry with the infrared video collecting device
It puts；
The 3-axis acceleration sensor is used to gather the 3-axis acceleration data of N number of livestock and poultry according to preset sample frequency,
Wherein N is the integer more than 0；
The identity recognizing unit is used to identify the information of electronic tag；The electronic tag is located at each livestock and poultry body
On outer surface；
The temperature sensor, baroceptor, relative humidity sensor are used to gather the ambient enviroment where livestock and poultry
Temperature, air pressure and relative humidity；
The infrared video collecting device is used to gather the complete monitoring video of each livestock and poultry behavior；
The subminiature memory cells are used to store data and information that the data acquisition unit collects；
The wireless transmission unit is used for the data for gathering the data acquisition unit and information passes through conversion process simultaneously
It is transmitted to the data processing unit；
The data processing unit carries out cluster analysis to the 3-axis acceleration data by clustering algorithm, obtains every
The time series data of a all kinds of basic acts of livestock and poultry；The time series data compared with default threshold parameter is analyzed, is drawn
The health information of each livestock and poultry；It is provided according to the health information of each livestock and poultry and the management of each livestock and poultry is built
View；The managerial integration includes dividing group, isolation or maintains former stable breeding mode.
The present invention carries out cluster analysis, the electronic tag with identification by clustering algorithm to the behavior acceleration information of livestock and poultry
Identification information is combined, and obtains the exception information of livestock and poultry behavior and health status.The present invention it is adaptable, by external environment situation
Influence small, accuracy rate is high, to judging that livestock and poultry behavior plays favorably with health status, livestock and poultry classification cultivation and whole quality monitoring
Effect.
Description of the drawings
The features and advantages of the present invention can be more clearly understood by reference to attached drawing, attached drawing is schematically without that should manage
It solves to carry out any restrictions to the present invention, in the accompanying drawings：
Fig. 1 shows livestock birds health condition monitoring method flow chart provided in an embodiment of the present invention；
Fig. 2 shows the structure diagram of livestock birds health condition monitoring system provided in an embodiment of the present invention；
Fig. 3 shows the flow chart of step S2 in livestock birds health condition monitoring method provided in an embodiment of the present invention；
Fig. 4 shows the 3-axis acceleration graph of 4 kinds of daily behaviors of livestock and poultry provided in an embodiment of the present invention.
Specific embodiment
With reference to the accompanying drawings and examples, the specific embodiment of the present invention is described in further detail.Implement below
Example is not limited to the scope of the present invention for illustrating the present invention.
Fig. 1 shows livestock birds health condition monitoring method flow chart provided in an embodiment of the present invention.As shown in Figure 1, this hair
Bright provided livestock birds health condition monitoring method, specifically includes following steps：
S1：3-axis acceleration sensor in data acquisition unit gathers three axis of N number of livestock and poultry according to preset sample frequency
Acceleration information, wherein N are the integer more than 0；
S2：Data processing unit carries out cluster analysis by clustering algorithm to the 3-axis acceleration data, obtains each
The time series data of all kinds of basic acts of livestock and poultry；
S3：Data processing unit analyzes the time series data compared with default threshold parameter, draws each poultry
The health information of fowl.
Livestock birds health condition monitoring method provided by the present invention it is adaptable it is strong, influenced by external environment situation it is small,
The characteristics of accuracy rate is high, can be to judging that it is favourable that livestock and poultry behavior and health status, livestock and poultry classification cultivation and whole quality monitoring play
Effect, during long-term monitoring in real time is carried out to the behavior of livestock and poultry, do not influence the daily production activity of livestock and poultry, substantially without
Stress reaction.
Preferably, while data processing unit draws the health information of each livestock and poultry described in the step S3,
Indicate the identity information of each livestock and poultry；Wherein, the identity information is the identity recognizing unit in the data acquisition unit
The information of the electronic tag identified；The electronic tag is located on the outer surface of each livestock and poultry body, as being worn on livestock and poultry
On ear.
Fig. 3 shows the flow chart of step S2 in livestock birds health condition monitoring method provided in an embodiment of the present invention.Such as Fig. 3
Shown, in the step S2, the data processing unit carries out the behavior acceleration information cluster point by clustering algorithm
Analysis, specifically includes following steps：
S21：All kinds of basic acts of N number of livestock and poultry are divided into K classification, in the cluster for presetting the K classification
The heart, wherein K are the integer more than 0；
S22：The behavior acceleration information of each livestock and poultry and the K cluster centre in N number of livestock and poultry are calculated respectively
Euclidean distance, by the behavior acceleration information of each livestock and poultry be assigned to representated by the cluster centre of its Euclidean distance minimum
Classification in；
S23：It averages respectively to all behavior acceleration informations that each classification includes in the K classification, by described in
The average cluster centre new as the category calculates all behavior acceleration informations in the category and gathers to the described new of the category
The square distance at class center and；
S24：Judge whether cluster centre and the value of the square distance sum change, if not changing, cluster
Terminate；If changing, repeatedly step S22.
Preferably, all kinds of basic acts of N number of livestock and poultry are divided into K classification in the step S21 is specially：
All kinds of basic acts of N number of livestock and poultry are divided into K=4 classification, 4 classifications include lying behaviour,
Stand or be careful behavior, foraging behaviour and across slip a line for.
Preferably, the cluster centre of the default K classification is specially in the step S21：According to ambient data
Preset the cluster centre of the K classification；
Wherein, the ambient data is temperature sensor, baroceptor and the phase in the data acquisition unit
Temperature, air pressure and the relative humidity of ambient enviroment where the livestock and poultry collected respectively to humidity sensor.Such as in different seasons
In the case of section, different rules can be presented in the daily behavior duration of livestock and poultry.Therefore, livestock birds health state is being judged
When, the ambient data where livestock and poultry should be taken into account, according to the difference of ambient data, be preset not for each classification
Same cluster centre.
Preferably, the step S1 further includes subminiature memory cells and stores the data letter that the data acquisition unit collects
Breath so can send instructions to micro- storage unit by PC machine timing and obtain data, cause prevented also from accidents such as power-off
Event of data loss.
Preferably, the step S1 is further included the data for being gathered the data acquisition unit using wireless transmission unit and believed
Breath is by conversion process and is transmitted to the data processing unit.
Preferably, the infrared video collecting device in the data acquisition unit gathers the complete monitoring of each livestock and poultry behavior
Video；The health information is verified using the monitor video.Such as turn in the complete monitoring video process of livestock and poultry behavior
It changes after being processed and transmitted to PC machine, the work for further verifying livestock birds health condition monitoring result can be played by manually being checked
With making the accuracy rate higher of monitoring.
Preferably, data processing unit provides the management to each livestock and poultry according to the health information of each livestock and poultry
It is recommended that；The managerial integration includes dividing group, isolation or maintains former stable breeding mode.
The specific workflow of the livestock birds health condition monitoring method and system is described below by citing.
Fig. 2 shows the structure diagram of livestock birds health condition monitoring system provided in an embodiment of the present invention.Such as Fig. 2 institutes
Show, the 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 includes collecting the behavior acceleration signature data of livestock and poultry (such as milk cow)
3-axis acceleration sensor 111 and temperature sensor 112, baroceptor 113 and the humidity sensor for collecting ambient data
The microsensor unit 11 for the microsensor composition that device 114 forms, this microsensor unit 11 can pass through fixing device
15 (such as bandages) are fixed on the leg of milk cow, will not damage milk cow health and influence the daily production activity of milk cow.It will be infrared
Video capture device 12 is placed in predetermined angle in the living environment of milk cow, obtains the monitor video of livestock and poultry behavior.Power supply mould
Block 13 uses battery to be powered for data acquisition unit 10.
Identity recognizing unit 30 is fixed at the predeterminated position in the living environment of milk cow, such as drinking water place, milking etc., with
Achieve the purpose that obtain milk cow specific behavior state.Identity recognizing unit 30, which further includes milk cow and carries, (such as is worn on milk cow
On ear) electronic tag 31, RFID read-write equipment 32 and identification control module 33.The effect of electronic tag 31 is identification milk cow
Identity information, identification control module 33 control 32 reading electronic labels 31 of RFID read-write equipment electronic label identification information.
As the preferred of the present embodiment, the EPC electronic tags of the model double antenna of RFID read-write equipment 32 fix reader.
Data processing unit 50 can elect PC machine as, be carried out with RFID read-write equipment 32 by being wirelessly transferred communication modes
The identification to the individual identity of milk cow is realized in data interaction.Clustering algorithm software in data processing unit 50 is installed, utilizes institute
It states clustering algorithm software to analyze and process second data set received, by the clustering algorithm of data mining to institute
Stating data set progress, superposition training obtains relatively stable cluster centre repeatedly, establishes basic act pattern architecture, basic principle
It is as follows：
Data set X={ the x for including n d dimensions strong point for given one1, x2..., xi..., xn, wherein xi∈
RdAnd the number K for the data subset to be generated, data object is organized as K division C={ ck, i=1,2 ... K }.Each
Division represents a class ck, each class ckThere are one class center μi.It is accurate as similitude and Distance Judgment to choose Euclidean distance
Then, such interior each point is calculated to cluster centre μiSquare distance and
Cluster target be make all kinds of total square distances andIt is minimum.
Then each data point is assigned in each classification by this algorithm since an initial K category division, to reduce
Total square distance and.Total square distance and being intended to the increase of classification number K reduce (as K=n, J (c)=
0).The process that iterates, it is therefore an objective to make sample all in Clustering Domain to cluster centre distance quadratic sum J (c) most
It is small.
According to this clustering algorithm, the 3-axis acceleration data ACC=(ACC of livestock and poultry individualx,ACCy,ACCz) represent.
Specific calculating process applied to the modeling of milk cow daily behavior is as follows：
First, it is assumed that the object clustered is needed to share n, sample set is X={ x1, x2..., xn, the purpose of the algorithm is
N sample object is divided into K=4 cluster, K here refers to that four main daily behaviors of milk cow are classified so that in cluster
Sample object has higher similitude, and the sample object similitude between cluster is very low.
For example, the daily behavior of milk cow is divided into K=4 classes, i.e., lying behaviour, stand or behavior of being careful, foraging behaviour
And it overstates and slips a line as division description is as shown in table 1.
The daily behavior classification of 1. milk cow of table
Under normal circumstances, milk cow is used for about 13.5 hours of time searched for food and ruminated daily；Lie down time about 7 of rest
A hour；Others were stood, across about 3.5 hours of times such as jumps.
Fig. 4 shows the 3-axis acceleration graph of 4 kinds of daily behaviors of milk cow provided in an embodiment of the present invention, wherein, figure
(a)~(d) respectively illustrates upper and lower 3-axis acceleration curve when jumping, lie down, searching for food and standing or be careful of milk cow.By
Scheme (a) understand, when milk cow be in up and down across slip a line for when, 3-axis acceleration sensor record data and curves be present with significantly
It rises suddenly and plunges and irregular fluctuation；Scheme in (b), when milk cow lies down, the acceleration information of 3-axis acceleration sensor record
Curve kept stable, and be concentrated mainly on after foraging behaviour；Scheme in (c), when milk cow is in the feeding stage, three axis add
The fluctuation of speed data curve is relatively more violent and acceleration information is without apparent regularity；Scheme in (d), when milk cow standing or slow
When walking, the presentation of acceleration information curve is more regularly fluctuated.Therefore the difference in response of 3-axis acceleration sensor axis of orientation is utilized
Different and combination cluster algorithm clusters the set of data samples of acquisition, can realize special to 4 kinds of main daily behaviors
Levy the classification of classification.
Then, by data mining clustering algorithm to the data set carry out repeatedly superposition training obtain it is relatively stable
Cluster centre, concrete operation flow are as follows：
(1) K=4 initial cluster centres are randomly selected：C1, C2..., CK。
(2) object in sample set X is assigned to according to minimal distance principle in some in K cluster；Most narrow spacing
From principle：Dj=min ‖ X-Cj‖, X={ x1, x2..., xn, j=1,2 ..., k.
(3) recalculate new cluster centre position, so as to each sample object in clustering average to new cluster
The sum of the distance at center minimum；
X={ x1, x2..., xn, j=1,2 ..., K.In formula：njIt is sample included in the cluster
Number.
(4) if cluster centre changes, repeatedly 2), 3) step, it is until cluster centre no longer change location, i.e., so that poly-
Class criterion function is restrained.
In formula：CjIt is cluster SjCluster centre.
After the modeling of milk cow daily behavior is completed, data processing unit is generated according to the exception information of generation to exception
Milk cow individual carries out the report of classification stable breeding, can promote management level accordingly, significantly improve the good and bad difference of milk cow individual, has
Body process is as follows：
PC machine is obtained according to the milk cow behavior classification analyzed and duration, the data such as combination temperature, humidity, air pressure
The behavior of current milk cow is differentiated as a result, normal or abnormal, and indicates the number of abnormal individuals automatically, for example, current certain
Under environment temperature, humidity, air pressure conditions, to stand, this discriminating data is normal information by PC machine for behavior.
Then it will differentiate that result is exported with report form, then by category filter, exception information report generated, such as 2 institute of table
Show, wherein the sample ie breakdown IE in remarks column is as shown in table 3, and the behavioral statistics example of milk cow is as shown in table 4.PC machine is according to defeated
The exception information report gone out, provides targetedly milk cow Managed Solution, such as divides group, point circle or isolated rearing, in a tabular form
Output category stable breeding report, as shown in table 5；If differentiating milk cow health, system does not provide anomaly management scheme, maintains former stable breeding
Mode.
01 day 06 month 2. 2015 years exception information report of table
3. No. 1434 sample ie breakdown IEs of table
4. No. 1,434 20150601 behavioral statistics examples of table
In the case of normally, milk cow is used for about 13.5 hours of time searched for food and ruminated daily；Lie down rest when
Between about 7 hours；Others stand, across about 3.5 hours of times such as jumping, and may determine that whether place's milk cow behavior is abnormal accordingly,
If its behavior not in normal range (NR), i.e., is judged as exception by the time of each behavior of milk cow.
The classification stable breeding report of table 5.
| Ear tag number | Temperature | Humidity | Air pressure | Behavior | As a result | Scheme |
| 1434 | 30.7 | 40% | 1004hPa | It stands | Health | Nothing |
| 1435 | 30.6 | 42% | 1006hPa | It is abnormal | It is abnormal | Isolation |
| 1334 | 30.5 | 44% | 1005hPa | It is abnormal | It is abnormal | Isolation |
| 1335 | 30.6 | 42% | 1006hPa | It lies down | Health | Nothing |
The livestock birds health condition monitoring method that the present embodiment is provided does not influence the daily production activity of livestock and poultry, to livestock and poultry row
To carry out long-term monitoring in real time, basic act pattern architecture is formed in data processing unit, by its with default threshold parameter into
Row comparative analysis indicates the identity information of the livestock and poultry of abnormal behavior or health status exception automatically, reaches to abnormal livestock and poultry
Carry out the purpose of classification stable breeding.The livestock birds health condition monitoring method of the present invention is low to monitoring condition requirement, and by extraneous ring
Border situation influences small, the basic non-stress of livestock and poultry body, to judge livestock and poultry individual daily behavior and disease relationship, animal welfare
Cultivation and the foundation of disease forecasting model provide the foundation.
Although being described in conjunction with the accompanying embodiments of the present invention, those skilled in the art can not depart from this hair
Various modifications and variations are made in the case of bright spirit and scope, such modifications and variations are each fallen within by appended claims
Within limited range.
Claims (8)
- A kind of 1. livestock and poultry behavior monitoring method, which is characterized in that comprise the following steps：S1：Three axis that 3-axis acceleration sensor in data acquisition unit gathers N number of livestock and poultry according to preset sample frequency accelerate Degrees of data, wherein N are the integer more than 0；S2：Data processing unit carries out cluster analysis by clustering algorithm to the 3-axis acceleration data, obtains each livestock and poultry The time series data of all kinds of basic acts；S3：Data processing unit analyzes the time series data compared with default threshold parameter, draws each livestock and poultry Abnormal behavior condition information indicates the identity information of each livestock and poultry；Wherein, the letter for the electronic tag that the identity information identifies for the identity recognizing unit in the data acquisition unit Breath；The electronic tag is located on the outer surface of each livestock and poultry body；S4：Data processing unit provides according to the abnormal behavior condition information of each livestock and poultry and the management of each livestock and poultry is built View, the managerial integration include dividing group, isolation or maintain former stable breeding mode.
- 2. livestock and poultry behavior monitoring method according to claim 1, which is characterized in that in the step S2, at the data It manages unit and cluster analysis is carried out to the behavior acceleration information by clustering algorithm, specifically include following steps：S21：All kinds of basic acts of N number of livestock and poultry are divided into K classification, preset the cluster centre of the K classification, Middle K is the integer more than 0；S22：The Euclidean of the behavior acceleration information of each livestock and poultry and the K cluster centre in N number of livestock and poultry is calculated respectively Distance, the behavior acceleration information of each livestock and poultry is assigned to the cluster centre of its Euclidean distance minimum representated by class Not in；S23：It averages respectively to all behavior acceleration informations that each classification includes in the K classification, by the average The cluster centre new as the category, calculate the category in all behavior acceleration informations into the new cluster of the category The square distance of the heart and；S24：Judge whether cluster centre and the value of the square distance sum change, if not changing, cluster terminates； If changing, repeatedly step S22.
- 3. livestock and poultry behavior monitoring method according to claim 2, which is characterized in that by N number of poultry in the step S21 All kinds of basic acts of fowl are divided into K classification：All kinds of basic acts of N number of livestock and poultry are divided into K=4 classification, 4 classifications include lying behaviour, stand Or behavior of being careful, foraging behaviour and across slip a line for.
- 4. livestock and poultry behavior monitoring method according to claim 2, which is characterized in thatThe cluster centre of the default K classification is specially in the step S21：The K are preset according to ambient data The cluster centre of classification；Wherein, the ambient data is temperature sensor, the baroceptor and relatively wet in the data acquisition unit Temperature, air pressure and the relative humidity of ambient enviroment where the livestock and poultry that degree sensor collects respectively.
- 5. the livestock and poultry behavior monitoring method according to any one of claim 1,4, which is characterized in that the step S1 is also wrapped It includes subminiature memory cells and stores the data message that the data acquisition unit collects.
- 6. livestock and poultry behavior monitoring method according to claim 1, which is characterized in that the step S1 is further included using wireless The data message that transmission unit gathers the data acquisition unit is by conversion process and is transmitted to the data processing unit.
- 7. the livestock and poultry behavior monitoring method according to any one in claim 1-4 or 6, which is characterized in that the data Infrared video collecting device in collecting unit gathers the complete monitoring video of each livestock and poultry behavior；Utilize the monitor video core Real health information.
- 8. a kind of system for implementing claim 1 livestock and poultry behavior monitoring method, which is characterized in that including data acquisition unit, micro- Type storage unit, wireless transmission unit and data processing unit；The data acquisition unit includes：3-axis acceleration sensor, identity recognizing unit, temperature sensor, baroceptor, Relative humidity sensor and infrared video collecting device；The 3-axis acceleration sensor, temperature sensor, baroceptor and relative humidity sensor are integrated into micro sensing Device unit is arranged on the outer surface of each livestock and poultry body；The predeterminated position of environment where the identity recognizing unit is separately positioned on livestock and poultry with the infrared video collecting device；The 3-axis acceleration sensor is used to gather the 3-axis acceleration data of N number of livestock and poultry, wherein N according to preset sample frequency To be more than 0 integer；The identity recognizing unit is used to identify the information of electronic tag；The electronic tag is located at the appearance of each livestock and poultry body On face；The temperature sensor, baroceptor, relative humidity sensor be used to gathering the temperature of the ambient enviroment where livestock and poultry, Air pressure and relative humidity；The infrared video collecting device is used to gather the complete monitoring video of each livestock and poultry behavior；The subminiature memory cells are used to store data and information that the data acquisition unit collects；The wireless transmission unit is used for the data for gathering the data acquisition unit and information by conversion process and transmits To the data processing unit；The data processing unit carries out cluster analysis to the 3-axis acceleration data by clustering algorithm, obtains each poultry The time series data of all kinds of basic acts of fowl；The time series data compared with default threshold parameter is analyzed, is drawn each The abnormal behavior condition information of livestock and poultry；The management to each livestock and poultry is provided according to the abnormal behavior condition information of each livestock and poultry It is recommended that；The managerial integration includes dividing group, isolation or maintains former stable breeding mode.
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