WO2022220317A1 - Ingestible health sensor for animal - Google Patents

Abstract

An ingestible health sensor device configured to stay in the stomach of an animal may be formed of a substantially cylindrical housing shell. A ballast weight and a power source may be disposed therein. The ballast weight may be configured to cause the health sensor device to remain in contact with the gastric wall of the animal when the health sensor device is disposed in the animal's stomach. The health sensor device may comprise: a sensor which measures a plurality of animal characteristics; a transmitter which wirelessly communicates with an animal monitoring system; a memory unit for storing the measured characteristics and health sensor device configuration data; and a processor which controls the operation of the components of the health sensor device. The transmitter may communicate with an antenna, and the antenna may be formed as a trace on an antenna circuit board such as a printed circuit board (PCB). The antenna may be separated from the sensor, the processor, and the transmitter to prevent and/or reduce interference and/or coupling therebetween. An accelerometer sensor may be a triaxial accelerometer and may be configured to detect motion characteristics of the animal and gastrointestinal contraction of the animal.

Description

Ingestible Animal Health Sensor

The present invention relates to a method and system for measuring digestibility in the rumen of a ruminant, and more particularly, to a method and system for measuring digestibility in the rumen by withdrawing gastric juice from various locations in the rumen. . The present invention relates to a health sensor device for monitoring the characteristics of a plurality of animals and a method for controlling the device. The health sensor device can in particular be installed in the stomach of a ruminant animal, for example in the rumen. More particularly, it relates to a device for detecting the health condition of an animal, and to a system and method for monitoring a plurality of animal characteristics.

As the global population increases, the need for a technology related to a health sensor system and method for monitoring the health status of livestock in general is increasing in order to increase the production of livestock and to provide healthier livestock.

In particular, in order to monitor the characteristics of a plurality of livestock and detect the health status of livestock in real time, a health sensor device is attached to the body of each animal, and the biometric data of the animal obtained from the health sensor device is analyzed and provided to the user. Technology is advancing.

According to embodiments of the present invention, a health sensor device capable of sensing and transmitting biometric information to determine the health state of a ruminant, for example, a health sensor device in the form of a biocapsule may be provided.

The biocapsule according to the embodiments may be easily orally administered to cattle, and may be seated in the rumen of the cattle, thereby providing a technology for monitoring the health of the cattle. According to embodiments, the biocapsule may provide a technology for managing diseases of cattle, fertilization time of cattle, delivery time, and the like.

However, it is not limited only to the above-mentioned purposes, and the scope of the present invention may be extended for other purposes that can be inferred by those skilled in the art based on the entire contents of the present specification.

This result was researched with support from the Ministry of Agriculture, Food and Rural Affairs, with the support of the Advanced Production Technology Development Project of the Institute for Planning and Evaluation of Food, Agriculture, Forestry and Food (318103-02).

An ingestible health sensor device according to an embodiment of the present invention is an ingestible health sensor device (bolus) that is disposable in the stomach of an animal to measure a plurality of characteristics of an animal, comprising: a sensor for measuring animal characteristics; a transmitter communicatively coupled to the sensor for transmitting the measured animal characteristic to a receiver and a power source in electrical communication with the sensor and the transmitter to power the sensor and the transmitter; includes a ballast weight to be seated on the lower part of the stomach.

In this embodiment, the ballast weight may be magnetized.

In this embodiment, the ballast weight may be configured such that the health sensor device is seated in contact with a portion of the wall of the stomach of the animal and is coupled to move along with the movement of the wall of the stomach.

In this embodiment, the sensor may be an acceleration sensor.

In this embodiment, the acceleration sensor may be a three-axis acceleration sensor configured to detect the contraction of the stomach.

In this embodiment, the health sensor device may further include a memory unit storing data and an animal identifier, and the transmitter may be configured to transmit the animal identifier including the measured animal characteristic.

In this embodiment, the transmitter may include a transceiver capable of receiving data of the health sensor device for storage on the memory unit.

In this embodiment, it may further include a housing shell having a cylindrical shape including the sensor, the transmitter, the power source, and the ballast weight.

In this embodiment, further comprising a message label disposed on the inner wall of the housing shell, the housing shell is substantially transparent, the label may be to provide a return address for the health sensor device.

In this embodiment, there is further provided a first circuit board that is substantially disk-shaped, wherein a diameter of the first circuit board consists of a diameter sized to accommodate the first circuit board in the housing shell, the sensor and the transmitter may be disposed on the first circuit board.

In this embodiment, it may further include an antenna substrate having a diameter accommodated in the housing shell and having a substantially disk shape, and an antenna formed on the antenna substrate and communicatively coupled to the transmitter.

In this embodiment, the antenna substrate may further include an insulating spacer separating the sensor, the transmitter, and the processor.

In this embodiment, the power supply may be a generator.

An ingestible health sensor device according to another embodiment of the present invention is an ingestible health sensor device that is disposable in the stomach of an animal to measure a plurality of characteristics of the animal, and includes a 3-axis accelerometer and the 3-axis accelerometer. a transmitter communicatively coupled and configured to transmit measurements derived from the three-axis accelerometer to a receiver; electrically coupled to the three-axis accelerometer and the transmitter to power the three-axis accelerometer and the transmitter; a power supply; and a housing shell, wherein the three-axis accelerometer, the transmitter, and the power supply are disposed within the housing shell.

In this embodiment, further comprising a ballast weight disposed within the housing shell, wherein the ballast weight is configured to allow the health sensor device to remain movably connected with a portion of the wall of the animal's stomach. have.

In this embodiment, the portion of the housing shell is substantially cylindrical and the ingestible health sensor device comprises: a processor communicatively coupled to the three-axis accelerometer and the transmitter; and a memory communicatively coupled to the processor. further comprising a unit, wherein the memory unit includes instructions for causing the processor to control the three-axis accelerometer and the transmitter, wherein the accelerometer, the transmitter, the processor and the memory unit are substantially disposed within the housing shell. As a result, it may be disposed on a disk-shaped circuit board.

In this embodiment, it may further include an antenna communicatively connected to a substantially disk-shaped antenna substrate disposed in the housing shell, and a transmitter formed as a trace on the antenna substrate.

In this embodiment, an insulating spacer for separating the antenna from the accelerometer, the transmitter, the processor, and the memory unit may be further included.

In this embodiment, it may further include a temperature sensor communicatively coupled to the transmitter disposed within the housing shell, wherein the transmitter is configured to transmit a measurement derived from the temperature sensor to a receiver.

A method for monitoring animal characteristics according to another embodiment of the present invention is a method for monitoring animal characteristics, comprising the steps of placing an ingestible large pill in the stomach of a ruminant, wherein the ingestible health sensor device is the health sensor placing an ingestible health sensor device in the stomach of a ruminant, the ingestible health sensor device comprising a ballast weight configured to cause the device to remain movably connected with a portion of the wall of the stomach of the animal; It may include measuring the acceleration characteristic of the animal using an accelerometer, and transmitting the measured acceleration characteristic using a radio frequency transmitter disposed in the health sensor device.

In this embodiment, the acceleration characteristic may be a vector magnitude of a 3-axis acceleration measured by the accelerometer.

In the present embodiment, the acceleration characteristic may be a time derivative of a vector magnitude of a 3-axis acceleration measured by the accelerometer.

In this embodiment, the acceleration characteristic may correspond to an animal gastrointestinal contractile activity.

In this embodiment, the measured acceleration characteristic may correspond to an animal movement activity.

In this embodiment, the measured acceleration characteristic may correspond to an animal gastrointestinal contractile activity and an animal movement activity.

The health sensor device according to the embodiments of the present invention may stably secure the bioactivity data of livestock.

Since the health sensor device according to embodiments of the present invention can provide a user with an analysis result that can efficiently utilize the secured data, the user can efficiently manage livestock.

However, it is not limited only to the technical effects described above, and the scope of the present invention may be extended to other technical effects that can be inferred by those skilled in the art based on the entire contents of the present specification.

1 shows an AI device 1000 according to an embodiment of the present invention.

2 shows an AI server 2000 according to an embodiment of the present invention.

3 shows an AI system 3000 according to an embodiment of the present invention.

4 shows a health sensor system 1600 including a learning processor.

5 is a block diagram of a system for monitoring an animal according to embodiments.

6 is a block diagram of an ingestible health sensor device according to embodiments.

7 is a cross-sectional view of an ingestible health sensor device according to embodiments.

8 shows one embodiment of a first PCB 425 and a second PCB 427 .

9 shows one embodiment of an antenna PCB 534 .

Hereinafter, the embodiments disclosed in the present specification will be described in detail with reference to the accompanying drawings, but the same or similar components are assigned the same reference numbers regardless of reference numerals, and redundant description thereof will be omitted. The suffixes "module" and "part" for components used in the following description are given or mixed in consideration of only the ease of writing the specification, and do not have distinct meanings or roles by themselves. In addition, in describing the embodiments disclosed in the present specification, if it is determined that detailed descriptions of related known technologies may obscure the gist of the embodiments disclosed in the present specification, the detailed description thereof will be omitted. In addition, the accompanying drawings are only for easy understanding of the embodiments disclosed in the present specification, and the technical spirit disclosed herein is not limited by the accompanying drawings, and all changes included in the spirit and scope of the present invention , should be understood to include equivalents or substitutes.

Of course, the following examples of the present invention are not intended to limit or limit the scope of the present invention only to embody the present invention. What can be easily inferred by an expert in the technical field to which the present invention pertains from the detailed description and embodiments of the present invention is construed as belonging to the scope of the present invention.

The above detailed description should not be construed as restrictive in all respects, but rather as illustrative. The scope of the present invention should be determined by a reasonable interpretation of the appended claims, and all modifications within the equivalent scope of the present invention are included in the scope of the present invention.

In embodiments of the present invention, artificial intelligence (AI) will be described. Artificial intelligence refers to a field that studies artificial intelligence or methodologies that can make it, and machine learning refers to a field that defines various problems dealt with in the field of artificial intelligence and studies methodologies to solve them. do. Machine learning is also defined as an algorithm that improves the performance of a certain task through continuous experience.

An artificial neural network (ANN) is a model used in machine learning, and may refer to an overall model having problem-solving ability, which is composed of artificial neurons (nodes) that form a network by combining synapses. An artificial neural network may be defined by a connection pattern between neurons of different layers, a learning process that updates model parameters, and an activation function that generates an output value.

The artificial neural network may include an input layer, an output layer, and optionally a plurality of hidden layers. Each layer may include a plurality of neurons, and the artificial neural network may include neurons and synapses connecting the neurons. In the artificial neural network, each neuron may output a function value of an activation function with respect to input signals inputted through a synapse, a weight, and a bias.

Model parameters refer to parameters determined through learning, and include the weight of synaptic connections and the bias of neurons. In addition, the hyperparameter refers to a parameter to be set before learning in a machine learning algorithm, and includes a learning rate, the number of iterations, a mini-batch size, an initialization function, and the like.

The purpose of learning the artificial neural network can be seen as determining the model parameters that minimize the loss function. The loss function may be used as an index for determining optimal model parameters in the learning process of the artificial neural network.

Machine learning can be classified into supervised learning, unsupervised learning, and reinforcement learning according to a learning method.

Supervised learning refers to a method of training an artificial neural network in a state in which a label for training data is given. can mean Unsupervised learning may refer to a method of training an artificial neural network in a state where no labels are given for training data. Reinforcement learning can refer to a learning method in which an agent defined in an environment learns to select an action or sequence of actions that maximizes the cumulative reward in each state.

Among artificial neural networks, machine learning implemented as a deep neural network (DNN) including a plurality of hidden layers is also called deep learning (deep learning), and deep learning is a part of machine learning. Hereinafter, machine learning is used in a sense including deep learning.

1 shows an AI device 1000 according to an embodiment of the present invention.

The AI device 1000 shown in FIG. 1 is a TV, a projector, a mobile phone, a smartphone, a desktop computer, a notebook computer, a digital broadcasting terminal, a personal digital assistant (PDA), a portable multimedia player (PMP), a navigation device, a tablet PC, and a wearable device. , a set-top box (STB), a DMB receiver, a radio, a washing machine, a refrigerator, a desktop computer, a digital signage, a robot, a vehicle, etc., may be implemented as a fixed device or a movable device.

Referring to FIG. 1 , the AI device 1000 includes a communication unit 1010 , an input unit 1020 , a learning processor 1030 , a sensing unit 1040 , an output unit 1050 , a memory 1070 and a processor 1080 , etc. may include

The communication unit 1010 may transmit/receive data to and from external devices such as another AI device or an AI server using wired/wireless communication technology. For example, the communication unit 1010 may transmit/receive sensor information, a user input, a learning model, a control signal, and the like with external devices.

At this time, the communication technology used by the communication unit 1010 includes GSM (Global System for Mobile communication), CDMA (Code Division Multi Access), LTE (Long Term Evolution), WLAN (Wireless LAN), Wi-Fi (Wireless-Fidelity), Bluetooth (Bluetooth), RFID (Radio Frequency Identification), infrared communication (Infrared Data Association; IrDA), ZigBee, NFC (Near Field Communication), and the like. In particular, the 5G technology described above with reference to FIGS. 1 to 9 may be applied.

The input unit 1020 may acquire various types of data. In this case, the input unit 1020 may include a camera for inputting an image signal, a microphone for receiving an audio signal, a user input unit for receiving information from a user, and the like. Here, by treating the camera or the microphone as a sensor, a signal obtained from the camera or the microphone may be referred to as sensing data or sensor information.

The input unit 1020 may acquire training data for model training and input data to be used when acquiring an output using the training model. The input unit 1020 may obtain raw input data, and in this case, the processor 1080 or the learning processor 1030 may extract input features as pre-processing for the input data.

The learning processor 1030 may train a model composed of an artificial neural network by using the training data. Here, the learned artificial neural network may be referred to as a learning model. The learning model may be used to infer a result value with respect to new input data other than the training data, and the inferred value may be used as a basis for a decision to perform a certain operation.

In this case, the learning processor 1030 may perform AI processing together with the running processor of the AI server.

In this case, the learning processor 1030 may include a memory integrated or implemented in the AI device 1000 . Alternatively, the learning processor 1030 may be implemented using the memory 1070 , an external memory directly coupled to the AI device 1000 , or a memory maintained in the external device.

The sensing unit 1040 may acquire at least one of internal information of the AI device 1000 , surrounding environment information of the AI device 1000 , and user information by using various sensors.

At this time, sensors included in the sensing unit 1040 include a proximity sensor, an illuminance sensor, an acceleration sensor, a magnetic sensor, a gyro sensor, an inertial sensor, an RGB sensor, an IR sensor, a fingerprint recognition sensor, an ultrasonic sensor, an optical sensor, a microphone, and a lidar. , radar, etc.

The output unit 1050 may generate an output related to sight, hearing, or touch.

In this case, the output unit 1050 may include a display unit that outputs visual information, a speaker that outputs auditory information, and a haptic module that outputs tactile information.

The memory 1070 may store data supporting various functions of the AI device 1000 . For example, the memory 1070 may store input data obtained from the input unit 1020 , learning data, a learning model, a learning history, and the like.

The processor 1080 may determine at least one executable operation of the AI device 1000 based on information determined or generated using a data analysis algorithm or a machine learning algorithm. In addition, the processor 1080 may control the components of the AI device 1000 to perform the determined operation.

To this end, the processor 1080 may request, retrieve, receive, or utilize the data of the learning processor 1030 or the memory 1070, and perform a predicted operation or an operation determined to be desirable among the at least one executable operation. The components of the AI device 1000 may be controlled to be executed.

In this case, when the connection of the external device is required to perform the determined operation, the processor 1080 may generate a control signal for controlling the corresponding external device and transmit the generated control signal to the corresponding external device.

The processor 1080 may obtain intention information with respect to a user input, and determine a user's requirement based on the obtained intention information.

In this case, the processor 1080 uses at least one of a speech to text (STT) engine for converting a voice input into a character string or a natural language processing (NLP) engine for obtaining intention information of a natural language. Intention information corresponding to the input may be obtained.

In this case, at least one of the STT engine and the NLP engine may be configured as an artificial neural network, at least a part of which is learned according to a machine learning algorithm. And, at least one of the STT engine or the NLP engine may be learned by the learning processor 1030, learned by the learning processor of the AI server, or learned by distributed processing thereof. For reference, specific components of the AI server are illustrated in detail in FIG. 11 below.

The processor 1080 collects history information including the user's feedback on the operation contents or operation of the AI device 1000 and stores it in the memory 1070 or the learning processor 1030, or to an external device such as an AI server. can be transmitted The collected historical information may be used to update the learning model.

The processor 1080 may control at least some of the components of the AI device 1000 to drive an application program stored in the memory 1070 . Furthermore, the processor 1080 may operate by combining two or more of the components included in the AI device 1000 with each other in order to drive the application program.

2 shows an AI server 1120 according to an embodiment of the present invention.

Referring to FIG. 2 , the AI server 1120 may refer to a device that trains an artificial neural network using a machine learning algorithm or uses a learned artificial neural network. Here, the AI server 1120 may be configured with a plurality of servers to perform distributed processing, and may be defined as a 5G network. In this case, the AI server 1120 may be included as a part of the AI device 1100 to perform at least a part of AI processing together.

The AI server 1120 may include a communication unit 1121 , a memory 1123 , a learning processor 1124 , and a processor 1126 .

The communication unit 1121 may transmit/receive data to and from an external device such as the AI device 1100 .

The memory 1123 may include a model storage unit 1124 . The model storage unit 1124 may store a model (or artificial neural network, 1125 ) being trained or learned through the learning processor 1124 .

The learning processor 1124 may train the artificial neural network 1125 using the training data. The learning model may be used while being mounted on the AI server 1120 of the artificial neural network, or may be used while being mounted on an external device such as the AI device 1100 .

The learning model may be implemented in hardware, software, or a combination of hardware and software. When a part or all of the learning model is implemented in software, a plurality of instructions constituting the learning model may be stored in the memory 1123 .

The processor 1126 may infer a result value with respect to new input data using the learning model, and may generate a response or a control command based on the inferred result value.

3 shows an AI system according to an embodiment of the present invention.

Referring to FIG. 3 , the AI system includes at least one of an AI server 1260 , a robot 1210 , an autonomous vehicle 1220 , a health sensor device 1230 , a smartphone 1240 , or a home appliance 1250 or more in the cloud. It is connected to the network 1210 . Here, the robot 1210 to which the AI technology is applied, the autonomous driving vehicle 1220 , the health sensor device 1230 , the smartphone 1240 , or the home appliance 1250 may be referred to as an AI device.

The cloud network 1210 may constitute a part of the cloud computing infrastructure or may refer to a network existing in the cloud computing infrastructure. Here, the cloud network 1210 may be configured using a 3G network, a 4G or Long Term Evolution (LTE) network, or a 5G network.

That is, each of the devices 1210 to 1260 constituting the AI system may be connected to each other through the cloud network 1210 . In particular, the devices 1210 to 1260 may communicate with each other through the base station, but may also directly communicate with each other without passing through the base station.

The AI server 1260 may include a server performing AI processing and a server performing an operation on big data.

The AI server 1260 includes at least one of the AI devices constituting the AI system, such as a robot 1210, an autonomous vehicle 1220, a health sensor device 1230, a smartphone 1240, or a home appliance 1250, and a cloud network. It is connected through 1210 and may help at least some of the AI processing of the connected AI devices 1210 to 1250 .

In this case, the AI server 1260 may train the artificial neural network according to a machine learning algorithm on behalf of the AI devices 1210 to 1250 , and directly store the learning model or transmit it to the AI devices 1210 to 1250 .

At this time, the AI server 1260 receives input data from the AI devices 1210 to 1250, infers a result value with respect to the input data received using the learning model, and provides a response or control command based on the inferred result value. It can be generated and transmitted to the AI devices 1210 to 1250 .

Alternatively, the AI devices 1210 to 1250 may infer a result value with respect to input data using a direct learning model, and generate a response or a control command based on the inferred result value.

Hereinafter, various embodiments of the AI devices 1210 to 1250 to which the above-described technology is applied will be described. Here, the AI devices 1210 to 1250 shown in FIG. 3 may be viewed as specific examples of the AI device 1000 shown in FIG. 1 .

In particular, embodiments of the present invention, by using the above-described HW/SW-related element technology, etc., communication problems with other devices, efficient memory use problems, problems of lowering data processing speed due to inconvenient UX/UI, image problems , to solve at least one of acoustic problems, motion sickness, or other problems.

4 shows a health sensor system 1600 including a learning processor.

The health sensor system 1600 shown in FIG. 4 may be equipped with a learning model. The learning model may be implemented in hardware, software, or a combination of hardware and software. When a part or all of the learning model is implemented in software, a plurality of instructions constituting the learning model may be stored in the memory 1650 .

The learning processor 1670 according to embodiments of the present invention may be communicatively connected to the processor 1640 , and may repeatedly learn a model composed of an artificial neural network using training data. An artificial neural network is an information processing system in which a number of neurons called nodes or processing elements are connected in the form of a layer structure by modeling the operating principle of biological neurons and the connection relationship between neurons. Artificial neural network is a model used in machine learning, and it is a statistical learning algorithm inspired by neural networks in biology (especially the brain in the central nervous system of animals) in machine learning and cognitive science. Machine learning can be used interchangeably with machine learning. Machine learning is a branch of artificial intelligence (AI), a technology that gives computers the ability to learn without an explicit program. Machine learning is a technology that studies and builds algorithms and systems that learn based on empirical data, make predictions, and improve their own performance. Therefore, the learning processor 1670 according to embodiments of the present invention may determine the optimized model parameters of the artificial neural network by repeatedly learning the artificial neural network, and infer the result value with respect to new input data. Accordingly, the learning processor 1670 may analyze the user's device use pattern based on the user's device use history information. In addition, the learning processor 1670 may be configured to receive, classify, store, and output information to be used for data mining, data analysis, intelligent decision-making, and machine learning algorithms and techniques.

The processor 1640 according to embodiments of the present invention may determine or predict at least one executable operation of the device based on data analyzed or generated by the learning processor 1670 . In addition, the processor 1640 may request, search, receive, or utilize the data of the learning processor 1670, and the health sensor system 1600 to execute a predicted operation or an operation determined to be desirable among at least one executable operation. can control The processor 1640 according to embodiments of the present invention may perform various functions for implementing intelligent emulation (ie, a knowledge-based system, an inference system, and a knowledge acquisition system). It can be applied to various types of systems (eg, fuzzy logic systems), including adaptive systems, machine learning systems, artificial neural networks, and the like. That is, the processor 1640 predicts the user's device use pattern later based on the data analyzed by the user's device use pattern in the learning processor 1670, so that the health sensor system 1600 provides a more suitable livestock health condition to the user. You can control what you can do. Here, the XR service includes at least one of an AR service, a VR service, and an MR service.

As described above, the present invention is applicable to the AI technology field, but in the drawings below, the present invention applicable to a health sensor device will be mainly described. However, it is also within the scope of the present invention that those skilled in the art combine the drawings to be described later with reference to FIGS. 1 to 4 and implement other embodiments.

In particular, the health sensor device to be described in the drawings to be described below is sufficient as long as a device having a function of sensing conditions related to the health state of livestock is sufficient, but it is not limited to a simple health sensor device, and the AI system described in FIGS. 1 to 4 before And it is also possible to additionally perform communication according to LTE, RoLa, 5G, etc. by connecting to the user's UE (User Equipment).

5 is a block diagram of a system for monitoring an animal according to embodiments.

Referring to FIG. 5 , a block diagram 100 of one embodiment of a system for monitoring a plurality of animal characteristics is shown. In the drawing, the ingestible health sensor devices 10 and 20 may be installed inside the body of the animal. For example, the health sensor device may be made in the form of a biocapsule. The health sensor device 10 , 20 may in particular be seated in the first stomach (rumen stomach) or the second stomach (honeycomb stomach) of the ruminant animal 12 , 22 .

The health sensor device (10, 20) may be ingested through the esophagus (13, 23) of a ruminant animal (12, 22) such as cattle. The health sensor device 10 , 20 allows it to remain in the stomach of the cow 12 , 22 , such that it is regurgitated from the animal's reticulum 14 , 24 and/or rumen 15 , 25 or , it may be configured to have a size, weight, center of gravity, or density that is not discharged to the outside through the digestive system.

5 shows an ingestible health sensor device 10 in the honeycomb stomach 14 (second stomach) of a ruminant 12, such as a cow, or ingestible health in the rumen 24 (first stomach) of a ruminant 22. The sensor device 20 is shown. Hereinafter, the rumen may include the first or second stomach of a ruminant.

The health sensor devices 10 and 20 may be injected through the cow's mouth.

The health sensor devices 10 and 20 are seated in the stomach, such as the rumen, and can be easily retained without being discharged during the life of the ruminant.

The health sensor device 10 , 20 may remain on the animal's hive 14 , 24 and/or the rumen 15 , 25 throughout the life of the animal 12 , 22 .

The health sensor devices 10 and 20 may include wireless communication means that allow the health sensor device 10 to be in a wireless communication state with the base station 40 . The base station 40 may include a computing device 42 communicatively coupled with the base station 40 . Computing device 42 may be a general-purpose and/or special-purpose computing device known in the art.

Base station 40 and/or computing device 42 may be monitored by, and/or in communication with, a server manager or livestock manager.

As used herein, livestock manager may refer to any human, machine, and/or process used to manage a plurality of animals. Livestock managers may include multiple automated systems such as feeding, heating, cooling and other systems. Livestock managers may further include human livestock managers and/or veterinarians. The base station 40 and/or computing system 42 may be configured by and/or interact with the livestock manager to monitor and/or respond to changes in the health status of the animals 12 , 22 . can work

The wireless communication means of the health sensor device 10, 20 may include a wireless transmitter and/or receiver operating at 900 MHz or some other suitable radio frequency (RF).

Since the health sensor devices 10 and 20 are inserted into the body of livestock, even if a transceiver for long-distance communication is used, the attenuation of radio waves may occur greatly, and the communication distance may be greatly reduced.

For example, you can use a transceiver that supports Sub-1-GHz. The specification of the transceiver is about 6.4 km ~ 4 miles, but if the transceiver is actually installed in the body of a livestock and used for data communication, the communication distance is from several hundred meters to several meters due to radio wave attenuation due to the skin or moisture of the livestock. can be reduced to

Therefore, when the wireless repeaters (60, 62) are installed far outside the communication distance from the health sensor devices (10, 20), transmitting data from the health sensor devices (10, 20) directly to the central server through the wireless repeater is It can be difficult. In such a case, a second device may be installed in another part of the animal's body (not shown). The second device receives data from the health sensor devices 10 and 20 installed in the body of the livestock and transmits it to the wireless repeaters 60 and 62 (or a drone (not shown)) or the base station 40 can do. Examples of the second device may include a necklace, an ear-tag (not shown), and the like.

The wireless communication may be bidirectional, so that the health sensor device 10 , 20 may transmit and receive data from the base station 40 . The health sensor devices 10 and 20 may only transmit data to the base station 40 .

Animals 12 and 22 may roam over relatively large areas, such as a feed lot, a dairy, a range area, an enclosure, and the like. In this way, the distance between the base station 40 and the health sensor device (10. 20) may be greater than the wireless communication range of the health sensor device (10, 20). In this case, a plurality of wireless repeaters (60, 62) may be installed to increase the communication range of the health sensor device (10, 20) to the base station (40). The repeaters 60 , 62 may wirelessly receive livestock biodata from the health sensor device 10 , and may retransmit them at a higher power and/or other frequency so that these transmissions are received by the base station 40 . have. Similarly, in this embodiment the repeater(s) 60, 62 may receive a signal transmitting from the base station 40 to the health sensor device 10, and the repeater(s) 60, 62 may receive the signal Transmits a signal back to the health sensor device 10. 20 at a higher power, so that the health sensor device can receive the signal.

A plurality of radio repeaters (60, 62) may be placed in the vicinity of the animals (12, 22). For example, FIG. 5 shows two wireless repeaters 60 , 62 capable of wireless communication with health sensor devices 10 , 20 . When a plurality of base stations 40 and/or repeaters exist within the wireless communication range of the health sensor devices 10 and 20, the health sensor devices 10 and 20 are the base stations 40 and/or repeaters having the strongest communication signal. (60, 62) may be configured to communicate. In this embodiment, each base station 40 and repeaters 60, 62 may be configured to communicate on separate frequencies and/or channels (eg, 900 MHz) within the RF frequency range. The health sensor device 10 , 20 may be configured to receive data for each of the communication channels used by the base station 40 and the repeaters 60 , 62 to receive the strongest signal received on each channel.

When determining the best (eg, strongest signal and/or least loaded) radio communication channel (eg, repeater 60, 62 and/or base station 40), health sensor device 10, 20 Only channels can be used to transmit and/or receive data. The health sensor device 10 , 20 may allow the health sensor device 10 , 20 to adapt to changes in animal position and/or changes in signal strength and/or configuration of the base station 40 and/or repeaters 60 , 62 . It can be configured to periodically re-evaluate the available channels for When the health sensor device 10 goes out of communication range with any one of the repeaters 60, 62 and the base station 40, the health sensor device 10, 20 stops the transmission, and the repeaters 60, 62 and / or may be configured to transmit a message searching for the base station 40 .

Figure 5 shows two health sensor devices (10, 20) and two wireless repeaters (60, 62), the animal monitoring system according to the present embodiment, the above-described wireless repeaters (60, 62), animal 12 , 22) and/or health sensor devices 10 and 20 are not limited, and may include various embodiments in the number or configuration.

The health sensor device 10 , 20 may include a plurality of sensors to detect a plurality of characteristics of the animal 12 , 22 . In this embodiment, the health sensor device 10. 20 may wirelessly transmit data corresponding to the monitored animal characteristics to the base station 40 . The monitored animal characteristics may include physiological characteristics such as the animal's rumen temperature, gastrointestinal pH, blood pH, heart rate, respiration, gastrointestinal contraction, gastrointestinal activity, and the like. The monitored animal characteristics may also include non-physiological characteristics such as movement of the animal itself and/or the position of the animal via GPS information.

The base station 40 uses the wireless communication characteristics of the health sensor device 10 , 20 between the base station 40 and/or the wireless repeater(s) 60 , 62 , to locate the animal 12. 22 . information can be obtained. In embodiments employing a single base station 40 , the base station 40 may obtain the distance of the animals 12 , 22 from the base station 40 .

As such, the method for determining the distance may include methods such as determining a distance value based on one radio signal strength or determining a distance from timestamp information in a radio message, and the present invention is not limited thereto. It may include embodiments that determine the distance in a variety of ways.

As shown in FIG. 5 , the system may include a plurality of base stations 40 and/or wireless repeater(s) 60 , 62 . In this case, the base station 40 may determine position information about the animals 12 , 22 using well-known wireless communication triangulation methods.

6 is a block diagram illustrating an ingestible health sensor device according to embodiments of the present invention.

Components of the health sensor device 210 may be disposed within the housing 205 . The housing 205 may be formed of any material capable of remaining in the stomach of an animal without degradation and/or decomposition. Further, the housing 205 may be formed of a material that does not cause adverse effects in the animal when installed in the animal (eg, in the rumen or honeycomb of the animal). For example, the housing 205 may be formed of a material such as non-toxic plastic or corn.

The health sensor device 210 may include a plurality of sensors 220 configured to measure a plurality of animal characteristics. The plurality of sensors 220 may include distance traveled by the animal; animal movement frequency; the speed of the animal's movement; etc. may be measured, and embodiments are not limited thereto, and movement and/or activity characteristics of the animal may be detected. For example, the accelerometer 221 may be used to detect movement and/or locomotor activity characteristics of the animal's stomach. The accelerometer 221 is a 3-axis or 6-axis accelerometer capable of detecting movement of an animal and/or amount of gastrointestinal activity in each of the Cartesian coordinate "x", "y" and "z" axes. can The health sensor device 210 may change orientation while in the animal (eg, in the animal's rumen and/or in the honeycomb). Thus, detecting animal movement and/or gastrointestinal activity in only one or both axes may yield inaccurate results.

The acceleration vector magnitude (VM) value can be calculated from the value measured with the 3-axis accelerometer by calculating the square root of the sum of the squares of each of the "x", "y" and "z" coordinate axes as shown in Equation 1.1 below. can

(Equation 1.1)

Equation 1. The derivative of 1 vector magnitude (VM) can be approximated by calculating the absolute value of the difference between the preceding vector value and the subsequent vector magnitude values, as shown in Equation 1.2.

(Equation 1.2)

The acceleration differential calculated according to Equation 1.2 can remove the error rate caused by movement caused by shaking of the health sensor device 210 itself in the animal's stomach or other acceleration forces (eg, gravity) acting on the animal. Therefore, it is useful when monitoring animal characteristics. Thus, the differentiation of the vector magnitude of the animal's motion and/or gastrointestinal activity may provide an accurate value of the animal's actual motion and/or gastrointestinal activity characteristic.

In addition to detecting animal movement and/or gastrointestinal activity, accelerometer 221 may be configured to detect gastrointestinal contractions. Since the health sensor device 210 can be placed in the animal's stomach (eg, in the rumen or honeycomb of a ruminant), the health sensor device 210 can be affected, such as moving by the animal's stomach contractions. have. In this case, the health sensor device 210 may be configured to have sufficient weight and/or density to allow the health sensor device 210 to be retained in the lower portion of the animal's stomach and/or to be moved and positioned against the wall of the animal's stomach. .

The health sensor device 210 coupled to move like the stomach of an animal is a health sensor device ( 210) by matching and correcting the movements, the values may be referred to for extracting the movement values of the stomach.

For example, a typical ruminant, in a normal state of health, can make three stomach contractions every minute during rumen activity, ie for 20 seconds each time.

Non-rumination time may indicate an animal health condition in which the animal no longer feeds and/or intermittently.

Thus, an administrator can detect when an animal becomes “non-ruminant” by observing a change and/or a decrease in the frequency of the animal's gastrointestinal contractions.

An extended period of time for an animal to be "non-rumination" can indicate a serious health condition.

Animals may also exhibit "non-rumination" before unusual health-state symptoms (eg increased/decreased movement or temperature) appear.

According to embodiments, the health sensor device 210 may include a plurality of sensors 220 that may determine the location of the health sensor device 210 , such as a location measurement system (GPS) receiver. The GPS receiver may be used to detect the position of the animal, and the movement of the animal, and/or the activity characteristics of the animal.

The plurality of sensors 220 of the health sensor device 210 according to embodiments may include: body temperature; heart rate; Breath; gastrointestinal contractions; stomach pH; blood pH; etc. may be measured, but the present invention is not limited thereto, and any number of sensors 220 may be configured to detect physiological characteristics of other animals.

For example, the temperature sensor 222 may be used to detect the animal temperature. The temperature sensor 222 may include a thermistor, a thermocouple, or a platinum resistance thermometer, or the like.

The health sensor device 210 may include a communication module 230 . The communication module 230 may include a transceiver 231 for wireless communication. The transceiver 231 may transmit and receive data via a single antenna (not shown) or a separate transmitter antenna 233 and receiver antenna 235 . As such, the transmitter 231 may include an active data transmitter 232 and a data receiver 234 . The active data transmitter 232 may be communicatively coupled to a transmitter antenna 233 . The transmitter antenna 233 may be disposed on its surface within the housing 205 of the health sensor device 210 , or it may be disposed outside the housing 210 of the health sensor device 10 . The data receiver 234 may be communicatively coupled to a receiver antenna 235 . The receiver antenna 235 may be disposed on its surface within the housing 205 of the health sensor device 210 or may be disposed outside the housing 210 of the health sensor device 10 . Transmitter antenna 233 may transmit data at 900 MHz and receiver antenna 235 may receive data at 900 MHz or some other suitable frequency. In another embodiment, the transmitter antenna 233 and the receiver antenna 235 may be configured as a single antenna (not shown) used for both data transmission and reception.

The health sensor device 210 may include a processor 240 communicatively coupled to the memory unit 250 . In one embodiment, memory unit 250 may include machine readable instructions 252 stored therein. In this embodiment, the processor 240 may read and execute the machine readable instructions 252 stored in the memory unit 250 . The machine readable instructions 252 may include: a polling and/or sampling frequency of one or more sensors 220; the transmission frequency of the communication unit 230; correction information for the plurality of sensors 220; may include, but are not limited to. The machine readable instructions 252 may comprise data measured at the health sensor device.

The processor 240 may be communicatively coupled to each of the sensors 220 . Machine readable instructions 252 stored in memory unit 250 may specify a sensor sampling frequency for each of sensors 220 . The sensor sampling frequency may determine how often sensor readings are obtained from a particular sensor 220 . For example, the sensor sampling frequency may define how often the temperature sensor 222 obtains a temperature sensor reading or sensor sample from an animal. The processor 240 may configure the plurality of sensors 220 with a sensor sampling frequency specified by the machine readable instructions 252 . Alternatively, the plurality of sensors 220 may be communicatively coupled to the memory unit 250 and configured to read the sensor sampling frequency directly from the machine readable instructions 252 .

The machine readable instructions 252 may specify a sensor reading duration for each of the sensors 220 . The sensor reading duration may limit the length of time that a particular sensor 220 may obtain a reading. For example, the reading duration may define how long the accelerometer 221 reads the animal's movement and/or motor activity characteristics. The reading duration may specify that the accelerometer 221 should read animal movement and/or motor activity characteristics for one minute each time a sensor sample is taken. The processor 240 may configure the plurality of sensors 220 with a sensor read duration specified by the machine readable instructions 252 .

The plurality of sensors 220 may be communicatively coupled to the memory unit 250 and configured to read their sensor read durations directly from the machine readable instructions 252 .

The machine readable instructions 252 may specify calibration information for the plurality of sensors 220 .

A plurality of sensors 220 according to embodiments may be tested to determine if correct readings are returned.

If a particular sensor 220 does not return an accurate reading, correction data may be stored in the memory unit 250 to adjust the reading to an accurate value.

The sensor 220 may be communicatively coupled to the memory unit 250 to enable the sensor 220 to read calibration data therefrom.

The sensor 220 may itself include a memory storage location where such correction information may be stored.

The machine readable instructions 252 can instruct the processor 240 to transfer the sensor calibration data stored in the memory unit 250 to a memory storage location of a particular sensor 220 .

In other embodiments, the sensor 220 may not include a memory storage location and may not be able to read the memory unit 250 . As such, the machine readable instructions 252 may configure the processor 240 to apply the calibration data stored in the memory unit 250 to the reading returned by the sensor 220 .

The machine readable instructions 252 may specify that the plurality of sensors 220 should be deactivated to reduce power consumed by the health sensor device 210 . The processor 240 may be communicatively coupled to the sensors 220 , and may configure and/or control the plurality of sensors 220 . The machine readable instructions 252 may specify that the plurality of sensors 220 should be re-activated.

The processor 240 may be communicatively coupled to the sensor 220 and may control the operation and configuration of the sensor 220 . The processor 240 may poll the plurality of sensors at a polling interval (ie, a polling frequency) specified by the machine readable instructions 252 stored in the memory unit 250 , ie, check whether there is a transmission request.

Polling may be a centralized multiple access control method. For example, it is a kind of multiple access control method in which the central controller 'sequentially or periodically checks' devices sharing one communication line (usually one output line) to check whether they have data to transmit. .

For example, a polling interval may be a period of time in a data collection system that requests data from one particular data source. Polling the sensors may mean obtaining measurement data from the plurality of sensors 220 . In polling the sensor, the processor 240 transmits a transmission request to the sensor 220 , and in response to the transmission request, the sensor 220 returns the sensor reading value obtained in advance to the processor 240 , that is, in response This may include sending For example, the temperature sensor 222 may respond to the poll by reading and returning the animal's current temperature.

In another embodiment, polling the sensor 220 may cause the processor 240 to read the current sensor value from the sensor 220 .

In another embodiment, the plurality of sensors 220 may be configured to store sensor measurements in the memory unit 250 . The plurality of sensors 220 may be configured with a sensor sampling frequency greater than the polling frequency of the processor 240 (the frequency of requesting a measurement data value) (in a structure of measuring more frequently). That is, the sensor 220 may store a plurality of sensor samplings in the memory unit 250 between polling intervals of the processor 240 . Accordingly, polling the sensor 220 may include the processor 240 reading all sensor readings stored in the memory unit 250 for each of the plurality of sensors 220 .

In another embodiment, the sensor 220 may include a memory storage location for storing sensor samples. Here, the polling may be that the processor 240 reads the sensor 220 storage location. In another embodiment, the sensor 220 may be a sensor that reads a duration, which may be such that the sensor 220 measures an animal characteristic over time, such as an accelerometer ( 221) may be.

The sensor 220 may store such measurements in an internal sensor storage location or in a memory unit 250 (hereinafter, memory). Processor 240 may poll such a sensor by reading an internal storage location of memory 250 or sensor 220 . In this embodiment, the processor 240 may be configured to pre-process the measurement data prior to transmission. Such pre-processing may include calculating measurement characteristics such as mean, standard deviation, etc., compressing data, and the like. As such, pre-processing may reduce the amount of data transmitted to a base station (not shown), thereby reducing power and RF transmission requirements.

In addition to transmitting the animal characteristics obtained by the sensors 220 , the plurality of health sensor devices 210 may have power available in the power source 260 (eg, monitored by the power monitor 266 ). and the state of the sensor 220 , the processor 240 and/or the memory unit 250 , the state of the health sensor device 210 , and the like.

The base station (not shown) may use this state information to warn the animal manager of a problem that may occur in the health sensor device 210 (eg, when the power source 260 is running out, etc.). have.

Health sensor device 210 may include sensors 220 having any number of sampling or measurement storage techniques, and processor 240 is configured to poll sensors 220 having such various sampling or measurement storage techniques. It should be understood that it may be configured by machine readable instructions 252 .

Machine readable instructions 252 may specify a polling frequency for each sensor 220 , or may specify a common polling interval for all or a sub-set of sensors 220 . The polling frequency used herein may specify how often the processor 240 polls the plurality of sensors 220 .

In one embodiment, the machine readable instructions 252 may define conditions under which the polling frequency associated with the plurality of sensors 220 may change. For example, the machine readable instructions 252 can instruct the processor 240 to increase the polling frequency and/or the sensor sampling frequency of the temperature sensor 222 when the animal temperature exceeds a threshold value. The machine readable instructions 252 may instruct the processor 240 to decrease the polling frequency and/or the sensor sampling frequency of the temperature sensor 222 if the animal's temperature remains below a threshold value. Processor 240 applies polling frequency and/or sensor sampling frequency to changing animal health conditions so that potential health risks and/or other changes in animal health conditions can be recognized as quickly as possible while minimizing external sensor measurements and message transmission. can do.

The frequency of sensor 220 polling transmissions may be configured to vary with the location of the animal. For example, the processor 240 may increase the polling and/or transmission frequency when the animal is in the vicinity of a carving pen and/or in the vicinity of a hospital pen. Reduce the frequency of polling and/or transmission when the animal leaves the pen.

The sensor polling frequency and/or transmission frequency may be configured to vary according to an animal schedule. For example, the health sensor device 210 may be configured to transmit measurements during animal milking time (eg, 3 times a day). Time information for this time-dependent command 252 may be provided by a real-time clock (RTC) 270 .

The processor 240 may transmit the sensor measurement value obtained by the polling sensor 220 through the data transmitter 232 . In one mode of operation, when sensor 220 readings are obtained (after polling multiple sensors 220 ), the processor 240 may form a message containing the measurements. These messages may be referred to as animal characteristics messages and may consist of sensor readings obtained by polling a plurality of sensors 220 .

Because sensor readings are sent when polled by processor 240 , this mode of operation may be referred to as an “instantaneous” mode. In another mode of operation, the processor 240 may not immediately transmit the polled sensor readings from the sensor 220 , but instead stores them in the memory unit 250 . In this mode, the machine readable instructions 252 may specify transmission intervals and the processor 240 may transmit an animal characteristic message including some or all of the measurements stored in the memory unit 250 at each transmission interval.

This mode of operation may be referred to as a “burst” mode because the sensor 220 readings are sent as periodic bursts rather than when sensor polling occurs. Operating in “burst” mode may reduce the power consumed by the health sensor device 210 by reducing the number of transmissions sent from the data transmitter 232 .

The message sent via the data transmitter 232 of the communication module 230 may include a medium access control (MAC) value. The MAC may be a 6 or 3 byte value used to uniquely identify a message originating from a particular health sensor device 210 . The MAC address may also be used by the data receiver 234 and/or the processor 240 to identify a message intended for the health sensor device 210 . As such, receiver 234 and/or processor 240 may ignore any incoming message with a MAC address other than itself, thereby reducing wireless traffic between health sensor device 210 and a base station or other wireless device. Eliminates the need to time-slice or otherwise manage. MAC addressing for routing and controlling network messages is generally known within networking technology.

In one embodiment, a programmable unique animal identifier (UAID) may be stored in the memory unit 250 . In this embodiment, the UAID may be used to associate the health sensor device 210 with a particular animal. The UAID value may be transmitted along with some or all of the messages originating from the particular health sensor device 210 such that these messages Allows the receiver of the system to associate the received data with a specific animal.

In one embodiment, the memory unit 250 of the health sensor device may include read-only storage 254 . Read-only storage 254 includes programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), and the like. can do. In this embodiment, the unique health sensor device identifier (UBID) may be stored in read-only storage 254 . The UBID value may be transmitted together with some of all messages transmitted from the health sensor device 210 . In this embodiment, the UBID may provide a tamper-resistant identifier to uniquely identify a particular health sensor device 210 . As used herein, “animal identifier” or “health sensor device identifier” may refer to any of the animal and/or health sensor device identifier values described above.

The communication module 230 may detect whether the health sensor device 210 is within range of a receiver, such as a base station (not shown) or a transceiver (not shown).

The processor 240 may cause the communication module 230 to transmit a simple message at a set interval. This simple message may be referred to as a “ping” and may include a plurality of unique identifiers (eg, MAC, UAID and/or UBID) associated with a particular health sensor device 10 .

The base station or transceiver receiving the ping message may be configured to send a short response message to the processor 240 indicating that the ping message has been received. The processor 240 may know that the health sensor device is within the radio range of the base station or transceiver. When the health sensor device 210 receives the response message, the health sensor device 210 may be configured to be in an “online” mode.

If the health sensor device 210 does not receive the response message within the threshold time period, it may additionally transmit a ping message. When a threshold number of retries or ping messages are sent without a response, the health sensor device 210 may be configured to be in “offline” mode. The machine readable instructions 252 may include instructions executed by the processor 240 corresponding to “online” and/or “offline” modes.

Meanwhile, according to embodiments, the communication unit 230 may be configured to receive, rather than send, a ping discovery message. A base station (eg, base station 40 of FIG. 5 ) may be configured to send periodic ping messages. Upon receiving one of these messages via the communication unit 230, the processor 240 may cause the health sensor device 210 to operate in an “online” mode, and if no ping message is received for a threshold period of time, The health sensor device 210 may be operated in “offline mode”. This may allow the health sensor device 210 to conserve power and reduce RF interference potentially caused by sending periodic ping messages.

The health sensor device 210 may transmit animal characteristic messages at the “online” transmission frequency specified by the machine readable command 252 . As described above, these messages may be transmitted when the processor 240 polls the sensor 220 , or may be transmitted at periodic transmission intervals. The recipient of such a message may be configured to respond with an acknowledgment message. The confirmation message may be used instead of a separate ping message to reduce message traffic between the health sensor device 210 and the receiver.

In “offline” mode, health sensor device 210 may reduce the frequency of sending messages according to machine readable instructions 252 . Additionally, while in “offline” mode, machine readable instructions 252 may instruct processor 240 to disable certain sensors 220 to conserve power. In the “offline” mode, the health sensor device 210 may continue to send a “ping” message to discover when the health sensor device 210 returns within range of a base station or transceiver unit. In this sense, the data transmitter ( ( 232) can be considered as an active transmitter. Health sensor device 210 may actively transmit animal characteristics and/or detect wireless communication without requiring a query by an external source.

In one embodiment, the health sensor device 210 may receive the new and/or modified machine readable instructions 252 via the data receiver 234 of the wireless communication module 230 . These received commands may include: sensor sampling frequency; sensor reading duration; sensor activation status; sensor calibration data; processor polling frequency; may include changes to the operation of the sensor 220 and/or the processor 240, including the processor mode of operation (ie, “instantaneous” or “burst”; etc.).

The embodiment of FIG. 6 includes a communication module 230 , a processor 240 , and a memory unit 250 including a power source 260 , a data transmitter 232 and a data receiver 234 coupled to each sensor 220 . ) and any other power consuming components of the health sensor device 210 . The power source 260 may include a battery energy storage device 262 such as a lithium ion battery, a lead battery, a nickel cadmium battery, or the like. In another embodiment, the power source 260 may include a generator 264 . Generator 264 may include a piezoelectric generator or a mass/alternating power source generator that generates power from movement and/or motor activity or vibration of the health sensor device 210 within the host animal. In another embodiment, the generator 264 may be a heat-activated generator for generating electrical energy from the body heat of the host animal. Generator 264 may include a microbial fuel cell (MFC) configured to generate electrical energy derived from bacteria that is supplied to organic material in the animal's stomach (ie, rumen or honeycomb). The generator 264 may be disposed outside the health sensor device housing 205 . Power source 260 may include both battery power storage 262 and generator 264; In this embodiment, the power generated by the generator 264 may be stored in the battery power storage 262 .

Power source 260 may include a power monitor 266 that may be used to monitor power and/or voltage levels of battery power storage 262 and/or generator 264 . Power monitor 266 may provide power status information to processor 240 and/or communication unit 230 . The communication unit 230 may transmit power state information to a base station (not shown), and the processor 240 may invoke a plurality of power-saving operations using the power state information provided by the power monitor 266 . have. For example, power monitor 266 may detect a low power condition in power storage 260 (eg, in battery power storage 262 and/or generator 264 ). In response to the detection, the processor 240 may invoke a plurality of power-saving operations defined by the machine readable instructions 252 of the memory unit 250 , which power-saving operations are performed by the health sensor device 210 . reducing the polling and/or transmission frequency of deactivating the plurality of sensors 22 ; etc., but are not limited thereto.

The power source 260 may include a voltage regulator 268 . Voltage regulator 268 provides normal input voltage levels for components of health sensor device 210 (eg, sensor 220 , communication unit 230 , processor 240 , memory unit 250 , etc.) can be configured to maintain Voltage regulator 268 may maintain a relatively constant voltage despite fluctuations in voltage levels generated by battery power storage 262 and/or generator 264 . Voltage regulator 268 may include any voltage regulator implementation known in the art, including a shunt regulator, such as a Zener diode, avalanche breakdown diode, or voltage regulator tube; linear regulator; switching regulator; Silicon Controlled Regulator (SRC); hybrid regulator; etc., but are not limited thereto.

The health sensor device 210 may further include a real-time clock 270 communicatively coupled to the processor 240 . The real-time clock 270 may be used to provide time information to the processor 240 . This time information may be used to perform a plurality of time-dependent operations defined by machine readable instructions 252 . For example, some monitoring tasks, such as movement monitoring, may be time-dependent (eg, movement may not be monitored while the animal is asleep or at rest). Thus, the animal motion sensor may be deactivated at a specific time. The machine readable instructions 252 may also indicate that the health sensor device 210 should be shut down at a specific time to save power, transmit animal characteristics at a specific time, and the like. Time information from the real-time clock 270 enables the processor 240 to properly execute such time-dependent instructions 252 .

Referring back to FIG. 5 , a plurality of health sensor devices 10 and 20 may wirelessly communicate with the base station 40 . In this way, the health sensor devices 10 and 20 may periodically transmit an animal characteristic message to the base station 40 . The base station 40 may be communicatively coupled to, and/or include, a general purpose and/or special purpose computing device 42 . Such computing device 42 may be configured to generate a plurality of animal profiles associated with a plurality of animals 12 , 22 . Such a device may also be configured to compare any animal characteristic message to a plurality of stored animal profiles.

As a result of this comparison, the computing device 42 modifies the configuration of the health sensor device 10 , 20 (eg, modifies the polling frequency, sample time, transmission time, etc. of the health sensor device 10 , 20 ). ) and detect the health status of the animal 12, 22 (eg, the estrous and/or feeding status of the animal 12, 22), the animal 12, 22 or group of animals, etc. Profile and/or baseline characteristics may be established.

7A to 7D are cross-sectional views of ingestible health sensor devices according to embodiments.

The health sensor device 310 may include a substantially hollow housing shell 305 . A portion of the housing shell 305 may be substantially cylindrical. As noted above, the housing shell 305 may be formed of any material capable of withstanding the ruminant's gastrointestinal environment. Further, the material of the housing 305 may be formed of a non-toxic material so as not to significantly adversely affect the host animal during placement in the animal's stomach.

The housing shell 305 may be configured to be openable at the shell end 306 . The cap 307 may be configured to engage within the end 306 of the shell 305 . The cap 307 may include a member 309 at the end 306 to securely engage the inner wall of the shell 305 . As such, the cap 307 can be tightly compression-fit over the shell 305 . In another embodiment, the cap 307 may include a friction fit mechanism, a screw fit mechanism (eg, a thread disposed on the inner surface of the shell 305 and the insert 309 ), an adhesive, a plastic. It may be secured to the shell 305 using welding or the like. The cap 307 may be removed to allow access to components disposed within the housing 305 .

The end 303 of the shell 305 may be sealed. As such, a ballast weight 315 may be disposed therein. Hereinafter, the ballast weight 315 may be used interchangeably as a weight, and the weight and the ballast weight may refer to the same member.

7 (a) to (d), the ballast weight 315 may be composed of a plurality of substantially spherical weights (eg, bearings, BB bullets, etc.). The weight 315 may be made of a material having a solid shape. The weight 315 may be configured such that when the health sensor device 310 is disposed in the stomach of the animal, the health sensor device 310 may be substantially maintained in a seated state on the bottom portion of the stomach.

The weight 315 of the health sensor device 310 according to embodiments may be configured only at one end of the health sensor device 310 as shown in (a) or (b) of FIG. 7, (c) of FIG. ) can be configured only in the center.

In order for the health sensor device 310 to have more stability and to be attached parallel to the stomach floor and move together with the stomach wall, a weight 315 is attached to both ends of the health sensor device 310 as shown in FIG. It can also be configured. In addition, instead of the ballast weight 315, the power source 360 shown in the drawing disposed on a line connected thereto may be replaced with a larger power source. That is, the ballast weight 315 may be removed, and a larger power source 360 may be configured instead of the ballast weight 315 and the power source 360 as a component including the space.

According to embodiments, the health sensor device 310 may maintain a seated state in contact with a portion of the gastrointestinal wall. As such, the health sensor device 310 detects that an acceleration sensor of the health sensor device 310 (eg, component 321 of FIG. The health sensor device 310 may be seated so that it can be detected. That is, the ballast weight 315 of the health sensor device 310 can be configured so that the health sensor device 310 can be seated in a form coupled to the stomach wall so that the acceleration sensor can move with the stomach wall. have.

In order for the health sensor device 310 according to embodiments to be configured to contact the lower portion of the wall of the stomach, the weight 315 is configured such that the health sensor device 310 is generally fluid and/or food within the stomach of the host animal. It may be composed of a member having a higher density to have a higher density.

The health sensor device 310 may also be applied to the health sensor device 210 of FIG. 6 , and may be coupled to move like the stomach of an animal as described above.

In some embodiments, the weight 315 may be constructed of a metal material that may be magnetized (eg, iron, steel, etc.).

When the weight 315 according to the embodiments is magnetic in the stomach of the animal, the health sensor device 210 may be configured to attract and receive substances attracted to the magnet (not shown). In this way, the health sensor device 310 can act as a cow magnet to prevent potentially hazardous objects (eg, nails, tacks, etc.) from passing through the digestive system of the host animal.

The health sensor device 310 may be configured by attaching a message label 316, but in general, when the health sensor device 310 is put into cattle, the message label 316 is removed and separated (eg, in FIG. 7 (b) to (d)), the health sensor device 310 may be put into the cow.

The message label 316 may include an ID capable of identifying the health sensor device 310 . The message label 316 is attached to a predetermined position of the housing shell 305, so that if the service provider turns on (wake-up) the health sensor device using a member such as a magnet, the magnetic member may be contacted. A message label 316 may be affixed to an indicator position so that an appropriate position can be easily found.

For example, if the message label 316 is to be left on the health sensor device without being removed, the housing shell 305 may be made of a substantially transparent material, and the message label 316 may be placed inside the housing shell 305 . It may be arranged in the part so that the information written therein can be read from the outside. With this configuration, it is possible to prevent the label 316 from being deteriorated by acid and/or abrasion when the health sensor device 310 is placed in the stomach of the animal.

The message label 316 may be formed on the inner surface or the outer surface of the housing shell 305 during manufacturing. For example, the information included in the message label 316 may be configured in the form of etching and/or embedding in the surface inside and outside the housing shell 305 . When the health sensor device 310 is returned to the animal manager and/or manufacturer, the health sensor device 310 may be regenerated, upgraded, disposed of, and/or relocated according to the information in the message label 316 .

The power source 360 may be disposed within the shell 305 of the health sensor device 310 . As described above with respect to FIG. 2 , the health sensor device 310 provides power to electrical components (eg, sensor 320 , communication module 330 , processor 340 , memory unit 350 , etc.). A power source 360 for supplying may be included. The power source 360 includes a lithium ion battery; lithium polymer batteries; lead acid batteries; energy storage means including, but not limited to, nickel-cadmium batteries, alkaline batteries, capacitors, high capacity capacitors, supercapacitors, and the like. Power source 360 may include means for generating power, such as piezoelectric generators, thermal energy generators, MFC generators, motion and/or motion active generators, and the like. The power source 360 may comprise a combination of energy storage means and energy generating means for generating and/or supplying power to the health sensor device 310 . Those skilled in the art will recognize that any power source may be used under the teachings of this disclosure. As such, this disclosure should not be construed as limited to any particular power source 360 implementation.

In the embodiment of FIG. 7 , the power source 360 may include a substantially cylindrical battery energy storage device 360 having a diameter configured to be rigidly secured within an inner wall of the housing shell 305 .

The health sensor device 310 may include an insulator 317 disposed between a power source 360 and first and second printed circuit boards (PCBs) 325 , 327 . 3 depicts 325 and 327 as PCBs, those skilled in the art will recognize that any circuit substrate may be used under the teachings of the present disclosure. As such, this disclosure should not be construed as limited to any particular circuit board material. As used herein, a substrate may refer to any support material from which circuitry is formed or manufactured. The insulator 317 protects the circuitry disposed on the first PCB 325 from the power source 360 and/or prevents unwanted electrical connections between the circuitry of the PCBs 325 and 327 and the energy storage device 360 . can be prevented (eg, to prevent short circuits, etc.).

Power source 360 may be electrically coupled to electrical components of health sensor device 310 via voltage regulator 368 and power monitor 366 . As described above, the power monitor 366 may be configured to monitor the power and/or voltage level of the power storage device 360 to detect a low-power condition of the power storage device 360 . The power level information obtained by the power monitor 366 may be provided to the processor 340 and/or the communication unit 330 . The voltage regulator 368 provides a constant voltage input to the electrical components of the health sensor device 310 despite fluctuations in the voltage level of the power storage 360 .

Electrical components of the health sensor device 310 may be disposed on the first PCB 325 and the second PCB 327 . In embodiments that use fewer and/or smaller sized circuit components, the health sensor device 310 may include a single PCB. The first and second PCBs 325 , 327 may be substantially flat and substantially disk-shaped. The diameters of the first and second PCBs 325 , 327 disks may be configured such that the first and second PCBs 325 , 327 fit within the inner wall of the housing shell 305 .

The first PCB 325 may be coupled to the second PCB 327 using a prong 329 . The hook 329 may be disposed along the outer diameters of the first and second PCBs 325 and 327 to couple the first PCB 325 to the second PCB 327 . The plurality of prongs 329 act as vias to provide electrical communication between circuitry disposed on the first and second PCBs 325 , 327 .

Electrical components of the health sensor device 310 may be disposed on first and second PCBs 325 , 327 , with electrical communication therebetween being on PCBs 325 , 327 and/or hooks 329 . It may be provided by a plurality of PCB traces arranged. The electrical component may include a plurality of sensors 320 including an accelerometer 321 and a thermistor 322 . The accelerometer 321 may be a three-axis accelerometer. Thermistor 322 may be configured to detect an internal temperature of the animal (eg, the temperature of the stomach). The electrical component may further include a communication module 330 , a processor 340 , and a memory unit 350 . The communication module 330 may include a transceiver 331 . The transceiver 331 may transmit and receive data wirelessly using the antenna 333 .

As described above, although not shown in FIG. 7 , the health sensor device 310 includes an electrical connection between the power source 360 and the first and/or second PCBs 325 , 327 , including the health sensor device ( Power may be supplied to a circuit (eg, the sensors 320 and 321 , the communication module 330 , the processor 340 , the memory unit 350 , etc.) disposed in the 310 . A power connection (not shown) may pass through a voltage regulator 368 to regulate the input voltage of an electrical component of the health sensor device 310 . In addition, the power monitor 366 may monitor the power and/or voltage level of the power supply 360 .

A substantially disk-shaped insulator and/or cushion member 331 may be disposed between the first and second PCBs 325 , 327 and the transmitter antenna PCB 334 . The insulating cushion part 331 may provide a cushion between the first and second PCBs 325 and 327 and the antenna 333 . In addition, the cushion part 331 may act as a spacer for separating the antenna 333 from circuits disposed on the first and second PCBs 325 and 327 . This spacing may reduce radio frequency (RF) interference and/or capacitive coupling between the antenna 333 and circuitry on the PCBs 325 , 327 .

The antenna 333 may be disposed on the antenna PCB 334 . As such, the antenna 333 may be configured with a plurality of traces on the antenna PCB 334 . This may allow the antenna 333 to be precisely positioned on the antenna PCB 334 . Also, forming the antenna 333 as a trace on the antenna PCB 334 allows the antenna 333 to deform within the housing shell 305 due to movement of the health sensor device 310 within the animal or otherwise change its orientation. It can be guaranteed not to change. Antenna 333 may be used by communication unit 330 and transceiver 331 to transmit and receive data wirelessly (eg, on an RF carrier).

The health sensor device 310 may further include padding (not shown) disposed between the antenna PCB 334 and the cap 307 and the cap insert 309 . This padding (not shown) may be used to secure the components 315 , 317 , 325 , 327 , 331 , 334 and 360 within the housing shell 305 of the health sensor device. In some embodiments, cap 307 and cap insert 309 may be hollow. In this case, the padding (not shown) is a cap (not shown) to secure the components 315, 317, 325, 327, 331, 334 and 360 of the health sensor device 310 within the housing shell 305 of the health sensor device. 307 ) and to fill the hollow area of the cap insert 309 .

FIG. 8 shows one embodiment of a first PCB 425 and a second PCB 427 . The first PCB 425 and the second PCB 427 may be substantially disk-shaped. The diameter of the first PCB 425 and the second PC 427 is that of the housing shell 305 of the health sensor device 310 together with the component 305 of FIG. It may be configured to fit within the inner wall. The first PCB 425 may be coupled to the second PCB 427 using a member 429 (hereinafter, referred to as a prong) in the form of prongs. The hook 429 may be disposed on the outer portion of the first and second PCBs 425 , 427 . A portion of the hook 429 provides electrical communication between a component disposed on the first PCB 425 (not shown) and a component disposed on the second PCB 427 (not shown).

9 shows one embodiment of an antenna PCB 534 . The antenna PCB 534 may include a notch 537 that allows the conductor 539 to contact the antenna 533 . The notch 537 may be used when the diameter of the antenna PCB 534 is approximately equal to the inner diameter of the shell (not shown) of the health sensor device. In this case, the conductor 539 can only reach the antenna PCB 534 through the notch 537 . The antenna 533 may consist of one or a plurality of traces disposed on the antenna PCB 534 made of one or more layers. 9 shows the antenna 533 as a single trace, but is not limited thereto. A plurality of antennas 533 may be formed on the antenna PCB 534 .

As such, this disclosure should not be construed as limited to the configuration and/or orientation of any particular antenna 533 . It will be apparent to those skilled in the art that many changes can be made in the details of the above-described embodiments without departing from the basic principles of the invention. Accordingly, the scope of the present invention should be determined solely by the following claims.

The present invention can be used in methods and systems for measuring digestibility in animals.

Claims (25)

1. An ingestible health sensor device (bolus) disposable in the stomach of an animal for measuring a plurality of characteristics of the animal, comprising:

   sensors for measuring animal characteristics;

   a transmitter communicatively coupled to the sensor for transmitting the measured animal characteristic to a receiver;

   a power source in electrical communication with the sensor and the transmitter to power the sensor and the transmitter; and

   Intakeable health sensor device comprising a ballast weight (ballast weight) so that the health sensor device is seated in the lower part of the stomach.
2. The method of claim 1,

   The ballast weight is a magnetized, ingestible health sensor device.
3. The method of claim 1,

   The ballast weight is configured so that the health sensor device is seated in contact with a portion of the wall of the stomach of the animal and is coupled to move along with the movement of the wall of the stomach.
4. 4. The method of claim 3,

   The sensor is an acceleration sensor, an ingestible health sensor device.
5. 5. The method of claim 4,

   The ingestible health sensor device, wherein the acceleration sensor is a three-axis acceleration sensor configured to detect the contraction of the stomach.
6. 5. The method of claim 4,

   The health sensor device further comprises a memory unit storing data and an animal identifier, wherein the transmitter is configured to transmit the animal identifier including the measured animal characteristic.
7. 7. The method of claim 6,

   wherein the transmitter comprises a transceiver capable of receiving data of the health sensor device for storage on the memory unit.
8. The method of claim 1,

   Ingestible health sensor device, further comprising a housing shell having a cylindrical shape comprising the sensor, the transmitter, the power source and the ballast weight.
9. 9. The method of claim 8,

   and a message label disposed on an inner wall of the housing shell, the housing shell being substantially transparent, and the label providing a return address for the health sensor device.
10. 9. The method of claim 8,

    a first circuit board substantially disk-shaped, wherein a diameter of the first circuit board is configured to a diameter sized for the first circuit board to be received within the housing shell, and wherein the sensor and the transmitter are connected to the second circuit board. 1 An ingestible health sensor device disposed on a circuit board.
11. 9. The method of claim 8,

    an antenna substrate having a diameter received within the housing shell and being substantially disk-shaped; and

    Formed on the antenna substrate, the ingestible health sensor device further comprising an antenna communicatively coupled to the transmitter.
12. 11. The method of claim 10,

    An ingestible health sensor device, further comprising an insulating spacer separating the antenna substrate from the sensor, the transmitter and the processor.
13. The method of claim 1,

    The power supply unit is an ingestible health sensor device that is a generator.
14. A disposable ingestible health sensor device in the stomach of an animal to measure a plurality of characteristics of the animal, comprising:

    3-axis accelerometer;

    a transmitter communicatively coupled to the three-axis accelerometer and configured to transmit measurements derived from the three-axis accelerometer to a receiver;

    a power supply unit electrically coupled to the three-axis accelerometer and the transmitter to supply power to the three-axis accelerometer and the transmitter; and

    a housing shell;

    wherein the three-axis accelerometer, the transmitter and the power supply are disposed within the housing shell.
15. 15. The method of claim 14,

    an ingestible health sensor device, further comprising a ballast weight disposed within the housing shell, the ballast weight configured to cause the health sensor device to remain movably connected with a portion of the wall of the animal's stomach;
16. 15. The method of claim 14,

    A portion of the housing shell is substantially cylindrical and the ingestible health sensor device comprises:

    a processor communicatively coupled to the three-axis accelerometer and the transmitter; and

    a memory unit communicatively coupled to the processor;

    the memory unit includes instructions for causing the processor to control the three-axis accelerometer and the transmitter;

    wherein the accelerometer, the transmitter, the processor and the memory unit are disposed on a substantially disk-shaped circuit board disposed within the housing shell.
17. 17. The method of claim 16,

    a substantially disk-shaped antenna substrate disposed within the housing shell; and

    and an antenna communicatively coupled to a transmitter formed as a trace on the antenna substrate.
18. 18. The method of claim 17,

    An ingestible health sensor device, further comprising an insulating spacer for isolating the antenna from the accelerometer, the transmitter, the processor and the memory unit.
19. 15. The method of claim 14,

    an ingestible health sensor device, further comprising a temperature sensor communicatively coupled to the transmitter disposed within the housing shell, the transmitter configured to transmit a measurement derived from the temperature sensor to a receiver
20. A method for monitoring animal characteristics, comprising:

    placing an ingestible large pill in the stomach of a ruminant, wherein the ingestible health sensor device comprises a ballast weight configured to maintain the health sensor device movably connected with a portion of the wall of the stomach of the animal placing an ingestible health sensor device in the stomach of a ruminant;

    measuring an acceleration characteristic of the animal using an accelerometer disposed within the health sensor device; and

    and transmitting the measured acceleration characteristic using a radio frequency transmitter disposed within the health sensor device.
21. 21. The method of claim 20,

    wherein the acceleration characteristic is a vector magnitude of a three-axis acceleration measured by the accelerometer.
22. 21. The method of claim 20,

    wherein the acceleration characteristic is a time derivative of a vector magnitude of a three-axis acceleration measured by the accelerometer.
23. 21. The method of claim 20,

    wherein the accelerating characteristic corresponds to an animal gastrointestinal contractile activity.
24. 21. The method of claim 20,

    wherein the measured acceleration characteristic corresponds to an animal movement activity.
25. 21. The method of claim 20,

    wherein the measured acceleration characteristic corresponds to an animal gastrointestinal contractile activity and an animal movement activity.

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