CN104077550B - The method and system that a kind of health index for realizing animal behavior monitoring is evaluated - Google Patents
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Abstract
The invention discloses the method and system that a kind of health index for realizing animal behavior monitoring is evaluated, its method includes：It is every animal wears RFID label tag, and corresponding RFID collectors is set in animal activity point；Obtain every translational speed weighted value of animal；Obtain every animal robs food ability weighted value；Obtain every motion frequency weighted value of animal；Obtain every residence time weighted value of animal；Motion frequency weighted value and residence time weighted value sum；Aggregative weighted value based on all animals judges every health index of animal.The embodiment of the present invention, the animal behavior analysis method that system is used is simple, practical, is suitable for the collection and analysis of the mass data of large-scale farming, accelerates the response time of system, shortens the time that animal epidemics are realized.
Description
Technical Field
The invention relates to the technical field of information agriculture, in particular to a method and a system for evaluating health indexes by monitoring animal behaviors.
Background
With the development of agriculture, the scale of the breeding industry in China is larger and larger, and the breeding density is higher and higher. However, means for observing the physical condition of the animals to be cultured still remain in a mode in which the culturing personnel periodically performs population visual observation. The traditional mode cannot carry out detailed observation on the condition of an individual animal, and only can evaluate the physical condition of an animal population through visual inspection and the experience of workers. This observation increases the test period over which improved feed or farming practices are conducted.
Taking poultry farming as an example, avian influenza has been a nightmare in poultry farming from the early stage of H1N1 to the recent period of H7N 9. These avian influenza often causes death of a large number of poultry in the same farm due to the inability to make early warning of epidemic diseases at the early stage of the onset of disease in individual poultry, in addition to the strong pathogenicity of avian influenza virus.
Therefore, a method capable of comprehensively evaluating the health condition of animals is needed, and evaluation basis is provided for different systems in the breeding industry, such as animal condition monitoring, disease early warning, feed improvement testing, breeding process information tracing and the like.
The behaviors of animals such as feeding, perching, running and the like are important bases for judging the health and diseases of the animals. In recent years, some developed countries have made some progress in the study of animal behavior. The image processing technology is used by Leroy T and Vranken E to analyze abnormal behaviors appearing in each state in the growth process of the hens and track the growth process of the hens, and the method saves time and reduces labor cost. The Australian Federal science and industry research organization applies a sensor network to establish an intelligent farm, and wears a collar with a Global Positioning System (GPS) and wireless sensor nodes on the neck of a cow to record the relevant environment and the behavior characteristics of the cow. Kwong applies wireless sensor network technology to monitor cattle herds for disease and lameness. Nadimi et al propose to use wireless sensor network nodes to measure the rotation angle and the movement speed of the neck of a cow and use a classification tree to classify the behavior of the cow. The Yi Ding has proposed a digital intelligent system for monitoring the behavioral characteristics of cows by applying a wireless sensor network, which is used for predicting the oestrus, diseases and other conditions of cows.
The monitoring of animal behavior using image processing techniques is limited by image processing algorithms, the accuracy and resolution are not high, and identification of id tag codes of animals and fast moving small animals is particularly limited.
The behavior of animals can be carefully monitored by using a wireless sensor network, but because the cultivation production process has the characteristics of strong destruction, high pollution and the like, the system application and the cultivation process have several problems:
1) the node is easily damaged by the animal consciously and unconsciously;
2) the nodes are easily polluted by the environment;
3) the cost of the node is high;
4) the node is limited to the node volume and is difficult to apply to small animals.
Disclosure of Invention
In view of the problems of the information acquisition end of the wireless sensor network, the system can avoid or reduce the short part of the information acquisition end of the wireless sensor network and develop the advantage of mass data analysis of a background cloud computing platform in the face of the cultivation production characteristics of high pollution, strong destruction and thin profit. A sensor with high reliability is used at the acquisition end, only less basic information is acquired, the gravity center of the system is placed in a background server, such as a cloud computing server, as much behavior characteristic information as possible is mined from less acquired information, and animal behavior results are analyzed by means of the powerful data mining function of the cloud computing server.
The invention provides a method for evaluating a health index for monitoring animal behaviors, which comprises the following steps:
the method comprises the following steps of wearing an RFID tag for each animal, and arranging a corresponding RFID collector at an animal activity point;
acquiring the moving speed of each animal based on an RFID (radio frequency identification) collector and a speed behavior characteristic function, and acquiring a moving speed weighted value of each animal based on normalization processing on the moving speeds of all animals;
acquiring the snatching capability of each animal based on the RFID collector and the snatching capability behavior characteristic function, and acquiring the snatching capability weighted value of each animal based on normalization processing on the snatching capability of all animals;
acquiring the activity frequency of each animal based on the RFID collector and the activity frequency behavior characteristic function, and acquiring the activity frequency weighted value of each animal based on the normalization processing of the activity frequencies of all animals;
acquiring the residence time of each animal based on an RFID (radio frequency identification) collector and a residence time behavior characteristic function, and acquiring a residence time weighted value of each animal based on normalization processing on the residence time of all animals;
calculating a comprehensive weighted value of each animal, wherein the comprehensive weighted value is the sum of the moving speed weighted value, the food snatching ability weighted value, the activity frequency weighted value and the residence time weighted value of each animal;
the health index of each animal was judged based on the combined weight values of all animals.
The step of acquiring the moving speed of each animal based on the RFID collector and the speed behavior characteristic function specifically comprises the following steps:
and obtaining the moving speed of each animal by using the distance between the two nearest RFID collectors and the time for the two nearest RFID collectors to identify the RFID tags.
The normalization processing specifically comprises:
converting the original data into standard normal distribution score values;
and obtaining the comprehensive evaluation value of each animal for the normal distribution score value according to an index comprehensive evaluation formula.
Correspondingly, the embodiment of the invention also provides a system for realizing the health index evaluation of animal behavior monitoring, which comprises the following steps: the system comprises an RFID tag worn by each animal and an RFID collector arranged at an animal activity site;
the moving speed weighted value module is used for acquiring the moving speed of each animal based on the RFID collector and the speed behavior characteristic function, and acquiring the moving speed weighted value of each animal based on normalization processing on the moving speeds of all animals;
the food snatching capability weighted value module is used for acquiring the food snatching capability of each animal based on the RFID collector and the food snatching capability behavior characteristic function, and acquiring the food snatching capability weighted value of each animal based on normalization processing on the food snatching capability of all animals;
the activity frequency weighted value module is used for acquiring the activity frequency of each animal based on the RFID collector and the activity frequency behavior characteristic function, and acquiring the activity frequency weighted value of each animal based on normalization processing on the activity frequencies of all animals;
the stay time weighted value module is used for acquiring the stay time of each animal based on the RFID collector and the stay time behavior characteristic function, and acquiring the stay time weighted value of each animal based on normalization processing of the stay time of all the animals;
the comprehensive weighted value module is used for calculating the comprehensive weighted value of each animal, and the comprehensive weighted value is the sum of the moving speed weighted value, the food snatching capability weighted value, the activity frequency weighted value and the residence time weighted value of each animal;
and the health index evaluation module is used for evaluating the health index of each animal based on the comprehensive weighted value of all the animals.
The moving speed weighting value module obtains the moving speed of each animal by using the distance between the two nearest RFID collectors and the time for the two nearest RFID collectors to identify the RFID tags.
The normalization processing specifically comprises:
converting the original data into standard normal distribution score values;
and obtaining the comprehensive evaluation value of each animal for the normal distribution score value according to an index comprehensive evaluation formula.
In the invention, the RFID collector is used as a behavior collecting terminal of the animal, and the ear tag foot ring and the like are only needed to be worn on the animal, so that the system has absolute advantages in the performances of cost, pollution resistance and the like; compared with the conventional video monitoring method, the method adopted by the invention has the advantages of low recognition rate, high cost and great technical difficulty compared with the video method.
The system simplifies the easily damaged Internet of things acquisition end as much as possible, gives full play to the powerful data mining function of the background server, acquires the simplest two basic data, and generates a plurality of behavior characteristics by using a data mining method, thereby greatly enhancing the reliability of the system and reducing the cost of the system. The animal behavior analysis method adopted by the system is simple and practical, can be more suitable for acquisition and analysis of mass data of large-scale breeding, quickens the response time of the system and shortens the time for discovering animal epidemic situation.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a flow chart of a method of achieving health index assessment for animal behavior monitoring in an embodiment of the invention;
FIG. 2 is a schematic diagram of a system for implementing health index evaluation for animal behavior monitoring in an embodiment of the present invention;
fig. 3 is a schematic view of a specific application scenario for realizing health index evaluation of broiler behavior monitoring in an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Fig. 1 shows a flow chart of a method for implementing health index evaluation for animal behavior monitoring in an embodiment of the invention, comprising the following steps:
s101, wearing an RFID tag for each animal, and arranging a corresponding RFID collector at an animal activity point;
s102, obtaining the moving speed of each animal based on an RFID collector and a speed behavior characteristic function, and obtaining the moving speed weighted value of each animal based on normalization processing of the moving speeds of all animals;
in the embodiment of the invention, the moving speed of each animal is obtained by utilizing the distance between the two closest RFID collectors and the time for the two closest RFID collectors to identify the RFID tags.
S103, acquiring the snatching capability of each animal based on the RFID collector and the snatching capability behavior characteristic function, and acquiring a snatching capability weighted value of each animal based on normalization processing on the snatching capability of all animals;
s104, acquiring the activity frequency of each animal based on the RFID collector and the activity frequency behavior characteristic function, and acquiring the activity frequency weighted value of each animal based on the normalization processing of the activity frequencies of all animals;
s105, obtaining the stay time of each animal based on the RFID collector and the stay time behavior characteristic function, and obtaining the stay time weighted value of each animal based on normalization processing of the stay time of all the animals;
s106, calculating a comprehensive weighted value of each animal, wherein the comprehensive weighted value is the sum of the moving speed weighted value, the food snatching ability weighted value, the activity frequency weighted value and the residence time weighted value of each animal;
and S107, judging the health index of each chicken based on the comprehensive weighted value of all animals.
It should be noted that the normalization process in the embodiment of the present invention specifically includes: converting the original data into standard normal distribution score values; and obtaining the comprehensive evaluation value of each animal for the normal distribution score value according to an index comprehensive evaluation formula.
Correspondingly, fig. 2 also shows a schematic structural diagram of a system for implementing health index evaluation of animal behavior monitoring in the embodiment of the invention, wherein the system comprises: the system comprises an RFID tag worn by each animal and an RFID collector arranged at an animal activity site;
the moving speed weighted value module is used for acquiring the moving speed of each animal based on the RFID collector and the speed behavior characteristic function, and acquiring the moving speed weighted value of each animal based on normalization processing on the moving speeds of all animals;
it should be noted that the moving speed weighting value module obtains the moving speed of each animal by using the distance between the two closest RFID collectors and the time when the two closest RFID collectors recognize the RFID tag.
The food snatching capability weighted value module is used for acquiring the food snatching capability of each animal based on the RFID collector and the food snatching capability behavior characteristic function, and acquiring the food snatching capability weighted value of each animal based on normalization processing on the food snatching capability of all animals;
the activity frequency weighted value module is used for acquiring the activity frequency of each animal based on the RFID collector and the activity frequency behavior characteristic function, and acquiring the activity frequency weighted value of each animal based on normalization processing on the activity frequencies of all animals;
the stay time weighted value module is used for acquiring the stay time of each animal based on the RFID collector and the stay time behavior characteristic function, and acquiring the stay time weighted value of each animal based on normalization processing of the stay time of all the animals;
the comprehensive weighted value module is used for calculating the comprehensive weighted value of each animal, and the comprehensive weighted value is the sum of the moving speed weighted value, the food snatching capability weighted value, the activity frequency weighted value and the residence time weighted value of each animal;
and the health index evaluation module is used for evaluating the health index of each chicken based on the comprehensive weighted value of all animals.
It should be noted that the number of the RFID tags worn by the animals is determined according to the number of the raised animals, each animal is worn with an RFID tag, and the RFID collectors are arranged at the activity sites of the animals, generally at the exits of the chicken coop, the areas where the animals frequently move, and the like. The moving speed weighted value module, the food snatching ability weighted value module, the activity frequency weighted value module, the stay time weighted value module, the comprehensive weighted value module, the health index evaluation module and the like are operated in the server, and can provide data collected by the corresponding RFID system for the server, and the server completes corresponding background processing, thereby realizing accurate monitoring of animals and the like.
It should be noted that the normalization process in the embodiment of the present invention specifically includes: converting the original data into standard normal distribution score values; and obtaining the comprehensive evaluation value of each animal for the normal distribution score value according to an index comprehensive evaluation formula.
Animal behaviors such as domestic fowls and livestock bred in a stocking mode are mainly used as research objects, animal behavior evaluation parameters are monitored by using Internet of things equipment such as RFID and a wireless sensor network, and data are provided for an animal refined breeding and disease early warning system. In order to collect enough evaluation parameters and verify the practicability of the system, the system is deployed in a chicken farm in the high town of the river and is tested on the spot for a period of time. In order to facilitate comparison of results of manual observation and results of system supervision, a small-scale chicken flock is selected as an experimental target in the experiment. The system takes 33 animals which are bred in a free-range mode in a certain fence of a chicken farm as a specific experimental object. According to field visual analysis, the daily activities of animals in the chicken farm have population and certain individual difference. Most animals gather activity at several stationary habitats during the day, except during feeding. More active animals will be flushed around the farm, while less active animals will be moved at the habitat.
The habit of activity of most stocking animals is that they often move about several more stationary habitats in addition to feeding at the feeding point. The RFID tag binding belt is worn by each animal, the RFID collectors are arranged at a plurality of fixed inhabitation points, the collectors continuously collect the id codes of the animals reaching the inhabitation points at the frequency of 3 times/second (meanwhile, the collection time is also recorded), and the collected data are uploaded by the wireless transmission nodes in real time.
It should be noted that the animals in the embodiments of the present invention are breeding type species such as poultry or livestock, for example, breeding type species such as broiler chicken, meat duck, pork pig, and mutton sheep, and certainly not limited to this type. The whole implementation process will be described in detail by taking the broiler chicken as an introduction.
In the field verification test, the feet of 23 broilers for testing are bound with RFID label foot rings, an RFID collector, a weighing sensor and a wireless transmission node are arranged at a feeding point of a farm, so that the id code, the id arrival time and the weight corresponding to the id of each broiler are read, and the sequence of the individual weight of the broilers and the arrival of the broilers at the feeding point during snatching can be analyzed; RFID tag identifiers are arranged at two main inhabitation points of broiler groups in a farm, and the running speed, the activity frequency between the acquisition points, the residence time in the habitat and other behavior characteristics of each broiler can be analyzed according to the displacement time of the id codes of the broilers at the acquisition points of the two RFID acquisition devices and the distance between the two RFID acquisition devices. The device deployment is shown in figure 3.
Four behavior characteristics of the running speed, the food snatching ability, the activity frequency and the residence time of the broiler chickens can be used for instantly detecting the injured or infected chicken, and the four behavior characteristics and the weight of the broiler chickens can be used for identifying the grade of the broiler chickens on line. Weak broilers have low running speed, low food snatching capability, low activity frequency and long residence time in habitats, and four behavioral characteristic data of the broilers are subjected to data mining by an index comprehensive evaluation method, so that a group of sick broilers can be discovered immediately; the chickens with high quality grades run fast, have strong food snatching capability, high activity frequency, short stay time in the habitat and moderate weight, and the grades of the broilers with different qualities can be mined by carrying out cluster analysis on the four behavior characteristics and the weight of the chickens.
The system mainly comprises an RFID label recognizer, a weighing sensor, a wireless sensor network node and intermediate circuits of all parts. The model of the RFID tag identifier is JT900A, and the set scanning period is 300 milliseconds; the type of the weighing sensor is YZC-1B, and the comprehensive error is less than or equal to +/-0.030%; the model of the wireless sensor network node is GAINS3, and the communication frequency is 433 MHz. The RFID tag tape chip model is F43.
In the field test of the present invention, two RFID tag identifiers were installed at two major habitats, and one RFID tag identifier and a weighing sensor were installed at a chicken house-playground passageway, as shown in fig. 1. Each broiler wear an RFID tag tie that encapsulates an F43 chip. The acquisition frequency of the RFID tag identifier of the habitat is 3 times/second, so that the system can record the id code and the occurrence time of each broiler, and the residence time of each broiler at the habitat, the frequency of going to and from different habitats and the running speed (the distance between habitats is known) can be calculated through the characteristic function calculation of software; the sampling frequency of a weighing sensor and an RFID tag recognizer of the feeding point is 3 times/second, the weight of the broilers can be provided, and the sequence of the food snatching arrival of the broilers in the feeding process is recorded.
Animal behaviors include snatching ability, speed of walking, perching time, frequency of activity, and the like. Establishing a behavior characteristic function of the broiler chicken by using the id and the collection time collected by the RFID collector and the distance between the three RFID tag identifiers; data mining is carried out by using animal behavior characteristic data, and epidemic situations can be discovered at the first time.
(1) Construction of behavior characteristic function of running speed
The speed of the animal's speed of the speed may reflect the health and activity of the animal. Animals in good health and relatively active, often walk quickly or run forward during daily activities; whereas animals that are sick or inactive move at a slower rate.
When an animal enters an effective identification area of the RFID tag identifier, the RFID tag identifier acquires the id code of the animal; when the animal leaves the valid identification area of the RFID tag identifier, the animal's id code disappears. The time difference between the time when an id code for an animal disappears from one RFID tag identifier and the time when the id code appears from another RFID tag identifier can be considered as the time required for the animal to pass the adjacent distance between the two RFID tag identifiers. The specific formula is as follows:
where V is the speed at which the animal moves between the two RFID tag identifiers, Sr is the distance between the two RFID tag identifiers, t1 is the time at which the animal leaves the first RFID tag identifier, and t2 is the time at which the animal enters the second RFID tag identifier.
Since an animal does not intentionally move from one RFID tag identifier to another RFID tag identifier, the time difference of the animal moving between the two RFID tag identifiers is not necessarily the time difference of the linear movement, and thus data having a moving time greater than a certain threshold value is regarded as non-linear movement data and is not used for the calculation of the behavior feature. Therefore, data with higher speed is selected as the running speed characteristic parameter of the animal coded by the id.
(2) Construction of behavior characteristic function of animal activity frequency
The frequency of activity of an animal is one of the important indicators of its activity and health status. Animals with higher activity can often run back and forth in the activity field even if the animals have fixed inhabitation points; animals with low activity stay at the same habitat for a long time and do not move frequently. If an animal is injured or ill, its activity is greatly reduced and may even be left in place until it dies. The activity of the animal is greatly increased if predators, strong noise sources, or other factors that can irritate the animal. Therefore, the activity frequency can judge the quality of the animal individuals and can also give an early warning to factors influencing animal breeding through the change of the activity degree of the individuals or the groups.
When an animal enters the effective identification area of the RFID tag identifier, the RFID tag identifier can record the id code of the animal until the animal leaves the effective identification area, and the number of activities for identifying the animal is increased by 1 time. Since the RFID tag identifier cannot realize continuous identification of id codes due to body occlusion of other animals or the animal is in the edge position of the effective identification area, a threshold value needs to be set to eliminate the influence of discontinuous data on the characteristic function. If the time interval between disappearance and appearance of an id code in the same RFID tag identifier is less than a threshold value, the animal to which the id code belongs can be judged to be interfered and not to leave the effective identification area. The activity level of each animal can be calculated by analyzing the activity frequency of each animal on a daily basis. By comparing the activity frequency of the latest day with the past activity frequency, the id number of the animal with the suddenly increased, decreased or even disappeared activity frequency can be found, and farm workers can timely deal with the outbreak situations such as epidemic diseases.
(3) Construction of behavior characteristic function of animal food snatching capability
The desire to eat of an animal is an index reflecting the amount of activity and health condition. In the breeding farms with the feeding areas and the activity areas which are relatively independent, when the feed is put in, animals which are healthy and have large activity can quickly rush to eat after the feed is put in, and strong animals can crowd to a position which is relatively far ahead; animals with poor physical condition or infected diseases will not immediately catch the feeding trough, and will be pushed to the back due to weak body even if they have a desire to eat food.
By deploying an RFID tag identifier on the pathway between the feeding zone and the active zone, the id code and elapsed time of the animal passing through the pathway can be identified and recorded. After the farm worker finishes feeding the feed, the id code of the first entering channel is used as a timing zero point, and the time is divided into 10 equal parts with different lengths according to the number of the id codes passing through the channels in different time periods. The id code detected in the time period closest to the zero point is most active, and the id code detected in the time period farthest from the zero point is least active.
(4) Construction of a behavioral characteristic function of animal residence time
The time that an animal stays within the effective identification area of the RFID tag identifier is also a factor in determining the activity and health of the animal. Animals with higher activity degree have shorter stay time at the inhabitation point; while animals with low activity or poor health have a longer stay at the habitat.
Partial RFID tag identifiers are deployed at several major animal habitats within the live field, so by recording the time each animal's id number enters and leaves the valid identification area of these RFID tag identifiers, the length of time the animal remains in that area can be calculated. The activity of the animals can be known by counting the cumulative residence time of the id number of each animal at each deployment at the animal habitat each day. If the residence time of an animal increases suddenly over the last few days, it is possible that the animal is injured or infected with a disease resulting in a decrease in activity.
4. Data mining of animal behavior data-on-line monitoring of animal epidemic situation behaviors by index comprehensive evaluation method
Mass data acquired by the animal behavior monitoring system are subjected to data mining, so that the health condition and the growth condition of an individual can be analyzed, and animal epidemic can be found at the first time. The invention uses an index comprehensive evaluation method to carry out data mining on the running speed, the residence time in a habitat, the activity frequency and the food snatching capability of the chickens, and can excavate weak or infected individuals in animal groups.
The index comprehensive evaluation method is characterized in that the number of each evaluation index is quantified, dimensionless uniform scores of all the evaluation indexes of each evaluation object are obtained, then index comprehensive evaluation is carried out by adopting an index comprehensive evaluation method, so that the comprehensive evaluation value of each animal can be obtained, and the quality of the evaluated animal is obtained according to the height of the comprehensive evaluation value.
Take the verification test of the present invention as an example. Firstly, the manual detection method is used for detecting that 6 broilers are relatively obvious strong and healthy, 3 broilers with weak and small diseases, wherein 1 broilers are light and have small body weight, and the other two broilers have obvious injury signs. The id codes for 6 strong broilers were: 090A0033, 090A0055, 090A0059, 04160001, 090A0037, 090A 0051; the id codes for the 3 sick chickens are: 070A0061, 090A0047, 090A 0063. Field testing was performed 3 days after deployment of the invention at this farm. A total of 135700 data were collected for case analysis, with some data shown in table 3. The food snatching sequence with the largest value indicates that the user firstly runs to the feeding trough; data with shorter residence time in the habitat indicate that the chickens are more active; the activity frequency represents the average number of times that the broiler chicken enters or exits the habitat one day, and the data with high activity frequency represents that the broiler chicken is more active.
TABLE 1 poultry behavior characteristic values
And (3) normalizing the data according to a formula (2), and converting the original data into a standard normal distribution score value.
Standard normal transformation formula:
wherein,mean of table variables, standard deviation of S table variables. . The data obtained after conversion are shown in table 2:
TABLE 2 normalized poultry behavior characteristic values
Since the snatching sequence, speed and frequency are all the better the larger the value is, and the lingering time is the better the value is. In order to use these four indices for the comprehensive evaluation calculation, it is necessary to keep them in the same direction of change, and therefore, it is necessary to reverse all the characteristic values of the residence time. The converted data are shown in table 3.
TABLE 3 normalized poultry behavior characteristic values
And comprehensively evaluating indexes of the m animals according to the n behavior characteristics of the animals to evaluate the quality of the animals. The system can monitor large-scale cultured animal groups in real time for 24 hours, and find weak groups in time to early warn epidemic situations. The formula of the index comprehensive evaluation is as follows:
wherein ω isjAs the weight coefficient, the following relation is satisfied:
wherein the behavior characteristic variable phiiDenotes the overall evaluation value of an animal with a tag code of i, aijRepresents the jth variable of the animal with tag code i.
According to the animal comprehensive evaluation method, all the collected original data in the verification test are subjected to standardization treatment, and the four behavior characteristic values are comprehensively evaluated by a multi-index comprehensive evaluation method. Since it is a comprehensive index for evaluating animals, ω is1＝ω2＝ω3＝ω41. The results of the evaluation by the integrated weighting are shown in Table 4.
TABLE 4 results of comprehensive evaluation of four behavior characteristic values by index comprehensive evaluation method
After data processing, the data of 23 broilers can be used for data processing of field tests. The results of the systematic monitoring, 6 strong chickens were: 090A0033, 090A0055, 090A0059, 04160001, 090A0037, 090A0051, the 3 sick and injured chickens were: 070A0061, 090A0047, 090A 0063. The experiment is completely consistent with the real result.
In conclusion, the system simplifies the easily damaged Internet of things acquisition end as much as possible, gives full play to the powerful data mining function of the background server, acquires the simplest two basic data, and generates a plurality of behavior characteristics by using the data mining method, thereby greatly enhancing the reliability of the system and reducing the cost of the system. The animal behavior analysis method adopted by the system is simple and practical, can be more suitable for acquisition and analysis of mass data of large-scale breeding, quickens the response time of the system and shortens the time for discovering animal epidemic situation.
Those skilled in the art will appreciate that all or part of the steps in the methods of the above embodiments may be implemented by associated hardware instructed by a program, which may be stored in a computer-readable storage medium, and the storage medium may include: a Read Only Memory (ROM), a Random Access Memory (RAM), a magnetic or optical disk, or the like.
The method and the system for evaluating the health index for monitoring animal behaviors provided by the embodiment of the invention are described in detail, the principle and the implementation mode of the invention are explained by applying specific examples, and the description of the embodiment is only used for helping to understand the method and the core idea of the invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present invention.
Claims (6)
1. A method for realizing health index evaluation of animal behavior monitoring is characterized by comprising the following steps:
the method comprises the following steps of wearing an RFID tag for each animal, and arranging a corresponding RFID collector at an animal activity point;
acquiring the moving speed of each animal based on an RFID (radio frequency identification) collector and a speed behavior characteristic function, and acquiring a moving speed weighted value of each animal based on normalization processing on the moving speeds of all animals;
acquiring the snatching capability of each animal based on the RFID collector and the snatching capability behavior characteristic function, and acquiring the snatching capability weighted value of each animal based on normalization processing on the snatching capability of all animals;
acquiring the activity frequency of each animal based on the RFID collector and the activity frequency behavior characteristic function, and acquiring the activity frequency weighted value of each animal based on the normalization processing of the activity frequencies of all animals;
acquiring the residence time of each animal based on an RFID (radio frequency identification) collector and a residence time behavior characteristic function, and acquiring a residence time weighted value of each animal based on normalization processing on the residence time of all animals;
calculating a comprehensive weighted value of each animal, wherein the comprehensive weighted value is the sum of the moving speed weighted value, the food snatching ability weighted value, the activity frequency weighted value and the residence time weighted value of each animal;
the health index of each animal was judged based on the combined weight values of all animals, wherein:
the speed behavior characteristic function is: the animal does not purposefully move from one RFID tag identifier to the other RFID tag identifier, the time difference of the animal moving between the two RFID tag identifiers is not necessarily the time difference of linear movement, therefore, the data with the moving time larger than a certain threshold value is regarded as non-linear movement data and is not used for calculating the behavior characteristic, and the data with higher speed is selected as the running speed characteristic parameter of the animal coded by the id;
the activity frequency behavior characteristic function is: in the same RFID tag identifier, if the interval time between disappearance and appearance of an id code is less than a threshold value, the animal to which the id code belongs can be judged to be only interfered and not leave an effective identification area, and the activity frequency of each animal in each day is analyzed by taking the day as a unit, so that the activity degree of each animal can be counted;
the behavior characteristic function of the snatching ability is as follows: according to the number of id codes passing through channels in different time periods, dividing time into 10 equal parts with different lengths, wherein the id code detected in the time period closest to the zero point is most active, and the id code detected in the time period farthest from the zero point is least active;
the residence time behavior characteristic function is: recording the time when the id number of each animal enters and leaves the effective identification area of the RFID tag identifiers, calculating the length of time that the animals stay in the area, and counting the cumulative stay time of the id number of each animal at each deployment in the animal habitat each day to know the activity degree of the animals.
2. The method for evaluating the health index of animal behavior monitoring as claimed in claim 1, wherein the step of obtaining the moving speed of each animal based on the RFID collector and the speed behavior feature function specifically comprises:
and obtaining the moving speed of each animal by using the distance between the two nearest RFID collectors and the time for the two nearest RFID collectors to identify the RFID tags.
3. The method for achieving a health index assessment for animal behavior monitoring as claimed in claim 1, wherein said normalization process is specifically:
converting the original data into standard normal distribution score values;
and obtaining a comprehensive evaluation value of each animal for the normal distribution score value according to an index comprehensive evaluation formula, wherein the index comprehensive evaluation formula is as follows:
wherein ω isjAs the weight coefficient, the following relation is satisfied:
wherein n is the number of animal behavior characteristic indexes, m is the number of animals to be scored, and a behavior characteristic variable phiiDenotes the overall evaluation value of an animal with a tag code of i, aijRepresents the jth variable of the animal with tag code i.
4. A system for implementing health index assessment for animal behavior monitoring, comprising: the system comprises an RFID tag worn by each animal and an RFID collector arranged at an animal activity site;
the moving speed weighted value module is used for acquiring the moving speed of each animal based on the RFID collector and the speed behavior characteristic function, and acquiring the moving speed weighted value of each animal based on normalization processing on the moving speeds of all animals;
the food snatching capability weighted value module is used for acquiring the food snatching capability of each animal based on the RFID collector and the food snatching capability behavior characteristic function, and acquiring the food snatching capability weighted value of each animal based on normalization processing on the food snatching capability of all animals;
the activity frequency weighted value module is used for acquiring the activity frequency of each animal based on the RFID collector and the activity frequency behavior characteristic function, and acquiring the activity frequency weighted value of each animal based on normalization processing on the activity frequencies of all animals;
the stay time weighted value module is used for acquiring the stay time of each animal based on the RFID collector and the stay time behavior characteristic function, and acquiring the stay time weighted value of each animal based on normalization processing of the stay time of all the animals;
the comprehensive weighted value module is used for calculating the comprehensive weighted value of each animal, and the comprehensive weighted value is the sum of the moving speed weighted value, the food snatching capability weighted value, the activity frequency weighted value and the residence time weighted value of each animal;
a health index evaluation module for evaluating the health index of each animal based on the combined weight values of all animals, wherein:
the speed behavior characteristic function is: the animal does not purposefully move from one RFID tag identifier to the other RFID tag identifier, the time difference of the animal moving between the two RFID tag identifiers is not necessarily the time difference of linear movement, therefore, the data with the moving time larger than a certain threshold value is regarded as non-linear movement data and is not used for calculating the behavior characteristic, and the data with higher speed is selected as the running speed characteristic parameter of the animal coded by the id;
the activity frequency behavior characteristic function is: in the same RFID tag identifier, if the interval time between disappearance and appearance of an id code is less than a threshold value, the animal to which the id code belongs can be judged to be only interfered and not leave an effective identification area, and the activity frequency of each animal in each day is analyzed by taking the day as a unit, so that the activity degree of each animal can be counted;
the behavior characteristic function of the snatching ability is as follows: according to the number of id codes passing through channels in different time periods, dividing time into 10 equal parts with different lengths, wherein the id code detected in the time period closest to the zero point is most active, and the id code detected in the time period farthest from the zero point is least active;
the residence time behavior characteristic function is: recording the time when the id number of each animal enters and leaves the effective identification area of the RFID tag identifiers, calculating the length of time that the animals stay in the area, and counting the cumulative stay time of the id number of each animal at each deployment in the animal habitat each day to know the activity degree of the animals.
5. The system for implementing health index evaluation for animal behavior monitoring as claimed in claim 4, wherein the moving speed weight value module obtains the moving speed of each animal by using the distance between the two nearest RFID collectors and the time when the two nearest RFID collectors recognize the RFID tag.
6. The system for performing health index assessment for animal behavior monitoring as claimed in claim 4, wherein said normalization process is specifically:
converting the original data into standard normal distribution score values;
and obtaining a comprehensive evaluation value of each animal for the normal distribution score value according to an index comprehensive evaluation formula, wherein the index comprehensive evaluation formula is as follows:
wherein ω isjAs the weight coefficient, the following relation is satisfied:
wherein n is the number of animal behavior characteristic indexes, m is the number of animals to be scored, and a behavior characteristic variable phiiDenotes the overall evaluation value of an animal with a tag code of i, aijRepresents the jth variable of the animal with tag code i.
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| CN106447117B (en) * | 2016-10-10 | 2018-05-01 | 重庆科技学院 | Pet feeding method and system based on the daily data analysis of pet |
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| CN107480892A (en) * | 2017-08-17 | 2017-12-15 | 广州市华南畜牧设备有限公司 | Comprehensive livestock-raising data rank method and device |
| CN109767231A (en) * | 2017-11-01 | 2019-05-17 | 杭州沃朴物联科技有限公司 | A kind of system for verifying activity data in chicken developmental process |
| CN109757403B (en) * | 2019-01-31 | 2021-10-15 | 福建省农业科学院科技干部培训中心 | Method for evaluating poultry quality based on perching position and sleep quality |
| CN109892254B (en) * | 2019-01-31 | 2021-12-14 | 福建省农业科学院科技干部培训中心 | Method for evaluating poultry quality based on perching position |
| CN109757404B (en) * | 2019-01-31 | 2021-10-15 | 福建省农业科学院科技干部培训中心 | Method for evaluating poultry quality based on perching position and movement time |
| CN110288059A (en) * | 2019-06-24 | 2019-09-27 | 哈尔滨理工大学 | A kind of management method in wisdom pasture |
| CN110646568A (en) * | 2019-10-12 | 2020-01-03 | 中国农业科学院麻类研究所 | Feed palatability screening method based on animal group behaviors |
| CN111275911B (en) * | 2020-01-16 | 2021-02-26 | 珠海格力电器股份有限公司 | Danger prompting method, equipment and computer readable storage medium |
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