CN116763300A - Ruminant animal activity state judging system and method - Google Patents
Ruminant animal activity state judging system and method Download PDFInfo
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- A61B5/11—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb
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Abstract
A ruminant animal activity state determination method, comprising the steps of: collecting the activity state of the ruminant by using an acceleration sensor, and continuously generating corresponding activity data; receiving the activity data and recording the time of receiving the activity data; acquiring corresponding sinusoidal activity curve data according to the received activity data and the recorded time for receiving the activity data; finding peak data from sinusoidal activity curve data; dividing sinusoidal activity curve data by taking adjacent peak data as a reference to obtain corresponding multiple adjacent peak sinusoidal activity curve data, and calculating a period value corresponding to each adjacent peak sinusoidal activity curve data according to each adjacent peak sinusoidal activity curve data; and judging the ruminant activity state according to the period value, the peak value, the pre-stored reference activity type period value and the reference activity type peak value corresponding to the adjacent peak sinusoidal activity curve data. The invention also provides a ruminant animal activity state judging system.
Description
Technical Field
The invention relates to the technical field of ruminant activity monitoring, in particular to a ruminant activity state judging system and method.
Background
The economic benefit of dairy cow raising enterprises or farmers mainly depends on the milk yield, which mainly depends on the milk cow's annual lactation period, and the conception rate and calving interval of the dairy cows are decisive factors of milk yield.
In the past, the cow house is regularly patrolled by a veterinarian to check cow behaviors, such as feeding, resting, climbing and the like, so as to initially judge whether the cow is in oestrus. However, due to the fact that the estrus time of each dairy cow is quite different, the time interval and the coverage observed by naked eyes exist, the estrus uncovering rate of the dairy cows is basically lower than 70%, and along with the rapid development of embedded hardware and sensor technology, at home and abroad, dairy farms gradually start to adopt electronic devices (acceleration sensors) to assist veterinarians in judging whether the dairy cows are estrus.
For example, patent number 202010041742.4 and the invention creation name are the technical scheme recorded in the "a milk cow individual behavior monitoring device and method based on vibration signals": the monitoring device is fixed on one side of the neck of the dairy cow through a hanging rope and a balancing weight, and a proper balancing weight is selected according to different individual dairy cows, so that the position of the monitoring device is kept unchanged after the monitoring device is fixed; after the monitoring device is fixed, the piezoelectric sensor collects vibration signals generated by feeding, chewing, swallowing, rumination, drinking, breathing and coughing of the dairy cows, the geomagnetic sensor collects the standing and lying state of individual behaviors of the dairy cows, and the acceleration sensor detects the acceleration of the standing and lying behaviors of the dairy cows; the processor receives the signals detected by the sensor and sends the signals to the remote monitoring computer through the wireless transmission equipment, so that the vibration, the activity state and the frequency information generated in the individual behaviors of the dairy cows are monitored.
Among the above-mentioned prior art, utilize three different sensors to gather the different actions of milk cow, three different sensors all can consume the electric energy, unsuitable low-power consumption product design, use three different sensors also can increase milk cow detection device's manufacturing cost simultaneously, lead to milk cow raising enterprise or peasant to raise the cost increase.
Disclosure of Invention
In view of the foregoing, there is a need for a ruminant activity status determination system that meets the needs of low power consumption and low production costs.
It is also necessary to provide a method for determining the activity state of ruminants.
A ruminant activity state judging system comprises an acceleration sensor, an activity data arrangement module, a sinusoidal activity curve data generation module, a wave crest data search module, an adjacent wave crest sinusoidal activity curve data generation module, an adjacent wave crest sinusoidal activity curve period value calculation module and a ruminant activity state judging module;
the acceleration sensor is used for collecting the activity state of the ruminant and continuously generating corresponding activity data;
the activity data arrangement module is used for receiving the activity data and recording the time for receiving the activity data;
the sinusoidal activity curve data generation module is used for obtaining corresponding sinusoidal activity curve data according to the received activity data and the recorded time for receiving the activity data;
the peak data searching module is used for searching peak data from sinusoidal activity curve data;
the adjacent wave crest sinusoidal activity curve data generation module is used for dividing sinusoidal activity curve data by taking the adjacent wave crest data as a reference to obtain corresponding multiple adjacent wave crest sinusoidal activity curve data;
the adjacent peak sinusoidal activity curve period value calculation module is used for calculating a period value corresponding to the adjacent peak sinusoidal activity curve data according to each adjacent peak sinusoidal activity curve data;
the ruminant activity state judging module is used for judging the ruminant activity state according to the period value corresponding to the adjacent peak sinusoidal activity curve data, the peak value corresponding to the adjacent peak sinusoidal activity curve data, the pre-stored reference activity type period value and the reference activity type peak value.
A ruminant animal activity state determination method, comprising the steps of:
collecting the activity state of the ruminant by using an acceleration sensor, and continuously generating corresponding activity data;
receiving the activity data and recording the time of receiving the activity data;
acquiring corresponding sinusoidal activity curve data according to the received activity data and the recorded time for receiving the activity data;
finding peak data from sinusoidal activity curve data;
dividing the sinusoidal activity curve data by taking the adjacent wave crest data as a reference to obtain a plurality of corresponding adjacent wave crest sinusoidal activity curve data,
calculating a period value corresponding to the adjacent peak sinusoidal activity curve data according to each adjacent peak sinusoidal activity curve data;
judging the ruminant activity state according to the period value corresponding to the adjacent peak sinusoidal activity curve data, the peak value corresponding to the adjacent peak sinusoidal activity curve data, the pre-stored reference activity type period value and the reference activity type peak value.
In the ruminant animal activity state judging system and method, an acceleration sensor is utilized to collect the activity state of the ruminant animal and continuously generate corresponding activity data; receiving the activity data and recording the time of receiving the activity data; acquiring corresponding sinusoidal activity curve data according to the received activity data and the recorded time for receiving the activity data; finding peak data from sinusoidal activity curve data; dividing sinusoidal activity curve data by taking adjacent peak data as a reference to obtain corresponding multiple adjacent peak sinusoidal activity curve data, and calculating a period value corresponding to each adjacent peak sinusoidal activity curve data according to each adjacent peak sinusoidal activity curve data; judging the ruminant activity state according to the period value corresponding to the adjacent peak sinusoidal activity curve data, the peak value corresponding to the adjacent peak sinusoidal activity curve data, the pre-stored reference activity type period value and the reference activity type peak value, thereby meeting the requirements of low power consumption and low production cost.
Drawings
FIG. 1 is a functional block diagram of a ruminant activity status determination system according to a preferred embodiment.
FIG. 2 is a flow chart of a ruminant activity status determination method according to a preferred embodiment.
In the figure: the ruminant activity state judging system 10, the acceleration sensor 20, the activity data sorting module 30, the sinusoidal activity curve data generating module 40, the peak data searching module 50, the adjacent peak sinusoidal activity curve data generating module 60, the adjacent peak sinusoidal activity curve period value calculating module 70, the ruminant activity state judging module 80, the ruminant final activity state determining module 90, the ruminant low head judging module 100 and the ruminant activity state judging method steps S300-S311.
Detailed Description
According to the ruminant activity state judging system provided by the invention, the acceleration sensor arranged in the neck ring senses the movement state of the ruminant, corresponding activity data is generated, the activity data is filtered to obtain sinusoidal activity curve data, and the ruminant activity state is judged after the obtained sinusoidal activity curve data and a preset reference value are compared.
Referring to fig. 1, the ruminant activity status determination system 10 includes an acceleration sensor 20, an activity data arrangement module 30, a sinusoidal activity curve data generation module 40, a peak data search module 50, an adjacent peak sinusoidal activity curve data generation module 60, an adjacent peak sinusoidal activity curve period value calculation module 70, and a ruminant activity status determination module 80;
the acceleration sensor 20 is used for collecting the activity state of the ruminant and continuously generating corresponding activity data, wherein the activity data is acceleration data generated by the acceleration sensor; the activity data sorting module 30 is configured to receive the activity data and record a time for receiving the activity data, for example, the activity data generated by the acceleration sensor 20 is filtered and decontaminated by a hardware filtering circuit and then is transmitted to the activity data sorting module 30; the sinusoidal activity curve data generating module 40 is configured to obtain corresponding sinusoidal activity curve data according to the received activity data and the recorded time of receiving the activity data, for example, the sinusoidal activity curve data generating module 40 performs software filtering and impurity removal on the received activity data to obtain sinusoidal activity curve data; the peak data searching module 50 is used for searching peak data from sinusoidal activity curve data; the adjacent peak sinusoidal activity curve data generating module 60 is configured to divide sinusoidal activity curve data with the adjacent peak data as a reference, and obtain a corresponding plurality of adjacent peak sinusoidal activity curve data; the adjacent peak sinusoidal activity curve period value calculation module 70 is configured to calculate a period value corresponding to each adjacent peak sinusoidal activity curve data according to the adjacent peak sinusoidal activity curve data; the ruminant activity state judging module 80 is configured to judge the ruminant activity state according to the period value corresponding to the adjacent peak sinusoidal activity curve data, the peak value corresponding to the adjacent peak sinusoidal activity curve data, the pre-stored reference activity type period value and the reference activity type peak value.
Wherein the baseline activity type cycle value comprises a ruminant feeding baseline cycle value, a ruminant baseline cycle value, a ruminant lying baseline cycle value, and a ruminant walking baseline cycle value; the reference activity type peaks include ruminant feeding reference peaks, ruminant reference peaks, ruminant lying reference peaks, and ruminant walking reference peaks; the ruminant activity state judging module 80 is configured to judge that the period value corresponding to the sinusoidal activity curve data with the adjacent peak corresponds to a ruminant feeding reference period value, and that the peak value corresponding to the sinusoidal activity curve data with the adjacent peak corresponds to a ruminant feeding reference peak value, so as to generate ruminant feeding state information; the ruminant activity state judging module 80 is further configured to judge that the period value corresponding to the adjacent peak sinusoidal activity curve data corresponds to a ruminant reference period value, and that the peak value corresponding to the adjacent peak sinusoidal activity curve data corresponds to a ruminant reference peak value, and generate ruminant state information; the ruminant activity state judging module 80 is further configured to judge that a period value corresponding to the adjacent peak sinusoidal activity curve data corresponds to a ruminant lying reference period value, and a peak value corresponding to the adjacent peak sinusoidal activity curve data corresponds to a ruminant lying reference peak value, so as to generate ruminant lying state information; the ruminant activity state judging module 80 is further configured to judge that the period value corresponding to the sinusoidal activity curve data with the adjacent peak corresponds to the ruminant walking reference period value, and that the peak value corresponding to the sinusoidal activity curve data with the adjacent peak corresponds to the ruminant walking reference peak value, so as to generate ruminant walking state information.
Further, the ruminant activity state determination system 10 further comprises a ruminant final activity state determination module 90, the ruminant final activity state determination module 90 being configured to divide each adjacent peak sinusoidal activity curve data within a predetermined ruminant activity state duration into a set according to the predetermined ruminant activity state duration, the number of ruminant feeding states, the number of ruminant feeding states, the number of ruminant lying states, the number of ruminant walking states within the group are recorded, and the final ruminant activity state within the predetermined ruminant activity state duration is determined from the recorded number of ruminant feeding states, the number of ruminant feeding states, the number of ruminant lying states, the number of ruminant walking states within the group. For example, the maximum number of ruminant fed states within the predetermined ruminant activity state duration is considered to be fed by the ruminant final activity state within the predetermined ruminant activity state duration. In other embodiments, the ruminant final activity state determination module 90 divides each adjacent peak sinusoidal activity curve data within a predetermined ruminant activity state duration into a group according to the predetermined ruminant activity state duration, records the number of times the ruminant is eating, ruminant is ruminant, the number of times the ruminant is lying down, the number of times the ruminant is walking, and sequentially records the order in which the ruminant is eating, ruminant, lying down, walking, and when the most frequent activity state is determined, accumulates the number of times other activity states between the most frequent activity states to the most frequent activity state. For example, ruminant feeding status is denoted by 0, ruminant status is denoted by 1, ruminant lying status is denoted by 2, ruminant walking status is denoted by 3, and the ruminant movement status within this group is in turn: 30003300001100000022000011 the number of feeding states of the ruminant is judged to be the maximum (17), considering that one activity of the ruminant should be intermittent and continuous, such as eating grass activity, the ruminant is low-head to gnaw grass, then heads up to chew, then advances by two steps, and then low-head to gnaw grass, instead of low-head to gnaw grass for up to half an hour; then 33 between 000330000 is changed to 00, 11 between 000011000000 is changed to 0, and 22 between 000000220000 is changed to 00, then the final number of ruminant feeding states is 23, and the group is finally noted as ruminant feeding states, and the predetermined ruminant activity state duration is ruminant feeding time.
Further, the ruminant low head judging module 100 is further included, the ruminant low head judging module 100 judges whether the ruminant is low head according to the adjacent peak sinusoidal activity curve data, when the ruminant is judged to be in a low head state, a first starting signal is output to the ruminant activity state judging module 80, the ruminant activity state judging module 80 responds to the first starting signal, judges whether a period value corresponding to the adjacent peak sinusoidal activity curve data corresponds to a ruminant feeding reference period value, whether a peak value corresponding to the adjacent peak sinusoidal activity curve data corresponds to a ruminant feeding reference peak value or not, and generates ruminant feeding state information when the ruminant feeding state information is judged to correspond.
When the ruminant low head judging module 100 judges that the ruminant is not in the low head state, a second starting signal is output to the ruminant activity state judging module 80: the ruminant activity state judging module 80 is used for responding to the second starting signal, judging whether the period value corresponding to the adjacent peak sinusoidal activity curve data corresponds to the ruminant reference period value, and if so, generating ruminant state information; the ruminant activity state judging module 80 responds to the second starting signal to judge whether the period value corresponding to the adjacent peak sinusoidal activity curve data corresponds to the ruminant lying reference period value, and whether the peak value corresponding to the adjacent peak sinusoidal activity curve data corresponds to the ruminant lying reference peak value or not, and generates ruminant lying state information when the period value corresponding to the adjacent peak sinusoidal activity curve data corresponds to the ruminant lying reference peak value is judged; the ruminant activity state determination module 80 determines whether a period value corresponding to the adjacent peak sinusoidal activity curve data corresponds to a ruminant walking reference period value, a peak value corresponding to the adjacent peak sinusoidal activity curve data corresponds to a ruminant walking reference peak value, and generates ruminant walking state information when the period value corresponding to the adjacent peak sinusoidal activity curve data corresponds to the ruminant walking reference peak value in response to the second start signal.
The activity data sorting module 30, the sinusoidal activity curve data generating module 40, the peak data searching module 50, the adjacent peak sinusoidal activity curve data generating module 60, the adjacent peak sinusoidal activity curve period value calculating module 70, the ruminant activity state judging module 80, the ruminant final activity state determining module 90 and the ruminant low head judging module 100 may be a functional module generated by a single chip microcomputer or a microcomputer running a set of computer application programs, wherein the computer application programs are used for completing the ruminant activity state judging function.
The computer programs are divided into two groups of programs, for example, a first group of programs are run in a singlechip arranged in a neck ring on the neck of a ruminant, and the functions of the activity data arrangement module 30 and the sinusoidal activity curve data generation module 40 are completed; the second set of programs is run in the microcomputer for managing the cloud platform to complete the functions of the peak data searching module 50, the adjacent peak sinusoidal activity curve data generating module 60, the adjacent peak sinusoidal activity curve period value calculating module 70, the ruminant activity state judging module 80, the ruminant final activity state determining module 90 and the ruminant low head judging module 100, and correspondingly, the neck ring and the microcomputer for managing the cloud platform can be communicated in a wireless or wired mode to realize data transmission.
Further, the present invention also provides a ruminant activity state determining method, referring to fig. 2, comprising the following steps:
step S300, collecting the activity state of the ruminant by using an acceleration sensor, and continuously generating corresponding activity data, wherein the activity data is acceleration data generated by the acceleration sensor;
step S301, receiving the activity data and recording the time of receiving the activity data;
step S303, obtaining corresponding sinusoidal activity curve data according to the received activity data and the recorded time for receiving the activity data;
step S305, finding out peak data from sinusoidal activity curve data;
step S307, dividing the sinusoidal activity curve data by taking the adjacent wave crest data as a reference to obtain a plurality of corresponding adjacent wave crest sinusoidal activity curve data;
step S309, calculating a period value corresponding to the adjacent peak sinusoidal activity curve data according to each adjacent peak sinusoidal activity curve data;
step S311, judging the ruminant activity state according to the period value corresponding to the adjacent peak sinusoidal activity curve data, the peak value corresponding to the adjacent peak sinusoidal activity curve data, the pre-stored reference activity type period value and the reference activity type peak value. Wherein the baseline activity type cycle value comprises a ruminant feeding baseline cycle value, a ruminant baseline cycle value, a ruminant lying baseline cycle value, and a ruminant walking baseline cycle value; the reference activity type peaks include ruminant feeding reference peaks, ruminant reference peaks, ruminant lying reference peaks, and ruminant walking reference peaks; judging that the period value corresponding to the adjacent peak sinusoidal activity curve data corresponds to a ruminant feeding reference period value, and the peak value corresponding to the adjacent peak sinusoidal activity curve data corresponds to a ruminant feeding reference peak value, and determining that the ruminant feeding state is realized; judging that the period value corresponding to the sinusoidal activity curve data of the adjacent wave peaks corresponds to the ruminant reference period value, and the peak value corresponding to the sinusoidal activity curve data of the adjacent wave peaks corresponds to the ruminant reference peak value, and determining the ruminant state; judging that the period value corresponding to the adjacent peak sinusoidal activity curve data corresponds to a ruminant lying reference period value, and the peak value corresponding to the adjacent peak sinusoidal activity curve data corresponds to a ruminant lying reference peak value, and determining that the ruminant lying state is achieved; and judging that the period value corresponding to the sinusoidal activity curve data of the adjacent wave peaks corresponds to the ruminant walking reference period value, and the peak value corresponding to the sinusoidal activity curve data of the adjacent wave peaks corresponds to the ruminant walking reference peak value, and determining the ruminant walking state.
In the present embodiment, in order to improve the judgment efficiency, step S311 is completed by the following steps: judging whether the ruminant is in a low head state according to the adjacent peak sinusoidal activity curve data, judging whether the period value corresponding to the adjacent peak sinusoidal activity curve data corresponds to a ruminant feeding reference period value, judging whether the peak value corresponding to the adjacent peak sinusoidal activity curve data corresponds to a ruminant feeding reference peak value, and determining that the ruminant is in a ruminant feeding state when the period value corresponding to the adjacent peak sinusoidal activity curve data corresponds to the ruminant feeding reference peak value; judging whether the ruminant is in a low head state according to the sinusoidal activity curve data of the adjacent wave peaks, and when the ruminant is not in the low head state: judging whether the period value corresponding to the sinusoidal activity curve data of the adjacent wave peak corresponds to the ruminant reference period value, and whether the peak value corresponding to the sinusoidal activity curve data of the adjacent wave peak corresponds to the ruminant reference peak value, if so, determining that the ruminant is in a ruminant state; judging whether the period value corresponding to the adjacent peak sinusoidal activity curve data corresponds to the ruminant lying reference period value, and whether the peak value corresponding to the adjacent peak sinusoidal activity curve data corresponds to the ruminant lying reference peak value or not, and if so, determining that the ruminant lying state is achieved; judging whether the period value corresponding to the sinusoidal activity curve data of the adjacent wave crest corresponds to the ruminant walking reference period value, and whether the peak value corresponding to the sinusoidal activity curve data of the adjacent wave crest corresponds to the ruminant walking reference peak value, if so, determining that the ruminant walking state is realized.
Further, the ruminant animal activity state judging method further comprises the following steps:
step S313, dividing each adjacent peak sinusoidal activity curve data within a predetermined ruminant activity state duration into a set according to the predetermined ruminant activity state duration;
step S315, recording the number of ruminant feeding states, ruminant feeding states, ruminant lying states, and ruminant walking states in the group;
step S317, determining a final ruminant activity state for the predetermined ruminant activity state duration based on the recorded number of ruminant feeding states, number of ruminant feeding states, number of ruminant lying states, number of ruminant walking states within the group. For example, in the present embodiment, step S317 is specifically: recording the number of ruminant feeding states, ruminant feeding states, ruminant lying states, and ruminant walking states in the group; sequentially recording the order of feeding state, ruminant state, lying state and walking state of ruminant, and accumulating the times of other activity states between the most activity states to the most activity state when judging the most activity state
In the ruminant activity state judging system 10 and the ruminant activity state judging method, an acceleration sensor is utilized to collect the activity state of the ruminant and continuously generate corresponding activity data; receiving the activity data and recording the time of receiving the activity data; acquiring corresponding sinusoidal activity curve data according to the received activity data and the recorded time for receiving the activity data; finding peak data from sinusoidal activity curve data; dividing sinusoidal activity curve data by taking adjacent peak data as a reference to obtain corresponding multiple adjacent peak sinusoidal activity curve data, and calculating a period value corresponding to each adjacent peak sinusoidal activity curve data according to each adjacent peak sinusoidal activity curve data; judging the ruminant activity state according to the period value corresponding to the adjacent peak sinusoidal activity curve data, the peak value corresponding to the adjacent peak sinusoidal activity curve data, the pre-stored reference activity type period value and the reference activity type peak value, thereby meeting the requirements of low power consumption and low production cost.
Claims (10)
1. A ruminant activity state judgment system, characterized in that: the system comprises an acceleration sensor, an activity data arrangement module, a sinusoidal activity curve data generation module, a wave crest data searching module, an adjacent wave crest sinusoidal activity curve data generation module, an adjacent wave crest sinusoidal activity curve period value calculation module and a ruminant activity state judgment module;
the acceleration sensor is used for collecting the activity state of the ruminant and continuously generating corresponding activity data;
the activity data arrangement module is used for receiving the activity data and recording the time for receiving the activity data;
the sinusoidal activity curve data generation module is used for obtaining corresponding sinusoidal activity curve data according to the received activity data and the recorded time for receiving the activity data;
the peak data searching module is used for searching peak data from sinusoidal activity curve data;
the adjacent wave crest sinusoidal activity curve data generation module is used for dividing sinusoidal activity curve data by taking the adjacent wave crest data as a reference to obtain corresponding multiple adjacent wave crest sinusoidal activity curve data;
the adjacent peak sinusoidal activity curve period value calculation module is used for calculating a period value corresponding to the adjacent peak sinusoidal activity curve data according to each adjacent peak sinusoidal activity curve data;
the ruminant activity state judging module is used for judging the ruminant activity state according to the period value corresponding to the adjacent peak sinusoidal activity curve data, the peak value corresponding to the adjacent peak sinusoidal activity curve data, the pre-stored reference activity type period value and the reference activity type peak value.
2. The ruminant activity status determination system of claim 1, wherein: the reference activity type cycle values include ruminant feeding reference cycle values, ruminant lying reference cycle values, and ruminant walking reference cycle values; the reference activity type peaks include ruminant feeding reference peaks, ruminant reference peaks, ruminant lying reference peaks, and ruminant walking reference peaks;
the ruminant activity state judging module is used for judging that the period value corresponding to the adjacent peak sinusoidal activity curve data corresponds to the ruminant feeding reference period value, and the peak value corresponding to the adjacent peak sinusoidal activity curve data corresponds to the ruminant feeding reference peak value, so as to generate ruminant feeding state information;
the ruminant activity state judging module is further used for judging that the period value corresponding to the sinusoidal activity curve data with the adjacent wave peaks corresponds to the ruminant reference period value, and the peak value corresponding to the sinusoidal activity curve data with the adjacent wave peaks corresponds to the ruminant reference peak value, so as to generate ruminant state information;
the ruminant activity state judging module is further used for judging that the period value corresponding to the adjacent peak sinusoidal activity curve data corresponds to a ruminant lying reference period value, and the peak value corresponding to the adjacent peak sinusoidal activity curve data corresponds to a ruminant lying reference peak value, so as to generate ruminant lying state information;
the ruminant activity state judging module is further used for judging that the period value corresponding to the adjacent peak sinusoidal activity curve data corresponds to a ruminant walking reference period value, and the peak value corresponding to the adjacent peak sinusoidal activity curve data corresponds to a ruminant walking reference peak value, so as to generate ruminant walking state information.
3. The ruminant activity status determination system of claim 1, wherein: the ruminant final activity state determining module is used for dividing each adjacent peak sinusoidal activity curve data in the preset ruminant activity state duration into a group according to the preset ruminant activity state duration time, recording the times of ruminant feeding states, the times of ruminant lying states and the times of ruminant walking states in the group, and determining the ruminant final activity state in the preset ruminant activity state duration time according to the recorded times of ruminant feeding states, the times of ruminant lying states, the times of ruminant lying states and the times of ruminant walking states in the group.
4. A ruminant activity status determination system according to claim 2 or 3, wherein: the ruminant low head judging module judges whether the ruminant is low or not according to the adjacent peak sinusoidal activity curve data, when the ruminant is in a low head state, a first starting signal is output to the ruminant activity state judging module, the ruminant activity state judging module responds to the first starting signal, judges whether a period value corresponding to the adjacent peak sinusoidal activity curve data corresponds to a ruminant feeding reference period value, a peak value corresponding to the adjacent peak sinusoidal activity curve data corresponds to a ruminant feeding reference peak value or not, and ruminant feeding state information is generated when the period value corresponding to the adjacent peak sinusoidal activity curve data corresponds to the ruminant feeding reference peak value.
5. The ruminant activity status determination system of claim 4, wherein: the ruminant low head judging module judges whether the ruminant is low head according to the adjacent peak sinusoidal activity curve data, and outputs a second starting signal to the ruminant activity state judging module when the ruminant is not in a low head state:
the ruminant activity state judging module responds to the second starting signal to judge whether the period value corresponding to the adjacent peak sinusoidal activity curve data corresponds to a ruminant reference period value or not, and whether the peak value corresponding to the adjacent peak sinusoidal activity curve data corresponds to a ruminant reference peak value or not, and when the period value corresponding to the adjacent peak sinusoidal activity curve data corresponds to the ruminant reference peak value is judged, ruminant state information is generated;
the ruminant activity state judging module responds to the second starting signal, judges whether the period value corresponding to the adjacent peak sinusoidal activity curve data corresponds to a ruminant lying reference period value, and generates ruminant lying state information when judging that the period value corresponding to the adjacent peak sinusoidal activity curve data corresponds to a ruminant lying reference peak value;
the ruminant activity state judging module responds to the second starting signal to judge whether the period value corresponding to the adjacent peak sinusoidal activity curve data corresponds to the ruminant walking reference period value or not, and generates ruminant walking state information when judging that the period value corresponding to the adjacent peak sinusoidal activity curve data corresponds to the ruminant walking reference peak value or not.
6. A ruminant animal activity state determination method, comprising the steps of:
collecting the activity state of the ruminant by using an acceleration sensor, and continuously generating corresponding activity data;
receiving the activity data and recording the time of receiving the activity data;
acquiring corresponding sinusoidal activity curve data according to the received activity data and the recorded time for receiving the activity data;
finding peak data from sinusoidal activity curve data;
dividing the sinusoidal activity curve data by taking the adjacent wave crest data as a reference to obtain a plurality of corresponding adjacent wave crest sinusoidal activity curve data,
calculating a period value corresponding to the adjacent peak sinusoidal activity curve data according to each adjacent peak sinusoidal activity curve data;
judging the ruminant activity state according to the period value corresponding to the adjacent peak sinusoidal activity curve data, the peak value corresponding to the adjacent peak sinusoidal activity curve data, the pre-stored reference activity type period value and the reference activity type peak value.
7. The ruminant activity status determination method of claim 6, wherein: the reference activity type cycle values include ruminant feeding reference cycle values, ruminant lying reference cycle values, and ruminant walking reference cycle values; the reference activity type peaks include ruminant feeding reference peaks, ruminant reference peaks, ruminant lying reference peaks, and ruminant walking reference peaks;
judging that the period value corresponding to the adjacent peak sinusoidal activity curve data corresponds to a ruminant feeding reference period value, and the peak value corresponding to the adjacent peak sinusoidal activity curve data corresponds to a ruminant feeding reference peak value, and determining that the ruminant feeding state is realized;
judging that the period value corresponding to the sinusoidal activity curve data of the adjacent wave peaks corresponds to the ruminant reference period value, and the peak value corresponding to the sinusoidal activity curve data of the adjacent wave peaks corresponds to the ruminant reference peak value, and determining the ruminant state;
judging that the period value corresponding to the adjacent peak sinusoidal activity curve data corresponds to a ruminant lying reference period value, and the peak value corresponding to the adjacent peak sinusoidal activity curve data corresponds to a ruminant lying reference peak value, and determining that the ruminant lying state is achieved;
and judging that the period value corresponding to the sinusoidal activity curve data of the adjacent wave peaks corresponds to the ruminant walking reference period value, and the peak value corresponding to the sinusoidal activity curve data of the adjacent wave peaks corresponds to the ruminant walking reference peak value, and determining the ruminant walking state.
8. The ruminant activity status determination method of claim 6, further comprising the steps of: dividing each adjacent peak sinusoidal activity curve data within a predetermined ruminant activity state duration into a set according to the predetermined ruminant activity state duration;
recording the number of ruminant feeding states, ruminant feeding states, ruminant lying states, and ruminant walking states in the group;
determining a final ruminant activity state for the predetermined ruminant activity state duration based on the number of ruminant feeding states, the number of ruminant feeding states, the number of ruminant lying states, the number of ruminant walking states within the set.
9. The ruminant activity status determination method of claim 6 or 8, wherein: the method also comprises the following steps: judging whether the ruminant is in a low head state according to the adjacent peak sinusoidal activity curve data, judging whether the period value corresponding to the adjacent peak sinusoidal activity curve data corresponds to a ruminant feeding reference period value, judging whether the peak value corresponding to the adjacent peak sinusoidal activity curve data corresponds to a ruminant feeding reference peak value, and determining that the ruminant is in a ruminant feeding state when the period value corresponding to the adjacent peak sinusoidal activity curve data corresponds to the ruminant feeding reference peak value. .
10. The ruminant activity state determination method of claim 9, wherein determining whether the ruminant is low based on the adjacent peak sinusoidal activity curve data, when it is determined that the ruminant is not in a low state:
judging whether the period value corresponding to the sinusoidal activity curve data of the adjacent wave peak corresponds to the ruminant reference period value, and whether the peak value corresponding to the sinusoidal activity curve data of the adjacent wave peak corresponds to the ruminant reference peak value, if so, determining that the ruminant is in a ruminant state;
judging whether the period value corresponding to the adjacent peak sinusoidal activity curve data corresponds to the ruminant lying reference period value, and whether the peak value corresponding to the adjacent peak sinusoidal activity curve data corresponds to the ruminant lying reference peak value or not, and if so, determining that the ruminant lying state is achieved;
judging whether the period value corresponding to the sinusoidal activity curve data of the adjacent wave crest corresponds to the ruminant walking reference period value, and whether the peak value corresponding to the sinusoidal activity curve data of the adjacent wave crest corresponds to the ruminant walking reference peak value, if so, determining that the ruminant walking state is realized.
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