This application claims the benefit of priority to Chinese Patent Application No. 202010101545.7 titled “INTELLIGENT METHOD AND SYSTEM FOR MONITORING PIG BEHAVIOR ABNORMALITY”, filed with the Chinese State Intellectual Property Office on Feb. 19, 2020, the entire disclosure of which is incorporated herein by reference.
The disclosure relates to the field of motion state identification, in particular to an intelligent method and system for monitoring pig behavior abnormality.
With a rapid development of China's intelligent agricultural production, National Medium- and Long-term Science and Technology Development Program (2006-2020) has clearly brought a “precise operation and informatization of agriculture” into an optimization subject. Therefore, an establishment of a modern livestock and poultry feeding management system by using big data technology is of great significance to development of China's agricultural modernization and improvement of agricultural competitiveness.
In alive pig feeding process, some abnormal signs appears for an epidemic disease, oestrus and other phenomena of pigs, but the traditional method excessively depends on the long-term feeding experience of feeders. The probability of an abnormal behavior occurring in practical feeding of live pigs is not high, and the abnormal behavior is not easily found by production managers. Therefore, how to realize timely monitoring of the live pig abnormal behavior has become a problem to be settled urgently.
The disclosure intends to provide an intelligent method and system for monitoring pig behavior abnormality to detect an abnormal behavior of a live pig timely.
In order to achieve the above effect, the disclosure provides the following solutions.
An intelligent method for monitoring pig behavior abnormality comprises:
Optionally, the calculating the instantaneous acceleration variation according to the instantaneous acceleration specifically comprises: calculating the instantaneous acceleration variation according to a formula
Δaccx(k)=accx(k)−accx(k−1)
Δaccy(k)=accy(k)−accy(k−1)
Δaccz(k)=accz(k)−accz(k−1);
wherein Δaccx(k), Δaccy(k) and Δaccz(k) are instantaneous acceleration variations in three axial directions respectively, k is the number of sampling points, and accx(k), accy(k) and Δaccz(k) are the instantaneous accelerations in the three axial directions respectively.
Optionally, the calculating the sampling characteristic value according to the instantaneous acceleration and the instantaneous acceleration variation comprises:
Optionally, the calculating the first characteristic value according to the instantaneous acceleration variation specifically comprises: calculating the first characteristic value according to a formula
T1(k)=√{square root over (Δaccx(k)2+Δaccy(k)2+Δaccz(k)2)};
Optionally, the calculating the second characteristic value according to the instantaneous acceleration comprises:
Optionally, the acquiring the standard deviation value of the current sampling point according to the instantaneous acceleration specifically comprises: calculating the standard deviation value of the current sampling point according to a formula
t2[k]=std({tilde over (x)}[k]);
Optionally, the calculating the second characteristic value according to the standard deviation value specifically comprises: calculating the second characteristic value according to a formula T2[k]=SQRT(t2[k]); where T2[k] is the second characteristic value.
Optionally, the calculating the sampling characteristic value according to the first characteristic value and the second characteristic value specifically comprises: calculating the sampling characteristic value according to a formula T[k]=max(T1[k])2.max(T2[k])2; wherein T[k] is the sampling characteristic value.
Optionally, the calculating the threshold according to the historical data specifically comprises:
In order to achieve the above effect, the disclosure also provides the following technical solution.
An intelligent system for monitoring pig behavior abnormality comprises:
According to the detailed embodiments of the disclosure, the disclosure can achieve following technical effects:
According to the disclosure, the characteristic value of the instantaneous acceleration of the live pig is calculated, the characteristic value is compared with the threshold calculated according to historical data to determine whether the behavior of the live pig is normal or not, and an alarm signal is sent out after the abnormal behavior is detected, so that the abnormal behavior of the live pig can be found in time to improve the feeding safety.
The embodiments, examples and alternatives of the preceding paragraphs, the claims, or the following description and drawings, including any of their various aspects or respective individual features, may be taken independently or in any combination. Features described in connection with one embodiment are applicable to all embodiments, unless such features are incompatible.
In order to more clearly explain the embodiments of the present disclosure or the technical solutions in the conventional technology, the drawings used in the embodiments will be briefly described below. Obviously, the drawings in the following description are only some embodiments of the present disclosure. For those skilled in the art, other drawings may be obtained based on the drawings without creative efforts.
1, an acquisition unit; 2, a variation calculation unit; 3, a sampling characteristic value calculation unit; 4, a threshold calculation unit; 5, a drawing unit; 6, a judgment unit; 7, a control unit; and 8, an alarm unit.
In the following, the technical solutions in the embodiments of the present disclosure will be clearly and completely described with reference to the drawings in the embodiments of the present disclosure. Obviously, the described embodiments are only a part of the embodiments of the present disclosure, but not all the embodiments. Based on the embodiments of the present disclosure, all other embodiments obtained by those skilled in the art without any creative efforts shall fall within the scope of the present disclosure.
The disclosure intends to provide an intelligent method and system for monitoring pig behavior abnormality to detect abnormal behaviors of live pigs timely.
For a better understanding of above intention, features and advantages of the present disclosure, the disclosure will be described in details by reference to the accompanying drawings and specific embodiments thereof.
The intelligent method for monitoring pig behavior abnormality of the disclosure is performed by calculating the characteristic value of the instantaneous acceleration of the live pig, comparing the characteristic value with the threshold calculated according to historical data to determine whether the behavior of the live pig is normal or abnormal, and sending out an alarm signal when the abnormal behavior is detected, so that the abnormal behavior of the live pig can be found by the feeder in time, and the feeding safety is improved.
The step 101 can specifically comprises steps of:
Due to a small motion range of the neck of the live pig, the acceleration sensor can be mounted on the neck of the live pig to effectively reduce the data processing complexity. The accuracy of the data can be effectively improved by noiseless processing and abnormal value removal processing on the acquisition data, so as to increase the reliability of the alarm signal.
The step 102 can specifically comprises calculating the instantaneous acceleration variation according to a formula
Δaccx(k)=accx(k)−accx(k−1)
Δaccy(k)=accy(k)−accy(k−1)
Δaccz(k)=accz(k)−accz(k−1);
wherein Δaccx(k), Δaccy(k) and Δaccz(k) are instantaneous acceleration variations in three axial directions respectively, k is the number of sampling points, and accx(k), accy(k) and accz(k) are the instantaneous accelerations in the three axial directions respectively.
The instantaneous accelerations of the live pig in three axial directions are collected to truly indicate the motion state of the live pig.
The step 103 can specifically comprises steps of:
The second step 103 substep can include the step of:
The second step 103 substep can then further include the step of:
The step 104 can include steps of:
The following technical effects can be achieved by the present disclosure:
In order to achieve above technical effects, the disclosure also provides a technical solution as follows:
An intelligent system for monitoring pig behavior abnormality is shown in
The acquisition unit 1 is configured to acquire an instantaneous acceleration of the live pig;
Various embodiments of the description have been described in a progressive way, each of which emphasizes the difference from the others, and among which the same and similar parts can be referred to each other.
The preceding description is exemplary rather than limiting in nature. Variations and modifications to the disclosed examples may become apparent to those skilled in the art that do not necessarily depart from the essence of this disclosure. Thus, the scope of legal protection given to this disclosure can only be determined by studying the following claims.
Number | Date | Country | Kind |
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202010101545.7 | Feb 2020 | CN | national |
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Number | Date | Country | |
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20210251195 A1 | Aug 2021 | US |