CN117398076A - Monitoring algorithm for analyzing lying behaviors of livestock - Google Patents
Monitoring algorithm for analyzing lying behaviors of livestock Download PDFInfo
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- CN117398076A CN117398076A CN202311623129.3A CN202311623129A CN117398076A CN 117398076 A CN117398076 A CN 117398076A CN 202311623129 A CN202311623129 A CN 202311623129A CN 117398076 A CN117398076 A CN 117398076A
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- 238000012544 monitoring process Methods 0.000 title claims abstract description 90
- 244000144972 livestock Species 0.000 title claims abstract description 27
- 230000006399 behavior Effects 0.000 title abstract description 23
- 241000283690 Bos taurus Species 0.000 claims abstract description 66
- 241001494479 Pecora Species 0.000 claims abstract description 66
- 230000000694 effects Effects 0.000 claims abstract description 59
- 241001465754 Metazoa Species 0.000 claims abstract description 50
- 230000008859 change Effects 0.000 claims abstract description 28
- 230000002496 gastric effect Effects 0.000 claims abstract description 21
- 239000002775 capsule Substances 0.000 claims abstract description 11
- 210000002784 stomach Anatomy 0.000 claims description 24
- 238000000034 method Methods 0.000 claims description 18
- 230000001133 acceleration Effects 0.000 claims description 15
- 238000012545 processing Methods 0.000 claims description 13
- 238000004364 calculation method Methods 0.000 claims description 12
- 230000002503 metabolic effect Effects 0.000 claims description 12
- 238000007405 data analysis Methods 0.000 claims description 9
- 210000002249 digestive system Anatomy 0.000 claims description 9
- 230000030135 gastric motility Effects 0.000 claims description 9
- 238000004458 analytical method Methods 0.000 claims description 7
- 230000029087 digestion Effects 0.000 claims description 6
- 230000008569 process Effects 0.000 claims description 5
- 230000002159 abnormal effect Effects 0.000 claims description 4
- 238000012935 Averaging Methods 0.000 claims description 3
- 230000005540 biological transmission Effects 0.000 claims description 3
- 230000002194 synthesizing effect Effects 0.000 claims description 3
- 201000010099 disease Diseases 0.000 abstract description 6
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 abstract description 6
- 206010000117 Abnormal behaviour Diseases 0.000 abstract description 3
- 238000001514 detection method Methods 0.000 abstract description 2
- 230000000737 periodic effect Effects 0.000 abstract description 2
- 230000009471 action Effects 0.000 description 3
- 230000009286 beneficial effect Effects 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 230000036541 health Effects 0.000 description 2
- 230000005802 health problem Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000011160 research Methods 0.000 description 1
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/01—Measuring temperature of body parts ; Diagnostic temperature sensing, e.g. for malignant or inflamed tissue
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/01—Measuring temperature of body parts ; Diagnostic temperature sensing, e.g. for malignant or inflamed tissue
- A61B5/015—By temperature mapping of body part
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/103—Detecting, measuring or recording devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
- A61B5/11—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb
- A61B5/1116—Determining posture transitions
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/103—Detecting, measuring or recording devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
- A61B5/11—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb
- A61B5/1118—Determining activity level
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- A—HUMAN NECESSITIES
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- A61B5/103—Detecting, measuring or recording devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
- A61B5/11—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb
- A61B5/1121—Determining geometric values, e.g. centre of rotation or angular range of movement
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- A61B5/1126—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb using a particular sensing technique
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- A61B5/42—Detecting, measuring or recording for evaluating the gastrointestinal, the endocrine or the exocrine systems
- A61B5/4222—Evaluating particular parts, e.g. particular organs
- A61B5/4238—Evaluating particular parts, e.g. particular organs stomach
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- A61B5/68—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient
- A61B5/6846—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient specially adapted to be brought in contact with an internal body part, i.e. invasive
- A61B5/6847—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient specially adapted to be brought in contact with an internal body part, i.e. invasive mounted on an invasive device
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Abstract
In order to solve the problem that the current monitoring equipment is inconvenient to monitor the lying behavior of livestock, the monitoring capsule is orally put into the bodies of cattle and sheep to monitor the change of gastric momentum, so that the activity level and lying time of the cattle and sheep are known, the longer lying time possibly indicates that the animals are in a relaxed or rest state, the shorter lying time possibly indicates that the animals are in a certain discomfort or stress state, the potential disease signs or abnormal behaviors are detected by analyzing the range of the activity difference and the average activity, the early detection and the taking of measures are facilitated, the diseases are prevented and treated, and a farmer or a breeder can adjust the feeding time, the spatial layout and the comfort degree according to the recorded lying time point and the standing time point to provide better living conditions and feeding environment and further know the daily activity mode, habit and periodic behavior of the farmer or breeder by recording the change of the lying time and the activity level.
Description
Technical Field
The invention relates to the technical field of livestock lying behavior monitoring, in particular to a monitoring algorithm for analyzing the lying behavior of livestock.
Background
The normal lying time and frequency of the livestock can be predicted, if the lying behavior of the livestock is abnormal, such as too long lying time, too high frequency or too low frequency, the livestock is usually indicated to possibly suffer from a certain disease or uncomfortable, and health problems can be found in time by monitoring and analyzing the lying behavior of the livestock, and corresponding treatment and protection measures are adopted to ensure the health of the livestock.
The monitoring equipment is used for monitoring the lying behaviors of the livestock, information is required to be acquired by means of manual observation or playback video recording and the like, and the problems of delay and omission possibly exist, so that the lying behaviors of the livestock are not good for being better monitored and analyzed.
To solve the above problems, a monitoring algorithm for analyzing the lying behavior of livestock is proposed.
Disclosure of Invention
The invention aims to provide a monitoring algorithm for analyzing the lying behaviors of livestock, which can solve the problem that the lying behaviors of the livestock are inconvenient to monitor by using monitoring equipment, which is proposed in the background art.
In order to achieve the above purpose, the present invention provides the following technical solutions: a monitoring algorithm for analyzing the lying behaviour of livestock, comprising:
monitoring unit: measuring the temperature change in the body, judging whether the digestive system of the cattle and sheep is in an active state or not, thereby estimating the gastric momentum of the cattle and sheep, measuring the movement and posture change, estimating the active state of the cattle and sheep, and further indirectly estimating the gastric momentum of the cattle and sheep;
a data processing unit: and processing and analyzing the received data, presuming the metabolic activity of the stomach, judging the activity state and the body position change of the animal, and presuming the gastric momentum condition of the animal by means of the data analysis results.
Further, the monitoring unit includes:
and a temperature monitoring module: the temperature monitoring module estimates the metabolic activity and digestion process of the cattle and sheep by measuring the temperature change in the cattle and sheep, when the cattle and sheep eat food, the stomach starts to work, the metabolic activity is quickened, and the temperature also correspondingly rises, so that the temperature change in the cattle and sheep can be measured to judge whether the digestion systems of the cattle and sheep are in an active state or not, and the gastric momentum of the cattle and sheep can be estimated;
acceleration monitoring module and gesture monitoring module: the acceleration monitoring module and the gesture monitoring module are used in a combined mode, the movement and gesture changes of the cattle and sheep are monitored to infer the movement states and the body position changes, when the cattle and the sheep are in a lying state, the movement amplitude is small, the gesture is stable, and when the cattle and the sheep stand or walk, the movement amplitude is large, the gesture changes frequently, so that the movement states of the cattle and the sheep can be inferred through measuring the movement and the gesture changes, and further the gastric momentum of the cattle and the sheep can be indirectly inferred.
Further, the data processing unit includes:
and a data acquisition module: acquiring data in the animal stomach through a temperature monitoring module, an acceleration monitoring module and a posture monitoring module, and acquiring the latest data in 2 hours;
and a difference value calculation module: processing the acquired data, and calculating the activity difference value in each time period, namely the movement amplitude in the stomach in different time periods, wherein the index reflects the activity level of the animal;
maximum value removing module: for some reasons (e.g. eating or other exercise) that may lead to abnormally high activity over a certain period of time, it is necessary to remove a maximum value in order to calculate the average activity more accurately in order to reduce the impact of such abnormal values on the outcome;
and an average value calculation module: averaging the remaining activity differences to obtain a value of average activity, which may reflect the average activity level of the animal over a period of time;
the maximum value judging module: comparing whether the maximum value in the activity level difference after the maximum value is removed is lower than 80, and if the maximum value is lower than 80, indicating that the activity level of the animal is lower;
the average value judging module: comparing whether the average activity is in the range of 0 to 50, if so, indicating that the animal is in a lying state;
the time point recording module is used for: according to the judgment result, the lying time point and standing time point of the animal are recorded for further analysis and observation.
Further, the formula of the difference calculation module algorithm is as follows:
ΔA＝A[i]-A[i-1]；
wherein ΔA represents the activity difference, A [ i ] represents the gastric motility value at the ith time point, i-1 represents the previous time point, and the activity difference (ΔA) between the two time points can be obtained by subtracting the gastric motility value at the previous time point from the gastric motility value at the current time point for subsequent analysis and judgment.
Further, the maximum value removal module algorithm:
and removing a maximum value from the delta A, sorting the activity difference delta A from small to large and removing the maximum value by using a sorting method and the like, wherein if only one element is in the delta A, the removal operation is not required, and if a plurality of elements are in the delta A, the last element (namely the maximum value) is removed.
Further, the formula of the average value calculation module algorithm is as follows:
Avg_A＝(ΣΔA)/(n-1)；
wherein avg_a represents the average of the activity, ΣΔa represents the sum of all the remaining differences, n represents the number of the remaining differences, i.e. the number of the differences remaining after sorting and removing the maximum value, (n-1) represents the number of the remaining differences minus 1, and is used as a denominator when calculating the average.
Further, the algorithm of the maximum value judging module:
it is checked whether there is a case where the maximum value is lower than 80 in the remaining Δa.
Further, the algorithm of the average value judging module:
judging whether the Avg_A is in the range of 0 to 50, and if so, indicating that the cattle and sheep are in a lying state.
The invention provides another technical scheme that: there is provided a monitoring method for analyzing lying behavior of livestock, comprising the steps of:
s1, a preparation stage: the monitoring capsule is put into the bodies of cattle and sheep in an oral mode, and enters the digestive system of animals after being swallowed and continuously works in the digestive system;
s2, data acquisition: the monitoring capsule is positioned in the stomach of the animal, the temperature monitoring module records the temperature change of the stomach, the acceleration monitoring module and the gesture monitoring module record the movement and gesture change of the animal, and the sensors continuously collect data and store the data;
s3, data transmission stage: the monitoring capsule enables the acquired data to be transmitted to the data acquisition module in real time;
s4, data analysis: the received data are processed and analyzed, the data of the temperature monitoring module are used for presuming the metabolic activity of the stomach, the data of the acceleration monitoring module and the posture monitoring module can be used for judging the activity state and the posture change of the animal, and the data analysis results are used for presuming the gastric momentum condition of the animal;
s5, a result display stage: by analyzing and synthesizing the data, the method can draw conclusions about the stomach momentum of the cattle and sheep, and display the results to veterinarians or breeders so as to accurately monitor the lying time and times of each cattle and sheep, thereby helping the veterinarians and pasture owners to judge the cattle and sheep states and providing reliable data support.
Compared with the prior art, the invention has the beneficial effects that:
according to the monitoring algorithm for analyzing the lying behaviors of livestock, the monitoring capsules are orally thrown into bodies of cattle and sheep to monitor the change of gastric momentum, so that the activity level and lying time of the cattle and sheep are known, the longer lying time possibly represents that the animals are in a relaxed or rest state, the shorter lying time possibly represents that the animals are in a certain uncomfortable state or stress state, potential disease signs or abnormal behaviors are detected by analyzing the range of activity amount differences and average activity amounts, the potential disease signs or abnormal behaviors are detected, early detection and measures are facilitated to prevent and treat diseases, a farmer or a breeder can adjust feeding time, spatial layout and comfort level according to recorded lying time points and standing time points to provide better living conditions and feeding environment, the daily activity mode, periodic behaviors and the behavior pattern of the cattle and sheep are deeply known through the recorded change of the lying time and the activity level, and the gastric momentum analysis can be used for researching the behavior mode of the cattle and sheep, the beneficial information on the health, the behaviors and the feeding management aspect can be facilitated to improve animal husbandry and animal welfare and provide data for the relevant research fields.
Drawings
FIG. 1 is a block diagram of a monitoring system;
FIG. 2 is a block diagram of a data processing unit;
FIG. 3 is a graph of 24-hour activity;
fig. 4 is a flow chart of a method.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
In order to solve the technical problems that equipment such as a camera is required to be installed on a livestock body or in an environment where the equipment is located by using the monitoring equipment, which may cause a certain interference to the comfort and welfare of the livestock, and information is required to be acquired by means of manual observation or playback video recording and the like when the lying behavior of the livestock is monitored by using the monitoring equipment, delay and omission problems may exist, and the following preferable technical scheme is provided as shown in fig. 1-4:
a monitoring algorithm for analyzing the lying behaviour of livestock, comprising:
monitoring unit: measuring the temperature change in the body, judging whether the digestive system of the cattle and sheep is in an active state or not, thereby estimating the gastric momentum of the cattle and sheep, measuring the movement and posture change, estimating the active state of the cattle and sheep, and further indirectly estimating the gastric momentum of the cattle and sheep;
a data processing unit: and processing and analyzing the received data, presuming the metabolic activity of the stomach, judging the activity state and the body position change of the animal, and presuming the gastric momentum condition of the animal by means of the data analysis results.
The monitoring unit includes:
and a temperature monitoring module: the temperature monitoring module estimates the metabolic activity and digestion process of the cattle and sheep by measuring the temperature change in the cattle and sheep, when the cattle and sheep eat food, the stomach starts to work, the metabolic activity is quickened, and the temperature also correspondingly rises, so that the temperature change in the cattle and sheep can be measured to judge whether the digestion systems of the cattle and sheep are in an active state or not, and the gastric momentum of the cattle and sheep can be estimated;
acceleration monitoring module and gesture monitoring module: the acceleration monitoring module and the gesture monitoring module are used in a combined mode, the movement and gesture changes of the cattle and sheep are monitored to infer the movement states and the body position changes, when the cattle and the sheep are in a lying state, the movement amplitude is small, the gesture is stable, and when the cattle and the sheep stand or walk, the movement amplitude is large, the gesture changes frequently, so that the movement states of the cattle and the sheep can be inferred through measuring the movement and the gesture changes, and further the gastric momentum of the cattle and the sheep can be indirectly inferred.
The data processing unit includes:
and a data acquisition module: acquiring data in the animal stomach through a temperature monitoring module, an acceleration monitoring module and a posture monitoring module, and acquiring the latest data in 2 hours;
and a difference value calculation module: processing the acquired data, and calculating the activity difference value in each time period, namely the movement amplitude in the stomach in different time periods, wherein the index reflects the activity level of the animal;
maximum value removing module: for some reasons (e.g. eating or other exercise) that may lead to abnormally high activity over a certain period of time, it is necessary to remove a maximum value in order to calculate the average activity more accurately in order to reduce the impact of such abnormal values on the outcome;
and an average value calculation module: averaging the remaining activity differences to obtain a value of average activity, which may reflect the average activity level of the animal over a period of time;
the maximum value judging module: comparing whether the maximum value in the activity level difference after the maximum value is removed is lower than 80, and if the maximum value is lower than 80, indicating that the activity level of the animal is lower;
the average value judging module: comparing whether the average activity is in the range of 0 to 50, if so, indicating that the animal is in a lying state;
the time point recording module is used for: according to the judgment result, the lying time point and standing time point of the animal are recorded for further analysis and observation.
The formula of the difference calculation module algorithm is as follows:
ΔA＝A[i]-A[i-1]；
wherein ΔA represents the activity difference, A [ i ] represents the gastric motility value at the ith time point, i-1 represents the previous time point, and the activity difference (ΔA) between the two time points can be obtained by subtracting the gastric motility value at the previous time point from the gastric motility value at the current time point for subsequent analysis and judgment.
The maximum value removal module algorithm:
and removing a maximum value from the delta A, sorting the activity difference delta A from small to large and removing the maximum value by using a sorting method and the like, wherein if only one element is in the delta A, the removal operation is not required, and if a plurality of elements are in the delta A, the last element (namely the maximum value) is removed.
The formula of the average value calculation module algorithm is as follows:
Avg_A＝(ΣΔA)/(n-1)；
wherein avg_a represents the average of the activity, ΣΔa represents the sum of all the remaining differences, n represents the number of the remaining differences, i.e. the number of the differences remaining after sorting and removing the maximum value, (n-1) represents the number of the remaining differences minus 1, and is used as a denominator when calculating the average.
Algorithm of the maximum value judging module:
it is checked whether there is a case where the maximum value is lower than 80 in the remaining Δa.
Algorithm of the average value judging module:
judging whether the Avg_A is in the range of 0 to 50, and if so, indicating that the cattle and sheep are in a lying state.
The invention provides another technical scheme that: there is provided a monitoring method for analyzing lying behavior of livestock, comprising the steps of:
step one, a preparation stage: the monitoring capsule is put into the bodies of cattle and sheep in an oral mode, and enters the digestive system of animals after being swallowed and continuously works in the digestive system;
step two, data acquisition phase: the monitoring capsule is positioned in the stomach of the animal, the temperature monitoring module records the temperature change of the stomach, the acceleration monitoring module and the gesture monitoring module record the movement and gesture change of the animal, and the sensors continuously collect data and store the data;
step three, data transmission stage: the monitoring capsule enables the acquired data to be transmitted to the data acquisition module in real time;
step four, data analysis stage: the received data are processed and analyzed, the data of the temperature monitoring module are used for presuming the metabolic activity of the stomach, the data of the acceleration monitoring module and the posture monitoring module can be used for judging the activity state and the posture change of the animal, and the data analysis results are used for presuming the gastric momentum condition of the animal;
step five, a result display stage: by analyzing and synthesizing the data, the method can draw conclusions about the stomach momentum of the cattle and sheep, and display the results to veterinarians or breeders so as to accurately monitor the lying time and times of each cattle and sheep, thereby helping the veterinarians and pasture owners to judge the cattle and sheep states and providing reliable data support.
It is noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
The foregoing is only a preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art, who is within the scope of the present invention, should be covered by the protection scope of the present invention by making equivalents and modifications to the technical solution and the inventive concept thereof.
Claims (9)
1. A monitoring algorithm for analyzing the lying behaviour of livestock, comprising:
monitoring unit: measuring the temperature change in the body, judging whether the digestive system of the cattle and sheep is in an active state or not, thereby estimating the gastric momentum of the cattle and sheep, measuring the movement and posture change, estimating the active state of the cattle and sheep, and further indirectly estimating the gastric momentum of the cattle and sheep;
a data processing unit: and processing and analyzing the received data, presuming the metabolic activity of the stomach, judging the activity state and the body position change of the animal, and presuming the gastric momentum condition of the animal by means of the data analysis results.
2. A monitoring algorithm for analysing the lying behaviour of a domestic animal according to claim 1, wherein: the monitoring unit includes:
and a temperature monitoring module: the temperature monitoring module estimates the metabolic activity and digestion process of the cattle and sheep by measuring the temperature change in the cattle and sheep, when the cattle and sheep eat food, the stomach starts to work, the metabolic activity is quickened, and the temperature also correspondingly rises, so that the temperature change in the cattle and sheep can be measured to judge whether the digestion systems of the cattle and sheep are in an active state or not, and the gastric momentum of the cattle and sheep can be estimated;
acceleration monitoring module and gesture monitoring module: the acceleration monitoring module and the gesture monitoring module are used in a combined mode, the movement and gesture changes of the cattle and sheep are monitored to infer the movement states and the body position changes, when the cattle and the sheep are in a lying state, the movement amplitude is small, the gesture is stable, and when the cattle and the sheep stand or walk, the movement amplitude is large, the gesture changes frequently, so that the movement states of the cattle and the sheep can be inferred through measuring the movement and the gesture changes, and further the gastric momentum of the cattle and the sheep can be indirectly inferred.
3. A monitoring algorithm for analysing the lying behaviour of livestock according to claim 2, characterized in that: the data processing unit includes:
and a data acquisition module: acquiring data in the animal stomach through a temperature monitoring module, an acceleration monitoring module and a posture monitoring module, and acquiring the latest data in 2 hours;
and a difference value calculation module: processing the acquired data, and calculating the activity difference value in each time period, namely the movement amplitude in the stomach in different time periods, wherein the index reflects the activity level of the animal;
maximum value removing module: for some reasons (e.g. eating or other exercise) that may lead to abnormally high activity over a certain period of time, it is necessary to remove a maximum value in order to calculate the average activity more accurately in order to reduce the impact of such abnormal values on the outcome;
and an average value calculation module: averaging the remaining activity differences to obtain a value of average activity, which may reflect the average activity level of the animal over a period of time;
the maximum value judging module: comparing whether the maximum value in the activity level difference after the maximum value is removed is lower than 80, and if the maximum value is lower than 80, indicating that the activity level of the animal is lower;
the average value judging module: comparing whether the average activity is in the range of 0 to 50, if so, indicating that the animal is in a lying state;
the time point recording module is used for: according to the judgment result, the lying time point and standing time point of the animal are recorded for further analysis and observation.
4. A monitoring method for analyzing the lying behaviour of livestock as claimed in claim 3, characterized in that: the formula of the difference calculation module algorithm is as follows:
ΔA＝A[i]-A[i-1]；
wherein ΔA represents the activity difference, A [ i ] represents the gastric motility value at the ith time point, i-1 represents the previous time point, and the activity difference (ΔA) between the two time points can be obtained by subtracting the gastric motility value at the previous time point from the gastric motility value at the current time point for subsequent analysis and judgment.
5. A monitoring algorithm for analysing the lying behaviour of a domestic animal according to claim 4, wherein: the maximum value removal module algorithm:
and removing a maximum value from the delta A, sorting the activity difference delta A from small to large and removing the maximum value by using a sorting method and the like, wherein if only one element is in the delta A, the removal operation is not required, and if a plurality of elements are in the delta A, the last element (namely the maximum value) is removed.
6. A monitoring algorithm for analysing the lying behaviour of a domestic animal according to claim 5, wherein: the formula of the average value calculation module algorithm is as follows:
Avg_A＝(ΣΔA)/(n-1)；
wherein avg_a represents the average of the activity, ΣΔa represents the sum of all the remaining differences, n represents the number of the remaining differences, i.e. the number of the differences remaining after sorting and removing the maximum value, (n-1) represents the number of the remaining differences minus 1, and is used as a denominator when calculating the average.
7. A monitoring algorithm for analysing the lying behaviour of a domestic animal as claimed in claim 6, wherein: algorithm of the maximum value judging module:
it is checked whether there is a case where the maximum value is lower than 80 in the remaining Δa.
8. A monitoring algorithm for analysing the lying behaviour of a domestic animal as claimed in claim 7, wherein: algorithm of the average value judging module:
judging whether the Avg_A is in the range of 0 to 50, and if so, indicating that the cattle and sheep are in a lying state.
9. A monitoring method for analyzing the lying behaviour of livestock according to any of claims 1-8, comprising the steps of:
s1, a preparation stage: the monitoring capsule is put into the bodies of cattle and sheep in an oral mode, and enters the digestive system of animals after being swallowed and continuously works in the digestive system;
s2, data acquisition: the monitoring capsule is positioned in the stomach of the animal, the temperature monitoring module records the temperature change of the stomach, the acceleration monitoring module and the gesture monitoring module record the movement and gesture change of the animal, and the sensors continuously collect data and store the data;
s3, data transmission stage: the monitoring capsule enables the acquired data to be transmitted to the data acquisition module in real time;
s4, data analysis: the received data are processed and analyzed, the data of the temperature monitoring module are used for presuming the metabolic activity of the stomach, the data of the acceleration monitoring module and the posture monitoring module can be used for judging the activity state and the posture change of the animal, and the data analysis results are used for presuming the gastric momentum condition of the animal;
s5, a result display stage: by analyzing and synthesizing the data, the method can draw conclusions about the stomach momentum of the cattle and sheep, and display the results to veterinarians or breeders so as to accurately monitor the lying time and times of each cattle and sheep, thereby helping the veterinarians and pasture owners to judge the cattle and sheep states and providing reliable data support.
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