System for determining time distribution of animal entering a barn area

Abstract

The invention provides a system (100) for determining a distribution of time spent by respective animals (101, 102, 103) in different zones (210, 220, 230) of a barn (200) during a predetermined time period. The system (100) comprises a real-time positioning system (110, 120a, 120b, 120c, 130), a database (140) with location coordinates of the respective zones (210, 220, 230) and a processing controller (150). The processing controller (150) is configured to determine the distribution of time by: associating each obtained data entity (301) with a zone (210, 220, 230) based on the location coordinates of the respective information entity (301) and the location coordinates of the respective zone (210, 220, 230); counting the number of data entities (301) in each respective zone (210, 220, 230); and calculating the amount of time spent by the animal (101) in the zone (210, 220, 230) by multiplying the number of data entities (301) of each respective zone (210, 220, 230) by a regular time interval.

Description

[0001] illustrate

[0002] The present invention relates to a system for determining the distribution of time spent by animals in different areas of an agricultural indoor environment, such as a dairy cow shed, during a predetermined time period.

[0003] Dairy plants typically have automated milking systems where animals can roam freely in their living areas and can enter automated milking equipment (such as milking robots, rotating milking parlors, etc.) for milking. Animals can then voluntarily go to and enter the automated milking equipment for milking, lured by the nutrients offered and / or selected by gates in a forced animal traffic layout within the barn. This is sometimes referred to as a voluntary milking system, or simply robotic milking.

[0004] Animal herds are becoming increasingly large. For farmers, detecting abnormal animals can be challenging, such as those expected to be in estrus (for insemination), or those that are sick, injured, or exhibit other abnormal conditions or behaviors. Various attempts have been made to find solutions, for example, based on measurements and analyses of the corresponding animals' milk yield, rumination, milk composition, hormones, etc. However, these solutions all have their limitations. For this reason, it may be desirable to find another method to identify abnormal animals, either alone or in combination with other measurements.

[0005] Real-time location systems (RTLS) have emerged that can locate animals indoors, such as in barns. Animals are tagged with radio transmitters that emit radio signals or flash them. These radio signals from the tags are received by receivers, or anchor receivers, located at different known locations within the barn. The receivers determine the direction, angle of arrival, and / or time delay of the received signals and forward this information to a location controller, which calculates a set of location coordinates for the animal based on one or more signal localization algorithms, such as trilateration, polygonation, and / or triangulation of the tag / radio transmitter's radio signals, as received by the appropriate receivers.

[0006] This allows us to determine the animal's current location. However, various problems are associated with RTLS. Simply being able to detect the animal's current location within the barn does little to determine its current state.

[0007] One object of the present invention is to enable the simulation of farmers' daily animal monitoring and close contact with their herds, and to enable the detection of abnormal animals.

[0008] This objective is achieved by the system according to claim 1. Specifically, the system aims to determine the distribution of time spent by a corresponding animal in different areas of the barn during a predetermined time period. These areas may be dedicated to corresponding activities, including, for example, a feeding area dedicated to eating, a resting area dedicated to resting, and / or a transport area dedicated to walking. By determining the distribution of time spent by the animal in different areas, the distribution of activities performed by the animal is also indirectly determined.

[0009] The system includes a processing controller and a database. The database is configured to store the location coordinates of corresponding areas in the livestock shed. The system also includes a positioning controller and a set of tags, each associated with a corresponding animal. Each tag includes a processing device, a radio transmitter, and a memory. The memory stores a tag identifier, i.e., a code that uniquely identifies the tag. The tag is then associated with an animal identifier, for example, in a lookup table or in the database, of the animal that is associated with / carrying the tag. The processing device is configured to repeatedly transmit radio signals at regular time intervals via the radio transmitter; each radio signal includes the tag identifier.

[0010] The regular time interval between radio signal transmissions can be, for example, approximately every 2.2 seconds. Other regular time intervals, such as every 2 seconds, every 3 seconds, etc., can be applied in other implementations.

[0011] The system also includes at least three receivers positioned at corresponding predetermined locations within the livestock shed. Each receiver or anchor is configured to receive the transmitted radio signals and transmit information related to the received radio signals to the positioning controller. The transmitted information may include, for example, the measured angle of arrival of the received signal, the measured signal strength of the received signal, and / or the arrival time / delay time of the received signal.

[0012] The positioning controller is configured to repeatedly acquire information related to received radio signals received from the corresponding receiver. Then, based on the information related to the received radio signals from the radio transmitter received by the receiver, the positioning controller calculates a set of location coordinates for each tag identifier, including the corresponding tag identifier. The positioning controller is also configured to provide a data entity to the processing controller, each data entity including the calculated location coordinates of the tag associated with a timestamp and / or index number.

[0013] The processing controller is configured to determine the distribution of time spent by animals associated with tags, including tag identifiers, in different areas of the barn by associating each acquired data entity with a corresponding area based on the location coordinates of the corresponding information entity and the location coordinates of the area. The number of data entities in each corresponding area is then counted and calculated by multiplying the number of data entities associated with each corresponding area by a regular time interval (such as, for example, 2.2 seconds), relating to the amount of time animals spend in each corresponding area.

[0014] This allows for the determination of the distribution of time animals spend in each corresponding zone, and indirectly, the approximation of the activities animals perform during predetermined time periods. Since most animals are reliably habitual, farmers can immediately detect deviations from normal behavior. For example, by comparing the current time distribution in different zones with the expected / average time distribution, farmers can detect deviant animal behavior at an early stage. Farmers can then make decisions regarding appropriate measures at an early stage based on the type of deviation, such as insemination, for example, when high temperatures occur due to excessive walking / activity, i.e., when animals spend more time in the transport area of ​​the barn than average / expected. Farmers can also perform visual health checks on specific animals when walking activity is low and / or resting time is long and / or feeding time is short. Thus, qualified veterinary assistance can be applied at a very early stage to eliminate, minimize, or at least reduce the time animals spend in deviant states, thereby increasing farm milk production while also alleviating animal suffering.

[0015] If animals spend too little time eating in the feeding area of ​​the barn, it may be because the animals are ranked low and may never / rarely be able to enter the feed table, which may require changing the feed group for specific animals, etc.

[0016] In some implementations, the database includes the historical distribution of time spent by the corresponding animals in different areas of the barn. The distribution of a determined time spent by the animals in different areas can be compared with the historical distribution of time spent by the animals in those areas, extracted from the database. If the deviation between the determined time distribution and the historical time distribution of the animals exceeds a threshold limit, an alert can be generated based on the comparison. Furthermore, the distribution of a determined time spent by the animals in different areas can be stored in the database, thereby forming part of the animals' future reference time distribution.

[0017] This allows for the automatic detection of discrepancies between the current and historical time distributions of different zones / activities, and can immediately alert farmers to take appropriate measures.

[0018] The historical distribution of time spent by the corresponding animals in different areas of the barn can be stored in a database in association with the time of day when the distribution was determined. The processing controller can then be configured to determine the time of day when the distribution of time spent by the animals in different areas is determined using a clock function, and compare it with the historical distribution of the animals' time at the corresponding time of day.

[0019] Animals exhibit different behaviors at different times of the day; for example, they rest more at night and are more active during the day. By storing and comparing the temporal distribution of these behaviors at the same time of day, relevant comparisons can be ensured. Another advantage of determining the time of day when identifying animal location / activity is that it allows for the detection of behavioral changes over time, which may be related to the animal's state and condition, potentially affecting milk production.

[0020] The processing controller can also define clusters of acquired data entities with location coordinates within distance limits and timestamps and / or index numbers within time limits. The location coordinates of the gravity point for the defined cluster can then be calculated. Furthermore, the regions associated with the location coordinates of the gravity point are determined. Additionally, the processing controller can determine the regions associated with the cluster's gravity point for all data entities within the cluster.

[0021] The location of an animal / tag standing near the boundary between two zones can be exchanged between zones, even though the animal may actually only move within the same zone, or not at all. This could be due to signal interference, radio signal responses to different objects, such as in a barn. More reliable zone classification can be achieved by defining clusters and categorizing all data entities within a cluster into coordinate zones of gravity points.

[0022] The processing controller can be additionally configured to determine the zone association of a data entity by applying a rolling average of the position coordinates of previous data entities within a predetermined window length and associating all data entities within the predetermined window length with the same zone.

[0023] This provides another or additional solution for enhancing the identification of tags / animal zones, which can be important, especially when the animal is located near the zone boundary.

[0024] The tag may also include an accelerometer. The accelerometer determines the animal's movement data, or more precisely, the movement data of the body part to which the tag / accelerometer is attached. Each data entity may thus include accelerometer data. The processing controller may also be configured to detect that an animal is ruminating at the location coordinates of any of the acquired data entities, based on analysis of the accelerometer data of the data entities. If the location coordinates of the database are close to the boundaries / boundaries of the rest area, the animal's database is associated with the rest area when rumination is detected.

[0025] At least some animals (such as dairy cows) typically exhibit the behavior of ruminating on their feed multiple times, usually while they are resting in their resting compartments. Therefore, when an animal is near the boundary between its resting area and any other area, it can be assumed that the animal is in its resting area, as can be concluded based on accelerometer readings of the animal's rumination.

[0026] In some implementations, the processing controller may be configured to compare the calculated time an animal spends in the transport area with an estrus time threshold limit, and generate an estrus alarm for the animal when the estrus time threshold limit is exceeded. The estrus time threshold limit may be applied individually to a specific animal, or alternatively include general values / average values.

[0027] This allows farmers to detect estrus in animals at an early stage, which is crucial for successful insemination, and insemination is also important for the farm's milk production.

[0028] The processing controller can also, or alternatively, be configured to compare the time an animal spends in the rest area with a no-resistance time threshold limit, and generate an abnormal alarm for the animal when the no-resistance time threshold limit is exceeded. The no-resistance time threshold limit may be applied individually to a specific animal, or alternatively may include a general value.

[0029] As a result, farmers are able to detect sick or injured animals at an early stage and apply appropriate solutions (medication, veterinary care, etc.) to shorten and / or eliminate animal downtime, which increases milk production.

[0030] The tag's radio transmitter can be configured to transmit radio signals in ultra-wideband (UWB), a radio technology suitable for indoor positioning.

[0031] Alternatively, at least one area of ​​the barn may be divided into sub-areas. For example, a resting area sub-area may consist of multiple compartments, and a feeding area sub-area may include feeding stations. The processing controller may be configured to compile a calculated amount of time spent by each animal in each sub-area. Furthermore, based on this compilation, the processing controller may detect sub-areas where usage time is less than a threshold time.

[0032] By dividing one or more zones into subzones and determining the animals' locations at the subzone level, it's possible to identify, for example, whether animals dislike certain areas of the barn; and / or whether there are areas in the barn that all animals avoid. Farmers can then be advised to inspect the problematic areas to find out why they are avoiding them. For example, this area might be a compartment that the animals find uncomfortable. Farmers can then implement different solutions (providing better bedding on the floor, improving ventilation, etc.) and track animal use of the barn's zones / subzones to achieve optimal barn area utilization. It's even possible to add more animals to the farm, thereby increasing the farm's milk production.

[0033] The system may also include output devices for farmers, such as computers, portable communication devices, and tablets. The processing controller can be configured to output information on the distribution of time animals spend in different areas of the barn onto the output devices. In some further embodiments, the processing controller can be configured to output generated alarms onto the output devices.

[0034] Therefore, farmers can obtain information and alerts for continuous monitoring of their livestock and be able to detect behavioral deviations in animals at an early stage. Attached Figure Description

[0035] The invention will then be further explained with reference to non-limiting embodiments as schematically shown and described in the accompanying drawings, in which:

[0036] Figure 1 An example of the interior of a livestock shed including a system according to one embodiment of the present invention is shown;

[0037] Figure 2 An overview image of a livestock shed according to one embodiment is shown;

[0038] Figure 3 A virtual map of a livestock shed according to one implementation scheme is shown;

[0039] Figures 4A to 4F The tracking sequence of information entities in a virtual map of a livestock shed according to different implementation schemes is shown;

[0040] Figure 5 Labels for various entities are shown in the implementation scheme.

[0041] Figure 1 This is an illustration depicting an example of the interior of a barn including system 100 according to one embodiment of the invention. Animal 101 is associated with tag 110, which includes a radio transmitter that repeatedly transmits or flashes radio signals at regular time intervals, for example, approximately once every 2.2 seconds in some examples. The regular time interval may be set to another time interval, such as a fraction of a second, per second, every 3 seconds, etc.

[0042] Animal 101 can be like Figure 1 The cow shown is an example of a dairy cow, but in other examples it can be any arbitrary domesticated animal, such as, for example, a bull, a horse, a goat, a sheep, a camel, a dairy cow, a yak, etc.

[0043] Tag 110 is affixed to a body part of animal 101, such as around the neck or piercing one ear of animal 101, or possibly any other body part. Tag 110 may have memory that may include data uniquely identifying the tag and / or animal 101, such as an identification reference like a local or globally unique number, name, and / or code. Details of tag 110 and the various components included therein are... Figure 5 It is shown in the figure and discussed in the corresponding section of the specification.

[0044] The transmitter of tag 110 emits wireless signals that can be received by positioning controller 130 via multiple receivers 120a, 120b, 120c (such as typically at least three receivers 120a, 120b, 120c). These receivers 120a, 120b, 120c or anchors are installed at predetermined, known locations different from each other in the barn.

[0045] The wireless signal can be transmitted between the transmitter of tag 110 and the wireless signal receivers 120a, 120b, and 120c via any convenient wireless communication technology such as Ultra Wideband (UWB), Bluetooth (BT), Wireless Universal Serial Bus (Wireless USB), Radio Frequency Identification (RFID), Wi-Fi, etc.; thus the location of tag 110 can be determined, and thereby indirectly the location of animal 101 associated with tag 110 can be determined.

[0046] Compared to alternative radio band solutions, UWB-based wireless signaling offers certain advantages and allows for more detailed location of tag 110 / animal 101.

[0047] After repeatedly receiving data related to received radio signals received from the respective receivers 120a, 120b, 120c via gateway 125, the positioning controller 130 is configured to calculate a set of location coordinates of tag 110, including the tag identifier, based on information related to the received radio signals of radio transmitter 110 received by receivers 120a, 120b, 120c.

[0048] The positioning controller 130 can determine the position of tag 110 based on signals emitted by tag 110. The position of tag 110 (and thus the associated animal 101) can be determined, for example, via triangulation or trilateration in at least two directions (e.g., two perpendicular directions such as X and Y). In some embodiments, the position of tag 110 can also be determined in the Z direction.

[0049] Each data entity comprising the positioning controller 130 may include or be configured to include timestamps, tag identifiers, flashing index numbers, X coordinates, Y coordinates, Z coordinates, and / or accelerometer data.

[0050] Ideally, receivers 120a, 120b, and 120c can receive each flash of tag 110, thereby enabling the positioning controller 130 to continuously determine the position of tag 110. However, flashes may not be received by one, some, or all of receivers 120a, 120b, and 120c, resulting in gaps in a series of flashes.

[0051] Sometimes, the received flashes may be distorted or interfered with by other signals or by signal reflections from obstacles in the barn, which affects the location of tag 110 / animal 101.

[0052] The positioning controller 130 is configured to provide data entities associated with timestamps and / or index numbers to the processing controller 150 and / or database 140, each data entity including calculated location coordinates of tag 110 including tag identifier.

[0053] In the illustrated example, the computational functionality of the provided system 100 is divided between a positioning controller 130 and a processing controller 150, which are physically separate from each other and from the farm. However, in other embodiments, the computational functionality of both the positioning controller 130 and the processing controller 150 may be performed by a single controller, which may be located at the farm or, when a communication connection is established, remote from the farm. In still other embodiments, the computational functionality of the described positioning controller 130 and processing controller 150 may be further subdivided into additional controllers that are communicatively connected to each other, thereby enabling them to perform the computations of system 100.

[0054] In some implementations, the processing controller 150 and / or database 140 can be remotely located relative to the farm, connected to the location controller 130 / RTLS via a wired or wireless network. This allows for centralized data processing, computation, and data storage, saving resources and sparing farmers from data maintenance, software updates, etc.

[0055] Alternatively, the processing controller 150 and / or database 140 can be located locally on the farm. This provides a solution independent of network connectivity.

[0056] Therefore, the processing controller 150 can acquire and analyze the collected data, for example, by sorting the acquired data entities according to the sampling order based on the index number and / or timestamp associated with the same animal 101 during a predetermined time period. This allows for the detection of missing data entities or data entities that do not contain data or contain incomplete data.

[0057] Data entities that do not include location coordinates (X / Y and possibly Z) or include at least incomplete location coordinates can be eliminated.

[0058] In one example, analysis of the obtained data entities can lead to the filtering and removal of outlier locations.

[0059] In the presence of one or more data entities, interpolation can be performed based on the preceding and following data entities; or extrapolation can be performed based on the previous data entities.

[0060] Then, the processing controller 150 can determine the distribution of time that the animal 101 spends in different areas of the barn.

[0061] System 100 may include output devices 160, such as a farmer's portable / fixed display. It may output information about the distribution of time spent by the animal 101 in different areas of the barn and / or various alarms to draw the farmer's attention to the most anxious animal behavior detected.

[0062] Figure 2 An overview of a possible implementation of a livestock shed 200 is shown, in which signal receivers 120a, 120b, 120c may be provided for receiving radio signals transmitted by tags 110 of the respective animals 101, 102, 103.

[0063] The barn 200 may include various areas dedicated to different purposes, such as, for example, a feeding platform 210 for eating, a resting compartment 220, and a walking area 230 for transport, movement, and socialization. In this case, the barn also has a door 240 through which animals 101, 102, and 103 can leave the barn 200, for example, to go to a pasture for outdoor recreation. By assuming that animals 101, 102, and 103 leave the barn 200 when they no longer receive radio signals from their tag 110 after being near the door 240, and correspondingly assuming that they return to the barn 200 when they reappear at the door 240, the time animals spend outside can be estimated.

[0064] In other livestock sheds 200, there may be water dispenser areas, brushing areas, milking robot areas, waiting areas for using milking robots, milking areas, multiple entrance / exit areas, etc.

[0065] Figure 3 A virtual representation 300 of the livestock shed 200 is shown, which includes multiple sets of position coordinates 310, 320, 330 corresponding to the position coordinates of the corresponding areas 210, 220, 230 of the livestock shed 200.

[0066] The current position of the corresponding animals 101, 102, and 103 can be represented by the corresponding data entities 301, 302, and 303. In addition to the other data already mentioned, each data entity also includes X and Y coordinates.

[0067] Figure 4A A data entity 301 of a specific animal 101 is schematically shown, which is captured during a predetermined time period (e.g., about 10-20 minutes, several hours, or some other user-defined time period).

[0068] The aim is to determine the distribution of time spent by animal 101 in different zones 210, 220, and 230 of barn 200 during a predetermined time period.

[0069] Figure 4B The diagram schematically illustrates a data entity 301 of a specific animal 101 during a predetermined time period. By sorting the data entities 301 according to the sampling order based on the index number and / or timestamp, missing data entities 301 can be detected and replaced by interpolation / extrapolation of surrounding / previous data entities.

[0070] Figure 4C An example of data entity 301 is illustrated, in which outlier data entities 410a, 410b, and 410c are filtered out and removed according to some different principles or methods.

[0071] Due to factors such as radio wave reflections and signal interference between tags 110 of different but closely located animals 101, 102, and 103, some data entities 301 may include incorrect location coordinates relative to the actual location of animal 101. The signaling may also be affected, at least temporarily, by various machines temporarily placed in or moving around within the barn.

[0072] Therefore, the signal may be lost, and / or alternatively include incomplete information that enables the location of animals 101, 102, 103 at the time the signal was emitted. If only a single signal or possibly a few signals are lost and / or include incomplete data, data entity 301 can be located by interpolating / extrapolating.

[0073] The identification and removal of the most obvious outliers 410a, 410b, and 410c caused by reflection, etc., can be an iterative process based on the velocity calculation of the animal velocity between continuous data entities 301.

[0074] The algorithm for calculating animal speed may include first calculating dx, dy, and dt for all data entities 301, and then calculating: v = sqrt(dx) 2 +dy 2 ) / dt.

[0075] Subsequently, when animal 101 is a cow, the position with the highest speed can be deleted as long as the maximum speed is >2000 mm / s (2 m / s or 7.2 km / h), and the speed of the remaining data entity 301 in array 400 can be recalculated. Other animals may have other speed threshold limits.

[0076] Based on the speed distribution calculated from these figures, it can be assumed that the cows are unlikely to move at speeds exceeding 2 m / s. This is why data entity 301 involving speeds faster than 2 m / s can be removed. Sometimes, data entity 301 preceding data entities with higher speeds can also be removed.

[0077] It can be assumed that animal 101 is located near data entity 301 before and after the missing or incomplete data entity.

[0078] For a series of missing or incomplete data entities 301, such as Figure 4D As shown, the whereabouts of animal 101 become more uncertain, and the location and temporal distribution of animals in different zones 210, 220, and 230 can be reconstructed.

[0079] Figure 4E Examples are shown of determining the location of animal 101 and the distribution of time spent by animal 101 in different zones 210, 220, and 230 of barn 200.

[0080] In some implementations, the processing controller 150 may define and assemble clusters 470 of data entities 301 obtained from the positioning controller 130, these clusters having location coordinates within distance limits and timestamps and / or index numbers within time limits.

[0081] Then, the gravity point 480 of the defined cluster 470 can be determined, and the position coordinates of the gravity point 480 can be calculated. Furthermore, it can be determined which regions 210, 220, and 230 the position coordinates of the gravity point 480 are associated with. Additionally, the processing controller 150 can determine that all data entities 301 of the cluster 470 are associated with regions 210, 220, and 230 of the cluster gravity point 480.

[0082] This balances the fluctuations in the position coordinates of animal 101, which is particularly advantageous when animal 101 is located near the boundary between two different zones 210, 220, and 230.

[0083] Figure 4FAn embodiment is shown in which zones 210, 220, 230, or at least one of zones 210, 220, 230, can be divided into sub-zones 310a, 310b, 320a, 320b, 320c, 320d, 320e, 320f, 320g, 330a, 330b. Sub-zones 310a, 310b, 320a, 320b, 320c, 320d, 320e, 320f, 320g, 330a, 330b may, for example, include compartments and / or feeding stations. Transport zone 230 may be divided into different sections.

[0084] Figure 5 A tag 110 is shown attached to or carried by an animal 101. Tag 110 includes a processing device 510, a radio transmitter 520, and a memory 530. The memory 530 stores a unique tag identifier for tag 110. The processing device 510 is configured to repeatedly transmit or flash radio signals via the radio transmitter 520 at regular time intervals, such as every 2.2 seconds or approximately every 2.2 seconds. Each radio signal includes the tag identifier. In one example, the transmitted radio signal may be a radio signal in ultra-wideband.

[0085] In some optional embodiments, tag 110 may also include a device 540 for determining the activity of animal 101, such as, for example, one or more three-dimensional (3D) accelerometers, gyroscopes, inertial sensors, etc.

[0086] The optional 3D accelerometer 540 of tag 110 can perform high-frequency recording of biaxial and / or triaxial acceleration, which allows for the identification of behavioral patterns, such as determining whether animal 101 is ruminating.

[0087] The memory 530 stores the tag identifier and / or identifier reference of the animal 101.

[0088] In some implementations, tag 110 may include a receiver 550 configured to receive radio signals. Other entities, such as, for example, a positioning controller 130 and / or a processing controller 150, may communicate commands, such as to trigger tag 110 to transmit signals, via their respective associated transmitters.

[0089] Tag 110 may also include an energy source 560, such as a battery, that provides energy to other enumerated entities included in tag 110.

Claims

1. A system (100) for determining the distribution of time spent by corresponding animals (101, 102, 103) in different zones (210, 220, 230) of a livestock pen (200) during a predetermined time period, wherein the system (100) comprises: Processing controller (150); Database (140), the database including the location coordinates of the corresponding area (210, 220, 230); Positioning controller (130); A set of tags (110), each tag (110) associated with a corresponding animal (101, 102, 103), wherein each tag (110) includes a processing device (510), a radio transmitter (520), and a memory (530) storing tag identifiers, wherein the processing device (510) is configured to repeatedly transmit radio signals at regular time intervals via the radio transmitter (520); wherein each radio signal includes the tag identifier, and At least three receivers (120a, 120b, 120c) are positioned at corresponding predetermined locations within the livestock shed (200), each receiver being configured to... Receive transmitted radio signals; as well as The positioning controller (130) transmits information related to the received radio signals; The positioning controller (130) is configured to repeatedly: For each tag identifier, obtain information related to the received radio signals received from the corresponding receiver (120a, 120b, 120c); A set of location coordinates of the tag (110) including the corresponding tag identifier is calculated based on the information related to the radio signals received by the receiver (120a, 120b, 120c) from the received radio transmitter (520). The processing controller (150) is provided with data entities (301), each data entity (301) including the calculated location coordinates of the tag (110) associated with a timestamp and / or index number; and The processing controller (150) is configured to The distribution of time spent by the animal (101) associated with the tag (110) including the tag identifier in different areas (210, 220, 230) of the livestock pen (200) was determined by the following operations: Based on the location coordinates of the corresponding data entity (301) and the location coordinates of the region (210, 220, 230), each obtained data entity (301) is associated with the corresponding region (210, 220, 230); Count the number of data entities (301) in each corresponding region (210, 220, 230); and The amount of time the animal (101) spends in each corresponding zone (210, 220, 230) is calculated by multiplying the number of data entities (301) associated with each corresponding zone (210, 220, 230) by the time interval of the rule. The areas (210, 220, 230) include a feeding area (210) for eating, a rest area (220) for resting, and a transport area (230) for walking. The tag (110) includes an accelerometer (540); and each data entity (301) includes accelerometer data of the accelerometer (540); and wherein The processing controller (150) is configured to detect that the animal (101) is ruminating at the position coordinates of any of the data entities (301) based on the analysis of the accelerometer data of the data entities (301); as well as If the location coordinates of the data entity (301) are close to the boundary of the rest area (220): When rumination is detected, the data entity (301) of the animal (101) is associated with the rest area (220).

2. The system (100) according to claim 1, wherein the database (140) includes a historical distribution of the time spent by the corresponding animals (101, 102, 103) in different areas (210, 220, 230) of the livestock shed (200); and wherein the processing controller (150) is configured to: The determined distribution of the time spent by the animal (101) in different zones (210, 220, 230) is compared with the historical distribution of the time spent by the corresponding animal (101, 102, 103) in different zones (210, 220, 230) extracted from the database (140); The determined distribution of the time spent by the animal (101) in different zones (210, 220, 230) is stored in the database (140); and Based on the comparisons made, an alarm is generated when the deviation between the determined distribution of time of the animal (101) and the historical distribution of time of the animal (101) exceeds a threshold limit.

3. The system (100) of claim 2, wherein the historical distribution of the time spent by the corresponding animals (101, 102, 103) in different zones (210, 220, 230) of the barn (200) is stored in association with the time of day when the distribution is determined; and wherein the processing controller (150) is configured to determine the time of day when the distribution of the time spent by the animals (101) in different zones (210, 220, 230) is determined; and to compare it with the historical distribution of the time spent by the corresponding animals (101, 102, 103) in different zones (210, 220, 230) in the day.

4. The system (100) according to any one of claims 1 to 3, wherein the processing controller (150) is configured to: Define a cluster (470) of the obtained data entities (301) having location coordinates within the distance limit and timestamps and / or index numbers within the time limit. Calculate the position coordinates of the gravity point (480) of the defined cluster (470); Determine which region (210, 220, 230) the position coordinates of the gravity point (480) are associated with; as well as All data entities (301) of the cluster (470) are determined to be associated with the regions (210, 220, 230) of the gravity point (480) of the cluster (470).

5. The system (100) according to any one of claims 1 to 3, wherein the processing controller (150) is configured to determine the region association of a corresponding data entity (301) by applying a rolling average of the position coordinates of the previous data entity (301) within a predetermined window length and associating all data entities (301) within the predetermined window length with the same region (210, 220, 230).

6. The system (100) according to claim 1, wherein the processing controller (150) is configured to: The calculated time spent by the animal (101) in the transport area (230) is compared with the estrus time threshold limit; and When the estrus time threshold limit is exceeded, an estrus alarm is generated for the animal (101).

7. The system (100) according to claim 1, wherein the processing controller (150) is configured to: The time the animal (101) spent in the rest area (220) was compared with a no-resistance time threshold; and When the time threshold of no resistance is exceeded, an abnormal alarm is generated for the animal (101).

8. The system (100) of claim 1, wherein the radio transmitter (520) is configured to transmit radio signals in ultra-wideband.

9. The system (100) according to claim 1, wherein at least one of the regions (210, 220, 230) is divided into sub-regions (310a, 310b, 320a, 320b, 320c, 320d, 320e, 320f, 320g, 330a, 330b), wherein the processing controller (150) is configured to: Compile the amount of calculated time spent by each animal (101, 102, 103) in each subregion (310a, 310b, 320a, 320b, 320c, 320d, 320e, 320f, 320g, 330a, 330b); and Based on the compilation, sub-regions (310a, 310b, 320a, 320b, 320c, 320d, 320e, 320f, 320g, 330a, 330b) that used less than the threshold time were detected.

10. The system (100) of claim 9, wherein the sub-regions (310a, 310b, 320a, 320b, 320c, 320d, 320e, 320f, 320g, 330a, 330b) include compartments and / or feeding stations.

11. The system (100) according to any one of claims 2, 6 or 7, the system comprising an output device (160); and wherein the processing controller (150) is configured to: Information about the distribution of time spent by the animal (101) in different areas (210, 220, 230) of the livestock shed (200) is output on the output device (160).

12. The system (100) of claim 11, wherein the processing controller (150) is configured to: The generated alarm is output on the output device (160).

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