Pig rearing support device, pig rearing support method, and pig rearing support program

Abstract

This pig rearing assistance apparatus is provided with: an acquisition unit that acquires image data of an image captured by a camera directed to a plurality of pens in each of which a group of pigs are being raised; a detection unit that detects a specific posture of the pigs on the basis of the image of the image data; and a count unit that counts the number of times of the specific posture detected for each of the plurality of pens during a preset observation time. This pig rearing assistance apparatus can notify rearing staff of which pen includes a pig having a poor health condition among the plurality of pens in each of which the group of pigs are being raised at an appropriate timing without excessive cost and labor.

Description

[Technical Field]

[0001] The present invention relates to a pig rearing support device, a pig rearing support method, and a pig rearing support program. [Background technology]

[0002] Systems for detecting abnormalities in livestock are known. For example, various sensors are attached to individual livestock, and if the output is a value that cannot be expected in a healthy state, the individual is judged to be abnormal (see, for example, Patent Document 1). [Prior art documents] [Patent Documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2017-201930 [Overview of the Initiative] [Problems that the invention aims to solve]

[0004] Detecting various abnormalities that can occur in various types of livestock would require attaching multiple sensors to each animal or preparing a vast amount of analytical data. In the case of pig farming, a method of raising pigs in groups in pens or partitioned sections is commonly used, making it impractical to attach sensors to each individual pig to detect abnormalities. Furthermore, preparing the vast amount of analytical data required for this purpose is also difficult. Moreover, since multiple pens are often installed in pigpens on pig farms, it is difficult for farmers to continuously monitor each pig thoroughly.

[0005] This invention was made to solve these problems and provides a pig rearing support device that can promptly inform rearers of which pen contains a pig that is unwell, without requiring excessive cost or effort. [Means for solving the problem]

[0006] A pig rearing support device in a first aspect of the present invention includes an acquisition unit that acquires image data of images captured by cameras installed facing a plurality of pens in which pigs are reared in groups, a detection unit that detects a specific posture of a pig based on the image data, and a counting unit that counts the number of times the specific posture is detected in each of the plurality of pens during a set observation time.

[0007] Furthermore, the pig rearing support method in the second aspect of the present invention includes an acquisition step of acquiring image data of images captured by cameras installed facing a plurality of pens in which pigs are reared in groups, a detection step of detecting a specific posture of a pig based on the image data, and a counting step of counting the number of times the specific posture was detected in each of the plurality of pens during a set observation time.

[0008] Furthermore, the pig rearing support program in the third aspect of the present invention causes a computer to perform the following steps: an acquisition step of acquiring image data of images captured by cameras installed facing multiple pens in which pigs are reared in groups; a detection step of detecting a specific posture of a pig based on the image data; and a counting step of counting the number of times the specific posture was detected in each of the multiple pens during a set observation time. [Effects of the Invention]

[0009] The present invention provides a pig rearing support device that, by utilizing the habits of pigs, can promptly inform rearers which of multiple pens where pigs are being raised in groups contains pigs that are experiencing health problems, without requiring excessive cost or effort. [Brief explanation of the drawing]

[0010] [Figure 1] This figure shows an overall view of the pig farming environment using the pig farming support device according to this embodiment. [Figure 2] This is a diagram illustrating an example of a specific posture. [Figure 3] It is a diagram for explaining the procedure of detecting a specific posture using a learning model. [Figure 4] It is a diagram showing the hardware configuration of the pig breeding support device and peripheral devices. [Figure 5] It is a diagram for explaining the reference observation time. [Figure 6] It is a diagram for explaining the count list. [Figure 7] It is a diagram showing an example of the display on the breeder terminal that has received an over-limit notification. [Figure 8] It is a flowchart for explaining the processing procedure of the arithmetic unit. [Figure 9] It is a diagram for explaining the count list of the pig breeding support device according to another embodiment. [Figure 10] It is a diagram showing an overall view of a pig-raising environment adopting a pig breeding support device according to yet another embodiment. [Figure 11] It is a diagram for explaining the count list of the pig breeding support device according to yet another embodiment.

Mode for Carrying Out the Invention

[0011] Hereinafter, the present invention will be described through embodiments of the invention, but the invention according to the claims is not limited to the following embodiments. Also, not all of the configurations described in the embodiments are necessarily essential as means for solving the problems.

[0012] FIG. 1 is a diagram showing an overall view of a pig-raising environment adopting the pig breeding support device according to the present embodiment. The pig farm includes a plurality of pens 301 partitioned by walls and fences. A plurality (for example, about 10) of pigs 302 are housed in each pen 301 and are raised in a group. The number of pigs 302 raised in each pen 301 can be adjusted according to the breed of pigs 302, the breeding environment, and the like.

[0013] A camera unit 210 for observing the housed pigs 302 is installed for each pen 301. The camera unit 210 is installed, for example, suspended from the ceiling, facing the pen 301 so that it can capture an image overlooking the entire pen 301 which is the observation target. The camera unit 210 converts the captured image into image data and transmits it to the server 100 via the network 200. Specifically, a wireless unit 230 installed in the facility is connected to the network 200, and the camera unit 210 can transmit the image data to the server 100 by establishing wireless communication with the wireless unit 230. Of course, it may be configured to establish communication by a wired connection. The network 200 connecting the camera unit 210 and the server 100 may use the Internet or an intranet, or may employ short-range wireless communication when the management facility where the server 100 is installed is provided within the pig farm.

[0014] The breeder who takes care of the pigs 302 may carry a breeder terminal 220. The breeder terminal 220 is, for example, a tablet terminal or a smartphone, and can exchange various information with the server 100 via the wireless unit 230 and the network 200. The breeder can, for example, input breeding records into the breeder terminal 220 and transfer them to the server 100, or can also call up the breeding records stored in the server 100. Further, when the breeder terminal 220 receives an over-limit notification described later, it displays the fact.

[0015] The management facility is equipped with a server 100, which serves as a pig rearing support device. The server 100 is connected to a network 200. The server 100 sequentially acquires image data from camera units 210 installed for each pen 301, detects specific postures of the pigs 302 based on the image data, and counts the number of times each posture occurs. The specific postures will be described later. The server 100 can display the results on a display monitor 150 at the request of the administrator or rearing staff. The display monitor 150 is, for example, a monitor equipped with an LCD panel. The server 100 is also connected to an input device 160 that accepts operations from the administrator or rearing staff. The input device 160 consists of a keyboard, mouse, touch panel superimposed on the display surface of the display monitor 150, etc.

[0016] In pig farming, it is crucial to identify when a pig 302 is unwell. If a particular pig shows signs of illness, it needs to be treated individually. If many pigs in pen 301 show signs of illness, it is necessary to mix medication into their feed or drinking water or adjust the environment. However, in relatively large-scale pig farms where multiple pens of communal rearing are installed in the pigsty, it is a laborious and skilled task for farmhands to constantly observe a large number of pigs and identify when they are unwell. The pig rearing support device in this embodiment assists in rearing operations by detecting specific postures that pigs 302 in pen 301 tend to exhibit when they are unwell, and by notifying farmhands of specific pens where at least one pig is likely to be unwell.

[0017] As shown in Figure 1, if there are multiple pens 301 in a pig farm, the farm staff can reduce their workload considerably simply by being notified by the pig farming support device which pen 301 contains a pig 302 showing signs of poor health. In other words, the farm staff does not need to perform the task of identifying pigs 302 showing signs of poor health until notified by the pig farming support device, and even when notified, they only need to perform the task on that specific pen. If the presence of pigs 302 showing signs of poor health is indicated for a limited number of pigs in a single pen, even an inexperienced farm staff member can identify them relatively easily.

[0018] The pig rearing support device in this embodiment detects specific postures of pigs 302 using images captured by the camera unit 210. These specific postures are those that pigs tend to exhibit when they are unwell, and the applicant has gained knowledge of several of these specific postures. Figure 2 illustrates an example of a specific posture.

[0019] Figure 2(A) shows the dog-sitting posture, specifically a sitting position with the front legs raised. The hind legs are often bent and touching the abdomen, and the head may be raised or drooping. The dog-sitting posture is one of the postures that pigs tend to exhibit when they are unwell, and in this embodiment, it is treated as a specific posture.

[0020] Figure 2(B) shows the hiding posture, specifically a posture in which the forelegs are tucked under the prone body. In other words, the forelegs are folded and tucked between the floor and the body, and the head is often in contact with the floor, resulting in a docile posture. The hiding posture is one of the postures that pigs tend to exhibit when they are unwell, and in this embodiment, it is treated as a specific posture.

[0021] Figure 2(C) shows a hunched posture, specifically a posture in which the back is rounded and the pig is bent forward. In this posture, the distance between the front and rear legs is narrower than the distance between the feet. The hunched posture is one of the postures that pigs tend to exhibit when they are unwell, and in this embodiment, it is treated as a specific posture.

[0022] Figure 2(D) shows panting, specifically a posture involving movement where the abdomen undulates while lying on its side. While lying on its side is a posture seen in healthy pigs, pigs in poor health may exhibit a movement where their abdomen repeatedly moves up and down, hitting the floor. Panting is one of the postures associated with movement that pigs tend to exhibit when they are unwell, and in this embodiment, it is treated as a specific posture.

[0023] For other livestock, such as cattle, it is conceivable to estimate signs of poor health by observing the presence or absence of postures different from those of healthy animals. However, because cattle are raised in small numbers and each individual animal is highly valued, methods such as attaching infrared sensors or accelerometers to detect posture to each individual cow are employed. However, in the group rearing of pigs, where a relatively large number of pigs are housed in a limited space, attaching sensors to each pig is not practical. In particular, the market price of a pig per animal is cheaper than that of a cattle, making it difficult to justify the cost of raising them.

[0024] In light of this background, the pig rearing support device according to this embodiment detects a specific posture of the pigs 302 being reared in a group based on images captured using a camera unit 210 installed facing the pen 301. Each camera unit 210 is installed to look down in an inclined direction so that the posture of the pigs 302 housed in the pen 301 that are being captured can be observed.

[0025] From an overhead view of the Pen 301, for example, the contour lines of each individual dog can be extracted, and specific postures can be detected by pattern matching the shape of each contour line against a template pattern. The template patterns are contour lines of each posture captured from various angles and are prepared in advance. Specifically, as will be described later, postures that can be detected even without changes in movement, such as the sitting posture, reclining posture, and back-bending posture, can be detected from a single still image, while postures associated with movement, such as panting, are detected using multiple still images or videos in sequence.

[0026] Thus, with this method of detecting a specific posture from an overhead image of the group-raised pigs 302, there is no concern about false detections, such as two pigs equipped with sensors being detected as being in a specific posture simply because they are approaching each other. Furthermore, unlike livestock such as cattle raised in large outdoor pastures, the overhead camera unit 210 is relatively easy to install for the pigs 302 raised in an indoor pen, and the light intensity and imaging angle can be easily stabilized, making the image-based detection method suitable.

[0027] As described above, it is possible to extract contour lines from the acquired image and detect a specific posture by pattern matching. However, in this embodiment, the acquired image is input to a learning model that has been trained using images of pigs in the target specific posture as training images to detect the specific posture. Figure 3 is a diagram illustrating the procedure for detecting a specific posture using the detection neural network 121, which is the learning model.

[0028] The detection neural network 121 is pre-created through supervised learning, where it is trained by providing a considerable number of training data for each of the following: training data for images of pigs in a canine posture associated with "canine posture" as the correct answer; training data for images of pigs in a reclining posture associated with "reclining posture" as the correct answer; training data for images of pigs in a hunched posture associated with "hunched posture" as the correct answer; and training data for images of pigs panting associated with "panting" as the correct answer. In this embodiment, since panting, which involves changes in movement, is also included as a specific posture, the input image for the detection neural network 121 is a video image of a length sufficient to detect panting (for example, 3 seconds). Therefore, the training data for each is also prepared as a video image. If postures involving changes in movement are not included as specific postures, the input image for the detection neural network 121 may be a still image.

[0029] The detection neural network 121, which is a learning model generated in this way, is incorporated into the server 100, a pig farming support device, and made available for use. Specifically, for example, if there are eight pens 301, which are the objects of observation, in the pig farm, image data is sequentially sent to the server 100 from eight camera units 210 that overlook each pen 301. Images img1 to img8 of this image data are sequentially input into the detection neural network 121.

[0030] The detection neural network 121 outputs the number of pigs determined to be in a specific posture within an image as the detection count each time an image is input. Specifically, it outputs the number of pigs in a doggy-style posture, a reclining posture, a hunched-over posture, and a panting posture as the detection count for each posture. In this way, for example, the detection count for the image img1 of the first pen is "0" for doggy-style, "1" for reclining, "1" for hunched-over, and "1" for panting, and the detection count for the image img2 of the second pen is "2" for doggy-style, "0" for reclining, "0" for hunched-over, and "0" for panting, and so on, obtaining the detection count for each posture for each pen 301. The server 100 repeats this process for a preset observation time, counting and accumulating the detection count for each pen 301.

[0031] Figure 4 shows the hardware configuration of the server 100 and peripheral devices as a pig farming support system. As described above, the server 100 can be connected to the display monitor 150, input device 160, camera unit 210, and farm worker terminal 220.

[0032] The server 100 mainly consists of an arithmetic unit 110, a storage unit 120, and a communication unit 130. The arithmetic unit 110 is a processor (CPU: Central Processing Unit) that controls the server 100 and performs program execution processing. The processor may be configured to work in conjunction with an arithmetic processing chip such as an ASIC (Application Specific Integrated Circuit) or a GPU (Graphics Processing Unit). The arithmetic unit 110 reads the pig farming support program stored in the storage unit 120 and performs various processes related to supporting pig farming.

[0033] The memory unit 120 is a non-volatile storage medium, such as an HDD (Hard Disk Drive). In addition to programs that control and process the server 100, the memory unit 120 can store various parameter values, functions, display element data, lookup tables, etc., used for control and calculations. In particular, the memory unit 120 stores the detection neural network 121 and the counting list 122. As described above, when the detection neural network 121 receives an image captured by the camera unit 210 as input, it outputs a detection count representing the number of animals in a specific posture present in the image. The counting list 122 is a record of the counting of specific postures, which will be described in detail later. Note that the memory unit 120 may be composed of multiple hardware components; for example, the storage medium that stores the program and the storage medium that stores the detection neural network 121 may be composed of separate hardware components.

[0034] The communication unit 130, which includes, for example, a LAN unit, transmits imaging control signals generated by the processing unit 110 to the camera unit 210 via the network 200, and also transfers image data received from the camera unit 210 to the processing unit 110. It also relays the exchange of data between the animal handler terminal 220 and the processing unit 110. The communication unit 130 can also relay the exchange of data and control signals with other external devices. For example, it can be used to retrieve update data for the pig farming support program or the detection neural network 121 from an external server.

[0035] The calculation unit 110 also serves as a functional calculation unit that performs various calculations in accordance with the processing instructed by the pig farming support program. The calculation unit 110 can function as an acquisition unit 111, a detection unit 112, and a counting unit 113. The acquisition unit 111 mainly acquires image data of images captured by the camera unit 210 and passes it to the detection unit 112. The detection unit 112 mainly detects specific postures of the pigs 302 based on the image data received from the acquisition unit 111 and passes the results to the counting unit 113. The counting unit 113 mainly counts the number of times specific postures are detected in each of the multiple pens 301 during a set observation time.

[0036] Next, the processing of the counting unit 113 will be explained. Figure 5 is a diagram illustrating the reference observation time, which is the period for which the counting unit 113 counts the number of times a specific posture is maintained. The counting unit 113 resets the counted number at each preset reference observation time.

[0037] In this embodiment, the reference observation time is set to 24 hours. The counting unit 113 counts how many times a specific posture is detected in each pen 301 during this reference observation time. Specifically, as explained with reference to Figure 3, the detection unit 112 uses a detection neural network 121 to detect the number of animals (detections) in each image of image data img1 to img8 of each pen 301, which is periodically acquired by the acquisition unit 111. This is repeated during the reference observation time to count how many times a specific posture is detected in each pen 301.

[0038] However, even within the standard observation period, periods corresponding to certain situations are excluded from the count. Here, the period of animal handler proximity is set as such an excluded period. The period of animal handler proximity is set as a fixed period including the scheduled time from when an animal handler approaches pen 301 until when they leave. For example, the period of animal handler proximity is set from 8:00 to 9:00 when an animal handler enters pen 301 for feeding. In addition, periods when an animal handler approaches pen 301 for cleaning or inspecting pigs 302 may also be set as the period of animal handler proximity.

[0039] Thus, when a caretaker approaches or enters pen 301, the pigs 302 become a certain state of excitement, and healthy pigs may assume specific postures, while unwell pigs may break those postures. Therefore, for events that may cause such irregular behavior, it is advisable to set an exclusion period in which a certain period including the duration of the event is excluded from the count. Specifically, the exclusion period should be set by adding the period before and after the event, during which the pigs 302 sense the event and become excited, and the period after the event during which they regain their composure.

[0040] The exclusion period can be set in advance by an administrator or other user operating the input device 160. The exclusion period does not have to be included in each standard observation time; for example, in the case of an event where a boar is briefly placed in a pen where sows are kept, the exclusion period may be set only for the standard observation time on the specific day the event takes place. The counting unit 113 excludes the exclusion period set in this way from the counting target. Specifically, the counting unit 113 may stop counting, the detection unit 112 may stop detecting a specific posture, the acquisition unit 111 may stop acquiring image data, and the camera unit 210 may stop imaging.

[0041] Furthermore, the period during which the detection unit 112 detects a specific posture using image data is adjusted and set so that one specific posture is detected as one instance, taking into account the standard duration for which the pig 302 maintains the specific posture. Other factors such as the breed of the pig 302, rearing environment, and age can also be taken into consideration when setting the period.

[0042] The counting unit 113 manages the number of times a specific posture is counted for each pen 301 using a counting list 122. Figure 6 illustrates an example of the counting list 122. One counting list 122 is generated for each standard observation time, and it is updated as needed during that observation time.

[0043] The counting list 122 includes a notification threshold and an observation date. The notification threshold is a value set in advance by the administrator, etc. When the total number of specific postures counted in each pen 301 exceeds this notification threshold, the counting unit 113 outputs an overage notification to the animal caretaker terminal 220, etc. The administrator, etc. sets the notification threshold considering the breed of pigs 302, the rearing environment, and especially the number of pigs 302 housed in one pen 301. More specifically, a threshold is set based on past statistics and experience that allows for the determination that there is at least one pig 302 showing signs of poor health in the target pen 301. In the example in Figure 6, "50 times" is set. The observation date is the date on which the observation is performed, and if the counting list 122 is referenced after the observation, it represents the date the observation was performed. If the standard observation time is less than 24 hours, for example, the observation time when the observation started may be added.

[0044] The counting list 122 includes a summary table showing the number of times each pen 301 has performed a specific posture. The summary table consists of the pen number (for example, eight pens from the 1st to the 8th), the number of times each specific posture has been performed (dog sitting posture, reclining posture, back arching posture, panting), the total number of these postures, and flag information. When the counting unit 113 confirms that a pen 301 has been performed for a total number of times that exceeds the notification threshold, it generates an overage notification and outputs it to the caretaker terminal 220, etc. At this time, the counting unit 113 adds pen information about the specific pen whose count has exceeded the notification threshold to the overage notification and outputs it. In this embodiment, the pen number is added as pen information. For pens 301 for which an overage notification has been output, the information "Notified" is recorded as flag information.

[0045] The counting list 122 includes information on exclusion periods. Specifically, the exclusion periods explained using Figure 5 are recorded as list information. Note that if the exclusion period is long, the period to be counted becomes shorter, so even if there are pigs showing signs of poor health, the number of counts may not exceed the notification threshold. Therefore, the counting unit 113 may automatically adjust the notification threshold by considering the ratio of the total set exclusion period time to the standard observation time. For example, if the standard observation time is 24 hours and the total exclusion period is 3 hours, the notification threshold is adjusted to 50 × (24 - 3) / 24 = 43.75 times. In this case, the counting unit 113 outputs an overage notification when it confirms that a pen 301 has appeared in which the total number of counts exceeds the adjusted notification threshold.

[0046] Furthermore, if the number of pigs 302 housed in each pen 301 differs from one another, the notification threshold may be adjusted for each pen, taking into account the number of pigs housed. For example, if the notification threshold is set to "50 times" assuming that 10 pigs 302 are housed in one pen, then for a pen 301 housing 8 pigs 302, the threshold should be adjusted to 50 × (8 / 10) = 40 times. In this case, the counting unit 113 will output an overage notification if the total number of times counted for the pen 301 housing 8 pigs exceeds 40.

[0047] Figure 7 shows an example of the display on the caretaker terminal 220 when it receives an overage notification. As described above, when the counting unit 113 outputs an overage notification, the caretaker terminal 220 receives the notification and displays its contents on the display panel. Specifically, as shown in the figure, the caretaker terminal 220 refers to the pen information attached to the overage notification and displays the pen number for which the number of times a specific posture has exceeded the notification threshold (default value) (in the example shown, it is "Pen 2"). In addition, if the terminal has an indoor map of the pen placement in the pig farm, it also displays the location of the specific pen so that it can be recognized. The caretaker terminal 220 may also emit a notification sound in addition to displaying this information.

[0048] Next, the processing procedure for the pig farming support method using server 100 will be described. Figure 8 is a flowchart illustrating the processing procedure of the calculation unit 110. The flow starts from the beginning of the standard observation time. Note that the processing for the exclusion period will be omitted in this explanation.

[0049] As an initial process at the start of observation, the counting unit 113 starts the time interval using the time interval timer T in step S101 and counts the total number of times the pigs 302 housed in the nth pen are in a specific posture using counter C. n Reset everything. Note that there are m pens in the pig farm, and each pen corresponds to C1 to C m Assume that a counter up to a certain point is provided.

[0050] The counting unit 113 proceeds to step S102 and sets the variable n to 1. Accordingly, it switches the counter to be processed to C1. Proceeding to step S103, the acquisition unit 111 takes an image from the camera unit 210 pointed at the nth pen. n The image data is acquired via the communication unit 130. If n=1, the image data of img1 is acquired from the camera unit 210 pointed towards the first pen. The acquisition unit 111 passes the acquired image data to the detection unit 112.

[0051] In step S104, the detection unit 112 inputs the image img of the received image data into the detection neural network 121 read from the storage unit 120, and outputs the number of pigs 302 taking a specific posture (detection number) within the image img. Specifically, as described using FIG. 3, it outputs the number of heads in the dog posture, the number of heads in the huddled sleep posture, the number of heads in the arched back posture, and the number of heads in panting. The detection unit 112 delivers those numbers of heads to the counting unit 113 as the detection numbers. n The counting unit 113 reads the counting list 122 in step S105, adds the received respective detection numbers corresponding to each posture, and adds the total number of the detection numbers received from the detection unit 112 to the counter value of C at that time point to update C. n Specifically, as described using FIG. 3, it outputs the number of heads in the dog posture, the number of heads in the huddled sleep posture, the number of heads in the arched back posture, and the number of heads in panting. The detection unit 112 delivers those numbers of heads to the counting unit 113 as the detection numbers. n The counting unit 113 reads the counting list 122 in step S105, adds the received respective detection numbers corresponding to each posture, and adds the total number of the detection numbers received from the detection unit 112 to the counter value of C at that time point to update C. n

[0052] Proceed to step S106, and the counting unit 113 determines whether the updated value of C exceeds the notification threshold value C. n If it is determined that the value of C exceeds the notification threshold value C, proceed to step S107, generate an excess notification, and output it to the breeder terminal 220. At this time, add that the nth pen is the specific pen as the pen information. After outputting the excess notification, proceed to step S108. If the counting unit 113 determines in step S106 that the value of C does not exceed the notification threshold value C, skip step S107 and proceed to step S108. d If it is determined that the value of C exceeds the notification threshold value C, proceed to step S107, generate an excess notification, and output it to the breeder terminal 220. At this time, add that the nth pen is the specific pen as the pen information. After outputting the excess notification, proceed to step S108. If the counting unit 113 determines in step S106 that the value of C does not exceed the notification threshold value C, skip step S107 and proceed to step S108. d If it is determined that the value of C exceeds the notification threshold value C, proceed to step S107, generate an excess notification, and output it to the breeder terminal 220. At this time, add that the nth pen is the specific pen as the pen information. After outputting the excess notification, proceed to step S108. If the counting unit 113 determines in step S106 that the value of C does not exceed the notification threshold value C, skip step S107 and proceed to step S108. d If it is determined that the value of C exceeds the notification threshold value C, proceed to step S107, generate an excess notification, and output it to the breeder terminal 220. At this time, add that the nth pen is the specific pen as the pen information. After outputting the excess notification, proceed to step S108. If the counting unit 113 determines in step S106 that the value of C does not exceed the notification threshold value C, skip step S107 and proceed to step S108.

[0053] The counting unit 113 increments the variable n in step S108 and proceeds to step S109. After proceeding to step S109, it determines whether the variable n exceeds the number of pens m in the pig farm. If it is determined that it does not exceed, return to step S103 and execute the same process for the incremented variable n. If it is determined that it exceeds, proceed to step S110.

[0054] After the counting unit 113 proceeds to step S110, it determines whether the elapsed timer T is the reference observation time T. c ​Determine whether the threshold has been exceeded. If it is determined that the threshold has not been exceeded, return to step S102 after an interval corresponding to a predetermined period. If it is determined that the threshold has been exceeded, terminate the series of processes. If observation is to be performed continuously, start the process again from step S101.

[0055] Next, several other embodiments of this embodiment will be described. Figure 9 is a diagram illustrating the counting list 122' of a pig rearing support device according to another embodiment. The counting list 122' differs from the counting list 122 shown in Figure 6 in that it has a weighting coefficient table. In the embodiments described so far, the dog sitting posture, reclining posture, back arching posture, and panting, which were targeted for detection as specific postures, were treated equally, and the total number of times each posture was detected was simply added up to count the total number of times. However, the degree to which each posture indicates signs of poor health, in other words, the degree to which it contributes to the judgment of poor health, may differ from one another.

[0056] For example, panting is often observed when the pigsty is hot and heat stress is high, and if left untreated, it is highly likely to lead to the death of the pig. On the other hand, a hunched posture is often observed in pigs with mild health problems. Therefore, in this embodiment, weights are assigned to each posture detected as a specific posture, and the total number of occurrences is counted.

[0057] According to the counting list 122' in Figure 9, the weighting coefficient for the dog-sitting posture is "1.0", the weighting coefficient for the bald-back posture is "1.0", the weighting coefficient for the arched-back posture is "0.8", and the weighting coefficient for panting is "1.6". Here, the contribution of the arched-back posture to the judgment of poor health is reduced, and the contribution of panting is increased. Administrators can set the weighting coefficients in advance according to the contribution of each posture which they have grasped empirically and statistically. When such weighting coefficients are set, for example, if the dog-sitting posture is observed 4 times, the bald-back posture 3 times, the arched-back posture 4 times, and panting 1 time, the total number of times the second pen is observed is calculated as 4 × 1.0 + 3 × 1.0 + 4 × 0.8 + 1 × 1.6 = 11.8 times. By assigning weights in this way and counting the total number of times as a score, it is possible to achieve a more accurate prediction of poor health that takes into account the characteristics of each posture.

[0058] In the embodiment using the counting list 122' in Figure 9, weighting was assigned according to each detected posture, but a method of assigning weighting to the duration for which each posture was detected can also be adopted. For example, even for a dog sitting posture which is detected as one instance, the number of counts will differ depending on whether it is released in 1 minute or continues for 10 minutes. Specifically, for example, for the first minute from the start of detection, the weighting could be set to detection time (minutes) × 1.0, then for the next 3 minutes to be detection time (minutes) × 1.2, and thereafter to detection time (minutes) × 1.5, and so on. By assigning such weights and counting the total number of counts, a more accurate prediction of physical ailments can be expected. In this case, weighting by posture may also be applied.

[0059] Figure 10 shows an overall view of a pig farming environment employing a pig farming support device according to another embodiment. Elements similar to those in Figure 1 are given the same reference numerals, and their explanations are omitted.

[0060] In the embodiment shown in Figure 10, the caretaker does not possess a caretaker terminal 220; instead, one indicator light 240 is installed adjacent to each pen 301. Each indicator light 240 is connected to a server 100 via a wireless unit 230 and a network 200. For example, if the number of times a specific posture is counted in the fifth pen exceeds a notification threshold, the server 100 sends a notification signal equivalent to an overage notification to the indicator light 240 installed adjacent to the fifth pen, causing the indicator light 240 to light up. By using such indicator lights 240, caretakers can recognize which pen 301 to go to even without possessing a caretaker terminal 220. The caretaker can then look for pigs showing signs of poor health among the pigs 302 housed in the pen 301 where the indicator light 240 is lit.

[0061] Figure 11 is a diagram illustrating the counting list 122" of a pig rearing support device according to another embodiment. In the embodiment described above, multiple pigs 302 housed in one pen 301 were not recognized as distinct from one another. Therefore, if any of the pigs 302 housed in a specific pen 301 under observation assumed a specific posture, it was detected as one specific posture. For example, when the notification threshold is set to 50 times, the counting unit 113 outputs an excess notification whether one pig 302 assumed a specific posture more than 50 times, or whether 10 pigs 302 each assumed a specific posture 5 to 6 times. In other words, even if the rearer knows which pen 301 has detected more than the specified number of specific postures, it is necessary to determine whether a specific pig 302 is showing strong signs of poor health, or whether the pigs 302 in the pen as a whole are showing a tendency toward poor health.

[0062] On the other hand, technologies are becoming known for distinguishing and recognizing multiple pigs 302 housed in each pen 301. For example, individual identification can be achieved by attaching identification markers to each pig 302 and analyzing the images obtained from the camera unit 210. Alternatively, each pig 302 may be photographed at the time of placement in the pen 301, and an identification number may be associated with the captured image. Subsequently, a learning model may be used to detect which image corresponds to which identification number when a pig 302 is detected to be in a specific posture.

[0063] The counting list 122 shown in Figure 11 is a counting list for cases where individual pigs 302 housed in each pen 301 can be identified. Each pen 301 houses, for example, 10 pigs 302, and each pig 302 is distinguished by an assigned identification number. The detection unit 112 detects a specific posture and identifies the identification number of the pig 302 that assumed that posture. The counting unit 113 receives this information from the detection unit 112 and updates the number of times the pig has assumed the specific posture corresponding to the identified identification number.

[0064] Furthermore, if individual identification is performed, setting the notification threshold to a smaller value than when individual identification is not performed allows for early detection of poor health in a specific pig 302. In the counting list 122, the notification threshold is set to 25. When a specific pig 302 exceeds this notification threshold, the counting unit 113 outputs an overage notification to the caretaker terminal 220, adding information about its identification number. If the notification light 240 described using Figure 10 has a display unit, the counting unit 113 may output the overage notification to the notification light 240 adjacent to the pen containing the specific pig 302, and display its identification number on the display unit of the notification light 240. If the caretaker can also obtain information about the specific pig 302, they can easily find that specific pig 302 among the multiple pigs 302 contained in the pen 301.

[0065] In this embodiment, as described through several examples above, one camera unit 210 was installed for each pen 301. However, a camera unit that provides an overview of multiple pens 301 together may also be installed. In that case, the acquisition unit 111 can divide the images acquired from the camera unit along the boundaries of each pen 301 and sequentially pass each divided image to the detection unit 112. Conversely, multiple camera units 210 may be installed for a single pen 301. For example, by installing a camera unit 210 that images the pig 302 inside the pen 301 from the side, false detection of a specific posture can be reduced.

[0066] Furthermore, in the embodiment described above, we assumed that multiple pens 301 are installed in a single pigsty, but it is also possible to observe pens 301 installed across multiple pigsties. In this case, the notification threshold and weighting settings may be different depending on the circumstances of the pigsty and the types of pigs housed in each.

[0067] Furthermore, in the embodiment described above, the records up to that point were reset each time the reference observation time elapsed, and counting started from 0 for the new reference observation time. However, the counting method is not limited to this. For example, the observation results for the oldest unit time (e.g., 1 hour) could be discarded when a new unit time (e.g., 1 hour) of observation begins within the reference observation time (e.g., 24 hours). By shifting the reference observation time as time progresses in this way, the current status of each pen 301 can be grasped more accurately, and if a pig 302 with poor health appears, an overage notification can be output with little delay.

[0068] Furthermore, in this embodiment described above, the output destination for the excess notification was either the zookeeper terminal 220 or the notification light 240, but it is not limited to these. The counting unit 113 may also directly display information regarding the excess notification on the display monitor 150 connected to the server 100. In addition to outputting an excess notification when the number of times a specific posture is counted exceeds the notification threshold, the counting unit 113 may also output the number of times the specific posture is being counted on a regular basis instead of outputting an excess notification. For example, the current number of times the specific posture is being counted by each pen 301 may be displayed in a list on the zookeeper terminal 220.

[0069] Furthermore, in the embodiment described above, the number of times each of the following four specific postures was counted was used: the dog-sitting posture, the hunched-over posture, the arched-back posture, and panting. However, the specific postures to be counted are not limited to these. Any one of the four may be selected, or other specific postures exhibited by pigs in poor health may be added to or replaced with these.

[0070] Furthermore, although the embodiment described above describes a case where the server 100 functions as a pig farming support device, the hardware configuration is not limited to this. If the mobile terminal described as the farm worker terminal 220 performs the same processing as the server 100, the mobile terminal can function as a pig farming support device. Also, for example, if the farm worker terminal 220 is configured to handle a part of the processing of the server 100, the system in which the server 100 and the farm worker terminal 220 cooperate can become a pig farming support device. [Explanation of Symbols]

[0071] 100...Server, 110...Calculation unit, 111...Acquisition unit, 112...Detection unit, 113...Counting unit, 120...Storage unit, 121...Detection neural network, 122...Counting list, 130...Communication unit, 150...Display monitor, 160...Input device, 200...Network, 210...Camera unit, 220...Caregiver terminal, 230...Wireless unit, 240...Indicator light, 301...Pen, 302...Pig

Claims

1. Each unit acquires image data of images captured by cameras installed facing multiple pens where pigs are kept in groups, A detection unit detects, based on the image data, at least one of the following specific postures of the pig: a dog-like sitting posture with the front legs raised, a prone sleeping posture with the front legs tucked under the torso, a hunched posture with the back rounded and the body bent forward, and a panting posture with the abdomen rippling while lying on its side. A counting unit that counts the number of times the specific posture is detected in each of the plurality of pens during a set observation period. A pig farming support device equipped with the following features.

2. The pig rearing support device according to claim 1, wherein the counting unit outputs an excess notification including pen information for any of the plurality of pens when the number of counts for any of the pens exceeds a set threshold.

3. The pig rearing support device according to claim 2, wherein the counting unit identifies each of the pigs being reared in a group and counts the number of times the specific posture is held, and when an excess notification is output, identification information relating to the pig that has shown the specific posture is added to the excess notification.

4. The pig farming support device according to any one of claims 1 to 3, wherein the detection unit detects the specific posture based on a plurality of consecutive images.

5. The pig farming support device according to any one of claims 1 to 4, wherein the detection unit detects the specific posture using a learning model learned from a training image of a pig taking the specific posture.

6. The pig farming support device according to any one of claims 1 to 5, wherein the counting unit, when the detection unit detects multiple types of postures as the specific posture, assigns weights according to the detected postures and counts them.

7. The pig rearing support device according to any one of claims 1 to 6, wherein the counting unit, when the detection unit continuously detects the specific posture, assigns weights according to the duration of detection and counts accordingly.

8. The acquisition step involves acquiring image data of images captured by cameras installed facing multiple pens where pigs are kept in groups, and A detection step that detects, based on the image data, at least one of the following specific postures of the pig: a dog-like sitting posture with the front legs raised, a hunched-over posture with the front legs tucked under the torso, a hunched-over posture with the back rounded and the body bent forward, and a panting posture with the abdomen rippling while lying on its side. A counting step of counting the number of times the specific posture is detected in each of the plurality of pens during a set observation time. A method for supporting pig farming that has the following characteristics.

9. The acquisition step involves acquiring image data of images captured by cameras installed facing multiple pens where pigs are kept in groups, and A detection step that detects, based on the image data, at least one of the following specific postures of the pig: a dog-like sitting posture with the front legs raised, a hunched-over posture with the front legs tucked under the torso, a hunched-over posture with the back rounded and the body bent forward, and a panting posture with the abdomen rippling while lying on its side. A counting step of counting the number of times the specific posture is detected in each of the plurality of pens during a set observation time. A pig farming support program that uses a computer to perform certain tasks.

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