CN114258877A - Poultry health assessment method and system based on group motion quantity statistical characteristics - Google Patents
Poultry health assessment method and system based on group motion quantity statistical characteristics Download PDFInfo
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Abstract
The invention relates to the technical field of artificial intelligence, and provides a poultry health assessment method and system based on group exercise amount statistical characteristics, wherein the poultry health assessment method comprises the following steps: acquiring poultry data from a foot ring with a three-axis sensor worn by poultry, and preprocessing the acquired data to obtain the poultry exercise amount data; abnormal data detection and correction are carried out on the poultry exercise amount data to obtain corrected poultry exercise amount data; according to the corrected poultry exercise amount data, carrying out statistics and data distribution on the poultry exercise amount data of the same individual and the group in different time periods, and carrying out individual scoring and group scoring on the poultry according to the statistics and data distribution results of the poultry exercise amount data; and evaluating the health state of the poultry by combining the poultry exercise amount data, the individual scoring result and the group scoring result to obtain a poultry health evaluation result. The poultry health detection method can effectively improve the accuracy and precision of poultry health detection, and can visually reflect the health condition of poultry.
Description
Technical Field
The invention relates to the technical field of artificial intelligence, in particular to a poultry health assessment method and system based on group motion quantity statistical characteristics.
Background
With the continuous improvement of the living standard of people, the demand of people for various poultry is increased. In the process of breeding large-scale poultry (chickens, ducks and geese), it is necessary that weak and small individuals are injured by accidents, such as snatching and eating, or the situations that the individuals are injured by being put on a shelf cannot be avoided, and the individuals need to be rescued in time or cleaned in time so as to avoid further loss. Therefore, for reasonable monitoring and transformation of exercise amount, obtaining the health score for health assessment is of great significance for ensuring stable breeding of poultry (chickens, ducks and geese) and improving the yield value. In traditional poultry breeding, the health condition of poultry is observed manually, and as poultry diseases occur and develop rapidly and time occurs randomly, the method of manual observation is time-consuming, labor-consuming and easy to make mistakes. With the maturity and popularization of computer vision technology, more and more scholars acquire life images or videos of animals (chickens, ducks and geese) through cameras and detect the behaviors of the animals (chickens, ducks and geese) according to image characteristics, but the methods need to deploy cameras and other equipment, and a large number of cameras are required to be deployed to meet the requirements of a shooting range or the requirements of shooting definition no matter in a cage culture condition or a flat culture condition, otherwise, the effect of later judgment is influenced.
The existing detection method for detecting the moving track data of the running poultry by adopting the foot ring can effectively reduce the transformation cost, can finish the classification of health states according to the moving track data of the poultry, but has the defect of low detection precision aiming at the classification of the weakness and diseases of the poultry. In addition, the existing method usually directly gives out early warning information or gives out unhealthy warning, and does not give out a health condition score, so that the monitoring of abnormal behaviors at a certain time point can only be achieved, the health condition evaluation of individual poultry or group poultry cannot be carried out by combining past data, and the health condition of the poultry cannot be described.
Disclosure of Invention
The invention provides a poultry health assessment method based on group motion amount statistical characteristics and a poultry health assessment system based on the group motion amount statistical characteristics, aiming at overcoming the defects that the poultry health detection precision is low and the health condition of poultry cannot be described in the prior art.
In order to solve the technical problems, the technical scheme of the invention is as follows:
a poultry health assessment method based on group exercise quantity statistical characteristics comprises the following steps:
s1, acquiring poultry data from a foot ring with a three-axis sensor worn by poultry, and preprocessing the acquired data to obtain the poultry exercise amount data;
s2, carrying out abnormal data detection and correction on the poultry motion amount data to obtain corrected poultry motion amount data;
s3, carrying out statistics and data distribution on the poultry exercise amount data of the same individual and the group in different time periods according to the corrected poultry exercise amount data, and carrying out individual grading and group grading on the poultry according to the statistics and data distribution results of the poultry exercise amount data;
and S4, evaluating the health status of the poultry by combining the poultry exercise amount data, the individual scoring results and the group scoring results to obtain poultry health evaluation results.
According to the technical scheme, poultry is used as a research object, the motion quantity of the poultry is collected as estimation data through a three-axis sensor configured on a foot ring, and the collected data of the three-axis sensor is preprocessed to obtain high-precision poultry motion quantity data; carrying out statistics and data distribution by combining the distribution of the same individual in different time periods and different time periods of the group, and further obtaining corresponding health scores; in the process of further combining the poultry exercise amount data, the individual scoring results and the group scoring results to evaluate the health state of the poultry, corresponding threshold values can be set according to practical application, and the poultry health evaluation results with high accuracy and multiple angles, such as the disability, illness, death, robustness and the like of the poultry individuals, can be obtained through comparison of the obtained individual scoring and the group scoring.
Furthermore, the invention also provides a poultry health assessment system based on the statistical characteristics of the group exercise amount, which is applied to the poultry health assessment method based on the statistical characteristics of the group exercise amount. Which comprises the following steps:
the poultry foot ring is provided with a three-axis sensor and a communication module and is worn on the feet of poultry;
the data receiving module is used for receiving poultry data returned by the foot rings at certain time intervals;
the data preprocessing module is used for preprocessing the received poultry data to obtain poultry exercise amount data;
the abnormality detection and correction module is used for detecting and correcting the abnormal data of the poultry exercise amount data to obtain corrected poultry exercise amount data;
the individual scoring module is used for counting and distributing the poultry exercise amount data of the same individual in different time periods according to the corrected poultry exercise amount data and scoring the individual;
the group scoring module is used for counting and distributing the poultry exercise amount data of the group to which the same individual belongs in different time periods according to the corrected poultry exercise amount data and scoring the group;
and the evaluation module is used for evaluating the health state of the poultry by combining the poultry exercise amount data, the individual scoring result and the group scoring result to generate a poultry health evaluation result.
Compared with the prior art, the technical scheme of the invention has the beneficial effects that: according to the poultry health status evaluation method, the poultry data are acquired by the three-axis sensor and used for grading calculation and evaluation of the poultry health status, and meanwhile, the acquired poultry data are subjected to abnormal detection and correction, so that the poultry health detection precision and accuracy can be effectively improved; the poultry health detection method carries out statistics and data distribution on the poultry motion amount data of the same individual and the group in different time periods, further carries out individual scoring and group scoring on the poultry, effectively avoids estimation deviation caused by single data, further improves poultry health detection precision, and can intuitively reflect poultry health conditions.
Drawings
FIG. 1 is a flow chart of a poultry health assessment method based on statistical characteristics of group exercise amounts according to example 1.
FIG. 2 is a flow chart of the pretreatment of poultry data in example 2.
FIG. 3 is a flowchart of individual scoring of poultry in example 3.
FIG. 4 is a flow chart of group scoring of poultry in example 3.
FIG. 5 is a flowchart of the evaluation of the health status of poultry in example 3.
FIG. 6 is an architecture diagram of the poultry health assessment system based on statistical characteristics of group exercise amounts of example 4.
Detailed Description
The drawings are for illustrative purposes only and are not to be construed as limiting the patent;
it will be understood by those skilled in the art that certain well-known structures in the drawings and descriptions thereof may be omitted.
The technical solution of the present invention is further described below with reference to the accompanying drawings and examples.
Example 1
The present embodiment provides a poultry health assessment method based on statistical characteristics of group exercise amount, and as shown in fig. 1, is a flowchart of the poultry health assessment method based on statistical characteristics of group exercise amount according to the present embodiment.
The poultry health assessment method based on the statistical characteristics of the group exercise amount provided by the embodiment comprises the following steps:
and S1, acquiring poultry data from the foot ring with the triaxial sensor worn by the poultry, and preprocessing the acquired data to obtain the poultry motion amount data.
In this embodiment, the poultry data including displacement amounts of individual poultry in three axes directions is acquired by using the foot ring provided with the three-axis sensor, and the high-precision poultry motion amount data is further obtained after data processing, so that the poultry motion amount data has certain adaptability and is adapted to detection of data such as body temperature.
In this embodiment, the accumulated displacement amount and the accumulated rotation angle amount may be further calculated for calculating the poultry exercise amount data.
And S2, carrying out abnormal data detection and correction on the poultry motion amount data to obtain corrected poultry motion amount data.
In this embodiment, considering that the hardware foundation is better today, most of the pin rings include an exception handling module, and this embodiment assumes that the obtained exception data only includes spike data, that is, in a small time domain, only data of one pin ring in the group is abnormal. Aiming at the characteristics of the peak data, the corrected poultry exercise amount data can be obtained by adopting modes such as linear correction, mode correction and the like in the data correction process.
And S3, carrying out statistics and data distribution on the poultry exercise amount data of the same individual and the poultry group in different time periods according to the corrected poultry exercise amount data, and carrying out individual grading and group grading on the poultry according to the statistics and data distribution results of the poultry exercise amount data.
In consideration of avoiding estimation deviation caused by single data, the embodiment adopts a mode of comparing data in a small time neighborhood, and combines the distribution of the same individual in different time periods and different time periods of a group to make linear estimation and distribution similarity estimation so as to obtain the individual score and the group score of the poultry, so that the activity condition of the poultry can be visually reflected.
And S4, evaluating the health status of the poultry by combining the poultry exercise amount data, the individual scoring results and the group scoring results to obtain poultry health evaluation results.
In the specific implementation process, aiming at health states of poultry individuals, such as disability, sickness, death, health and the like, evaluation can be carried out through individual scores and group scores of the poultry obtained through statistical analysis and calculation based on a threshold value, wherein the health states of the poultry, such as disability, health and the like, are obtained by using group exercise amount distribution based on the threshold value, a batch with the highest exercise amount is used as healthy poultry, and a batch with the lowest exercise amount is used as defective poultry; while the health states of diseases, deaths and the like can be represented by the score change in a short period, if the score change is extremely low, the death is evaluated, and if the score change is low, the disease is evaluated. The health states of the poultry, such as disability, sickness, death, health and the like, can be distinguished through the method.
The embodiment adopts the triaxial sensor to obtain poultry data for the scoring calculation and evaluation of poultry health status, and simultaneously carries out abnormity detection and correction on the collected poultry data, thereby effectively improving the poultry health detection precision and accuracy. In addition, according to the corrected poultry exercise amount data, statistics and data distribution are carried out on the poultry exercise amount data of the same individual and the poultry exercise amount data of the same group in different time periods, and then individual scoring and group scoring are carried out on the poultry, so that estimation deviation caused by single data is effectively avoided, the poultry health detection precision is further improved, and meanwhile the active condition of the poultry group can be intuitively reflected. And finally, poultry health status evaluation is carried out by combining the exercise amount data of the poultry, the individual scores and the group scores of the poultry, and related threshold values are set according to conditions reflected under different health statuses of the poultry, so that various poultry health evaluation results are obtained, and the health status of the poultry can be visually represented.
Example 2
This example is an improvement over the poultry health assessment method based on statistical characteristics of population motion quality as set forth in example 1.
Poultry health assessment method based on group exercise amount statistical characteristics provided by embodimentThe data of the birds acquired in the step S1 includes the displacement amount of the birdsvWherein the amount of displacementvIncluding displacement components in three axial directionsx、y、z。
Further, as shown in fig. 2, the step of preprocessing the acquired data in this embodiment includes:
s1.1, calculating the displacement accumulation amount of the poultry detected in the data currently returned by the foot ringVThe expression formula is as follows:
in the formula (I), the compound is shown in the specification,v n data return interval delta representing a foot ringtInner firstnThe next detected displacement of the poultry.
Wherein, the data return time interval delta of the foot ringtDetermined by parameters internal to the foot ring, due to ΔtHas an impact on the estimation, and in one embodiment, is initially set to 0.5h and then adjusted as the case may be.
S1.2, calculating data return time interval deltatWithin each detected angular component of rotation of the poultrywThen, the data return time interval delta is calculated by adopting an exponential scaling modetCumulative amount of rotation angle of inner poultryWThe expression formula is as follows:
in the formula (I), the compound is shown in the specification,x n 、y n 、z n is shown asnThe displacement component in the three-axis direction of the poultry detected next.τIs a constant close to 0 and, in one embodiment, is set to 0.0001.
αFor adjusting parameters of exponential scaling, making turnsThe angular and displacement accumulations are in a similar range. Considering the factors of species, region, etc., it is necessary to adjust the conditions according to the actual situation, and in one embodiment, the factors areαThe initial setting value is 1 and then adjusted according to the actual situation.
S1.3, according to the displacement accumulation of the poultryVSum rotation angle additionWCalculating the amount of poultry exercise in the currently returned datam=V+W。
And S1.4, carrying out group grouping on the poultry motion amount data, and taking the motion amount corresponding to the poultry with the same age in days as a group of group data.
In the embodiment, the age of day is used as a grouping condition, so that effective population estimation can be ensured.
The poultry motion amount data in the embodiment is composed of displacement accumulated amount and rotation angle accumulated amount, and calculation slightly differs according to difference of value ranges and motion characteristics of two kinds of data: the accumulated displacement quantity is directly formed by accumulating the displacement variation quantity; the value range of the cumulative amount of the rotation angle is smaller than that of the cumulative amount of the displacement, and the numerical difference is smaller under different motion amounts, so that the difference is increased by adopting exponential operation, the range is adjusted by utilizing a scaling factor, and then the difference is accumulated.
In the step S2, when the abnormality data is detected and corrected for the poultry motion amount data, specifically, the second order difference method is usedtMoment of poultry exercisem t A linear fit is performed in the small time neighborhood, which is expressed as follows:
using preset threshold valuesthTo the firsttDetecting abnormal data according to the second-order difference value of the poultry motion quantity at the moment:
if it is firsttSecond order difference value delta of poultry motion quantity at momentm t Greater than or equal to a preset threshold valuethIf so, judging that abnormal data exists, and comparing the data with the first datatMoment of poultry exercisem t Correcting;
if it is firsttTime of daySecond order difference value delta of poultry motion quantitym t Less than a predetermined thresholdthAnd judging the data to be normal data.
Further, setting a thresholdthThe method can be obtained by any one of the following methods:
(1) counting the second order difference value of the poultry motion amount in a certain time period, and taking the maximum value of the second order difference value of the poultry motion amount in the time period as a threshold valuethThe expression formula is as follows:
in the formula (I), the compound is shown in the specification,βfor adjustment parameters with values greater than 1, ΔmAnd the second-order difference value of the poultry motion quantity at each moment in a certain time period is shown. In one embodiment of the present invention, the substrate is,βthe value is 1.1.
(2) Counting the second order difference value of the poultry motion amount in a certain time period, and calculating the mean value of the second order difference value of the poultry motion amount in the certain time period
Sum variance
Calculating a threshold valuethThe expression formula is as follows:
in the formula (I), the compound is shown in the specification,θto adjust the parameters, values are set on a case-by-case basis, and in one embodiment, the parameters are adjustedθHas an initial value of 3.
After the abnormal data is determined, the data at that time is corrected. In this embodiment, the step of correcting the abnormal data includes:
for the firsttMoment of poultry exercisem t The correction is carried out by adopting a linear hypothesis based on linear fitting, and the expression formula is as follows:
in the formula (I), the compound is shown in the specification,m t,1is shown astFitting value of poultry motion amount at the moment.
Obtaining the same group of poultry motion amount data, calculating the first group of poultrytMode of timem t,2According to the firsttFitting value of poultry exercise amount at timem t,1Sum modem t,2The correction is carried out, and the expression formula is as follows:
in the formula (I), the compound is shown in the specification,γfor adjusting the parameters, the value range is [0,1 ]]. In one embodiment, the parameters are adjustedγThe value is 0.5.
In this embodiment, considering that the current hardware device is relatively stable, the data are adjacent in time and the motion is a continuous process, the embodiment assumes that the obtained abnormal data only includes spike data, that is, in a small time domain, the data of only one pin ring in the group is abnormal. And calculating the second-order difference of the data according to the peak characteristics of the peak, and detecting data abnormality by using a threshold value. For the abnormality, two correction methods are adopted: individual linearity correction for different time series and mode correction for group motion amount. And linearly combining the two correction methods to obtain a final correction result of the abnormal data.
Example 3
This example is an improvement over the poultry health assessment method based on statistical characteristics of group exercise amount as set forth in example 2.
In the poultry health assessment method based on the statistical characteristics of group motion amount provided by this embodiment, after detection and correction of abnormal data are completed, data structuring is performed on the poultry motion amount data judged to be normal data and/or completed correction, and the poultry motion amount data is stored in a buffer queue structure of a corresponding group; the above-mentionedThe buffer queue structure stores the data belonging to the same groupNEach individual poultry is close todPersonal exercise amount data of daily poultrym i,j And group motion amount data of the group
Wherein the amount of group exercise data
Is the packet inner proximitydThe average of the daily poultry exercise amount,
，
，Δtand returning a time interval for the data of the foot ring.
In this embodiment, the abnormal detection and correction of the data of the exercise amount of the poultry are stored in two types: individual data and population data. The data in a period of time span is only stored during storage, all the data are stored as a queue structure, when the data are obtained in a new day, the data are temporarily stored, after the data in one day are completely stored, the original earliest data are replaced, the timeliness of the data is ensured, so that the characteristics for analogy can be suitable for various changes, the self-adaptive function on the time sequence is completed, and the robustness of the algorithm on the time span is ensured. In the application of calculation, the group data is divided into short-term group data and long-term group data for use so as to obtain results in different time spans.
Further, in step S3, the step of individually scoring the poultry comprises:
s3.1, selecting the current momentj 0 A time neighborhood of the motion amount data of the individual poultrym i,j Wherein
，δIs a neighborhood parameter; for the historical number of movements of poultry in the same time neighborhoodThe normalization operation is performed, and the expression formula is as follows:
in the formula (I), the compound is shown in the specification,p i,j,k representing individual birds in the same temporal neighborhoodiThe result of normalization of the historical motion amount data of (a),m i,j-24*k is shown askIndividual poultry in the same time neighborhood before the dayiHistorical motion amount data.
In one embodiment, the neighborhood parametersδIs initialized to
I.e. to 2/deltatAnd taking the whole.
S3.2, normalizing the result according to the poultry exercise amount datap i,j,k Calculate the firstkResults of individual contemporary comparisons before the days i,k The expression formula is as follows:
in the formula (I), the compound is shown in the specification,ωto adjust the parameters, the value is a constant close to 0.
In one embodiment, the parameters are adjustedωThe initialization is set to 0.0000000001.
S3.3, adopting Gaussian convolution pairkFusing the results of individual synchronization comparison to obtain poultry individualiIndividual synchronization score ofc i The expression formula is as follows:
in the formula (I), the compound is shown in the specification,
the mean value is a normal distribution probability density function with 0 standard deviation of 1;σto adjust parameters, and
。
in one embodiment, the parameters are adjustedσThe initialization is set to 3.
S3.4, selecting the current momentj 0 Has a radius ofδTime neighborhood of poultry group exercise amount data
And then for the poultry group movement data in the time neighborhood
And carrying out normalization operation, wherein the expression formula is as follows:
in the formula (I), the compound is shown in the specification,p j a normalization result of the motion amount data representing the grouped group to which the poultry belongs;
s3.5, calculating group synchronization score by combining KL divergenced i The expression formula is as follows:
s3.6, for individual poultryiIndividual synchronization score ofc i And groupContemporaneous scoringd i Performing linear fusion to obtain individual scorea i The expression formula is as follows:
in the formula (I), the compound is shown in the specification,λfor adjusting the parameters, the value range is [0,1 ]]；
Representing an ceiling function.
In one embodiment, the parameters are adjustedλThe initial value is set to 0.3.
In this example, the scores are compressed nonlinearly and then scaled up to [100,0 ] to meet normal understanding]Is scored by the above individualsa i The results of the calculations of (a) are 100 to the most healthy and 0 to the least healthy. And storing the calculated poultry scoring result for subsequent judgment.
Fig. 3 is a flow chart of the individual scoring of poultry according to this embodiment.
In this embodiment, a KL divergence estimation method is mainly adopted, and an individual score is calculated by combining an individual synchronization score and a population synchronization score. The individual contemporaneous scoring is mainly achieved by comparing data of a single individual on different dates and at the same time, and in view of certain locality of motion change of the single individual, the individual scoring is obtained by convolving comparison results of Gaussian distribution on different dates. And directly comparing the individual data with the short-term group data by the group synchronization score, and finally performing linear fusion on the individual synchronization score and the group synchronization score to obtain the final individual score.
Further, two methods can be used for group scoring of poultry:
the method comprises the following steps: in calculating the corresponding group groups of poultryNIndividual evaluation of individual poultryIs divided intoa i Taking the average value to obtain poultry individualiMean individual poultry score for corresponding population groupso i Then, obtaining the group score through nonlinear compressiont i ：
The method 2 comprises the following steps:
1) calculating the current time by adopting a linear estimation methodj 0 Amount of theoretical exercise of
。
2) The current timej 0 Amount of theoretical exercise of
And the average value of the poultry individual scores
Comparing to obtain short-term score
：
3) Selecting the current timej 0 A time neighborhood of the amount of exercise of the poultry group
Wherein
(ii) a To the same time neighborNormalizing the poultry group exercise amount data in the domain:
in the formula (I), the compound is shown in the specification,l ,j,k a normalization result representing the historical exercise amount data of the poultry group in the same time neighborhood,
is shown askHistorical exercise amount data for a group of birds in the same time neighborhood before the day.
4) Calculate the firstkComparison results before day
。
5) Obtaining a preliminary long-term estimation score using gaussian convolution fusion
。
6) Scoring short term
And preliminary long term estimate score
After linear fusion, the population score is obtained through nonlinear compressiont i ：
In the formula (I), the compound is shown in the specification,
to adjust the parameters.
Fig. 4 is a flow chart of the method 2 for group scoring of poultry according to this example.
In this embodiment, the method 1 is directly adopted in the group groupingNIndividual score of individual poultrya i The average value is obtained by nonlinear compression, and the method is suitable for application scenes that the number of poultry individuals in a group is large, the calculation condition is limited, and the like. The method 2 adopts a small time neighborhood comparison mode to divide the population score into long-term population evaluation and short-term population evaluation, wherein the long-term population evaluation compares the distribution of the same time neighborhood in different dates, and then the score is obtained by adopting Gaussian convolution according to different dates; short-term population estimation utilizes the continuity of transformation, estimates a theoretical linear estimated value by using short-term data, and compares the estimated value with an actual value to obtain a score. And obtaining the final score through linear fusion of the two scores. Method 2 is able to more intuitively reflect the liveness of the birds in the group.
Further, the health status of the poultry is evaluated by combining the exercise amount data of the poultry, the individual scoring result and the group scoring result, and the method specifically comprises the following steps:
s4.1 according to poultryi(ii) individual score ofa i And a preset first threshold valueη 1A second threshold valueη 2And (4) judging:
when the poultry is in the process of being raisedi(ii) individual score ofa i Less than a preset first thresholdη 1Then the poultry will be treatediAssessed as dead;
when the poultry is in the process of being raisedi(ii) individual score ofa i Greater than or equal to a preset first threshold valueη 1And is less than a predetermined second threshold valueη 2Then the poultry will be treatediAssessed as diseased;
when the poultry is in the process of being raisedi(ii) individual score ofa i Greater than or equal to a preset second threshold valueη 2Then the poultry will be treatediEvaluated as normal.
Wherein the first threshold valueη 1Less than a second thresholdη 2According to the practical applicationAnd setting conditions. In one embodiment, the first threshold valueη 1Set to 25, second thresholdη 2Set to 70.
S4.2, calculating poultry according to the poultry motion amount dataiGroup of belongingszVariance of group motion amount
：
In the formula (I), the compound is shown in the specification,m i z,is poultryiThe amount of motion data.
S4.3, according to the variance of the group motion amount
And (4) judging:
if the poultry is a poultryiData of poultry exercise amount
Then the poultry will be treatediEvaluating as healthy poultry;
if the poultry is a poultryiData of poultry exercise amount
Then the poultry will be treatediEvaluating as defective poultry;
otherwise, the poultry will beiEvaluating as normal poultry;
wherein the content of the first and second substances,v a 、v b for adjusting the parameters, the value range is [0,5 ]]. In one embodiment of the present invention, the substrate is,v a =v b =3。
fig. 5 is a flow chart of the present embodiment for evaluating the health status of poultry. In this example, the classification of the defective, sick, dead and healthy poultry is divided into two classification problems.
The first category is the classification of diseased, dead and normal problems. And S4.1, evaluating the health states of the poultry, such as illness, death and normal, and calculating the health scores of the poultry based on a threshold value through the obtained individual health scores, wherein the illness and the death can be represented by score change in a short period, the death is judged if the score is extremely low, and the illness is judged if the score is low.
The second type is the defective, healthy and common poultry, and the evaluation is realized through the steps S4.2 and S4.3, wherein the defective and healthy using population motion amount distribution is obtained based on a threshold value, the batch with the highest motion amount is used as the healthy poultry, and the batch with the smallest motion amount is used as the defective poultry.
Example 4
The embodiment provides a poultry health assessment system based on statistical characteristics of group exercise amount, which is applied to the poultry health assessment method provided in any one of embodiments 1 to 3. Fig. 6 is a diagram showing the configuration of the poultry health evaluation system of the present embodiment.
The poultry health assessment system based on the statistical characteristics of the group exercise amount provided by the embodiment comprises:
the poultry foot ring comprises a foot ring 1, wherein the foot ring 1 is provided with a three-axis sensor 101 and a communication module 102, and the foot ring 1 is worn on the feet of poultry;
the data receiving module 2 is used for receiving poultry data returned by the foot ring 1 at certain time intervals;
the data preprocessing module 3 is used for preprocessing the received poultry data to obtain the poultry exercise amount data;
the abnormality detection and correction module 4 is used for detecting and correcting the abnormal data of the poultry exercise amount data to obtain corrected poultry exercise amount data;
the individual scoring module 5 is used for counting and distributing the poultry exercise amount data of the same individual in different time periods according to the corrected poultry exercise amount data and scoring the individual;
the group scoring module 6 is used for counting and distributing the poultry exercise amount data of the group to which the same individual belongs in different time periods according to the corrected poultry exercise amount data, and performing group scoring;
and the evaluation module 7 is used for evaluating the health state of the poultry by combining the poultry exercise amount data, the individual scoring result and the group scoring result to generate a poultry health evaluation result.
In the specific implementation process, the foot ring 1 provided with the three-axis sensor 101 and the communication module 102 is worn on the individual poultry to be evaluated, wherein the three-axis sensor 101 collects the displacement of the individual poultry in three-axis directions in real time, and then returns the displacement back at a preset data return time interval deltatThe current time interval Δ is transmitted by the communication module 102tThe poultry data collected at several moments in time during the period are sent to the data receiving module 2.
The data receiving module 2 receives the poultry data sent by the foot ring 1 and then transmits the poultry data to the data preprocessing module 3 for processing. The data preprocessing module 3 calculates the displacement accumulated amount, the rotation angle component and the rotation angle accumulated amount of the poultry detected in the data currently returned by the foot ring 1, further calculates the poultry motion amount in the currently returned data, and finally transmits the calculated poultry motion amount to the abnormality detection and correction module 4.
When the abnormality detection and correction module 4 detects and corrects the abnormal data of the poultry exercise amount data, specifically, the second order difference method is adopted to carry out the second order differencetThe motion amount of the poultry at the moment is linearly fitted in a small time neighborhood, and then a preset threshold value is utilizedthTo the firsttAnd detecting abnormal data by using the second-order difference value of the poultry motion amount at the moment, respectively performing individual linear correction aiming at different time sequences and mode correction aiming at group motion amount on the detected abnormal data, and performing linear combination to obtain a final correction result of the abnormal data.
The abnormality detection and correction module 4 groups the detected normal data and the corrected data into groups according to the ages of the individual poultry days.
The individual scoring module 5 reads the normal data and the corrected data of the poultry individuals, counts and distributes the poultry exercise amount data of the same individual in different time periods, and performs individual scoring.
Specifically, the individual scoring module 5 adopts a KL divergence estimation method and performs individual scoring calculation by combining the individual synchronization score and the group synchronization score. The individual synchronization scoring is mainly characterized in that individual scores are obtained by comparing data of a single individual at different dates and the same time and convolving comparison results of different dates by adopting Gaussian distribution; and the group synchronization score directly compares the individual data with the short-term group data, and finally, the individual synchronization score and the group synchronization score are subjected to linear fusion to obtain a final individual score, and the final individual score is sent to an evaluation module 7.
Meanwhile, the group scoring module 6 adopts the group groupingNIndividual score of individual poultrya i Carrying out nonlinear compression on the mean value to obtain a group scoring result; or dividing the population score into long-term population evaluation and short-term population evaluation by adopting a small time neighborhood comparison mode, wherein the long-term population evaluation compares the distribution of the same time neighborhood in different dates, and then the score is obtained by adopting Gaussian convolution according to different dates; short-term population estimation utilizes the continuity of transformation, estimates a theoretical linear estimated value by using short-term data, and compares the estimated value with an actual value to obtain a score. And obtaining the final group score through linear fusion of the two scores, and sending the final group score to the evaluation module 7.
And the evaluation module 7 receives the final individual scores and the group scores and then evaluates the health status of the poultry by combining the poultry exercise amount data, the individual score results and the group score results.
Specifically, the evaluation module 7 first evaluates the diseased, dead and normal states of the poultry, and calculates the individual health scores based on the threshold value, wherein the diseased and dead states can be represented by the score change in a short period, the score is dead when the score is extremely low, and the score is diseased when the score is low.
The evaluation module 7 further evaluates the defective, healthy, and normal states of the poultry, wherein the defective, healthy, and use group motion amount distribution is obtained based on a threshold value, a batch with the highest motion amount is used as a healthy poultry, a batch with the smallest motion amount is used as a defective poultry, and the other cases are evaluated as normal poultry.
It should be understood that the above-described embodiments of the present invention are merely examples for clearly illustrating the present invention, and are not intended to limit the embodiments of the present invention. Other variations and modifications will be apparent to persons skilled in the art in light of the above description. And are neither required nor exhaustive of all embodiments. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present invention should be included in the protection scope of the claims of the present invention.
Claims (10)
1. A poultry health assessment method based on group exercise quantity statistical characteristics is characterized by comprising the following steps:
s1, acquiring poultry data from a foot ring with a three-axis sensor worn by poultry, and preprocessing the acquired data to obtain the poultry exercise amount data;
s2, carrying out abnormal data detection and correction on the poultry motion amount data to obtain corrected poultry motion amount data;
s3, carrying out statistics and data distribution on the poultry exercise amount data of the same individual and the group in different time periods according to the corrected poultry exercise amount data, and carrying out individual grading and group grading on the poultry according to the statistics and data distribution results of the poultry exercise amount data;
and S4, evaluating the health status of the poultry by combining the poultry exercise amount data, the individual scoring results and the group scoring results to obtain poultry health evaluation results.
2. The method for evaluating health of poultry based on statistical characteristics of amount of group exercise according to claim 1, wherein the data of the poultry obtained in the step of S1 comprises displacement amount of the poultryvWherein the amount of displacementvIncluding displacement components in three axial directionsx、y、z(ii) a The step of preprocessing the acquired data comprises:
s1.1, calculating the displacement accumulation amount of the poultry detected in the data currently returned by the foot ringVThe expression formula is as follows:
in the formula (I), the compound is shown in the specification,v n data return interval delta representing a foot ringtInner firstnSecondarily detected displacement amount of the poultry;
s1.2, calculating data return time interval deltatWithin each detected angular component of rotation of the poultrywThen, the data return time interval delta is calculated by adopting an exponential scaling modetCumulative amount of rotation angle of inner poultryWThe expression formula is as follows:
in the formula (I), the compound is shown in the specification,x n 、y n 、z n is shown asnThe displacement components in the three axial directions of the poultry detected next,τis a constant;αis a parameter for adjusting the exponential scaling;
s1.3, according to the displacement accumulation of the poultryVSum rotation angle additionWCalculating the amount of poultry exercise in the currently returned datam=V+W；
And S1.4, carrying out group grouping on the poultry motion amount data, and taking the motion amount corresponding to the poultry with the same age in days as a group of group data.
3. The method for evaluating poultry health according to claim 2, wherein in step S2, the second order difference method is used to evaluate the poultry health according to the statistical characteristics of group motion quantitytMoment of poultry exercisem t A linear fit is performed in the small time neighborhood, which is expressed as follows:
using preset threshold valuesthTo the firsttDetecting abnormal data according to the second-order difference value of the poultry motion quantity at the moment:
if it is firsttSecond order difference value delta of poultry motion quantity at momentm t Greater than or equal to a preset threshold valuethIf so, judging that abnormal data exists, and comparing the data with the first datatMoment of poultry exercisem t Correcting;
if it is firsttSecond order difference value delta of poultry motion quantity at momentm t Less than a predetermined thresholdthAnd judging the data to be normal data.
4. The method of claim 3, wherein the threshold value is based on statistical characteristics of the amount of motion of the groupthObtained by any one of the following methods:
(1) counting the second order difference value of the poultry motion amount in a certain time period, and taking the maximum value of the second order difference value of the poultry motion amount in the time period as a threshold valuethThe expression formula is as follows:
in the formula (I), the compound is shown in the specification,βfor adjustment parameters with values greater than 1, ΔmExpressing the second-order difference value of the poultry motion quantity at each moment in a certain time period;
(2) counting the second order difference value of the poultry motion amount in a certain time period, and calculating the mean value of the second order difference value of the poultry motion amount in the certain time period
And variance Δm 2Calculating a threshold valuethThe expression formula is as follows:
in the formula (I), the compound is shown in the specification,θto adjust the parameters.
5. The method for evaluating poultry health according to claim 3 based on statistical characteristics of group exercise amount, wherein the step of correcting abnormal data in the step of S2 comprises:
for the firsttMoment of poultry exercisem t The correction is carried out by adopting a linear hypothesis based on linear fitting, and the expression formula is as follows:
m t ,1=2m t-1-m t-2
in the formula (I), the compound is shown in the specification,m t,1is shown astFitting values of the poultry exercise amount at all times;
obtaining the same group of poultry motion amount data, calculating the first group of poultrytMode of timem t,2According to the firsttFitting value of poultry exercise amount at timem t,1Sum modem t,2The correction is carried out, and the expression formula is as follows:
m t =γ∙2m t,1+(1-γ)m t,2
in the formula (I), the compound is shown in the specification,γto adjust the parameters.
6. The poultry health assessment method according to any one of claims 2 to 5, wherein the step S2 further comprises the following steps:
after the abnormal data detection and correction are completed, carrying out data structuralization on the poultry exercise amount data judged to be normal data and/or corrected, and storing the poultry exercise amount data in a buffer queue structure of a corresponding group; the buffer queue structure stores the data belonging to the same groupNEach individual poultry is close todPersonal exercise amount data of daily poultrym i,j And group motion amount data of the group
Wherein the amount of group exercise data
Is the packet inner proximitydThe average of the daily poultry exercise amount,
，
，Δtand returning a time interval for the data of the foot ring.
7. The method for evaluating poultry health according to claim 6 based on statistical characteristics of group exercise amount, wherein the step of individually scoring the poultry in the step of S3 comprises:
s3.1, selecting the current momentj 0 A time neighborhood of the motion amount data of the individual poultrym i,j Wherein
，δIs a neighborhood parameter; carrying out normalization operation on the historical exercise amount data of the poultry individuals in the same time neighborhood, wherein the expression formula is as follows:
in the formula (I), the compound is shown in the specification,p i,j,k representing individual birds in the same temporal neighborhoodiThe result of normalization of the historical motion amount data of (a),m i,j-24*k is shown askIndividual poultry in the same time neighborhood before the dayiHistorical motion amount data of (a);
s3.2, normalizing the result according to the poultry exercise amount datap i,j,k Calculate the firstkResults of individual contemporary comparisons before the days i,k The expression formula is as follows:
in the formula (I), the compound is shown in the specification,ωto adjust the parameters;
s3.3, adopting Gaussian convolution pairkFusing the results of individual synchronization comparison to obtain poultry individualiIndividual synchronization score ofc i The expression formula is as follows:
in the formula (I), the compound is shown in the specification,
the mean value is a normal distribution probability density function with 0 standard deviation of 1;
to adjust parameters, and
；
s3.4, selecting the current momentj 0 Has a radius ofδTime neighborhood of poultry group exercise amount data
Then to the time neighborhoodInternal poultry group exercise amount data
And carrying out normalization operation, wherein the expression formula is as follows:
in the formula (I), the compound is shown in the specification,p j a normalization result of the motion amount data representing the grouped group to which the poultry belongs;
s3.5, calculating group synchronization score by combining KL divergenced i The expression formula is as follows:
s3.6, for individual poultryiIndividual synchronization score ofc i Group synchronization scored i Performing linear fusion to obtain individual scorea i The expression formula is as follows:
in the formula (I), the compound is shown in the specification,λin order to adjust the parameters of the device,
representing an ceiling function.
8. The method for evaluating poultry health according to claim 7 based on statistical characteristics of group exercise amount, wherein the step of group scoring the poultry in the step of S3 comprises any one of the following steps:
(1) in calculating the corresponding group groups of poultryNIndividual score of individual poultrya i Taking the mean value and obtaining the group score through nonlinear compressiont i ：
In the formula (I), the compound is shown in the specification,o i representing individual poultryi(ii) a mean individual poultry score in the corresponding population group;
(2) calculating the current time by adopting a linear estimation methodj 0 Amount of theoretical exercise of
：
The current timej 0 Amount of theoretical exercise of
And the average value of the poultry individual scores
Comparing to obtain short-term score
：
Selecting the current timej 0A time neighborhood of the amount of exercise of the poultry group
Wherein
(ii) a Normalizing the poultry group exercise amount data in the same time neighborhood:
in the formula (I), the compound is shown in the specification,l ,j,k a normalization result representing the historical exercise amount data of the poultry group in the same time neighborhood,
is shown askHistorical movement amount data of the poultry groups in the same time neighborhood before the day;
calculate the firstkComparison results before day
：
Obtaining a preliminary long-term estimation score using gaussian convolution fusion
：
Scoring short term
And preliminary long term estimate score
After linear fusion, the population score is obtained through nonlinear compressiont i ：
In the formula (I), the compound is shown in the specification,
to adjust the parameters.
9. The poultry health assessment method according to claim 8, wherein the step of evaluating the health status of the poultry in combination with the poultry exercise amount data, the individual score results and the group score results in the step of S4 comprises:
s4.1 according to poultryi(ii) individual score ofa i And a preset first threshold valueη 1A second threshold valueη 2And (4) line judgment:
when the poultry is in the process of being raisedi(ii) individual score ofa i Less than a preset first thresholdη 1Then the poultry will be treatediAssessed as dead;
when the poultry is in the process of being raisedi(ii) individual score ofa i Greater than or equal to a preset first threshold valueη 1And is less than a predetermined second threshold valueη 2Then the poultry will be treatediAssessed as diseased;
when the poultry is in the process of being raisedi(ii) individual score ofa i Greater than or equal to a preset second threshold valueη 2Then the poultry will be treatediEvaluated as normal;
s4.2, calculating poultry according to the poultry motion amount dataiGroup of belongingszVariance of group motion amount
：
In the formula (I), the compound is shown in the specification,m i z,is poultryiThe amount of exercise data;
s4.3, according to the variance of the group motion amount
And (4) judging:
if the poultry is a poultryiData of poultry exercise amount
Then the poultry will be treatediEvaluating as healthy poultry;
if the poultry is a poultryiData of poultry exercise amount
Then the poultry will be treatediEvaluating as defective poultry;
otherwise, the poultry will beiEvaluating as normal poultry;
wherein the content of the first and second substances,v a 、v b to adjust the parameters.
10. A poultry health assessment system based on statistical characteristics of group exercise amount, which is applied to the poultry health assessment method according to any one of claims 1 to 9, and is characterized by comprising the following steps:
the poultry foot ring is provided with a three-axis sensor and a communication module and is worn on the feet of poultry;
the data receiving module is used for receiving poultry data returned by the foot rings at certain time intervals;
the data preprocessing module is used for preprocessing the received poultry data to obtain poultry exercise amount data;
the abnormality detection and correction module is used for detecting and correcting the abnormal data of the poultry exercise amount data to obtain corrected poultry exercise amount data;
the individual scoring module is used for counting and distributing the poultry exercise amount data of the same individual in different time periods according to the corrected poultry exercise amount data and scoring the individual;
the group scoring module is used for counting and distributing the poultry exercise amount data of the group to which the same individual belongs in different time periods according to the corrected poultry exercise amount data and scoring the group;
and the evaluation module is used for evaluating the health state of the poultry by combining the poultry exercise amount data, the individual scoring result and the group scoring result to generate a poultry health evaluation result.
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| CN115985502A (en) * | 2023-03-16 | 2023-04-18 | 华南农业大学 | Lion-head goose health decision method and device based on multivariate perception |
| CN116701886A (en) * | 2023-08-07 | 2023-09-05 | 知心健(南京)科技有限公司 | Intelligent analysis management system for exercise lung test data |
| WO2023165141A1 (en) * | 2022-03-01 | 2023-09-07 | 华南农业大学 | Poultry health assessment method and system based on group motion amount statistical characteristics |
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| CN107135983A (en) * | 2017-05-05 | 2017-09-08 | 北京农业信息技术研究中心 | Poultry health monitoring method, motion pin ring, server and system |
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| WO2023165141A1 (en) * | 2022-03-01 | 2023-09-07 | 华南农业大学 | Poultry health assessment method and system based on group motion amount statistical characteristics |
| CN115985502A (en) * | 2023-03-16 | 2023-04-18 | 华南农业大学 | Lion-head goose health decision method and device based on multivariate perception |
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