Wearable animal tracking device and control method thereof

Abstract

The invention provides wearable animal tracking equipment and a control method thereof, and the equipment comprises a data collection module which comprises a photoelectric sensing unit and an inertial sensing unit, the photoelectric sensing unit is used for collecting photoelectric signals of a wearer, and the inertial sensing unit is used for collecting motion data of the wearer; the attribute determination module is used for determining animal attribute information of the wearer based on the data acquired by the data acquisition module and a preset animal feature database; the data processing module is used for determining a physiological feature algorithm for processing the photoelectric signal and a motion feature algorithm for processing the motion data according to the animal attribute information of the wearer, and processing the photoelectric signal based on the physiological feature algorithm to obtain a physiological feature measurement value of the wearer; and processing the motion data based on the motion feature algorithm to obtain a motion feature measurement value of the wearer. According to the invention, the accuracy of animal tracking measurement is improved.

Description

Technical Field

[0001] The present application relates to the technical field of wearable devices, and in particular to a wearable animal tracking device and a control method thereof. Background Art

[0002] With the increasing demand for pet safety and health, wildlife protection, and animal husbandry management, real-time positioning, tracking, and health monitoring of various animals, especially small animals, has become critical. Traditional animal trackers not only have single functions, but also consume large amounts of power, and are not suitable for long-term, large-scale, and multi-dimensional animal positioning, tracking, and health status monitoring. Summary of the invention

[0003] In view of the problems in the prior art, the purpose of the present application is to provide a wearable animal tracking device and a control method thereof, so as to improve the accuracy of animal tracking measurement.

[0004] The present application provides a wearable animal tracking device, including:

[0005] A data acquisition module, comprising a photoelectric sensor unit and an inertial sensor unit, wherein the photoelectric sensor unit is used to collect photoelectric signals from the wearer, and the inertial sensor unit is used to collect motion data of the wearer;

[0006] An attribute determination module, used to determine the animal attribute information of the wearer based on the data collected by the data collection module and a preset animal feature database;

[0007] A data processing module is used to determine a physiological characteristic algorithm for processing the photoelectric signal and a motion characteristic algorithm for processing the motion data according to the animal attribute information of the wearer, process the photoelectric signal based on the physiological characteristic algorithm to obtain the physiological characteristic measurement value of the wearer, and process the motion data based on the motion characteristic algorithm to obtain the motion characteristic measurement value of the wearer.

[0008] In some embodiments, the data processing module is further used to determine the sampling requirements of the data acquisition module according to the animal attribute information of the wearer, generate a sampling control instruction according to the sampling requirements and send it to the data acquisition module.

[0009] In some embodiments, a positioning module is also included to obtain the location data of the wearer;

[0010] The data processing module is also used to calculate the wearer's physical energy consumption using a preset consumption algorithm based on the wearer's animal attribute information, physiological characteristic measurement values, motion characteristic measurement values ​​and position data.

[0011] In some embodiments, a communication module is further included, which is used to receive control instructions and send data externally;

[0012] The communication module includes at least two types of communication units, and is further configured to select a communication unit with the highest priority and disable other communication units when the at least two types of communication units are available.

[0013] In some embodiments, the data processing module is further used to determine whether the sleep condition is currently met based on the motion data and the photoelectric signal, and if so, control the device to enter a sleep state.

[0014] In some embodiments, the animal feature database pre-stores feature determination conditions corresponding to a plurality of animal attributes;

[0015] The attribute determination module is used to determine the characteristic determination conditions that the wearer meets based on the photoelectric signal and the motion data, so as to determine the animal attribute corresponding to the wearer.

[0016] In some embodiments, the animal attributes include species attributes, body shape attributes, and motion state attributes, and the attribute determination module is used to determine the species attributes and body shape attributes of the wearer based on the motion data and the animal feature database, and determine the motion state attributes of the wearer based on the species attributes, body shape attributes of the wearer and the motion data of the wearer;

[0017] The data processing module is used to adjust the algorithm parameters in the preset physiological characteristic algorithm and the algorithm parameters in the preset motion characteristic algorithm according to the species attributes, the body shape attributes and the motion state attributes.

[0018] In some embodiments, the animal attributes include fur classification attributes, the fur classification attributes including at least one of a fur color attribute, a skin color attribute, and a hair density attribute;

[0019] The photoelectric sensing unit is used to collect photoelectric signals of the wearer under different waveband signal channels, and the attribute determination module is used to determine the fur classification attributes of the wearer according to the photoelectric signals of the wearer under the different waveband signal channels;

[0020] The data processing module is used to adjust the algorithm parameters in the preset physiological characteristic algorithm according to the fur classification attributes of the wearer.

[0021] The embodiment of the present application also provides a control method of a wearable animal tracking device, which is used to control the wearable animal tracking device. The method comprises the following steps:

[0022] Collecting photoelectric signals from the wearer, and collecting motion data of the wearer through the inertial sensing unit;

[0023] Determining the animal attribute information of the wearer based on the photoelectric signal transmitted by the wearer, the motion data of the wearer and a preset animal feature database;

[0024] Determining a physiological feature algorithm for processing the photoelectric signal and a motion feature algorithm for processing the motion data according to the animal attribute information of the wearer;

[0025] The photoelectric signal is processed based on the physiological characteristic algorithm to obtain the wearer's physiological characteristic measurement value, and the motion data is processed based on the motion characteristic algorithm to obtain the wearer's motion characteristic measurement value.

[0026] In some embodiments, after the photoelectric signal is processed based on the physiological characteristic algorithm to obtain the physiological characteristic measurement value of the wearer, and the motion data is processed based on the motion characteristic algorithm to obtain the motion characteristic measurement value of the wearer, the following steps are also included:

[0027] Based on the animal attribute information, physiological characteristic measurement values, motion characteristic measurement values ​​and position data of the wearer, the wearer's physical energy consumption is calculated using a preset consumption algorithm.

[0028] In some embodiments, the animal attributes include species attributes, body shape attributes, movement state attributes, and fur classification attributes;

[0029] Based on the photoelectric signal of the wearer, the motion data of the wearer and a preset animal feature database, determining the animal attribute information of the wearer includes the following steps:

[0030] According to the motion data, determining the species attribute and body type attribute of the wearer based on the animal feature database;

[0031] Determine the wearer's motion state attributes according to the wearer's species attributes, body shape attributes, and the wearer's motion data;

[0032] The wearer's fur classification attributes are determined based on the photoelectric signals passing through the wearer under different band signal channels.

[0033] The wearable animal tracking device and control method thereof provided in this application have the following advantages:

[0034] The present application provides a wearable animal tracking device for tracking and measuring animals. The data collected by the sensor can be processed through a preset data processing algorithm to obtain the measurement value of the wearer, and the wearer can be classified through a preset animal feature database to determine the attribute information of the wearer. The preset data processing algorithm is adjusted based on the attribute information, so that the data processing algorithm is more in line with the characteristics of the wearer, taking into account the influence of the wearer's own characteristics on the measurement deviation, thereby further improving the accuracy of animal tracking measurement, which is conducive to the realization of multi-dimensional and accurate health status monitoring of animals. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Other features, objects and advantages of the present application will become more apparent by reading the detailed description of non-limiting embodiments made with reference to the following drawings.

[0036] Figure 1 is a structural block diagram of a wearable animal tracking device according to an embodiment of the present application;

[0037] Figure 2 is a flow chart of a control method of a wearable animal tracking device according to an embodiment of the present application;

[0038] Figure 3 This is a flowchart of determining the animal attribute information of the wearer according to an embodiment of the present application. DETAILED DESCRIPTION

[0039] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be implemented in a variety of forms and should not be construed as limited to the embodiments set forth herein; rather, these embodiments are provided so that this application will be comprehensive and complete and fully convey the concepts of the example embodiments to those skilled in the art. In the figures, the same reference numerals represent the same or similar structures, and thus their repeated description will be omitted. "or" and "or" in the specification may both mean "and" or "or".

[0040] In order to solve the technical problems in the prior art, the present application provides a wearable animal tracking device, which can be worn on the neck, chest or other parts of an animal through a ring belt made of biocompatible material, and the device shell adopts a waterproof and dustproof design to improve the universality of the device usage scenarios. The tracking device can also be equipped with components such as speakers and indicator lights to facilitate auxiliary searches in the wild by sound and light.

[0041] like Figure 1As shown, the present application provides a wearable animal tracking device. The tracking device includes a data acquisition module M100, an attribute determination module M200 and a data processing module M300, wherein the data acquisition module M100, the attribute determination module M200 and the data processing module M300 can be arranged inside the device housing, and the acquisition surface (the surface for sending photoelectric signals) of the data acquisition module M100 is facing the wearer. The data acquisition module M100 includes a photoelectric sensor unit M110 and an inertial sensor unit M120. The photoelectric sensor unit M110 adopts a high-sensitivity photoelectric sensor module for collecting photoelectric signals passing through the wearer. The photoelectric signal passing through the wearer here refers to the photoelectric signal reflected from the wearer after the photoelectric sensor module sends the photoelectric signal to the wearer. The photoelectric sensor unit M110 can transmit photoelectric signals of multiple bands to the wearer as needed to detect the wearer's response differences to photoelectric signals of different bands. The inertial sensor unit M120 is used to collect the wearer's motion data. The inertial sensing unit M120 has a built-in three-axis inertial sensor, which can accurately collect the animal's motion data in real time, and is used to calculate the frequency, stride, running and jumping, etc. The acceleration can be used to calculate the animal's motion consumption, analyze the danger of the action, etc. The wearer's motion data includes but is not limited to the wearer's speed, acceleration, angular velocity and other data.

[0042] The attribute determination module M200 is used to determine the animal attribute information of the wearer based on the data collected by the data acquisition module M100 and the preset animal feature database. The animal attribute information is the specific category corresponding to each animal attribute. In this embodiment, the animal attribute may include one or more of the animal's species attribute (attribute information such as rabbit, dog, cat, etc.), the animal's body attribute (attribute information such as large, medium, small, etc.), the animal's motion state attribute (attribute information such as sprint, jog, walk, standstill, jump, etc.), and the animal's fur classification attribute. The animal's fur classification attribute further includes one or more of fur color attribute, skin color attribute, and hair density attribute. The different attributes of animals have a certain impact on the animal's step counting, heart rate calculation, respiratory rate calculation, etc.

[0043] The data processing module M300 is used to process the data acquisition module M100 according to a preset data processing algorithm, and the data processing algorithm includes a physiological characteristic algorithm and a motion characteristic algorithm. The physiological characteristic algorithm is used to calculate the heart rate and breathing rhythm of the animal according to the photoelectric signal processing, and the motion characteristic algorithm is used to calculate the number of steps of the animal according to the motion data, count the steps of the animal, and further analyze whether the animal's movement posture is dangerous, etc. The physiological characteristic algorithm is, for example, a PPG algorithm. The motion characteristic algorithm is, for example, analyzing the vibration amplitude according to the dynamic waveform of the motion data, and counting the steps according to the vibration peak. Therefore, by adopting the wearable animal tracking device of the present application, the data collected by the sensor can be processed by a preset data processing algorithm to obtain the measurement value of the wearer.

[0044] Furthermore, considering that different attributes of animals may have different degrees of influence on the accuracy of the data processing algorithm, the data processing module M300 is also used to determine the physiological characteristic algorithm for processing the photoelectric signal and the motion characteristic algorithm for processing the motion data according to the animal attribute information of the wearer, and to process the photoelectric signal based on the determined physiological characteristic algorithm to obtain the wearer's physiological characteristic measurement value, and to process the motion data based on the determined motion characteristic algorithm to obtain the wearer's motion characteristic measurement value. The physiological characteristic measurement value here refers to the wearer's heart rate, breathing rhythm, etc. The motion characteristic measurement value refers to the wearer's step count, whether the motion posture is dangerous, etc. Therefore, by adopting the tracking device of the present application, the preset data processing algorithm is adjusted based on the attribute information, so that the data processing algorithm is more in line with the characteristics of the wearer, and the influence deviation of the wearer's own characteristics on the measurement value is taken into account, thereby further improving the accuracy of animal tracking measurement, which is conducive to the realization of multi-dimensional and accurate health status monitoring of animals.

[0045] In this embodiment, the data processing module M300 determines the physiological characteristic algorithm for processing the photoelectric signal and the motion characteristic algorithm for processing the motion data according to the animal attribute information of the wearer. It can be that a plurality of physiological characteristic algorithms and a plurality of motion characteristic algorithms are pre-set, a correspondence between different physiological characteristic algorithms and different animal attribute information is established, and a correspondence between different motion characteristic algorithms and different animal attribute information is established, and the corresponding physiological characteristic algorithm and motion characteristic algorithm are selected according to the animal attribute information. It can also be that a physiological characteristic algorithm and a motion characteristic algorithm are fixedly set, but the algorithm parameters are adjustable, and multiple groups of physiological characteristic algorithm parameters and multiple groups of motion characteristic algorithm parameters are set respectively, a correspondence between different physiological characteristic algorithm parameters and different animal attribute information is established, and a correspondence between different motion characteristic algorithm parameters and different animal attribute information is established, and the corresponding physiological characteristic algorithm parameters and motion characteristic algorithm parameters are selected according to the animal attribute information. Adjustable physiological characteristic algorithm parameters may include, for example, waveform decomposition frequency range, amplitude threshold, etc.

[0046] In this embodiment, different data sampling requirements may be adopted for different animal attributes, and the sampling requirements include sampling channel selection of different bands of the photoelectric sensor, sampling frequency of the sensor, sampling time window length of the sensor, etc. The data processing module M300 is also used to determine the sampling requirements of the data acquisition module according to the animal attribute information of the wearer, generate a sampling control instruction according to the sampling requirements, and send it to the data acquisition module M100. The data acquisition module M100 controls the photoelectric sensor unit M110 and the inertial sensor unit M120 according to the sampling control instruction.

[0047] Therefore, the present application collects data through a combination of multiple sensors, and can identify animal attributes based on the collected data, realize classification of animals from multiple dimensions, and perform secondary correction and analysis of the data collected by the sensors based on the animal attribute information, thereby eliminating the influence of different animal classifications on the data analysis results and improving the accuracy and precision of data analysis for animals.

[0048] like Figure 1 As shown, the wearable animal tracking device also includes a positioning module M400 for obtaining the location data of the wearer. The positioning module M400 supports GPS / GNSS / Beidou satellite positioning signals to ensure that the accurate location of the animal can be located in real time in both outdoor scenes and home scenes.

[0049] The data processing module M300 is also used to calculate the wearer's physical energy consumption based on the wearer's animal attribute information, physiological characteristic measurement values, motion characteristic measurement values ​​and position data using a preset consumption algorithm. The preset consumption algorithm here can be a preset consumption calculation formula, and its solution value is the animal's physical energy consumption. The variables include animal attribute information, physiological characteristic measurement values, motion characteristic measurement values ​​and the change in position data (movement distance), etc. Because animals of different species, different body shapes, and different movement states may have different consumption when exercising with the same number of steps, heart rate, and breathing rhythm. Therefore, the preset consumption algorithm further adds the consideration of animal attribute information on the basis of the existing calculation of exercise consumption. Animal attribute information can be used as a weight coefficient of a variable in the consumption calculation formula to affect the calculation of the final physical energy consumption.

[0050] like Figure 1 As shown, in this embodiment, the wearable animal tracking device also includes a communication module M500 for receiving control instructions and sending data outward. For example, the wearable animal tracking device can communicate directly with the cloud server, send data collected by the data acquisition module M100 and data processed by the data processing module M300, and can receive control instructions from the cloud server to control the work of each module. The wearable animal tracking device can also communicate with the terminal device carried by the staff to send data and receive control instructions. The communication module M500 supports WiFi communication mode and Bluetooth communication mode, and has built-in ultra-low power consumption LoRA communication technology, which supports the tracking device to work for a longer time in a larger range. LoRA (Long Range Radio) is a low-power LAN wireless standard. Its biggest feature is that it can propagate farther than other wireless methods under the same power consumption conditions, achieving the unity of low power consumption and long distance. Its communication distance is 3-5 times larger than that of traditional wireless radio frequency communication under the same power consumption.

[0051] In this embodiment, different types of communication units may be further prioritized for use. The communication module M500 includes at least two types of communication units, and the communication module M500 is also used to select the communication unit with the highest priority when at least two types of communication units are available, and to disable other communication units. For example, the priority of the WiFi communication unit / Bluetooth communication unit is set higher than the priority of the LoRA communication unit. When only a LoRA connection can be established, the LoRA communication unit is used to work. When the WiFi communication unit / Bluetooth communication unit can work normally, the LoRA communication unit is disabled, thereby further reducing communication power consumption and further increasing the use time of the tracking device.

[0052] In this embodiment, the data processing module M300 is also used to determine whether the sleep condition is currently met based on the motion data and the photoelectric signal. If so, the tracking device is controlled to enter a sleep state, thereby further reducing the energy consumption of the tracking device and ensuring that the tracking device can be used for a longer period of time in a wider range. For example, when the data processing module M300 detects that the wearer's acceleration value is less than the preset minimum acceleration threshold for a long time and the photoelectric sensor module does not receive a photoelectric signal, it is determined that the sleep condition is currently met, and the device is adaptively entered into a non-wearing state and performs sleep energy saving.

[0053] In this embodiment, the animal characteristic database is a pre-established database that associates different animal attributes with animal characteristic data. The animal characteristic data corresponding to different animal attributes are collected in advance, and the animal characteristic database can be constructed through data induction and feature extraction.

[0054] For example, the following experimental data are collected and stored in advance:

[0055] The numerical characteristic range of the inertial sensor unit of animals of different body shapes (weight, shoulder height, hip height, front and rear leg length) under different movement characteristics (cadence range, stride range, speed range, number of steps) and movement states (running, jogging, walking, stationary, jumping);

[0056] The range of heart rate, breathing rhythm and body size of animals of different species and sizes (e.g., large, medium and small dogs, large, medium and small cats, small and medium rabbits)

[0057] The interference characteristics of animals' respiratory rhythm and heart rate monitoring signals in different motion states and cadence, stride length, and gait speed;

[0058] The interference characteristics of different hair colors, skin colors, and hair densities on the photoelectric signals of photoelectric sensing units of different bands (intensity attenuation, angle deflection caused by scattered reflection);

[0059] By aggregating, organizing, summarizing and extracting features from the above experimental collected data, an animal feature database can be obtained.

[0060] In one embodiment, the animal feature database pre-stores feature determination conditions corresponding to a plurality of animal attributes. The attribute determination module M200 is used to determine the feature determination conditions that the wearer meets based on the photoelectric signal and the motion data, so as to determine the animal attribute corresponding to the wearer.

[0061] In this embodiment, the attribute determination module M200 is used to determine the species attribute and body shape attribute of the wearer based on the motion data and the animal feature database, and determine the motion state attribute of the wearer based on the species attribute, body shape attribute and the motion data of the wearer.

[0062] In this embodiment, the photoelectric sensing unit is used to collect photoelectric signals passing through the wearer under different band signal channels, and the attribute determination module M200 is used to determine the wearer's fur classification attributes according to the photoelectric signals passing through the wearer under the different band signal channels.

[0063] For example, the determination conditions for setting species attributes include: when the animal speed is within the calibrated speed range and the animal acceleration is within the calibrated acceleration range, the heart rate range and respiratory rhythm range of animals of various species, and judging whether the wearer falls into that species' heart rate range and respiratory rhythm range according to the heart rate and respiratory rhythm detected by the photoelectric signal. For another example, the characteristic determination conditions for setting body shape attributes are: when the animal speed is within the preset first speed range and the animal acceleration is within the preset first acceleration range, the heart rate detected by the photoelectric signal belongs to the preset first heart rhythm range, and the respiratory rhythm detected by the photoelectric signal belongs to the preset first respiratory rhythm range, then the wearer is judged to be a large animal. Similarly, when the animal speed is within the preset second speed range and the animal acceleration is within the preset second acceleration range, the heart rate detected by the photoelectric signal belongs to the preset second heart rhythm range, and the respiratory rhythm detected by the photoelectric signal belongs to the preset second respiratory rhythm range, then the wearer is judged to be a small animal. For another example, the determination condition of the motion state attribute is set as follows: for large animals, when the animal acceleration is greater than the first acceleration threshold and the heart rate is higher than the first heart rate threshold, the wearer is determined to be running fast; when the animal acceleration is less than the second acceleration threshold and the heart rate is lower than the second heart rate threshold, the wearer is determined to be walking slowly. For another example, the photoelectric sensing unit collects photoelectric signals reflected from the wearer in multiple bands, and compares the parameter difference of the photoelectric waveforms in multiple bands with the preset parameter difference ranges of various fur colors / skin colors / hair densities to determine the fur color / skin color / hair density of the wearer.

[0064] In another alternative embodiment, the determination of the animal attribute information of the wearer based on the data collected by the data acquisition module M100 and the preset animal feature database can also be achieved by constructing an animal attribute classification model based on deep learning. Specifically, the motion data and photoelectric signals of different animal attributes are collected through experiments, and the features of the motion data and photoelectric signals are extracted to obtain animal sample features, and animal attribute labels are added to the animal sample features. Then, the animal sample features are used as input data of the animal attribute classification model, and the loss function is calculated based on the output data of the animal attribute classification model and the animal attribute label, and then the animal attribute label is optimized and trained in reverse iteration. When applied, the wearer's motion data and photoelectric information extracted features collected in real time are input into the animal attribute classification model to obtain the wearer's animal attribute information. When there are multiple different types of animal attributes, multiple branches can be set in the animal attribute classification model, such as setting a species classification branch, a body type classification branch, a fur color classification branch, etc., or an animal attribute classification model can be trained separately for each animal attribute.

[0065] The data processing module M300 is used to adjust the algorithm parameters in the preset physiological characteristic algorithm and the algorithm parameters in the preset motion characteristic algorithm according to the species attribute, the body shape attribute, the motion state attribute and the fur classification attribute. For example, multiple groups of physiological characteristic algorithm parameters and multiple groups of motion characteristic algorithm parameters are set respectively, and the corresponding relationship between different physiological characteristic algorithm parameters and different animal attribute information is established, and the corresponding relationship between different motion characteristic algorithm parameters and different animal attribute information is established, and the corresponding physiological characteristic algorithm parameters and motion characteristic algorithm parameters are selected according to the animal attribute information. The adjustable physiological characteristic algorithm parameters may include, for example, the waveform decomposition frequency range, the amplitude threshold, etc.

[0066] In another alternative embodiment, the physiological feature algorithm and the motion feature algorithm can also be implemented by a deep learning model, that is, a physiological feature model is pre-trained, and the wearer's attribute information together with the wearer's motion data and photoelectric signals are used as inputs to the physiological feature model to obtain the physiological feature measurement values ​​output by the physiological feature model; a motion feature model is pre-trained, and the wearer's attribute information together with the wearer's motion data and photoelectric signals are used as inputs to the motion feature model to obtain the motion feature measurement values ​​output by the motion feature model.

[0067] like Figure 2 As shown, the embodiment of the present application also provides a control method of a wearable animal tracking device, which is used to control the wearable animal tracking device. The method can be specifically implemented by using the above-mentioned data acquisition module, attribute judgment module and data processing module. The method includes the following steps:

[0068] S100: collecting photoelectric signals from the wearer and collecting motion data of the wearer;

[0069] S200: Determine the animal attribute information of the wearer based on the photoelectric signal transmitted by the wearer, the motion data of the wearer and a preset animal feature database;

[0070] In this embodiment, the animal attributes include one or more of species attributes, body shape attributes, movement state attributes, and fur classification attributes, but the present application is not limited thereto. In other alternative implementations, the animal attributes may also include other types of attributes, not limited to those listed here.

[0071] S300: Determine a physiological feature algorithm for processing the photoelectric signal and a motion feature algorithm for processing the motion data according to the animal attribute information of the wearer;

[0072] S400: Processing the photoelectric signal based on the physiological characteristic algorithm to obtain a physiological characteristic measurement value of the wearer, and processing the motion data based on the motion characteristic algorithm to obtain a motion characteristic measurement value of the wearer.

[0073] In this embodiment, after the step S400: processing the photoelectric signal based on the physiological characteristic algorithm to obtain the wearer's physiological characteristic measurement value, and processing the motion data based on the motion characteristic algorithm to obtain the wearer's motion characteristic measurement value, the following steps are also included:

[0074] Based on the animal attribute information, physiological characteristic measurement values, motion characteristic measurement values ​​and position data of the wearer, the wearer's physical energy consumption is calculated using a preset consumption algorithm.

[0075] like Figure 3 As shown, the step S300: determining the animal attribute information of the wearer based on the photoelectric signal of the wearer and the motion data of the wearer and a preset animal feature database, comprises the following steps:

[0076] S310: Determine whether the species attribute, body shape attribute and fur classification attribute of the wearer are pre-stored;

[0077] In the case where a wearer wears a tracking device regularly, it is only necessary to judge the species attribute, body shape attribute and fur classification attribute when the wearer wears the tracking device for the first time. Since these attributes are relatively fixed, the first judgment can be used directly in the future. However, the motion state attribute changes in real time with the different motion states of the animal, so it needs to be judged every time. In the case where the wearer does not wear the tracking device regularly, or it is the first time for the wearer to wear a tracking device, it is necessary to judge the species attribute, body shape attribute and fur classification attribute.

[0078] If not, proceed to step S320: determine the species attribute and body shape attribute of the wearer based on the animal feature database according to the motion data;

[0079] S330: Determine the motion state attribute of the wearer according to the species attribute, body shape attribute and motion data of the wearer;

[0080] S340: Determine the fur classification attribute of the wearer according to the photoelectric signals of the wearer in different band signal channels;

[0081] If yes, proceed to step S350: obtain the pre-stored species attributes, body shape attributes and fur classification attributes of the wearer, and proceed to step S360: determine the motion state attributes of the wearer according to the species attributes, body shape attributes and motion data of the wearer.

[0082] The wearable animal tracking device of the present application can be applied to pet health monitoring, wildlife protection and ecological research, animal husbandry management, etc. For example, when the tracking device is applied to pet health monitoring, obtaining location data through the positioning module of the tracking device can prevent the pet from getting lost and facilitate quick retrieval, and the health monitoring of the pet can be achieved through the monitoring of heart rate, respiratory rhythm, and exercise consumption, thereby improving the quality of life of the pet. For another example, when the tracking device is applied to wildlife protection and ecological research, in order to protect wildlife, especially endangered animals, the positioning module of this tracking device can be used to track its activity trajectory for a long time, monitor its health status for a long time, collect data such as animal habits and activity range, and provide valuable data for animal protection and ecological research. For another example, when the tracking device is applied to animal husbandry management, for large ranches, the positioning module of this tracking device can be used to locate livestock, and collect exercise data and health data to improve the quality of life and management efficiency of livestock. The tracking device also has the functions of physiological characteristic monitoring, pedometer and satellite positioning, providing multi-dimensional management of animals. The data processing algorithm is further optimized according to various animal attributes, which improves the accuracy and precision of data processing calculations. It can also select low-power communication methods according to the working status and enter a sleep state when it automatically detects that it is not being worn, greatly reducing the power consumption of the tracking device. The structure is simple, and the size and weight of the device can be very small. It is suitable for long-term, large-scale, multi-dimensional animal positioning tracking and health monitoring, and has broad application prospects and market potential.

[0083] The above content is a further detailed description of the present application in combination with specific preferred implementation methods, and it cannot be determined that the specific implementation of the present application is limited to these descriptions. For ordinary technicians in the technical field to which the present application belongs, several simple deductions or substitutions can be made without departing from the concept of the present application, which should be deemed to fall within the scope of protection of the present application.

Claims

1. A wearable animal tracking device, characterized in that: include: A data acquisition module, comprising a photoelectric sensor unit and an inertial sensor unit, wherein the photoelectric sensor unit is used to collect photoelectric signals from the wearer, and the inertial sensor unit is used to collect motion data of the wearer; An attribute determination module, used to determine the animal attribute information of the wearer based on the data collected by the data collection module and a preset animal feature database; A data processing module is used to determine a physiological characteristic algorithm for processing the photoelectric signal and a motion characteristic algorithm for processing the motion data according to the animal attribute information of the wearer, process the photoelectric signal based on the physiological characteristic algorithm to obtain the physiological characteristic measurement value of the wearer, and process the motion data based on the motion characteristic algorithm to obtain the motion characteristic measurement value of the wearer.

2. The wearable animal tracking device according to claim 1, characterized in that: The data processing module is also used to determine the sampling requirements of the data acquisition module according to the animal attribute information of the wearer, generate a sampling control instruction according to the sampling requirements and send it to the data acquisition module.

3. The wearable animal tracking device according to claim 1, characterized in that: It also includes a positioning module for obtaining the location data of the wearer; The data processing module is also used to calculate the wearer's physical energy consumption using a preset consumption algorithm based on the wearer's animal attribute information, physiological characteristic measurement values, motion characteristic measurement values ​​and position data.

4. The wearable animal tracking device according to claim 1, characterized in that: It also includes a communication module for receiving control instructions and sending data outward; The communication module includes at least two types of communication units, and is further configured to select a communication unit with the highest priority and disable other communication units when the at least two types of communication units are available.

5. The wearable animal tracking device according to claim 1, characterized in that: The data processing module is also used to determine whether the sleep condition is currently met based on the motion data and the photoelectric signal, and if so, control the device to enter a sleep state.

6. The wearable animal tracking device according to claim 1, characterized in that: The animal feature database pre-stores feature determination conditions corresponding to a variety of animal attributes; The attribute determination module is used to determine the characteristic determination conditions that the wearer meets based on the photoelectric signal and the motion data, so as to determine the animal attribute corresponding to the wearer.

7. The wearable animal tracking device according to claim 1, characterized in that: The animal attributes include species attributes, body shape attributes and motion state attributes, and the attribute determination module is used to determine the species attributes and body shape attributes of the wearer based on the motion data and the animal feature database, and determine the motion state attributes of the wearer based on the species attributes, body shape attributes and motion data of the wearer; The data processing module is used to adjust the algorithm parameters in the preset physiological characteristic algorithm and the algorithm parameters in the preset motion characteristic algorithm according to the species attributes, the body shape attributes and the motion state attributes.

8. The wearable animal tracking device according to claim 1, characterized in that: The animal attributes include fur classification attributes, and the fur classification attributes include at least one of fur color attributes, skin color attributes, and hair density attributes; The photoelectric sensing unit is used to collect photoelectric signals of the wearer under different waveband signal channels, and the attribute determination module is used to determine the fur classification attributes of the wearer according to the photoelectric signals of the wearer under the different waveband signal channels; The data processing module is used to adjust the algorithm parameters in the preset physiological characteristic algorithm according to the fur classification attributes of the wearer.

9. A control method for a wearable animal tracking device, characterized in that: Used to control the wearable animal tracking device according to any one of claims 1 to 8, the method comprising the following steps: Collecting photoelectric signals from the wearer, and collecting motion data of the wearer through the inertial sensing unit; Determining the animal attribute information of the wearer based on the photoelectric signal transmitted by the wearer, the motion data of the wearer and a preset animal feature database; Determining a physiological feature algorithm for processing the photoelectric signal and a motion feature algorithm for processing the motion data according to the animal attribute information of the wearer; The photoelectric signal is processed based on the physiological characteristic algorithm to obtain the wearer's physiological characteristic measurement value, and the motion data is processed based on the motion characteristic algorithm to obtain the wearer's motion characteristic measurement value.

10. The control method of the wearable animal tracking device according to claim 9, characterized in that: After the photoelectric signal is processed based on the physiological characteristic algorithm to obtain the physiological characteristic measurement value of the wearer, and the motion data is processed based on the motion characteristic algorithm to obtain the motion characteristic measurement value of the wearer, the following steps are also included: Based on the animal attribute information, physiological characteristic measurement values, motion characteristic measurement values ​​and position data of the wearer, the wearer's physical energy consumption is calculated using a preset consumption algorithm.

11. The control method of the wearable animal tracking device according to claim 9, characterized in that: The animal attributes include species attributes, body shape attributes, movement state attributes and fur classification attributes; Based on the photoelectric signal of the wearer, the motion data of the wearer and a preset animal feature database, determining the animal attribute information of the wearer includes the following steps: According to the motion data, determining the species attribute and body type attribute of the wearer based on the animal feature database; Determine the wearer's motion state attributes according to the wearer's species attributes, body shape attributes, and the wearer's motion data; The wearer's fur classification attributes are determined based on the photoelectric signals passing through the wearer under different band signal channels.

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