• 专利附录
  • 专利说明
  • 权利要求
  • 类似技术
  • 同族专利
  • 引用文献
  • 法律状态
  • 优先权
    • 专利摘要:
    SYSTEM FOR DETERMINING FOOD CONSUMPTION AT LEAST ONE ANIMAL. THE INVENTION REFERS TO AN ANIMAL MONITORING SYSTEM TO DETERMINE FOOD CONSUMPTION OF ONE OR MORE ANIMAL FOODS IN A FEEDING AREA, UNDERSTANDING AN IMAGE UNIT TO CREATE FEEDING AREA INTERVAL IMAGE, CONFIGURATION OF IDENTIFICATION MEANS TO IDENTIFY-CAR IN A UNIQUE WAY FOR EACH ANIMAL FOR FOOD, AND CONFIGURED PROCESSING MEDIA TO ASSESS THE AMOUNT OF FOOD CONSUMED BY EACH IDENTIFIED ANIMAL WHEN DETERMINING FOOD REDUCTION IN SUBSEQUENT IMAGES OF THE FEEDING FRONT OF THE FEEDING FRONT.
    公开号:BR112015025972B1
    申请号:R112015025972-3
    申请日:2014-04-10
    公开日:2020-12-08
    发明作者:Søren BORCHERSEN；Niels Worsøe Hansen；Claus Borggaard
    申请人:Viking Genetics Fmba；
    IPC主号:
    专利说明:

    Field of invention
    [001] The invention relates to a system and method for determining food consumption of at least one livestock animal and / or for determining the individual food consumption of a plurality of livestock animals. Background of the invention
    [002] Livestock feed, such as livestock, is given mainly as concentrates and forage. The high-energy food concentrate comprises rapeseed flour, soy meal and minerals and vitamins, whereas fiber-rich forage comprises grass silage, corn silage, alfalfa or grass seed straw or grain crops. However, animal feed, as used here, can comprise concentrate, forage, additives, products and, in general, anything that can be ingested and digested by animals.
    [003] Some farmers prefer to separate concentrate and forage and provide each one separately in order to control and monitor the amount of concentrate provided for the animals, and systems for dosing concentrated feed are known in the art. However, it is becoming more common to mix the concentrate and the forage (and other appropriate and relevant animal food) and to provide this mixture to the animals through the normal feeding area, for example, in a stable. The feeding area is typically common for many animals, possibly feeding in the feeding area simultaneously. Summary of the invention
    [004] Total food consumption for an entire livestock is easily determined, due to the fact that the farmer monitors the gross amount of food purchased and distributed to the animals, but it is a challenge to monitor the individual animal's food consumption. in livestock. State-of-the-art systems are based on weighing the quantity of food and supplying it separately to specific animals, but this is not a practical and financially effective solution. But, when the food is distributed in a common feeding area in a stable, the farmer has no way of assessing the food consumption of the individual animals. It is, therefore, a purpose of the present disclosure to provide a method and system for determining food consumption of at least one animal in a livestock, and to determine and / or compare the individual food consumption of a plurality of animals in a livestock. In particular, it is a purpose of the present disclosure to monitor, determine and / or compare food consumption for individual animals among a plurality of animals feeding in a common feeding area. One modality, therefore, refers to an animal monitoring system to determine food consumption of one or more animals feeding in a feeding area, comprising an imaging unit to create an interval image of the feeding area, means of identification configured to uniquely identify each animal for food, and processing means configured to assess the amount of food consumed by each identified animal by determining the food reduction in subsequent images of the feeding area in front of each identified animal.
    [005] Other modalities refer to a system for determining food consumption of at least one animal in a livestock comprising at least one identification plate linked to at least one animal, by means of which a specific animal can be identified, a feeding area having food accessible to at least one animal, at least one camera adapted to acquire images of the food in the feeding area at different times, processing means adapted to determine the food consumed by a specific identified animal when analyzing the food reduction as represented in at least two images.
    [006] The animal monitoring system currently disclosed is preferably suitable for installation in a housing livestock under construction, such as a stable. In addition, the feed can be any feed suitable for animals, such as cows, in particular fodder, concentrate, and / or a mixture thereof.
    [007] An additional modality refers to a method to assess the food consumption of one or more animals feeding in a feeding area, comprising: - acquiring interval images of the feeding area at different times , - identifying at least one of said animals consuming food in at least two of said interval images, and - assessing the amount of food consumed by each identified animal when determining the reduction of food between said at least two interval images.
    [008] An additional modality refers to a method to assess food consumption related to a plurality of animals in a livestock feed in a feeding area, - acquiring interval images of the feeding area at different times, - identifying all animals consuming food, - assess the amount of food consumed by each identified animal by determining the food reduction between at least two interval images showing an identified animal, and - determine the amount of food consumed by an identified animal in relation to the amount of food consumed by the remaining identified animals.
    [009] Thus, with the systems and methods mentioned above it is possible to de-determine the amount of food each animal has consumed, due to the fact that creating an interval image of the food reduction can provide the volume of food consumed by each animal, for example whereby the farmer can take the total image of consumption, for example, for all livestock and / or for each individual animal in livestock. Correlating with the productivity of each animal, for example, milk production, the contribution margin for each animal can be determined. This allows the farmer to calculate the efficiency, cost effectiveness and environmental impact of an individual animal and / or all livestock. Based on the calculations, the farmer can, for example, identify the most appropriate animals for breeding. In addition, variations in feed intake for an individual animal can be used to detect the health condition and when an animal is in heat. Description of the figures
    [010] The invention will be described in more detail below with reference to the accompanying figures: Fig. 1 is a schematic view of an embodiment of the invention. Figs. 2a-d show relationships between the current and calculated food consumption of four different cows. Detailed description of the invention
    [011] The imaging unit preferably comprises one or more cameras, preferably cameras adapted to create interval images, such as interval cameras. Examples of interleaving image techniques applicable here are time-of-flight, stereo triangulation, structured light, light field image creation, etc. Each range camera can be provided with a depth sensor and a 2D camera, such as an RGB camera, for example, as known from Kinect cameras. Other possible solutions are stereo cameras (for example, pairs of 2D cameras), flight time cameras, structured light cameras, or light field cameras for creating a 4D light field image. The imaging unit can also be configured to acquire topographic images. With interval image creation it is possible to determine the distance from a camera to the food and, therefore, determine the volume of food with greater precision.
    [012] The imaging unit can be configured to image at least part of the feed area continuously. For example, the imaging unit can be adapted to acquire a series of images, which allows you to determine the animal's food consumption over a period of time. For example, the imaging unit may require images continuously, thus allowing the determination of food consumption in real time. In one embodiment, the imaging unit requires at least one image per minute, or at least one image every 1 to 5 minutes. For example, images are required as a video signal or at least once a minute, for example, every 1, 5, 10, 20 or 30 seconds. The number of images required must be sufficient to validly monitor food consumption. The imaging unit can be configured to image at least part of the feed area at selected and / or predefined time points.
    [013] That is, instead of continuously requiring images with fixed intervals, the system can be configured such that certain actions, for example, related to animals, can trigger the acquisition of an image or a series of images. Thus, the system can be configured to determine when an identified animal is starting, stopping and / or ending a feeding process. Or the system can be configured to determine when an identified animal removes its head from the feeding area. Such actions may result in the acquisition of one or more images. For example, the system can be configured such that an interval image is acquired when an identified animal removes the head from the feeding area or when an identified animal starts and / or ends a feeding process. The system can also be configured such that images are acquired continuously at fixed intervals, but only certain images are stored and / or processed, for example, images relating predefined actions, for example, relating animal feed. An animal can be identified before, during or after image acquisition, for example, animals are identified during image processing.
    [014] Animal food is not necessarily a homogeneous mixture and the density of the food can vary from time to time. Therefore, it can be difficult to determine the exact weight of the food consumed by the animals, based on image analysis. One way to assess the amount of food consumed by the animals is to determine the reduction of the food from the beginning of the feeding process to the end and / or while the animals are eating, even when using interval imaging. The reduction in feed between subsequent images can be determined by calculating the difference in height of corresponding image areas, such as pixels. The “missing” element or volume between subsequent images is the food consumed by an animal. Food can be identified in each image or a virtual feed area corresponding to a specific animal can be identified or selected in images, thus representing food in subsequent images, and only corresponding image areas are selected to determine the reduction in volume of the food . Interval images would be an advantage in such a situation.
    [015] The imaging unit can be configured such that several images are acquired simultaneously. The processing means can then be adapted to combine these images in order to determine the amount of food in the feed area. Thus, the amount of food in the food area can be determined with a higher requirement. The technique of combining images is also known as stitched images.
    [016] In one embodiment, the system further comprises means for controlling the position and / or the angle of the imaging unit and / or the position and / or the angle of cameras of the imaging unit. Thereby, the camera or cameras can be moved to the optimum position ensuring optimal images of the food, which leads to an accurate determination of the animals' food consumption. Additionally, it is possible to use a small number of cameras to cover a large amount of food when moving along the food and capturing images at the same time.
    [017] Alternatively, the imaging unit can be configured to be stationary. Although it may require more cameras, it can be simple and inexpensive to install and thus more cost effective in total. In addition, it is possible to use a plurality of fixed cameras instead of a smaller number of cameras moving, thus achieving the accuracy of measurements made based on the images.
    [018] The imaging unit can additionally be configured to image a selected and / or predefined part of the feed area. This may be the case with translatable and / or rotating cameras from the imaging unit. However, it may also be the case if the imaging unit comprises several cameras, each camera sees different parts of the eating area. The system can then be configured only to require images of the part of the feeding area where the activity, for example, feeding activity, is recorded. To reduce the cost of the system, the number of cameras in the imaging unit is typically less than the number of animals that are monitored. Thus, each image can contain a plurality of animals. In addition, the feeding area may be common for several animals. However, to the extent that each animal can typically be identified, the feeding area for each cow can typically be assessed with image processing, and if images are required continuously while animals are eating, each animal's food consumption can also be assessed by determining the reduction in food between subsequent images.
    [019] For example, the processing means can be configured to divide images of the feeding area into one, two, three, four or more specific animal parts, each specific animal part can be corresponding to an identified animal. That is, images from the imaging unit containing (at least part of) the feeding area can be divided according to the specific identified animals. The division can be predefined and fixed for each image. But the division can also be customized and / or continuously updated, for example, according to the identification and / or position of animals identified in at least part of the images. For example, the processing means can be configured to select a specific animal part of an image of the feeding area based on the position of the front or the head of said animal. For example, a specific animal part can be an area in front of said animal, such as a predefined area, such as a predefined area in relation to the animal's position, such as the animal's head. For example, the predefined area selected in an image relative to the position of the head of an identified animal, for example, when the animal removes the head from the feeding area. The selected feeding area is then dependent on the position of the animal's head and only food in this selected feeding area of the image is processed to determine the reduction in food between subsequent images, the reduction then corresponds to the amount of food ingested by the animal. specific animal in a specific period. In this way, information on what this specific identified animal has ingested during a certain period of ingestion can be determined, and the total amount of food ingested by each animal can be discovered by adding the amount ingested in each of these periods. The system can thus add up to the situation where a plurality of animals are next to each other eating in a shared feeding area, where some animals eat in the neighbor's feeding area. Identification
    [020] The means of identification of the system are preferably configured to uniquely identify each animal for food. This is to provide the necessary information such that the amount of food consumed can be related to specific animals. In one embodiment, the identification means are configured to identify an animal for food by means of an identification plate attached to each animal. The identification plates can be visible plates comprising letters, numbers and / or symbols. For example, in the form of color codes or black and white pattern codes. This is a relatively inexpensive arrangement and animals in livestock are normally marked, for example, cows are conventionally marked with a plaque attached to their ears. The identification means can be configured to identify an animal for food by identifying a color code, symbol code, pattern code and / or a bar code on a nameplate attached to the animal, for example, as a necklace or in an ear. From there, these visible plates can be viable in images acquired by the imaging unit. Animal nameplates are well known in the art. The identification of animals can be provided additionally by means of GPS, for example, each animal can be provided with a tracking unit, for example, the identification plates can form or comprise tracking units.
    [021] The identification of animals can be part of the processing means, for example, images showing the feeding area also show at least part of the animals for feeding, and the animals can thus be identified in the images by means of image processing . From there, the processing means can be adapted to identify a specific animal by means of a plate visible in the images. The processing means can be adapted to detect a specific color code, barcode or (2D) pattern on an animal ear plate or collar. In one embodiment, the animal carries a collar with a specific color code, symbol code, and / or bar code, which can be used to identify the individual animal by said processing means.
    [022] The imaging unit can comprise one or more specific cameras to provide the current identification of animals, such as 2D cameras, such as RGB cameras. For example, in one mode, the system comprises one or more cameras specifically adapted to detect a color code. Such cameras are generally capable of acquiring color images. However, the system may additionally comprise one or more cameras specifically adapted to detect a symbol code, pattern and / or a bar code, for example, in the form of black and white symbols. Some bar codes can, for example, be identified using simple line scanners.
    [023] In one embodiment, the system additionally comprises an appropriate plate reader to wirelessly identify a specific animal in the feeding area. For example, the identification means comprise one or more RF nameplate readers suitable for wirelessly identifying the animal (s) using an RF nameplate. This can, for example, be done using an RFID (radio frequency identification) chip implanted in the animal. Hereby, the identification of the animal is not dependent on the images acquired by a camera in the imaging unit and that a plate must be visible in order to identify the animal.
    [024] Identification can be additionally provided via GPS, for example, using GPS tracking units for each animal.
    [025] In one embodiment, the identification means comprise identification plates for connection to said animal (s). That is, the identification plates can be part of the system, and can be specifically developed for the purpose of being identifiable in the images acquired by the imaging unit. The plates can be visible and / or RF plates, as mentioned above. Method
    [026] As stated earlier, the present disclosure relates additionally to a method to assess the food consumption of one or more animals feeding in a feeding area, comprising: - acquiring interval images of the feeding area in different - identify at least one of the said animals consuming food in at least two of the said interval images, and - evaluate the amount of food consumed by each identified animal when determining the reduction of food among said at least two images of interval.
    [027] A method for assessing the relative food consumption of a plurality of animals in a livestock feed in a feeding area, - acquiring interval images of the feeding area at different times, - identifying all animals consuming food, - assessing the amount of food consumed by each identified animal by determining the food reduction between at least two interval images showing an identified animal, and - determining the amount of food consumed by an identified animal in relation to the amount of food consumed by the remaining identified animals.
    [028] The present disclosure additionally refers to a method to de-terminate food consumption of at least one animal in a livestock comprising the steps of, providing a feeding area having accessible food for at least one animal, providing the at least one animal with an identification plate to identify a specific animal, acquire a plurality of images of the feeding area at different times, identify an animal consuming specific food in the plurality of images, by using images of the animal consuming specific food determines the reduction of food as disclosed in those images, in which the consumption of food for the specific animal is defined as the reduction of food in those images.
    [029] The reduction in food between subsequent images can be determined by identifying the food in each image and calculating a difference in height of corresponding image areas, such as pixels, representing food in subsequent images. The base level of the feeding area can be known, for example, by having interval images of the empty feeding area as a reference. As mentioned earlier, it can be difficult to determine the exact amount of food consumed by each animal, but the relative food consumption of a plurality of animals in livestock can be compared using the system and method currently disclosed. The farmer also typically knows how much milk each cow produces and, by knowing the amount of food consumed (at least the relative) by the cows, the cow's yield can be optimized. Thus, it is not necessarily the cow that produces more that most efficiently converts food into concentrate and forage into milk. With the system and method currently disclosed, the farmer can have a complete picture of the conversion yield of each cow in livestock.
    [030] Advantageously, the images are acquired by at least one camera, preferably an interval camera, such as a flight time camera, structure light camera, stereo camera or a 3D camera, and thus the images can be 3D images.
    [031] In one embodiment, the animal consuming specific food is identified by using a visible plate attached to the animal and preferably visible in at least part of the images. In one embodiment, the visible plate comprises a color code and / or a bar code on an ear plate or an animal collar. In a preferred embodiment, the animal identity is identified by optimal detection of a specific color code and / or bar code on a collar or ear plate carried by the specific animal. Additionally, animals can be identified by legible signs wirelessly connected to the animals.
    [032] In one mode, images are acquired continuously, thereby allowing detection of food consumption in real time. For example, images are acquired as a video signal or at least once a minute, for example, every 1, 5, 10, 20 or 30 seconds. In a preferred embodiment, an image is acquired every 1 to 5 minutes; for example, an image is acquired approximately every 2 minutes. The images can additionally be acquired at selected time points. For example, the gap image of at least a part of the feeding area can be acquired when an animal starts, stops and / or ends a feeding process. Or an image of at least part of the feeding area is acquired when an animal removes the head from the feeding area.
    [033] It should be understood that the method can be adapted to understand any of the modalities mentioned above for the system.
    [034] An additional aspect concerns a computer-readable medium having computer executable instructions stored therein to perform a method as mentioned above and preferably performed on a system as mentioned above.
    [035] Fig. 1 shows a system for determining food consumption of at least one cow. The presented modality is a preferred modality for determining food consumption for individual cattle and / or cows. When using the term cow, reference is made to both male and female cattle.
    [036] In the modality disclosed in fig. 1 the food 2 placed in the feeding area is forage. But, as stated earlier, the methods and systems presently disclosed are not limited to food in the form of forage, but to any food distributed to animals through the feeding area.
    [037] Fig. 1 discloses part of the interior of a stable 1 having forage 2 in a feeding area being on one side and three cows on the other side of a feed fence 7. Stable 1 should be understood as housing for livestock, which can also be denoted as a granary. The system of the present modality can also be used outside; however, it is preferred to use a feed fence 7 to ensure that cows can access forage 2, but not walk and rest on it. Additionally, feed fence 7 makes it easier to feed cows.
    [038] Above the forage 2, three range 4 cameras are placed, to acquire images of the forage 2. The range 4 cameras are mounted on a bar that is part of the food fence 2.
    [039] The three cows 3 shown in fig. 1 have a nameplate 5 on the ear. Alternatively or in combination, cows can have a collar 8 that can be used as a nameplate. When positioning the identification plate on the cow, the neck or ear are preferred, as the cow 3 has the head and neck through the food fence 7 and is thus more clearly visible to the cameras 4 These identification plates are preferred, as the farmer can connect them to the animal himself, without the need for a veterinarian. In addition, the identification plates shown allow the farmer to identify animals by visual inspection.
    [040] Alternatively or in combination with the nameplate mentioned above, a chip can be implanted using a needle. These chips are known in the art and used as nameplates for pets, such as cats and dogs. The chip can be read using a digitizer that can be positioned close to the forage and connected to a processing unit. Such a chip can, for example, be an RFID chip.
    [041] In addition to an identification plate 5, it can be used when determining the composition of the food for a specific cow 5.
    [042] When a cow 3 feeds, a camera 4 sends images to processing media in the form of a computer 6, in the present mode cameras 4 send a video stream to computer 6 which then identifies cow 3 by use of nameplate 5 and record the amount of forage 2 present when cow 3 starts to feed. When cow 3 removes its head from the food fence 7, the computer records the amount of forage present when cow 3 stopped feeding. Using this data, it is possible for a computer 6 to calculate and thus determine the cow's forage consumption.
    [043] Computer 6 can be located in stable 1 or, for example, in a control room nearby. Computer 6 can be connected to cameras 4 by cable and / or without cable. The processing means can also be separated from a recording medium that acquires and stores images, such as video from the feed area and the images can then, possibly, later be transferred to the computer 6 for analysis.
    [044] By using the present invention it is possible to use the information relating an animal's food consumption to decide the general composition of the food for a specific animal. The food composition can, for example, be determined depending on milk production or growth of the animal in relation to food consumption. In order to ensure that one animal has access to the compound feed for that specific animal, and that the other animals do not, access control via the nameplate can be used.
    [045] By using the food consumption determined for each cow 3, the farmer can have enough information to calculate the contribution and efficiency margin of the individual cow 3 based on forage admission 2.
    [046] The images captured by cameras 4 of the modality in fig. 1 overlap, and as they are captured simultaneously, the computer 6 can compare them in order to increase the accuracy in determining the amount of forage 2 present in the feeding area. The computer 6 can also combine the images to form the stitched image and use it to determine the reduction in forage 2 and thereby the cow's forage consumption 3.
    [047] In a preferred mode, cameras 4 are 3D cameras or interval cameras. This allows the computer to calculate the distance for forage 2 and make it possible to calculate the volume of forage 2 with high accuracy.
    [048] Cameras 4 in fig. 1 are stationary - mounted on the food fence 7.
    [049] Alternatively or in combination, cameras can be mounted in a way that can also be moved and / or directed in order to take images of forage 2 from different angles and move to where forage 2 is located in the feeding area. In relation to stationary cameras, in this way it is possible to use fewer cameras to cover a larger area. However, when the mechanisms used to move cameras are exposed to the adverse environment of the stable, they can degrade, leading to higher maintenance costs. In addition, mobile cameras are more expensive than stationary ones.
    [050] The currently disclosed system and methods have been tested with four different animals (cows). Each cow was located in a box with a feeding area in front. A separate range camera was located in each box. The test was the same for the cow in each box. Initially, a gap image was acquired from the empty feed area, to obtain a basic level of the feed area. A specified weight of forage was placed in the empty feed area and an interval image was acquired. Additional interval images were acquired for each 2 minute period while the cow was in the box and eating. After 90 minutes, the remaining forage in the feeding area was weighed and returned to the feeding area. The cow remained in the box for a period after which it was removed for milking.
    [051] The remaining forage in the feeding area was weighed again. The cow entered the box again and after 90 minutes the forage was weighed again. A last image of the forage interval remaining in the feeding area was acquired before the final weighing of the forage.
    [052] The images were classified and processed and the reduction in forage was determined by calculating the height of each pixel of forage in the images. The volume of the reduction can then be calculated corresponding to the cow's food consumption. The base level of the eating area is also known.
    [053] Figs. 2a-d show correlations between current feed consumption and cal-culado of the four cows. The graphs on the left marked with “3D figure” show the volume of the food vs. time for the four cows. The volume is in arbitrary units. The reduction in the volume of food is seen by the decrease in the volume in the graphics, which is a result of image processing. The graphs to the right marked “3D count vs. forage” show the correlation between the volume of food consumed by each cow evaluated by image processing vs. the current measured consumption (by weighing) of cows in kilograms of forage (in the graph on the right in Fig. 3A the axes are switched) at the top. As seen from the graphs on the right, there is an almost linear correlation between the heavy amount of forage consumed by each cow and the amount assessed by the system and method currently disclosed. Reference list 1 stable 2 food 3 cow 4 camera 5 nameplate 6 computer 7 food fence 8 collar Additional details of the invention
    [054] The Invention will be described below with additional details with reference to the following listed items: 1. System for determining food consumption of at least one animal in a livestock comprising, - at least one nameplate attached to at least one animal , by means of which a specific animal can be identified, - a feeding area having food accessible to at least one animal, - at least one camera adapted to require images of the food in the feeding area at different times, - adapted processing means to determine the food consumed by a specific animal identified by analyzing the food reduction as represented in at least two images. 2. System according to item 1, in which at least one camera is a 3D camera, preferably the 3D camera is adapted to acquire topographic images. 3. System according to any of the previous items, in which the system additionally comprises means to control the position and / or the angle of the at least one camera. 4. System according to any of the previous items, in which at least one camera is stationary. 5. System according to any of the previous items, in which the processing means are adapted to identify a specific animal by means of a plate visible in the images. 6. System according to any of the previous items, in which the system additionally comprises an appropriate plate reader to wirelessly identify a specific animal in the feeding area. 7. System according to any of the previous items, in which at least two cameras acquire images simultaneously and in which the processing means are adapted to combine the images in order to determine the amount of food in the feeding area. 8. Method for determining food consumption of at least one animal in a livestock farm comprising the steps of, - providing a feeding area with accessible food for at least one animal, - providing at least one animal with an identification plate for identify a specific animal, - acquire a plurality of images of the feeding area at different times, - identify an animal consuming specific food in the plurality of images, - by using images of the animal consuming specific food to determine the reduction of food as disclosed in these images, in which the food consumption for the specific animal is determined as the food reduction in these images. 9. Method according to item 8, in which images are acquired by using at least one camera, preferably a 3D camera. 10. Method according to any of items 8 to 9, in which the animal consuming specific food is identified by the use of a visible sign attached to the animal in the plurality of images. 11. Method according to any of items 8 to 9, in which the animal consuming specific food is identified by the use of a plate that is legible without a handle. 12. A computer-readable medium having computer-executable instructions stored on it to perform a method in accordance with any of items 8 to 11.
    权利要求:
    Claims (25)
    [0001]
    1. Animal monitoring system to determine food consumption of one or more animals (3) feeding in a common feeding area, comprising: an imaging unit to create an image of the feeding area, means of identification configured to uniquely identify each animal (3) for food, and processing medium (6), CHARACTERIZED by the fact that: the imaging unit comprises one or more interval cameras (4) to create interval image of the area of feed, the processing medium (6) being configured to assess the amount of food consumed by each identified animal (3) when determining the food reduction in subsequent interval images of the common feeding area in front of each identified animal (3) .
    [0002]
    2. System, according to claim 1, CHARACTERIZED by the fact that the one or more cameras in range (4), are one or more stereo cameras, one or more cameras of flight time, one or more cameras of structured light , one or more light field cameras, one or more 2D cameras in combination with one or more depth sensors, or a combination thereof.
    [0003]
    3. System according to claim 2, CHARACTERIZED by the fact that each range camera (4) comprises a depth sensor and a 2D camera, such as an RGB camera.
    [0004]
    4. System, according to any of the previous claims, CHARACTERIZED by the fact that the imaging unit is configured to acquire topographic images.
    [0005]
    5. System, according to any of the preceding claims, CHARACTERIZED by the fact that the imaging unit is configured to continuously image at least part of the feeding area.
    [0006]
    6. System, according to any of the preceding claims, CHARACTERIZED by the fact that the imaging unit is configured to image at least part of the feeding area at selected and / or predefined time points.
    [0007]
    7. System, according to any of the previous claims, CHARACTERIZED by the fact that the imaging unit is configured to create an image of a selected and / or predefined part of the feeding area.
    [0008]
    8. System according to any one of the preceding claims, CHARACTERIZED by the fact that it additionally comprises a control unit configured to control the position and / or the angle of the imaging unit and / or the position and / or the angle of cameras (4) of the imaging unit.
    [0009]
    9. System, according to any of the preceding claims, CHARACTERIZED by the fact that the reduction in food between subsequent images is determined by calculating the difference in height of corresponding image areas and determining the volume of that difference.
    [0010]
    10. System, according to any of the previous claims, CHARACTERIZED by the fact that the reduction in food between subsequent images is determined by identifying the food in each image and calculating the difference in height of corresponding image areas, such as as pixels, representing food in subsequent images.
    [0011]
    11. System, according to any of the preceding claims, CHARACTERIZED by the fact that at least two interval cameras (4) of the imaging unit are configured to acquire images simultaneously and in which the processing medium (6) is configured to combine the images to determine the amount of food in the feed area.
    [0012]
    12. System, according to any one of the preceding claims, CHARACTERIZED by the fact that the identification means comprises identification plates (5) for attachment to said animal (s).
    [0013]
    13. System, according to any of the preceding claims, CHARACTERIZED by the fact that the identification means is configured to identify an animal for food by means of an identification plate (5) attached to each animal.
    [0014]
    14. System, according to any of the preceding claims, CHARACTERIZED by the fact that the identification means is configured to identify an animal (3) for feeding by identifying a color code of an identification plate (5) attached to the animal (3).
    [0015]
    15. System according to any one of claims 12 to 14, CHARACTERIZED by the fact that the identification plates (5) are RF plates, such as RFID plates or in which the identification plates are visible plates comprising letters, numbers and / or symbols, or color code, symbol and / or pattern.
    [0016]
    16. System, according to any of the preceding claims, CHARACTERIZED by the fact that it is configured to determine the time point of an identified animal (3) starting, stopping and / or ending a feeding process.
    [0017]
    17. System, according to any of the previous claims, CHARACTERIZED by the fact that it is configured to determine when an identified animal (3) removes the head from the feeding area.
    [0018]
    18. System, according to any of the previous claims, CHARACTERIZED by the fact that it is configured so that an interval image is acquired when an identified animal (3) removes the head from the feeding area or when an animal (3) identified starts and / or ends a feeding process.
    [0019]
    19. System, according to any of the preceding claims, CHARACTERIZED by the fact that the processing medium (6) is configured to divide images of the feeding area into one, two, three, four or more specific parts of animal , each specific animal part corresponding to an identified animal (3), or where the processing medium (6) is configured to select a specific animal part of an image from the feeding area based on the position of the front or head of said animal (3).
    [0020]
    20. System according to any one of the preceding claims, CHARACTERIZED by the fact that said specific animal part is an area in front of said animal (3), such as a predefined area, such as a predefined area in relation to position of the animal (3).
    [0021]
    21. System, according to any of the preceding claims, CHARACTERIZED by the fact that the food (2) is forage, concentrate and / or a mixture thereof.
    [0022]
    22. Method to assess the food consumption of one or more animals (3) feeding in a common feeding area, comprising: acquiring a series of interval images of the feeding area at different times during a period of time while the said animal (s) is (are) feeding, identify at least one of the said animals (3) consuming food in at least two of the said interval images, and FEATURED by the fact that it further comprises: evaluate the amount of food consumed by each animal (3) identified by determining a reduction in food between the said at least two interval images.
    [0023]
    23. Method for assessing food consumption related to a plurality of animals (3) in a livestock feed in a common feeding area, comprises: acquiring a series of interval images of the feeding area at different times during a period of time while the referred animal (s) is (are) feeding, identify all animals consuming food, CHARACTERIZED by the fact that it also comprises: evaluating the amount of food consumed by each identified animal (3) when determining the reduction of food between at least two interval images showing an identified animal, and determining the amount of food consumed by an identified animal (3) in relation to the amount of food consumed by the remaining identified animals.
    [0024]
    24. Method according to any of claims 22 to 23, CHARACTERIZED by the fact that the reduction in food between subsequent images is determined by calculating the difference in height of corresponding image areas and determining the volume of this difference.
    [0025]
    25. Method according to any one of claims 22 to 24, CHARACTERIZED by the fact that the reduction in food between subsequent images is determined by identifying the food in each image and calculating the difference in height of corresponding image areas , like pixels, representing the food in subsequent images.
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    同族专利:
    公开号 | 公开日
    EA028910B1|2018-01-31|
    UA119143C2|2019-05-10|
    LT2983465T|2021-02-10|
    US9861081B2|2018-01-09|
    CN105307482A|2016-02-03|
    PT2983465T|2021-01-19|
    HRP20210072T1|2021-04-30|
    JP2016514482A|2016-05-23|
    BR112015025972A2|2017-07-25|
    JP6556119B2|2019-08-07|
    SI2983465T1|2021-03-31|
    EA201591942A1|2016-03-31|
    DK2983465T3|2021-01-18|
    AU2014252457A1|2015-11-26|
    NZ714005A|2017-03-31|
    US10420328B2|2019-09-24|
    US20180249683A1|2018-09-06|
    US20160066546A1|2016-03-10|
    CA2908329A1|2014-10-16|
    ES2843528T3|2021-07-19|
    IL241819A|2020-05-31|
    AU2014252457B2|2016-08-04|
    EP2983465A1|2016-02-17|
    MX2015014287A|2016-07-20|
    PL2983465T3|2021-05-04|
    WO2014166498A1|2014-10-16|
    MX365564B|2019-06-05|
    CA2908329C|2021-07-13|
    CN105307482B|2019-04-12|
    ZA201508121B|2017-07-26|
    EP2983465B1|2020-10-14|
    引用文献:
    公开号 | 申请日 | 公开日 | 申请人 | 专利标题
    AT70693T|1987-06-22|1992-01-15|Dammann & Westerkamp|METHOD AND DEVICE FOR AUTOMATICALLY IDENTIFYING ANIMALS.|
    DE3833902C1|1988-10-05|1989-11-23|Norbert 4416 Everswinkel De Hoehmann|Device for identifying animals|
    SE9000164D0|1990-01-17|1990-01-17|Alfa Laval Agri Int|FEEDING CHEESE|
    US6342839B1|1998-03-09|2002-01-29|Aginfolink Holdings Inc.|Method and apparatus for a livestock data collection and management system|
    DE60016767T2|1999-09-02|2006-01-12|Kristoffer Larsen Innovation A/S|METHOD FOR CONTROLLING THE RESTORATION OF FREE-RACING ANIMALS|
    NL1016836C2|2000-12-08|2002-06-11|Nedap Nv|Farm management system with cameras for following animals on the farm.|
    JP3803750B2|2002-02-22|2006-08-02|防衛庁技術研究本部長|Volume measuring method and volume measuring program|
    US7399220B2|2002-08-02|2008-07-15|Kriesel Marshall S|Apparatus and methods for the volumetric and dimensional measurement of livestock|
    SE527130C2|2004-01-13|2005-12-27|Delaval Holding Ab|Apparatus and method for feeding animals|
    US20080314324A1|2004-03-30|2008-12-25|Delaval Holding Ab|Arrangement and Method for Determining Positions of the Teats of a Milking Animal|
    GB2427813A|2004-04-13|2007-01-10|Commw Scient Ind Res Org|Integrated animal management system and method|
    NL1033349C2|2007-02-06|2008-08-07|Maasland Nv|Feed wagon for feeding animals such as cows.|
    NL1033589C2|2007-03-26|2008-09-29|Maasland Nv|Assembly of a milking robot with a milking robot feeding place, and device for gripping and moving material.|
    NL1033590C2|2007-03-26|2008-09-29|Maasland Nv|Unmanned vehicle for delivering feed to an animal.|
    DK2134161T3|2007-04-10|2015-04-27|Delaval Holding Ab|Feeding system and method|
    US20090216775A1|2008-02-22|2009-08-27|Marc Gregory Ratliff|Platform for real-time tracking and analysis|
    GB0813782D0|2008-07-28|2008-09-03|Delaval Holding Ab|Animal installation with height measurement device|
    US8482329B2|2008-08-08|2013-07-09|Lsi Corporation|High voltage input receiver with hysteresis using low voltage transistors|
    GB2481924B|2009-01-08|2013-08-28|Pet Technology Store Ltd|Animal exercise and feeding apparatus|
    JP2011177116A|2010-03-02|2011-09-15|Mitsubishi Electric Corp|Rfid animal ear tag and method of manufacturing the same|
    JP5756967B2|2011-03-30|2015-07-29|国立研究開発法人農業・食品産業技術総合研究機構|Milk cow health condition management method and management system|
    CN202406785U|2011-10-31|2012-09-05|重庆理工大学|Pig growth performance detection system and automatic pig feeding control system|
    CN102510401B|2011-11-09|2014-11-19|南京农业大学|System and method for wirelessly monitoring water drinking behavior of sows raised in group based on machine vision technology|
    NL2008673C2|2012-04-20|2013-10-23|Lely Patent Nv|DEVICE FOR MOVING FOOD.|
    CN202635315U|2012-07-03|2013-01-02|深圳市润农科技有限公司|Pig intelligent breeding video measuring system|EP3122173B1|2014-03-26|2021-03-31|SCR Engineers Ltd|Livestock location system|
    US10986817B2|2014-09-05|2021-04-27|Intervet Inc.|Method and system for tracking health in animal populations|
    US11071279B2|2014-09-05|2021-07-27|Intervet Inc.|Method and system for tracking health in animal populations|
    WO2017001538A1|2015-07-01|2017-01-05|Viking Genetics Fmba|System and method for identification of individual animals based on images of the back|
    US10045511B1|2015-08-20|2018-08-14|Medisim, Ltd.|Cattle and other veterinary monitoring|
    US20170109621A1|2015-10-14|2017-04-20|Phoebe L. Brown|Protective Casing for a Machine Readable Tag|
    CN105432486B|2015-11-03|2019-04-30|内蒙古农业大学|A kind of feeding detection system and its feeding detection method|
    JP6525271B2|2016-03-28|2019-06-05|国立研究開発法人農業・食品産業技術総合研究機構|Residual feed measuring device and program for measuring residual feed|
    EP3468354A4|2016-06-08|2020-02-12|Commonwealth Scientific and Industrial Research Organisation|System for monitoring pasture intake|
    KR101814288B1|2016-08-17|2018-01-03|김영구|A Feeding System for Fish Farm using 3Dimension analyzer|
    WO2018057883A1|2016-09-22|2018-03-29|Src, Inc.|Methods and systems for detection and tracking of mastitis in dairy cattle|
    WO2018061003A1|2016-09-28|2018-04-05|Scr Engineers Ltd|Holder for a smart monitoring tag for cows|
    JP6825432B2|2017-03-13|2021-02-03|富士通株式会社|Analysis program, analysis method and analysis equipment|
    JP6834625B2|2017-03-13|2021-02-24|富士通株式会社|Behavior amount calculation program, behavior amount calculation method, behavior amount calculation device and animal monitoring system|
    IT201700069751A1|2017-06-22|2018-12-22|Luca Agostini|SYSTEM FOR DETECTION OF SPECIFIC CONDITIONS OF BREEDING ANIMALS|
    UY37539A|2017-12-21|2019-07-31|Marichal Jose|SYSTEM AND METHOD FOR IDENTIFYING, FEEDING AND HANDLING ANIMALS, IN SPECIAL DAIRY CATTLE|
    CN108477003A|2018-02-08|2018-09-04|东莞市车小秘智能科技有限公司|Feeding pet system and self-service feeding method|
    US11216643B1|2018-04-05|2022-01-04|Objectvideo Labs, Llc|Monitoring of pet feeding with video|
    WO2019194728A1|2018-04-05|2019-10-10|Delaval Holding Ab|A cooling system for cooling dairy animals|
    JP2022514115A|2018-10-17|2022-02-09|グループ ロ－マン インク．|Livestock surveillance|
    CN109618961B|2018-12-12|2020-11-03|京东数字科技控股有限公司|Intelligent feeding system and method for livestock|
    US20200323171A1|2019-04-09|2020-10-15|Ryan Crosby|Automated recreational device for pets|
    TWI714057B|2019-04-17|2020-12-21|國立臺灣大學|Analysis system and method for feeding milk-production livestock|
    CN110933263B|2019-10-21|2021-11-12|北京海益同展信息科技有限公司|Livestock face identification equipment and have its rail|
    法律状态:
    2018-02-27| B06F| Objections, documents and/or translations needed after an examination request according [chapter 6.6 patent gazette]|
    2019-07-09| B06T| Formal requirements before examination [chapter 6.20 patent gazette]|
    2020-05-05| B06A| Patent application procedure suspended [chapter 6.1 patent gazette]|
    2020-09-01| B09A| Decision: intention to grant [chapter 9.1 patent gazette]|
    2020-12-08| B16A| Patent or certificate of addition of invention granted [chapter 16.1 patent gazette]|Free format text: PRAZO DE VALIDADE: 20 (VINTE) ANOS CONTADOS A PARTIR DE 10/04/2014, OBSERVADAS AS CONDICOES LEGAIS. |
    优先权:
    申请号 | 申请日 | 专利标题
    DKPA201370195|2013-04-10|
    DKPA201370195|2013-04-10|
    PCT/DK2014/050087|WO2014166498A1|2013-04-10|2014-04-10|System for determining feed consumption of at least one animal|
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