Ear tag-based animal motion state detection method

Abstract

The application relates to an ear tag-based animal motion state detection method. The ID recognition module of an animal ear tag is utilized twice, ear tag signals in the animal motion state are received and noise reduction processing is conducted, and the nominal speed is calculated based on two technical methods of the Doppler effect and signal strength change to detect the animal motion state. The method can effectively inhibit noise influence and improve detection accuracy.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of animal motion state detection, in particular to an animal motion state detection method based on ear tags. BACKGROUND

[0002] In the livestock industry, how to monitor the health status of animals in real time is a very important work, and the administrator generally judges whether the animal is sick by detecting the body temperature and motion state of the animal. For animal motion state detection, the current application is more common based on computer vision and acceleration sensing technology, but these methods have shortcomings. The method based on computer vision is difficult to identify the detected animal ID, and the method based on acceleration sensing needs to increase the acceleration sensor in the animal ear tag, which is easy to cause the animal to be uncomfortable and drop or bite off the ear tag. SUMMARY

[0003] In view of the defects in the prior art, the purpose of the present application is to provide an animal motion state detection method based on ear tags. The present application realizes the detection of animal motion state by means of the existing ID recognition function (LoRa or RFID, etc.) in animal ear tags; at the same time, it adopts two technical methods of Doppler effect and signal strength change to detect the animal motion state, and through the combination of the two methods and the median filtering method, it can effectively suppress the influence of noise and improve the detection accuracy.

[0004] To achieve the above purpose, the technical scheme adopted by the present application is:

[0005] An animal motion state detection method based on ear tags, characterized in that it comprises the following steps:

[0006] Step 1, collect the ear tag signal in the animal static state, carry out noise reduction processing on the signal, and carry out fast Fourier transform on the noise-reduced ear tag signal to determine the signal center frequency ω0 in the static state;

[0007] Step 2, receive the ear tag signal in the animal motion state, carry out noise reduction processing on the signal, and carry out fast Fourier transform on the noise-reduced ear tag signal to determine the ear tag signal center frequency ω1 in the motion state;

[0008] Step 3, use the Doppler effect to compare the ear tag signal center frequency ω0 in the static state with the ear tag signal center frequency ω1 in the motion state to calculate the motion speed Δv of the animal ear tag relative to the signal receiving end D As shown in the following formula (1):

[0009]

[0010] In the formula, delta omega is a signal frequency variation, delta omega = | omega 1- omega 0 |; omega is a transmission frequency; and C is a light speed.

[0011] Step 4, the average movement speed of the ear tag away from the signal receiving end is calculated by using the relationship between the ear tag signal intensity and the receiving distance As shown in the following formula (2):

[0012]

[0013] In the formula, delta t is a time variation, e(t) is the ear tag signal intensity at t moment, e(t-delta t) is the ear tag signal intensity at t-delta t moment, and S is a constant, a plurality of groups of e(t) and e(t-delta t) data are obtained in an actual situation, and calibration is performed according to formula (2); e(t) and e(t-delta t) data are obtained in an actual situation, and calibration is performed according to formula (2);

[0014] Step 5, the nominal movement speed of the ear tag is calculated according to formula , and the movement state of the animal is judged according to the nominal movement speed.

[0015] On the basis of the above scheme,

[0016] The static state in step 1 refers to that the movement speed of the animal is less than 0.1 m / s, and the movement state in step 2 refers to that the movement speed of the animal is greater than or equal to 0.1 m / s.

[0017] On the basis of the above scheme,

[0018] The noise reduction processing in steps 1 and 2 both adopts median filtering.

[0019] On the basis of the above scheme,

[0020] The judgment of the movement state of the animal in step 5 is specifically:

[0021] By comparing the nominal movement speed of the ear tag With a preset threshold value v c , v c The value is 0.1 m / s.

[0022] On the basis of the above scheme,

[0023] The ear tag signal in step 1 is the transmission signal of the LoRa or RFID Internet of Things communication module in the ear tag.

[0024] The animal movement state detection method based on an ear tag has the beneficial effects that:

[0025] 1. The ID recognition module of the ear tag is reused: RFID, LoRa wireless module, etc. On the basis of realizing the basic function of animal ID recognition, the detection of animal movement state is realized. This technical upgrading method without introducing additional hardware is more acceptable to users and is more friendly to animals.

[0026] 2. The Doppler effect and signal strength change are used to detect the animal movement state. Through the combination of the two methods and the median filter, the noise influence can be effectively suppressed, and the detection accuracy can be improved. DETAILED DESCRIPTION

[0027] The application will be further described in detail below.

[0028] A) Ear tag speed detection method based on Doppler shift effect

[0029] The RFID, LoRa and other radio frequency chips for animal ID recognition have been integrated in the ear tag. The median filter is used to denoise the ear tag signal. When the animal moves, the signal frequency received by the signal receiving end will be shifted due to the Doppler shift effect. As long as the change amount of the signal frequency after demodulation and denoising is obtained, the moving speed of the ear tag can be quantitatively calculated. The Doppler shift formula is:

[0030]

[0031] Where ω is the received frequency, Ω is the transmitted frequency, C is the speed of light, Δv D is the speed of the ear tag relative to the signal receiving end. When the distance between the ear tag and the signal receiving end becomes smaller, the plus sign is taken in the denominator, and when the distance becomes larger, the minus sign is taken. Considering that the moving speed of the ear tag is very small compared with the speed of light, the above formula can be simplified as:

[0032]

[0033] Where Δω is the change amount of the received signal frequency. According to this formula, the movement of the ear tag relative to the signal receiving end can be determined by detecting Δω.

[0034] B) Ear tag speed detection method based on signal strength

[0035] The relationship between signal strength and distance is:

[0036]

[0037] Where e is the signal strength, S' is the proportional coefficient, and l is the distance between the ear tag and the signal receiving end. Then the speed of the ear tag away from the signal receiving end is:

[0038]

[0039] Where t is time. In order to weaken the adverse effects of signal intensity fluctuations caused by environmental effects, the average speed in the time window Δt is calculated to eliminate noise:

[0040]

[0041] Where, is the average movement speed of the ear tag away from the signal receiving end; Δt is the time change, which is recommended to be 3s; e(t) is the ear tag signal intensity at time t; e(t-Δt) is the ear tag signal intensity at time t-Δt; S is a constant, which is calibrated by obtaining multiple groups of e(t) and e(t-Δt) data in actual situations and according to the above formula. e(t) and e(t-Δt) data and according to the above formula.

[0042] C) Combination of the two methods

[0043] The ear tag speed calculated by the Doppler frequency shift and signal intensity change is averaged as the nominal ear tag movement speed, that is:

[0044]

[0045] When is considered to be moving, where v c is the standard for judging whether the ear tag is moving, and when the nominal ear tag movement speed is less than this value, it is considered that the ear tag is not moving, and vice versa, the ear tag is moving, v c The recommended value of v

[0046] Example:

[0047] First, prepare an animal ear tag equipped with a LoRa transmission module and a LoRa receiving device.

[0048] The example steps are as follows:

[0049] Step 1: Collect LoRa signals in a stationary state. First, let the animal remain stationary, then use the LoRa receiving device to receive the LoRa signals transmitted by the ear tag, and calculate the LoRa signal center frequency ω0 in the stationary state through fast Fourier transform (FFT).

[0050] Step 2: Receive LoRa signals in the animal movement state. Let the animal start moving, and let the LoRa receiving device receive the LoRa signals transmitted by the ear tag.

[0051] Step 3: Noise reduction processing of LoRa signals in the animal movement state. Use a median filter to perform noise reduction processing on the LoRa signals received in step 2 to eliminate possible noise effects.

[0052] Step 4: Calculate the center frequency of the LoRa signal in the animal's motion state. Perform a fast Fourier transform (FFT) on the LoRa signal processed in Step 3 to calculate the center frequency of the LoRa signal in the animal's motion state ω1.

[0053] Step 5: Calculate the motion speed of the animal's ear tag using the Doppler effect D . Compare ω1 obtained in Step 4 with ω0 obtained in Step 1, and use the Doppler effect to calculate the motion speed of the animal's ear tag Δv D .

[0054]

[0055] Step 6: Calculate the motion speed of the animal's ear tag away from the signal receiving end using the relationship between LoRa signal strength and receiving distance

[0056] Measure the LoRa signal strength in the animal's motion state, and use the relationship between LoRa signal strength and receiving distance to calculate the motion speed of the animal's ear tag away from the signal receiving end

[0057] Step 7: Calculate the nominal motion speed of the animal's ear tag According to the formula , the nominal motion speed of the animal's ear tag is calculated.

[0058] Step 8: Determine the animal's motion state. If (v c is a preset threshold, and the default value is 0.1 m / s), it is considered that the animal is in motion; if , it is considered that the animal is in a stationary state.

[0059] The contents not described in detail in the specification belong to the existing technology known to those skilled in the art.

Claims

1. A method for detecting animal movement status based on ear tags, characterized in that, Includes the following steps: Step 1: Collect the ear tag signal when the animal is at rest, perform noise reduction on the signal, and perform a fast Fourier transform on the noise-reduced ear tag signal to determine the center frequency ω0 of the signal in the resting state. Step 2: Receive the ear tag signal while the animal is in motion, perform noise reduction on the signal, and perform a fast Fourier transform on the noise-reduced ear tag signal to determine the center frequency ω1 of the ear tag signal in motion. Step 3: Using the Doppler effect, compare the center frequency ω0 of the ear tag signal in a stationary state with the center frequency ω1 of the ear tag signal in a moving state to calculate the velocity Δv of the animal ear tag relative to the signal receiver. D As shown in equation (1): In the above formula, Δω is the change in signal frequency, Δω=|ω1-ω0|; Ω is the transmission frequency; C is the speed of light; Step 4: Calculate the average speed at which the ear tag moves away from the signal receiver using the relationship between the ear tag signal strength and the receiving distance. As shown in equation (2): In the above formula, Δt is the time change, e(t) is the ear tag signal strength at time t, e(t-Δt) is the ear tag signal strength at time t-Δt, and S is a constant. Multiple sets of data are obtained under actual conditions. The data of e(t) and e(t-Δt) are calibrated according to equation (2); Step 5, according to the formula Calculate the nominal speed of the ear tag and use it to determine the animal's movement status.

2. The method for detecting animal movement status based on ear tags according to claim 1, characterized in that, The stationary state mentioned in step 1 refers to an animal moving at a speed of less than 0.1 m / s, while the moving state mentioned in step 2 refers to an animal moving at a speed of greater than or equal to 0.1 m / s.

3. The method for detecting animal movement status based on ear tags according to claim 1, characterized in that, The noise reduction process described in steps 1 and 2 both employs median filtering.

4. A method for detecting animal movement status based on ear tags according to claim 1 or 2, characterized in that, The specific steps for determining the animal's movement state in step 5 are as follows: By comparing the nominal speed of the ear tag With preset threshold v c Proceed, v c The value is 0.1 m / s.

5. The method for detecting animal movement status based on ear tags according to any one of claims 1-4, characterized in that, The ear tag signal mentioned in step 1 is the transmission signal of the LoRa or RFID Internet of Things communication module inside the ear tag.

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