WO2022181131A1 - Système d'estimation de poids corporel et procédé d'estimation de poids corporel - Google Patents

Système d'estimation de poids corporel et procédé d'estimation de poids corporel Download PDF

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Publication number
WO2022181131A1
WO2022181131A1 PCT/JP2022/002005 JP2022002005W WO2022181131A1 WO 2022181131 A1 WO2022181131 A1 WO 2022181131A1 JP 2022002005 W JP2022002005 W JP 2022002005W WO 2022181131 A1 WO2022181131 A1 WO 2022181131A1
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weight
livestock
unit
pig
pigs
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PCT/JP2022/002005
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English (en)
Japanese (ja)
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雄一 稲葉
保 尾崎
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パナソニックＩｐマネジメント株式会社
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Publication of WO2022181131A1 publication Critical patent/WO2022181131A1/fr

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    • A—HUMAN NECESSITIES
    • A01—AGRICULTURE; FORESTRY; ANIMAL HUSBANDRY; HUNTING; TRAPPING; FISHING
    • A01K—ANIMAL HUSBANDRY; AVICULTURE; APICULTURE; PISCICULTURE; FISHING; REARING OR BREEDING ANIMALS, NOT OTHERWISE PROVIDED FOR; NEW BREEDS OF ANIMALS
    • A01K29/00—Other apparatus for animal husbandry
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/02—Agriculture; Fishing; Forestry; Mining

Definitions

  • the present invention relates to a body weight estimation system and a body weight estimation method.
  • Patent Literature 1 discloses a weight output system that estimates the weight of a pig based on an image of a pig located in an imaging area.
  • the present invention provides a weight estimation system and a weight estimation method that can easily and accurately estimate the weight of one or more livestock without human intervention.
  • a body weight estimation system includes an acquisition unit that acquires an image of a plurality of domestic animals located in a breeding area, which is captured by an imaging device; an estimating unit that specifies one or more contour shapes whose degree of matching with a predetermined contour shape is a threshold value or more, and estimates the weight of one or more livestock corresponding to the one or more identified contour shapes; an output unit that outputs estimated information in which the weight of the one or more livestock and the identification information of the breeding area are associated with each other.
  • a body weight estimation method includes an acquisition step of acquiring an image of a plurality of domestic animals located in a breeding area captured by a photographing device; an estimating step of identifying one or more contour shapes whose degree of matching with a predetermined contour shape is equal to or greater than a threshold, and estimating the weight of one or more livestock corresponding to the identified one or more contour shapes; an output step of outputting estimated information in which the weight of the one or more livestock and the identification information of the breeding area are associated with each other.
  • a program according to one aspect of the present invention is a program for causing a computer to execute the weight estimation method.
  • the weight estimation system, weight estimation method and program of the present invention can easily and accurately estimate the weight of one or more domestic animals without human intervention.
  • FIG. 1 is a diagram showing a schematic configuration of a body weight estimation system according to an embodiment.
  • FIG. 2 is a flow chart showing an example of the operation of the body weight estimation system according to the embodiment.
  • FIG. 3 is a diagram for explaining operations from extraction of a plurality of pigs appearing in an image to calculation of the size of one or more pigs.
  • FIG. 4 is a diagram showing an example of detection of an individual pig in an image and extraction of the outline of the detected pig.
  • FIG. 5 is a diagram showing an example of extraction of an estimated image.
  • FIG. 6 is a diagram showing an example of pig weight estimation.
  • FIG. 7 is a diagram showing an example of estimation information.
  • FIG. 8 is a flow chart of an output operation of estimated information.
  • FIG. 1 is a diagram showing a schematic configuration of a body weight estimation system according to an embodiment.
  • FIG. 2 is a flow chart showing an example of the operation of the body weight estimation system according to the embodiment.
  • FIG. 3 is
  • FIG. 9 is a diagram showing an example of an image showing transitions in estimated body weight in a specific pig enclosure in tabular form.
  • FIG. 10 is a diagram showing an example of an image graphically showing temporal transitions of estimated body weights of one or more pigs in a plurality of pig farms.
  • FIG. 11 is a flow chart of the scheduled shipping date notification operation.
  • FIG. 12 is a diagram showing an example of a screen for notifying the scheduled shipping date.
  • FIG. 13 is a flow chart of the growth state determination operation.
  • FIG. 14 is a diagram showing an example of a notification screen of the determination result of the growing state of pigs.
  • FIG. 15 is a graph showing the weight values of eight pigs measured in Experimental Example 1 and their average values.
  • FIG. 16 is a table showing the average value of measured values, the average value of estimated values, and their differences in Experimental Example 1;
  • each figure is a schematic diagram and is not necessarily strictly illustrated. Moreover, in each figure, the same code
  • FIG. 1 is a block diagram showing the functional configuration of the body weight estimation system according to the embodiment.
  • the livestock is a pig and the breeding area is a piggery in a barn.
  • a piggery is a plurality of partitioned areas configured in a livestock barn (specifically, a piggery), and is a breeding area for raising pigs in units of several dozen.
  • the weight estimation system 100 is a system capable of estimating the weight of the pig 80 in the pig farm 70 based on the image inside the pig farm 70 captured by the imaging device 10 .
  • a breeder or the like of the pig 80 can easily grasp the weight of the pig 80 by using the weight estimation system 100 .
  • the body weight estimation system 100 includes, for example, multiple imaging devices 10 and an information processing device 20 .
  • a server device 30 and a mobile terminal 40 are also illustrated.
  • the weight estimation system 100 may include a server device 30 and a mobile terminal 40, as in the example of FIG.
  • the photographing device 10 is, for example, a camera that is attached to the ceiling of the pigs' bunch 70 and photographs at least part of the inside of the pigs' bunch 70 from above.
  • one photographing device 10 is provided for each of the plurality of pigs' bunches 70 , but at least one photographing device 10 may be provided for one pig's bunch 70 . or more may be provided.
  • the photographing device 10 is implemented by, for example, a lens and an image sensor.
  • the photographing device 10 is specifically a general camera used for purposes such as monitoring, but may be a fisheye camera or the like.
  • the information processing device 20 identifies one or more contour shapes whose degree of matching with a predetermined contour shape is equal to or greater than a threshold among the plurality of contour shapes of the pig 80 appearing in the image captured by the imaging device 10, and identified.
  • the information processing device 20 displays estimated information in which the estimated weight of one or more pigs 80 and the identification information of the pig enclosure 70 are associated with each other. Further, the information processing device 20 may estimate the average value of the weights of one or more pigs 80 as the weight of each of the pigs 80 positioned in the pig pen 70 .
  • the information processing device 20 is, for example, a stationary information terminal such as a personal computer.
  • the information processing device 20 includes an operation reception unit 21 , a display unit 22 , a first communication unit 23 , an information processing unit 24 , a second communication unit 25 and a storage unit 26 .
  • the operation accepting unit 21 accepts an operation by a breeder or the like (in other words, a user).
  • the operation reception unit 21 is implemented by, for example, an input device such as a keyboard or mouse, but may be implemented by a touch panel or the like.
  • the display unit 22 displays an image showing the weight estimation result.
  • the display unit 22 is realized by a display panel such as a liquid crystal panel or an organic EL (Electro Luminescence) panel.
  • the first communication unit 23 is a communication circuit (communication module) for the information processing device 20 to communicate with the multiple imaging devices 10 via the local communication network.
  • the first communication unit 23 for example, acquires an image (in other words, image data or image information) captured by the imaging device 10 and outputs the acquired image to the information processing unit 24 .
  • Communication performed by the first communication unit 23 may be wired communication or wireless communication.
  • the communication standard for communication performed by the first communication unit 23 is not particularly limited either.
  • the information processing unit 24 acquires a plurality of images from each of the photographing devices 10 in the plurality of pig houses 70 acquired via the first communication unit 23, and converts the images for estimation extracted from the acquired images into Based on this, the weight per pig 80 in each pig pen 70 is estimated, and the estimated weight is output in association with the identification information of the pig pen 70 in which the pig 80 is located.
  • the information processing section 24 is implemented by, for example, a microcomputer, but may be implemented by a processor.
  • the information processing unit 24 includes an acquisition unit 24a, an estimation unit 24b, a notification unit 24c, a determination unit 24d, and an output unit 24f. Functions of the acquisition unit 24a, the estimation unit 24b, the notification unit 24c, the determination unit 24d, and the output unit 24f will be described later in the description of the operation and method.
  • the second communication unit 25 is a communication circuit (communication module) for the information processing device 20 to communicate with other devices through the wide area communication network 50 such as the Internet.
  • the second communication unit 25 transmits notification information regarding the estimated weight calculated by the information processing unit 24 to the server device 30 or the mobile terminal 40, for example. If such notification information is sent to the mobile terminal 40 owned by the breeder, the breeder can receive a notification regarding the estimated weight of the pig 80 in the pig pen 70 . Note that the notification information may be transmitted to the mobile terminal 40 via the server device 30 .
  • the communication performed by the second communication unit 25 may be wired communication or wireless communication.
  • the communication standard of communication performed by the second communication unit 25 is not particularly limited either.
  • the storage unit 26 is a storage device that stores a program executed by the information processing unit 24 for information processing and various types of information used for the information processing.
  • the storage unit 26 is specifically realized by a semiconductor memory.
  • the server device 30 is a server (cloud server) used when the weight estimation system 100 is realized as a client-server system with the information processing device 20 as a client.
  • the mobile terminal 40 is a mobile information terminal such as a smartphone or a tablet terminal operated by a breeder or the like.
  • the mobile terminal 40 is used by the breeder or the like to receive notifications related to the estimated weight of the pig 80 .
  • FIG. 2 is a flowchart showing an example of the operation of body weight estimation system 100 according to the embodiment. Here, the operation of estimating the weight of one or more pigs 80 by the weight estimation system 100 will be described.
  • the weight estimation system 100 estimates the weight of one or more pigs 80 reared in each of a plurality of pig pens 70 as in the example of FIG. The operation of estimating the weight of one or more pigs 80 raised in the pig pen 70 will be described.
  • the acquisition unit 24a of the information processing device 20 acquires an image of a plurality of livestock (for example, pigs 80) located in a breeding area (for example, pigs 70) photographed by the photographing device 10 (S101). ). More specifically, the acquisition unit 24a obtains an image (more specifically, image information of the image) captured by the imaging device 10 installed in the pigsty 70 via the first communication unit 23. to get
  • the photographing device 10 may constantly photograph images, may start photographing images based on a command from the information processing device 20, or may photograph a plurality of images at regular time intervals within a prescribed period of time. You can take pictures. Further, each image is provided with identification information indicating which pig farm 70 the image belongs to (that is, identification information of the pig farm 70). For example, the MAC (Media Access Control) address of the photographing device 10 is used as the identification information of the pigsty 70 . In the following steps S102 and S103, for convenience of explanation, one image will be processed. performed for
  • the estimating unit 24b identifies one or more contour shapes whose degree of matching with a predetermined contour shape is equal to or greater than a threshold among the contour shapes of the plurality of livestock animals (pig 80) appearing in the image acquired in step S101. (S102).
  • the estimation unit 24b when the body weight estimation system 100 includes a database (not shown) in which the contour shape of the pig 80 and the measured body weight of the pig 80 are linked and stored, stores one or more The weight of pig 80 may be estimated. More specifically, the estimating unit 24b refers to the measured data stored in the database, and identifies a contour shape that has a high degree of matching with a predetermined contour shape among the plurality of contour shapes extracted in the image. may
  • the estimation unit 24b may include a trained model (not shown).
  • the trained model detects a plurality of pigs 80 in an image and extracts the contours of the detected plurality of pigs 80. do.
  • the estimating unit 24b selects one or more contours of the plurality of pigs 80 whose degree of matching with a predetermined contour shape is equal to or greater than a threshold value.
  • a shape may be identified and the weight of one or more pigs 80 corresponding to one or more identified outline shapes may be estimated.
  • FIG. 3 is a diagram for explaining operations from extraction of a plurality of pigs 80 in an image to calculation of the sizes of the plurality of pigs 80.
  • FIG. 3 is a diagram for explaining operations from extraction of a plurality of pigs 80 in an image to calculation of the sizes of the plurality of pigs 80.
  • step S102 the estimation unit 24b detects a plurality of individual pigs 80 in the image acquired in step S101 (eg, (a) of FIG. 3).
  • the estimating unit 24b uses object detection technology based on deep learning such as Mask-RCNN, for example. Extract image regions.
  • the estimation unit 24b extracts an image region including the entire body (from the head to the buttocks) of the pig 80 by filtering.
  • an image area showing only a part of the body of the pig 80 is excluded. For example, in (a) of FIG. 3, seven pigs 80 are shown in the image, but only part of the body is shown in four of them. In this case, as shown in (b) of FIG. Do not extract image regions where only part of the body of a person is visible.
  • step S102 if two or more pigs overlap and are recognized as one area, such an area is not extracted. For example, by setting an upper limit on the size of the image area, one area in which two or more pigs overlap can be excluded from the target area.
  • the estimation unit 24b extracts the outline of the pig 80 included in each of the plurality of extracted image regions.
  • a contour extraction method will be described later.
  • the estimating unit 24b compares, for example, the contours of the pig 80 in the measured data among the extracted contours of the pig 80, and selects contours with a high matching level (see (d) in FIG. 3).
  • the measured data is data in which the contour shape of the pig 80 and the measured weight of the pig 80 having the contour shape are associated with each other, and are stored in a database (not shown).
  • the database may be provided in the estimation unit 24b or may be provided in the storage unit 26.
  • the estimating unit 24b calculates the degree of matching (in other words, matching level) of the contour shapes of the plurality of pigs 80 shown in the image with a predetermined contour shape. Identify one or more contour shapes for which is greater than or equal to a threshold.
  • the estimation unit 24b estimates the weight of one or more livestock (pig 80) corresponding to one or more outline shapes identified in step S102 (S103). For example, the estimating unit 24b calculates the coordinates of the center of gravity of the contour shape and the lengths of the long and short axes passing through the center of gravity for each of the one or more pigs 80 corresponding to the one or more contour shapes identified in step S102. A parameter including weight (eg, Hu moment) is calculated, and the weight of one or more pigs 80 is estimated using the calculated parameter. Specifically, the estimation unit 24b calculates parameters from the shape of the extracted contour.
  • the estimation unit 24b calculates parameters from the shape of the extracted contour.
  • the Hu moment is a quantity that is invariant to translation, scale, and rotation obtained by computing an image, and is a quantity that depends only on the shape, so it is used to determine the similarity of shapes. More specifically, as shown in (d) of FIG. 3, the estimation unit 24b calculates the coordinates of the center of gravity (in other words, the position of the center of gravity in the image) from the outline shape of one or more pigs 80, A length L of a major axis (also referred to as a major axis) and a length D of a minor axis (also referred to as a minor axis) that pass through the center of gravity and intersect are calculated.
  • the lengths of the major axis and the minor axis are the lengths expressed in pixels on the image, but a specific length on the image (e.g., a feeder or known dimensions of a slatted floor, etc.) ) as a reference, and may be expressed as a relative size.
  • the estimating unit 24b derives a correction coefficient k for estimating the weight of the plurality of pigs 80 located in the pigsty 70 for each of the pigsty 70 based on the database described above, and calculates the correction coefficient k as a parameter. , and a correction factor k to estimate the weight of one or more pigs 80 .
  • the correction coefficient k is empirically or experimentally determined based on measured data showing the relationship between volume and measured body weight. A method of estimating body weight will be described later.
  • the processes in steps S102 and S103 are performed on each of the multiple images acquired in step S101.
  • the output unit 24f outputs the correspondence between the weight of the one or more pigs 80 estimated by the estimation unit 24b in step S103 and the identification information of the pig pen 70 where the one or more pigs 80 are located.
  • the attached estimation information is output (S104).
  • the average value of the weight of one or more pigs 80 is estimated as the weight of each of the plurality of pigs 80 located in the pig bund 70, and the estimated average weight of the plurality of pigs 80 and the weight of the pig bund 70 It may be output in association with identification information.
  • the estimation unit 24b stores the estimation information in the storage unit 26 (not shown). At this time, the estimation information may be stored in the storage unit 26 in association with the date and time (at least the date) when the image was captured by the image capturing device 10 .
  • FIG. 7 is a diagram showing an example of estimation information. As shown in FIG. 7, the estimated information is associated with the average value of the weights of the pigs 80 in each of the pig bunches 70 (estimated body weight in the figure) and the identification information of the pig bunch 70. This data is associated with the date and time. As described above, the identification information of the pigsty 70 is added to the image acquired in step S101. Also, the date and time is the shooting date and time of the image. By associating the estimated weight with the date and time, it can be said that the storage unit 26 manages the time transition of the estimated weight in each of the plurality of pig bunds 70 .
  • the body weight estimation system 100 identifies one or more outline shapes whose degree of matching with a predetermined outline shape is equal to or greater than a threshold among the plurality of outline shapes of the pig 80 shown in the image, and determines the specified one or more outline shapes. can estimate the weight of one or more pigs 80 corresponding to the contour shape of .
  • the weight estimating system 100 does not need to gather a plurality of pigs 80 located in the pig pen 70 at a predetermined place to take an image, and does not identify individual pigs 80 by ear markings or identification tags. Therefore, the weight estimation system 100 can estimate the weight of one or more pigs 80 relatively easily. It can be said that the weight estimation system 100 is well suited for an all-in-all-out breeding method in which pigs are put into the pig pen 70 all at once, and then all pigs are shipped at once.
  • FIG. 4 is a diagram showing an example of individual detection of a pig 80 appearing in an image and outline extraction of the detected pig 80.
  • FIG. 5 is a diagram showing an example of extraction of an estimated image.
  • the estimating unit 24b detects all the pigs 80 appearing in each of the plurality of images acquired by the acquiring unit 24a using, for example, the object detection technology described above, and detects the pigs 80.
  • An image region including the entire body of the pig 80 is extracted from all the pigs 80 that have been collected. For example, as shown in FIG. 4, the estimating unit 24b extracts image regions of all pigs 80 appearing in the image shown in FIG. 4(a) and the image shown in FIG. 4(b). , an image region including the entire body (from the head to the buttocks) of the pig 80 is extracted by filtering. Then, the estimation unit 24b calculates the detection level of the pig 80 included in the extracted image area (more specifically, the likelihood that the detected object is a pig).
  • the estimating unit 24b extracts the contour of the pig 80 depending on the image region (hereinafter also referred to as region-dependent contour). For example, as shown in FIGS. 4(b) and 4(c), the estimation unit 24b detects the region-dependent contour ( ) is extracted.
  • the estimation unit 24b corrects the region-dependent contour to a contour that follows the original shape of the pig. For example, as shown in (c) of FIG. 4, the estimating unit 24b expands the region-dependent contours in the directions of the arrows, respectively, so that the contours (thick solid lines in the drawing) along the original shape of the pig are drawn. corrected to Further, for example, as shown in (d) of FIG. 4, the estimation unit 24b calculates the region-dependent contour (shaded region in the figure) of the pig 80 (detection level: 0.910) detected in the image. outer circumference) is extracted and the region-dependent contours are expanded in the directions of a plurality of arrows to correct the contours (thick solid lines in the figure) along the original shape of the pig. This is also called a contour after correction.
  • the estimating unit 24b extracts the post-correction contour as the contour of the pig 80 included in the image area. Calculate the detection level again. Then, the estimating unit 24b extracts the contour of the pig 80 (also referred to as the contour to be matched) for which matching is performed between the measured data and the contour shape by performing filtering under a predetermined condition.
  • the predetermined conditions are, for example, (i) the recalculated detection level of the pig 80 is greater than a predetermined value (eg, 0.970), and (ii) the shape of the contour of the pig 80 after correction is an ellipse. It is the shape.
  • FIG. 6 is a diagram showing an example of estimating the weight of the pig 80. As shown in FIG.
  • the estimating unit 24b estimates the weight of one or more pigs 80 corresponding to one or more contour shapes whose degree of matching with a predetermined contour shape is equal to or greater than a threshold among the contour shapes of the plurality of pigs 80 shown in the image. .
  • the estimating unit 24b calculates a correction coefficient k from actual measurement data in which the size of the pig 80 and the actual weight of the pig 80 are associated with each of N pigs 1 to N, and The body weight of one or more pigs 80 is estimated using the calculated correction coefficient k and parameters.
  • the correction coefficient k is a coefficient that converts the volume of the pig 80 (eg, represented by the number of pixels) into weight.
  • the parameters are the length of the minor axis D and major axis L through the center of gravity.
  • the correction coefficient k is empirically or experimentally determined based on measured data showing the relationship between volume and measured body weight.
  • the estimation unit 24 b estimates the weight of one or more pigs 80 and estimates the average value of the estimated weights as the weight of each of the multiple pigs 80 in the pig pen 70 . In other words, the estimation unit 24b may estimate the average weight of one or more pigs as the average weight of the pigs 80 in the pig pen 70 .
  • the weight estimation system 100 can output estimated information in which the estimated weight of the pig 80 for each pig pen 70 and the date are associated with each other, and can present the estimated information to the breeder or the like.
  • the estimated weight output operation of the weight estimation system 100 will be described below.
  • FIG. 8 is a flow chart of an estimated weight output operation.
  • the estimation unit 24b estimates the weight of the livestock (pig 80) from each of a plurality of images captured on different dates by the imaging device 10 (S201). Next, the estimating unit 24b associates the estimated weight of the livestock (pig 80) with the identification information of the breeding area (pig pen 70) with the date and stores the estimated information in the storage unit 26. (S202).
  • the estimating unit 24b causes the display unit 22 to display pigs for each pig bunt 70 in accordance with the received operation.
  • An image showing the estimated weight of 80 is displayed.
  • the acquisition unit 24a acquires from the operation reception unit 21 a signal indicating a user's instruction to display the estimated information associated with the date on the display unit 22, the acquisition unit 24a stores the signal from the storage unit 26 in association with the date. read the estimated information, and output the read estimated information (more specifically, the estimated information associated with the date) to the output unit 24f (S203).
  • the display unit 22 displays, for example, an image showing changes in the estimated weight of one or more pigs 80 in a specific pig farm 70 in the form of a table, based on the estimated information output from the output unit 24f.
  • FIG. 9 is a diagram showing an example of an image showing changes in estimated body weight in a specific pig enclosure 70 in tabular form.
  • the estimated body weight for that day is, for example, the representative value (specifically, the average value or the median value) of the estimated body weights calculated multiple times. .
  • the display unit 22 may display an image showing the temporal transition of the estimated weight of the pigs 80 in the plurality of pig bunds 70 by graphs.
  • FIG. 10 is a diagram showing an example of an image graphically showing the temporal transition of the estimated weight of pigs 80 in a plurality of pig bunds 70. As shown in FIG.
  • the weight estimation system 100 can present the estimated weight of the pig 80 to the breeder or the like. By grasping the estimated weight, the breeder or the like can predict the timing of shipment of the pig 80 and control the amount of feed. In other words, the body weight estimation system 100 can assist a breeder or the like in breeding the pig 80 .
  • the weight estimation system 100 further includes a notification unit 24c that notifies the breeder (user) of notification information.
  • the weight estimation system 100 predicts the date on which the pig 80 will have a weight suitable for shipping for each pig bund 70 based on the above estimation information, and the predicted date on which the pig 80 will have a weight suitable for shipping. (hereinafter also referred to as the scheduled shipping date) can be notified in advance to the breeder or the like.
  • FIG. 11 is a flow chart of the scheduled shipping date notification operation.
  • the estimating unit 24b refers to the estimated information stored in the storage unit 26 in association with the date (not shown), and determines the time transition of the body weight of one or more pigs 80 (in other words, the fattening age of the pigs). based on each of the pig bunches 70, the scheduled shipping date of the livestock (pig 80) (in other words, the date when the estimated weight reaches within a predetermined range) is estimated (S301). For example, the estimating unit 24b predicts the scheduled shipping date by calculating an approximated curve or straight line of the estimated weight of one or more pigs 80, which is determined by the estimated information referred to, over time. can do.
  • the predetermined range is, for example, a range of 110 kg or more and 120 kg or less, but is not particularly limited.
  • the notification unit 24c notifies the breeder or the like of notification information in which the scheduled shipping date of the livestock (pig 80) estimated in step S301 and the identification information of the breeding area (pig pen 70) are associated with each other. (S302). Specifically, the notification unit 24 c transmits notification information for notifying the breeder or the like of the scheduled shipping date of the pig 80 for each pig house 70 to the mobile terminal 40 via the second communication unit 25 . As a result, a notification screen as shown in FIG. 11 is displayed on the mobile terminal 40 .
  • FIG. 11 is a diagram showing an example of a screen for notifying the scheduled shipping date.
  • the scheduled shipping date of the pig 80 may be notified by push. Further, the scheduled shipping date of the pig 80 may be displayed on the display unit 22 of the information processing device 20 based on the operation of the breeder or the like.
  • the body weight estimation system 100 can notify the scheduled shipping date of the pig 80 for each pig farm 70 based on the time transition of the estimated weight in each of the plurality of pig farms 70 .
  • the body weight estimation system 100 further includes a determination unit 24d that determines the growth state of livestock (pigs 80) in a plurality of breeding areas (pigs 70). Thereby, the body weight estimation system 100 determines whether the growing condition of the pigs 80 in the pig bunds 70 is good or bad by comparing the estimated body weights corresponding to the pig bunds 70 based on the above estimation information. Then, the judgment result can be presented to the breeder or the like (user).
  • the growth state determination operation of the weight estimation system 100 will be described below.
  • FIG. 12 is a flow chart of the growth state determination operation.
  • the determination unit 24d refers to the estimated information stored in the storage unit 26 (not shown), and compares the estimated weights of the plurality of livestock (pigs 80) corresponding to the plurality of pig bunches 70 ( S401), the growth state of the livestock (pigs 80) in each of the plurality of breeding areas (pigs 70) is determined (S402). For example, the determining unit 24d compares the average value of the estimated body weights of the pigs 80 in the plurality of pig bunches 70 with the average value of the estimated body weights of one or more pigs 80 in each of the plurality of pig bunches 70, and compares the average value.
  • a pig farm 70 in which the mean value of the estimated body weight is less than a predetermined value is determined to be a pig farm 70 in which the pig 80 is in a poor growth state.
  • the output unit 24f outputs growth information indicating the growth state (that is, the determination result of step S402) (S403). Specifically, the output unit 24f outputs notification information (so-called growth information) for notifying the breeder or the like of the pig bund 70 in which the pig 80 has been determined to be in poor growth condition by the determination unit 24d in step S402. Output to the mobile terminal 40 via the second communication unit 25 . As a result, a notification screen as shown in FIG. 14 is displayed on the mobile terminal 40 .
  • FIG. 14 is a diagram showing an example of a notification screen of the determination result of the growing state of the pig 80.
  • the determination result of the growth state may be notified by push notification. Further, the determination result of the growth state may be displayed on the display unit 22 of the information processing device 20 based on the operation of the breeder or the like.
  • the body weight estimation system 100 can notify the breeder or the like of the pig bund 70 in which the pig 80 has been determined to be in poor growth condition.
  • the breeder or the like can investigate the cause of the poor growth condition of the pig 80 in the pig pen 70 and improve the growth condition of the pig 80 in the pig pen 70 .
  • the pig bund 70 in which the pig 80 is in a good growing condition is determined instead of the pig bunch 70 in which the pig 80 is in a poor growing condition, or in addition to the pig bund 70 in which the pig 80 is in a poor growing condition.
  • the determination unit 24d compares the average value of the estimated body weights of the plurality of pig bunches 70 with the estimated body weight of each of the plurality of pig bunches 70, and selects the pig bunch 70 having an estimated body weight greater than the average value by a predetermined value or more. 80 can be determined to be pig bunch 70 in good growth condition.
  • the breeder or the like will investigate the cause of the good growing state and follow the pig farm 70 in which the pig 80 is in a good growing state.
  • the growing condition of the pigs 80 in the other pig bunch 70 can be improved.
  • Weight estimation system 100 may be implemented as a client-server system. In this case, part or all of the processing described as being performed by the information processing device 20 in the above embodiment may be performed by the server device 30 .
  • the body weight estimation system 100 was used to estimate the body weights of a plurality of pigs 80 in the pig pen 70 .
  • the pigs 80 to be tested are eight white pigs. Individual detection of pigs and outline extraction of white pigs were performed, and parameters were calculated from the shape of the extracted outlines. Then, a correction coefficient k was calculated from the measured data in which the parameters and the measured weights were associated with each other, and the weights of the eight white pigs were estimated using the calculated correction coefficient k. Furthermore, the weight of 8 white pigs was actually measured, and the difference between the measured weight and the estimated weight was calculated. The results are shown in FIGS. 15 and 16. FIG.
  • FIG. 15 is a graph showing the weight values of the eight pigs 80 measured in Experimental Example 1 and their average values.
  • FIG. 16 is a table showing the average value of measured values, the average value of estimated values, and their differences in Experimental Example 1;
  • the body weight estimation system 100 includes the acquisition unit 24a that acquires an image of the plurality of pigs 80 located in the pig enclosure 70, captured by the imaging device 10, and the An estimating unit that identifies one or more contour shapes whose degree of matching with a predetermined contour shape is equal to or greater than a threshold, and estimates the weight of one or more pigs 80 corresponding to the one or more identified contour shapes. and an output unit 24f for outputting estimated information in which the estimated weight of one or more pigs 80 and the identification information of the pig bunch 70 are associated.
  • a pig 80 is an example of livestock
  • a pig enclosure 70 is an example of a breeding area.
  • Such a weight estimation system 100 identifies one or more contour shapes that have a high degree of matching with a predetermined contour shape among the plurality of contour shapes of the pig 80 shown in the image, and uses the identified one or more contour shapes.
  • the weight of one or more corresponding pigs 80 can be estimated. Therefore, the weight estimation system 100 can easily and accurately estimate the weight of one or more pigs 80 without human intervention.
  • the estimating unit 24b estimates the average value of the weights of one or more pigs 80 as the weight of each of the pigs 80 located in the pig pen 70.
  • the body weight estimation system 100 estimates the body weights of the pigs 80 by estimating the average body weight of one or more pigs 80 as the body weight of each of the pigs 80 located in the pig enclosure 70. can do.
  • the estimating unit 24b determines the coordinates of the center of gravity of the contour shape and the lengths of the major and minor axes passing through the center of gravity for each of the one or more pigs 80 corresponding to the one or more specified contour shapes. and estimate the weight of one or more pigs 80 using the calculated parameters.
  • Such a weight estimation system 100 can estimate the weight of one or more pigs 80 based on the calculated parameters.
  • the weight estimation system 100 further includes a database (not shown) in which the outline shape of the pig 80 and the measured weight of the pig 80 are linked and stored. Estimate the weight of one or more pigs 80 .
  • Such a body weight estimation system 100 compares the measured data in which the contour shape of the pig 80 stored in the database and the measured weight of the pig 80 are linked with the contour shapes of the plurality of pigs 80 shown in the image. Therefore, it is possible to estimate the weight of one or more pigs 80 corresponding to one or more contour shapes that have a high degree of agreement with the measured data.
  • the estimating unit 24b derives a correction coefficient k for estimating the weight of the plurality of pigs 80 positioned in each of the pig bunds 70 based on a database (not shown). and the weight of one or more pigs 80 is estimated using the parameters and the correction factor k.
  • Such a weight estimation system 100 calculates the weight of one or more pigs 80 using a correction coefficient k and a parameter (for example, the length of the long axis and the short axis passing through the center of gravity of the outline of the pig 80 in the estimation image). can be estimated.
  • a correction coefficient k for example, the length of the long axis and the short axis passing through the center of gravity of the outline of the pig 80 in the estimation image.
  • the estimating unit 24b has a trained model (not shown), the trained model detects a plurality of pigs 80 in an image, extracts the contours of the detected plurality of pigs 80, and the estimating unit 24b identifying one or more contour shapes of the plurality of pigs 80 whose degree of matching with a predetermined contour shape is equal to or greater than a threshold value, based on the contours of the plurality of pigs 80 extracted by the learned model; Estimate the weight of one or more pigs 80 corresponding to the identified one or more outline shapes.
  • Such a body weight estimation system 100 uses a learned model to efficiently extract one or more pigs 80 having a contour shape that has a high degree of matching with a predetermined contour shape from a plurality of pigs 80 appearing in an image. , the weight of one or more pigs 80 can be estimated.
  • the estimating unit 24b estimates the weight of one or more pigs 80 from each of a plurality of images captured on different dates by the imaging device 10, and the estimated weight of the one or more pigs 80,
  • the estimated information associated with the identification information of the pigsty 70 is associated with the date and stored in the storage unit, and the output unit 24f outputs the estimated information associated with the date.
  • Such a body weight estimation system 100 can manage changes in the estimated body weight of one or more pigs 80 for each pig farm 70.
  • the weight estimation system 100 further includes a notification unit 24c that notifies the user of notification information, and the estimation unit 24b stores one or more bodies included in the estimation information stored in the storage unit 26 in association with the date.
  • the notification unit 24c estimates the estimated shipping dates of the plurality of pigs 80 in the pig bund 70. Notification information in which the scheduled date of shipment of the pig 80 and the identification information of the pigsty 70 are associated is notified to the user.
  • Such a body weight estimation system 100 can notify the scheduled shipping dates of a plurality of pigs 80 for each pig bunch 70.
  • the weight estimation system 100 further compares the weights of one or more pigs 80 corresponding to the pig bunches 70 to determine the growth state of the pigs 80 in the pig bunches 70.
  • the determination unit 24d is provided, and the output unit 24f outputs growth information indicating the growth state determined by the determination unit 24d.
  • Such a body weight estimation system 100 can determine the growth state of the pigs 80 based on the relative relationship between the estimated body weights of one or more pigs 80 corresponding to the pig bunds 70 .
  • the weight estimation method executed by a computer such as the weight estimation system 100 includes an acquisition step of acquiring an image of a plurality of pigs 80 positioned in a pig pen 70 captured by a photographing device; Among the contour shapes of the pig 80, one or more contour shapes having a degree of matching with a predetermined contour shape equal to or higher than a threshold are specified, and the weight of one or more pigs 80 corresponding to the specified one or more contour shapes and an output step of outputting estimated information in which the estimated weight of one or more pigs 80 and the identification information of the pig bunch 70 are associated.
  • Such a weight estimation method identifies one or more contour shapes that have a high degree of matching with a predetermined contour shape among the plurality of contour shapes of the pig 80 shown in the image, and corresponds to the identified one or more contour shapes.
  • the weight of one or more pigs 80 can be estimated.
  • the weight estimation method can estimate the weight of one or more pigs 80.
  • the weight estimation system manages the weight of pigs in the pig enclosure, but it may also manage the weight of livestock other than pigs.
  • Livestock is, for example, animals such as pigs, cows, sheep, and horses, but may also be poultry such as chickens.
  • processing executed by a specific processing unit may be executed by another processing unit.
  • order of multiple processes may be changed, and multiple processes may be executed in parallel.
  • each component may be realized by executing a software program suitable for each component.
  • Each component may be realized by reading and executing a software program recorded in a recording medium such as a hard disk or a semiconductor memory by a program execution unit such as a CPU or processor.
  • each component may be realized by hardware.
  • a component such as a controller may be a circuit (or integrated circuit). These circuits may form one circuit as a whole, or may be separate circuits. These circuits may be general-purpose circuits or dedicated circuits.
  • the present invention may be realized as a weight estimation method executed by a computer such as a weight estimation system, or as a program for causing a computer to execute the weight estimation method.
  • a computer such as a weight estimation system
  • a program for causing a computer to execute the weight estimation method may be implemented as a computer-readable non-transitory recording medium on which is recorded.
  • the body weight estimation system is implemented by a plurality of devices, but it may be implemented as a single device.
  • the components included in the body weight estimation system described in the above embodiments may be distributed to the multiple devices in any way.

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Abstract

L'invention concerne un système d'estimation de poids corporel (100) qui comprend : une unité d'acquisition (24a) pour acquérir une image photographiée à l'aide d'un dispositif de photographie (10), dans lequel une pluralité d'animaux domestiques se trouvant dans une zone de reproduction sont vus ; une unité d'estimation (24b) pour identifier une ou plusieurs formes de contour, parmi les formes de contour de la pluralité d'animaux domestiques vus dans l'image, le degré auquel lesdites formes de contour correspondent à une forme de contour prescrite étant supérieur ou égal à un seuil, ladite unité d'estimation (24b) estimant les poids corporels d'un ou de plusieurs animaux domestiques qui correspondent à la ou aux formes de contour identifiées ; et une unité de sortie (24f) pour délivrer en sortie des informations d'estimation dans lesquelles les poids corporels estimés d'un ou de plusieurs animaux domestiques et les informations d'identification de la zone de reproduction sont associés.
PCT/JP2022/002005 2021-02-25 2022-01-20 Système d'estimation de poids corporel et procédé d'estimation de poids corporel WO2022181131A1 (fr)

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Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2003250382A (ja) * 2002-02-25 2003-09-09 Matsushita Electric Works Ltd 水棲生物の成育状態監視方法及びその装置
JP2019045304A (ja) * 2017-09-01 2019-03-22 Ｎｔｔテクノクロス株式会社 体重出力装置、体重出力方法及びプログラム
JP2019205375A (ja) * 2018-05-29 2019-12-05 Ｎｅｃソリューションイノベータ株式会社 家畜の出荷判定表示装置、出荷判定表示方法、プログラム、および記録媒体
WO2020044869A1 (fr) * 2018-08-30 2020-03-05 パナソニックＩｐマネジメント株式会社 Système de gestion d'informations sur des animaux et procédé de gestion d'informations sur des animaux
JP6781440B1 (ja) * 2020-02-27 2020-11-04 株式会社Ｅｃｏ‐Ｐｏｒｋ 畜産情報管理システム、畜産情報管理サーバ、畜産情報管理方法、及び畜産情報管理プログラム

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2003250382A (ja) * 2002-02-25 2003-09-09 Matsushita Electric Works Ltd 水棲生物の成育状態監視方法及びその装置
JP2019045304A (ja) * 2017-09-01 2019-03-22 Ｎｔｔテクノクロス株式会社 体重出力装置、体重出力方法及びプログラム
JP2019205375A (ja) * 2018-05-29 2019-12-05 Ｎｅｃソリューションイノベータ株式会社 家畜の出荷判定表示装置、出荷判定表示方法、プログラム、および記録媒体
WO2020044869A1 (fr) * 2018-08-30 2020-03-05 パナソニックＩｐマネジメント株式会社 Système de gestion d'informations sur des animaux et procédé de gestion d'informations sur des animaux
JP6781440B1 (ja) * 2020-02-27 2020-11-04 株式会社Ｅｃｏ‐Ｐｏｒｋ 畜産情報管理システム、畜産情報管理サーバ、畜産情報管理方法、及び畜産情報管理プログラム

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