Animal trapping devices, animal trapping systems, animal trapping methods

Abstract

Easily change the activation conditions for box traps. [Solution] The system includes a storage unit that stores operating condition data representing the conditions for activating an animal trap, an operation control unit that activates the trap based on the imaging results captured by a camera and the operating condition data, an acquisition unit that acquires operating condition data transmitted from an external device via a communication network, and a writing unit that writes the acquired operating condition data to the storage unit.

Description

Technical Field

[0001] The present invention relates to an animal capture device, an animal capture system, and an animal capture method.

Background Art

[0002] In areas with animal damage, for example, box traps are set up to capture the harmful animals. There are various types of box traps. When an animal detection sensor is provided and it detects that an animal has entered the box trap, the inside of the box trap is imaged by a camera, and an image determination is made as to whether an image corresponding to the animal damage preset as the capture target is included in the captured image. If it is determined that an image corresponding to the harmful animal is included, the door is closed (for example, Patent Document 1). Such a box trap closes the door when operating conditions such as the determination conditions for image determination are satisfied.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] However, even if the operating conditions are set, when the ground is not dry after rain or the surrounding grass grows, as the environment around the box trap changes, the background imaged by the camera changes. Then, since the environment is different from when the operating conditions were set initially, the determination accuracy decreases, and the accuracy of capturing the capture target may decrease. In order to change the operating conditions, it is necessary to manually change the operating conditions set in the electronic device provided in the box trap, which causes a burden of going to the place where the box trap is installed.

[0005] This invention has been made in view of these circumstances, and its purpose is to provide an animal trapping device, an animal trapping system, and an animal trapping method that can easily change the operating conditions of a box trap. [Means for solving the problem]

[0006] To solve the above-mentioned problems, one aspect of the present invention is an animal trapping device comprising: a storage unit for storing operating condition data representing the conditions for activating an animal trap; an operation control unit for activating the trap based on imaging results captured by a camera and the operating condition data; an acquisition unit for acquiring operating condition data transmitted from an external device via a communication network; and a writing unit for writing the acquired operating condition data to the storage unit.

[0007] Furthermore, one aspect of the present invention is an animal trapping device comprising: a storage unit that stores operating condition data representing the conditions for activating a trap for capturing animals; and an operation control unit that activates the trap based on the imaging results captured by a camera and the operating condition data, wherein the operating condition data includes at least one of the following: the number of imaging times representing the number of times the camera takes images in response to an instruction to take images; the imaging interval representing the interval between imaging when multiple images are taken until the number of imaging times is reached; and a determination probability threshold that serves as a criterion for determining whether the animal in the image is the target animal to be captured, based on the probability that the type of animal included in the image captured as the imaging result is the target animal to be captured.

[0008] Furthermore, one aspect of the present invention is an animal capture system including a server and an animal capture device, wherein the server has a communication unit that transmits the received operating condition data, which represents the conditions for activating a trap for capturing animals, to the animal capture device in response to receiving such data from an externally connected terminal device, and the animal capture device has a storage unit that stores operating condition data, which represents the conditions for activating a trap for capturing animals, an operation control unit that activates the trap based on imaging results captured by a camera and the operating condition data, an acquisition unit that acquires the operating condition data transmitted from the server, and a writing unit that writes the acquired operating condition data to the storage unit.

[0009] Furthermore, one aspect of the present invention is a method for capturing animals performed by a computer, wherein the computer acquires operating condition data representing the conditions for activating an animal trap transmitted from an external device via a communication network, writes the acquired operating condition data to a storage unit, and activates the trap based on the imaging results of the trap being imaged by a camera and the operating condition data written to the storage unit. [Effects of the Invention]

[0010] As explained above, this invention makes it possible to easily change the operating conditions of a box trap. [Brief explanation of the drawing]

[0011] [Figure 1] This is a schematic system diagram showing the configuration of an animal capture system S according to one embodiment of the present invention. [Figure 2] This figure shows an example of operating condition data stored in the memory unit 331. [Figure 3] This flowchart shows an example of the process by which the animal trapping device 3 receives operating condition data. [Figure 4] This is a flowchart showing an example of the trap activation process for animal trapping device 3. [Modes for carrying out the invention]

[0012] The following describes an animal capture system S according to one embodiment of the present invention with reference to the drawings. Figure 1 is a schematic system diagram showing the configuration of an animal capture system S according to one embodiment of the present invention. The animal capture system S includes a terminal device 1, a server 2, and an animal capture device 3. Terminal device 1 is, for example, an electronic device such as a PC (Personal Computer), smartphone, or tablet, and is used by the administrator who manages the animal trapping device 3. Terminal device 1 communicates with server 2 wirelessly or via wired connection. Server 2 communicates with terminal device 1 wirelessly or via a wired connection. Server 2 has a communication unit that, upon receiving operating condition data representing the conditions for activating an animal trap from an externally connected terminal device (e.g., terminal device 1), transmits the received operating condition data to the animal trapping device 3. Server 2 may be a physical server or a cloud server provided by a cloud computing service.

[0013] The animal trapping device 3 captures animals using a trap. The trap may be a box trap or a snare trap, but in this embodiment, a box trap will be described as an example. The animals that the animal trapping device 3 targets may be any of the following: wild boar, deer, weasel, raccoon, civet, muntjac, rat, etc. In this embodiment, the case where the target animal is a wild boar will be described. The animal trapping device 3 includes a box trap 31 and a trapping control device 33. The box trap 31 includes the box trap body 311, a door 312, and a door drop mechanism 313. The box trap 31 is placed on the ground 4.

[0014] The box trap body 311 is a cage configured using frame members such as reinforcing bars. The size of the box trap body 311 is set to a size capable of accommodating the capture target G. When the species of the animal to be captured is a wild boar, the size of the box trap body 311 is set to a size capable of accommodating at least one wild boar. When it is assumed that multiple wild boars are to be captured, the size of the box trap body 311 may be set to a size capable of accommodating multiple wild boars. A part of the side surface of the box trap body 311 is provided with an entrance 311a through which an animal can pass.

[0015] The door 312 is held at a position above the box trap body 311 before the trap is activated, and it is possible for an animal to enter the box trap body 311 through the entrance 311a. Also, after the trap is activated, the door 312 closes the entrance 311a by falling, thereby blocking the animal from exiting the box trap body 311 through the entrance 311a.

[0016] Based on a control signal from the capture control device 33, the door drop part 313 closes the entrance 311a from an open state by dropping the door 312. The door drop part 313 can use, for example, a solenoid. By energizing the solenoid and storing a rod-shaped member that locks the door 312 so that it does not drop, the lock of the door 312 can be released, and the door 312 can be dropped to close the entrance 311a.

[0017] A support column 311c is provided at a position away from the box trap body 311. The capture control device 33 is attached to the upper end of the support column 311c.

[0018] By being attached to the support column 311c, the capture control device 33 is installed at a position separated from the box trap body 311 (outside the box trap body 311). Therefore, even if an animal (for example, a wild boar, etc.) housed in the box trap body 311 rampages inside the box trap body 311, the animal cannot directly contact the capture control device 33. Thereby, the capture control device 33 can be made less likely to be destroyed by the animal housed in the box trap body 311.

[0019] The capture control device 33 includes a communication unit 330, a storage unit 331, an acquisition unit 332, a writing unit 333, a thermal sensor 334, a camera 335, an operation control unit 336, and a control unit 337. The communication unit 330 communicates with the server 2 via a communication network. In at least a part of the section of the communication network through which the communication unit 330 communicates with the server 2, for example, an LPWA (Low Power Wide Area) network standard (such as ZETA (registered trademark), etc.) may be used. The communication unit 330 receives a downlink command from the server 2 via the communication network. Also, the communication unit 330 transmits uplink data to the server 2.

[0020] The storage unit 331 stores various data. The storage unit 331 is composed of a storage medium, for example, an HDD (Hard Disk Drive), a flash memory, an EEPROM (Electrically Erasable Programmable Read Only Memory), a RAM (Random Access read / write Memory), a ROM (Read Only Memory), or any combination of these storage media. For example, this storage unit 331 can use a non-volatile memory.

[0021] For example, the storage unit 331 stores an image recognition model and operation condition data.

[0022] The image recognition model uses, as teacher data, data in which an image of the box trap body 311 is associated with data indicating whether an image of an animal corresponding to the capture target is included in the image of the box trap body 311 that has been captured, and is a learned model generated by learning, by a learning device, the relationship of whether an image of an animal corresponding to the capture target is included in the image in which an animal has been captured.

[0023] The training data can include, for example, (A) data where an image of a wild boar inside the box trap body 311 is associated with data indicating that the image of the box trap body 311 contains an image corresponding to the target animal (e.g., a wild boar); (B) data where an animal not to be captured (e.g., a raccoon dog, weasel, cat, etc.) is inside the box trap body 311 is associated with data indicating that the image of the box trap body 311 contains an image of the animal not to be captured; (C) data where an image of an empty box trap body 311 is associated with data indicating that the image of the box trap body 311 does not contain an image corresponding to an animal.

[0024] It is preferable to first verify the accuracy rate of the image recognition model obtained through this training process by inputting multiple images for verification and determining whether or not an animal is present, and if an animal is present, determining the type of animal, and to confirm that a certain level of accuracy (for example, 80% or more) is achieved.

[0025] The learning device's functions may be installed on server 2, or on a server other than server 2. The image recognition model generated in this way is stored in the storage unit 331 beforehand.

[0026] The operating condition data represents the conditions under which an animal trap is activated. The operating condition data can be set to any value by a downlink command sent from the server 2 to the capture control device 33 in response to a request from the terminal device 1. The operating condition data may include at least one of the following: number of images taken, imaging interval, and determination probability threshold. Furthermore, the operating condition data may also include an observation count threshold for at least one of these three items.

[0027] Figure 2 shows an example of operating condition data stored in the memory unit 331. Here, the operating condition data is illustrated in a case where it includes the number of images taken, the imaging interval, the observation count threshold, and the determination probability threshold.

[0028] The number of images taken represents the number of times the camera 335 takes an image in response to an instruction to take an image. In this embodiment, the number of images taken represents the number of times the camera 335 takes an image between the time the system transitions from sleep state to wake state and the time it transitions to the next sleep state.

[0029] The imaging interval refers to the time interval between imaging scans when multiple scans are performed until the target number of scans is reached.

[0030] The observation count threshold is a value that serves as a criterion for determining whether or not to activate a trap, based on the ratio of the number of times an animal captured in an image was determined to be a target animal to be captured, and the number of times the image was taken, based on the probability that the animal species captured in the image is the target animal to be captured. For example, the observation threshold is a value that serves as a criterion for determining whether or not an imaged animal should be confirmed as a target animal, based on the ratio of the number of images obtained that are determined to be of an animal predetermined as a target for capture based on an image recognition model, to the total number of images taken.

[0031] The determination probability threshold is a value that serves as a criterion for determining whether an animal captured in an image is a target animal, based on the probability that the animal species captured in the image is the target animal.

[0032] The acquisition unit 332 acquires operating condition data transmitted from an external device via a communication network. For example, when the communication unit 330 receives operating condition data transmitted via LPWA, the acquisition unit 332 acquires the operating condition data received by the communication unit 330.

[0033] The writing unit 333 writes the received operating condition data to the storage unit 331. The writing unit 333 writes the operating condition data to the storage unit 331, thereby allowing the threshold values ​​and other parameters used in the animal capture device 3 to be reset.

[0034] The heat sensor 334 detects whether or not an animal is present inside the box trap body 311 by sensing the surrounding heat. When the heat sensor 334 detects the presence of an animal inside the box trap body 311, it outputs the detection result.

[0035] When the camera 335 obtains a detection result from the heat sensing sensor 32 indicating that an animal has been detected, it takes an image of the box trap body 311 based on the imaging conditions included in the operating condition data. Camera 335, for example, uses an infrared camera and can detect infrared light, making it possible to image animals at any time of day or night. Furthermore, the camera 335 is equipped with an infrared light 335a. The infrared light 335a emits infrared light into the surroundings. This makes it possible to image animals in a brightly lit environment, even when it is dark, such as at night, or when animals are present inside or near the trap body 311. The infrared light 335a may be a model that operates and illuminates when a voltage of 12V is supplied, for example.

[0036] The operation control unit 336 activates the trap based on the image capture results and operating condition data obtained from the camera. For example, the operation control unit 336 obtains a determination result by inputting the captured image, which is the result of the image acquisition, into the image recognition model stored in the memory unit 331. The determination result may be the probability that the captured image contains an image corresponding to the animal to be captured. For example, the determination result may be the probability that the object in the captured image is a wild boar.

[0037] The control unit 337 controls each part of the capture control device 33. The control unit 337 switches the capture control device 33 between a sleep state and an operating state. For example, when the control unit 337 obtains a detection result from the heat sensing sensor 32 indicating that an animal is present inside the box trap body 311, it switches the capture control device 33 from the sleep state to the operating state. After transitioning to the operating state, when the trap activation process based on the image captured by the camera 335 is completed, the control unit 337 switches from the operating state to the sleep state. Here, for example, if the operation control unit 336 is configured by a microcontroller, the control unit 337 may switch the microcontroller between a sleep state and an active state.

[0038] In the capture control device 33, the communication unit 330, acquisition unit 332, writing unit 333, operation control unit 336, and control unit 337 may be composed of a processing unit such as a CPU (Central Processing Unit) or a dedicated electronic circuit.

[0039] Next, we will explain the operation of the animal trapping device 3. Figure 3 is a flowchart showing an example of the process by which the animal capture device 3 receives operating condition data. When updating the operating condition data stored in the memory unit 331 of the animal trapping device 3, the administrator of the animal trapping device 3 uses the terminal device 1 to input the new value as the value to be updated. Here, the administrator inputs a new value for at least one item included in the operating condition data. This input may be done by inputting data corresponding to the item to be updated and the new value from among the multiple items of the operating condition data on the display screen of the terminal device 1, and then sending the updated operating condition data from the terminal device 1 to the server 2 by pressing the send button. The data input here may be fixed-length string data. Alternatively, the fixed-length string data may be written based on a predetermined definition according to the item to be updated and the updated value, etc., and sent from the terminal device 1, and the server 2 may recognize the item to be updated and the updated value, etc., based on the definition. Alternatively, the display screen of the terminal device 1 may display the currently set values ​​for each item of the operating condition data, and the administrator may be asked to input a new value for at least one of the items, and this new value and which item it is may be sent from the terminal device 1 to the server 2. Alternatively, regardless of whether new values ​​have been entered, the terminal device 1 may send the values ​​of each item indicating the operating condition data to the server 2.

[0040] In this case, if there are multiple animal traps 3, the terminal device 1 may send the operating condition data to the server 2, specifying the identification information assigned to the animal trap 3 to be updated as the destination, based on the identification information individually assigned to each animal trap 3. This makes it possible to specify the animal trap 3 whose operating condition data to be updated from among the multiple animal traps 3, and then send the operating condition data.

[0041] When Server 2 receives operating condition data from Terminal Device 1, it transmits the received operating condition data to Animal Capture Device 3.

[0042] The communication unit 330 of the capture control device 33 determines whether or not it has received the operating condition data transmitted from the server 2 (step S101). If it has not received the operating condition data (step S101-NO), after a certain waiting time has elapsed, it performs the reception determination process of step S101 again. If the communication unit 330 has received the operating condition data (step S101-YES), the acquisition unit 332 acquires the operating condition data received by the communication unit 330. The writing unit 333 stores the operating condition data acquired by the acquisition unit 332 by writing it to the storage unit 331 (step S102). When the operating condition data is written, the control unit 337 sends an uplink data to the server 2 via the communication unit 330 indicating that the rewriting of the operating condition data is complete (step S103). The timing of the communication unit 330 to send data to the server 2 is such that it may send the data when a transmission request is made, or if a communication timing is defined, it may send the data when that defined communication timing arrives. Furthermore, although the case of sending a notification indicating that the rewriting is complete to the server 2 is described, it is not necessary to send a notification to the server 2.

[0043] When Server 2 receives confirmation from Animal Capture Device 3 that the rewriting of the operating condition data is complete, it sends a message to Terminal Device 1 indicating that the rewriting of the operating condition data is complete. As a result, the display screen of Terminal Device 1 shows that the rewriting of the operating condition data is complete. This allows the administrator to understand that the rewriting of the operating condition data is complete. Note that the process of Server 2 sending a message to Terminal Device 1 indicating that the rewriting of the operating condition data is complete does not need to be performed.

[0044] Figure 4 is a flowchart showing an example of the trap activation process of the animal trapping device 3. The heat sensor 32 of the animal trapping device 3 monitors whether or not an animal is present in the inside or surrounding area of ​​the box trap body 311 (step S201). When the heat sensor 32 detects the presence of an animal (step S202), it outputs a detection result indicating the presence of an animal to the trapping control device 33.

[0045] When the control unit 337 of the capture control device 33 receives a detection result indicating the presence of an animal, it switches the operation control unit 336 from sleep state to operating state (step S203). Here, the camera 335 may be kept in an operating state at all times, or it may be kept in a sleep state, and the control unit 337 may switch the camera 335 to an operating state in response to the control unit 337 acquiring a detection result indicating the presence of an animal.

[0046] When switched to the operating state, camera 335 takes an image based on the operating condition data (step S204). Here, camera 335 first takes one image and outputs the resulting image to the operation control unit 336. When the operation control unit 336 acquires the captured image from the camera 335, it inputs the acquired image into the trained model and obtains a judgment result output from the trained model. Then, based on the judgment result and the judgment probability threshold, the operation control unit 336 determines whether or not the image of the animal included in the captured image is an image of a wild boar (step S205).

[0047] The operation control unit 336, in the obtained determination result, for example, if the determination result is "the probability of it being a wild boar is 80%, and the probability of it being an animal other than a wild boar is 20%", and the determination probability threshold is "70%", then the operation control unit 336 determines that the image of the animal included in this captured image is an image of a wild boar because the probability of it being a wild boar (80%) is greater than or equal to the determination probability threshold of "70%".

[0048] On the other hand, the operation control unit 336, in the obtained determination result, for example, if the determination result is "the probability of it being a wild boar is 50%, and the probability of it being an animal other than a wild boar is 50%", and the determination probability threshold is "70%", then the probability of it being a wild boar "50%" is less than the determination probability threshold of "70%", and therefore the operation control unit 336 determines that the image of the animal included in this captured image is not an image of a wild boar.

[0049] If the determination result in step S205 indicates that the image of an animal included in the captured image is an image of a wild boar (step S206-YES), the operation control unit 336 adds 1 to the count of images that are wild boars (step S207). If the determination result in step S205 indicates that the image of an animal included in the captured image is not an image of a wild boar (step S206-NO), the operation control unit 336 adds 1 to the count of images that are not wild boars (step S208).

[0050] Next, the operation control unit 336 determines whether the number of times the camera 335 has captured an image since transitioning to the startup state has reached the required number of images (step S209). If the required number of images has not been reached (step S209-NO), the unit waits until the imaging interval corresponding to the imaging interval defined as the operation condition data has elapsed (step S210), and then causes the camera 335 to take the next image (step S204).

[0051] On the other hand, the operation control unit 336 determines whether the count of images of wild boars exceeds the observation count threshold when the number of times images have been captured by the camera 335 since the system has entered the startup state (step S209-YES). If the count of images of wild boars exceeds the observation threshold (step S211-YES), the operation control unit 336 outputs a control signal to the door drop unit 313 to drop the door 312. Based on the control signal output from the operation control unit 336, the door drop unit 313 releases the lock and drops the door 312 (step S212). As a result, the door 312 closes the entrance 311a of the box trap body 311 from the open state.

[0052] For example, if the operating conditions data specifies that the number of images to be taken is 10, the imaging interval is t1 seconds, the observation threshold is 5, and the judgment probability threshold is "70%", the capture control device 33 will take an image with the camera 335 every time the imaging interval t1 seconds elapses until the number of images to be taken reaches 10. In this case, 10 images will be obtained from the camera 335. The operation control unit 336 then sequentially inputs the 10 captured images into the image recognition model and obtains the recognition result from the image recognition model. The operation control unit 336 then counts the number of captured images (times) for which a recognition result indicating a probability of 70% or more being a wild boar is obtained. If the count result is 5 images (5 times) or more, the final determination result is confirmed as "wild boar," and a control signal is output to the door closing unit 313, closing the entrance 311a with the door 312.

[0053] Meanwhile, the operation control unit 336 counts the number of captured images (times) in which a recognition result indicating a probability of 70% or more being a wild boar is obtained. If the count result is less than 5 images (5 times), it confirms that the final determination is not "wild boar," does not output a control signal to the door closing unit 313, and maintains the entrance 311a in the open state. If the image recognition model has an accuracy of 80% or higher in identifying an image as a wild boar, the probability of finally confirming it as a wild boar can be expected to exceed 99%. Condorcet's jury theorem may be used in such a determination method.

[0054] When a control signal is output to the door locking unit 313, the operation control unit 336 transmits uplink data to the server 2 via the communication unit 330 indicating that the trap has been activated (step S213). Subsequently, the control unit 337 transitions the operation control unit 336 from the startup state to the sleep state (step S214).

[0055] On the other hand, if the number of images counted as wild boars does not exceed the observation count threshold (step S211-NO), the control unit 337 transitions the operation control unit 336 from the startup state to the sleep state (step S214).

[0056] According to the embodiment described above, since operating condition data is set for the animal capture device 3 from a server 2 located outside the animal capture device 3, the operating condition data can be updated according to the environment in which the animal capture device 3 is installed. This makes it possible to capture target animals with higher accuracy.

[0057] For example, the environment in which the animal trap 3 is installed varies depending on the season, weather, time of day, etc. Depending on the season, the growth of plants around the animal trap 3 may differ, so the degree to which plants appear in the images captured by the camera may vary. Depending on the season, weather, and time of day, the target animal may be less likely to appear, or other animals may be more likely to appear. Also, when multiple animal traps 3 are installed in different locations, the environment of each installation location will be different. The animal trap 3 may be installed in an area with a relatively large area of ​​exposed ground, or in an area with a lot of grass, so the background that appears in the captured images will be different. For example, even if the same image recognition model is introduced to each animal trap 3, the captured images will also be different because the installation environment is different. This will affect the accuracy of determining whether the animal captured in the image is a target for capture. According to the embodiment described above, since the operating condition data can be rewritten remotely, even if the environment in which the animal capture device 3 is installed changes, the operating condition data can be rewritten at any time, and the operating condition data can be easily set according to the environment. This makes it possible to suppress a decrease in the accuracy of determining whether an animal captured in the image is a target for capture. It also makes it possible to improve the accuracy of capturing the target animal.

[0058] Furthermore, if the trap is activated and the door 312 closes, the administrator checks the status of the box trap body 311 to confirm whether or not the target animal has been captured. If an animal other than the target animal has been captured, or if nothing has been captured, it becomes necessary to release the other animals or reset the door 312 to the open position. Therefore, if an animal other than the target animal enters the box trap body 311, it is desirable to prevent the door 312 from closing as much as possible. In such cases, the administrator can change the activation condition data to set stricter conditions for closing the door 312, thereby preventing the door 312 from closing unnecessarily. This reduces the number of times the administrator has to make unnecessary visits to check on the animal trapping device 3.

[0059] When changing the number of images taken in the operating condition data, for example, even if a wild boar enters the box trap body 311, the image may differ depending on the boar's posture and orientation. Therefore, by taking images according to time intervals, it becomes possible to take images after the boar's posture changes, or when the boar moves from being out of the imaging range to being within the imaging range. On the other hand, if the number of images taken is too high, the time from when the boar enters the box trap body 311 until the trap is activated may be prolonged, and it may be desirable to avoid this prolongation. In such cases, changing the number of images taken can make it easier to obtain images that are easier to judge, or prevent the time until the trap is activated from being prolonged.

[0060] In the operating conditions data, changing the imaging interval to be shorter reduces the time required to determine whether or not to activate the trap, while changing the imaging interval to be longer allows the system to wait until the wild boar enters the box trap body 311 and changes its posture, making it possible to obtain images of the boar in various postures.

[0061] If the observation count threshold is changed in the operating condition data to be lower, the trap can be activated even if the number of images determined to be wild boars is small. If the observation count threshold is changed to be higher, the trap can be activated when the number of images determined to be wild boars is large, making it possible to close the door 312 with greater certainty.

[0062] In the operating condition data, changing the judgment probability threshold to a lower value makes it easier to determine that an animal in the captured image is a wild boar even if the probability of it being a wild boar is relatively low. Conversely, changing the judgment probability threshold to a higher value makes it easier to determine that an animal in the captured image is a wild boar when the probability of it being a wild boar is high, thereby improving the accuracy of the judgment for the captured image. Here, since wild boars differ in body size, fur, body color, etc., it is also possible to change the judgment probability threshold according to the general appearance of wild boars living near the location where the animal capture device 3 is installed.

[0063] In addition, although the above embodiment describes the case where the trap used in the animal capture device 3 is a box trap, it may also be a snare trap instead of a box trap. If the trap used in the animal capture device 3 is a snare trap, the camera may be used to capture an image including the inner circumference of the trap wire, and based on the image result, the capture control device 33 may determine whether or not it is an animal to be captured. If it is an animal to be captured, the lock on the trap wire may be released and the animal may be snagged by the trap wire.

[0064] The animal capture device 3 in the above-described embodiment may be implemented using a computer. In that case, the program for implementing this function may be recorded on a computer-readable recording medium, and the program recorded on this recording medium may be loaded into a computer system and executed. Here, "computer system" includes hardware such as an OS and peripheral devices. Furthermore, "computer-readable recording medium" refers to portable media such as flexible disks, magneto-optical disks, ROMs, CD-ROMs, and storage devices such as hard disks built into a computer system. Moreover, "computer-readable recording medium" may also include those that dynamically hold programs for a short period of time, such as communication lines used when transmitting programs via networks such as the Internet or communication lines such as telephone lines, and those that hold programs for a certain period of time, such as volatile memory inside a computer system that acts as a server or client in such cases. Furthermore, the above-mentioned program may be for implementing a part of the above-mentioned function, or it may be a program that can implement the above-mentioned function in combination with a program already recorded in the computer system, or it may be implemented using a programmable logic device such as an FPGA (Field Programmable Gate Array).

[0065] While embodiments of this invention have been described in detail above with reference to the drawings, the specific configuration is not limited to these embodiments and includes designs and the like that do not depart from the spirit of this invention. [Explanation of Symbols]

[0066] 1 Terminal device 2 servers 3 Animal capture device 31 Box Trap 33 Capture control device 311 Box trap body 311a Entrance 311b Base section 311c strut 312 Door 313 Door drop section 330 Communications Department 331 Storage section 332 Acquisition Department 333 Writing section 334 Thermal Sensor 335 Camera 335a Infrared Light 336 Operation Control Unit 337 Control Unit G (G) Target for capture S Animal Capture System

Claims

1. A memory unit that stores operating condition data representing the conditions for activating an animal trap, The trap is operated by an operation control unit that operates the trap based on the imaging results captured by the camera and the operating condition data, An acquisition unit that acquires operating condition data transmitted from an external device via a communication network, A writing unit that writes the acquired operating condition data to the storage unit, An animal trapping device having the following features.

2. The aforementioned operating condition data is The number of times the camera takes an image in response to the instruction to take the image, The imaging interval represents the interval between imaging sessions when multiple imaging sessions are performed until the aforementioned number of imaging sessions is reached. A determination probability threshold is a criterion that allows for the determination that the captured animal is a target animal based on the probability that the species of animal included in the captured image obtained as a result of the imaging is the target animal to be captured, Includes at least one of the following The animal capture device according to claim 1.

3. The aforementioned operating condition data is Based on the aforementioned probability, the number of times the imaged animal was determined to be a target for capture, The number of imaging sessions and Includes an observation count threshold for determining whether or not to activate the trap based on a ratio derived from the above. The animal capture device according to claim 2.

4. The aforementioned communication network uses LPWA in at least part of it. It has a communication unit that wirelessly receives operating condition data transmitted via the LPWA, The acquisition unit acquires the operating condition data received by the communication unit. The animal capture device according to any one of claims 1 to 3.

5. A memory unit that stores operating condition data representing the conditions for activating an animal trap, The trap has an operation control unit that activates the trap based on the imaging results captured by the camera and the operating condition data, The aforementioned operating condition data is The number of times the camera takes an image in response to the instruction to take the image, The imaging interval represents the interval between imaging sessions when multiple imaging sessions are performed until the aforementioned number of imaging sessions is reached. A determination probability threshold is a criterion that allows for the determination that the captured animal is a target animal based on the probability that the species of animal included in the captured image obtained as a result of the imaging is the target animal to be captured, Includes at least one of the following Animal trapping device.

6. This is an animal capture system that includes a server and an animal capture device. The aforementioned server, The device has a communication unit that, upon receiving operating condition data representing the conditions for activating an animal trap from an externally connected terminal device, transmits the received operating condition data to the animal trapping device. The aforementioned animal capture device, A memory unit that stores operating condition data representing the conditions for activating an animal trap, The trap is operated by an operation control unit that operates the trap based on the imaging results captured by the camera and the operating condition data, An acquisition unit that acquires operating condition data sent from the server, A writing unit that writes the acquired operating condition data to the storage unit, An animal capture system having

7. A method of capturing animals performed by computer, It acquires operating condition data, which represents the conditions for activating an animal trap, transmitted from an external device via a communication network. The acquired operating condition data is written to the storage unit. The trap is activated based on the imaging results captured by the camera and the operating condition data written to the storage unit. How to capture animals.

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