System and method for assessing degree of disturbance of winged insects to plurality of animals within given area

Abstract

The subject matter of the present disclosure is directed to systems and methods for assessing the degree of disturbance of a winged insect to a plurality of animals located in a given area, the system comprising processing circuitry configured to: obtain one or more ear motion patterns associated with at least one ear of at least one animal of the plurality of animals, each ear motion pattern is associated with a corresponding ear motion feature; for at least part of the one or more ear motion patterns, determining whether corresponding ear motion characteristics of the one or more ear motion patterns meet a predefined rule; and determining whether a plurality of ear motion modes whose ear motion features satisfy a predefined rule satisfy an action demand rule.

Description

[0001] This application is a divisional application of the invention patent application with application number 202280013841.9, application date February 8, 2022, entitled "System and method for assessing the degree of disturbance of multiple animals by flying insects in a given area". Technical Field

[0002] This invention relates to the field of assessing the level of disturbance caused by flying insects. Background Technology

[0003] Insects are hexapod invertebrates belonging to the class Insecta. They possess a chiral exoskeleton, a three-part body (head, thorax, and abdomen), three pairs of articulated legs, compound eyes, and a pair of antennae. Insects are the most diverse group of animals, comprising over one million described species, representing more than half of all known organisms.

[0004] During their development, insects go through several stages, from the initial egg or embryonic stage to the final adult stage. In the adult stage, most insects possess wings. This makes flight the preferred mode of locomotion for most adult insects, although walking or sometimes swimming is also a means of movement.

[0005] While most flying insects may be unpleasant to other animals, some pose additional risks to their health and well-being. For example, a wide variety of flies can cause real stress to farm animals such as goats, sheep, and cows, leading them to consume less food (resulting in slower growth) and produce less milk. It is estimated that flies are responsible for billions of dollars in losses globally each year as a result. Furthermore, due to their well-known role as disease carriers, flying insects are known to transmit pathogens such as conjunctivitis (pink eye) and summer mastitis, directly impacting the health of other animals.

[0006] Because current technologies primarily focus on pest control and reducing the number of potentially harmful flying insects without considering the level of disturbance caused by these insects, they fail to provide tools for assessing the level of disturbance caused by potentially harmful flying insects to animals. Furthermore, current technologies are not based on direct measurements obtained from animals within the population, which can determine the level of disturbance caused by flying insects in a given area. Similarly, in attempting to assess animal population welfare, current technologies do not take into account the level of disturbance caused by flying insects (which is well known to increase stress levels in animal populations and thus affect their health), and / or the distribution of specific diseases within the population.

[0007] Therefore, there is a need in the art for a system and method for assessing the degree of disturbance caused by flying insects to multiple animals in a given area. Summary of the Invention

[0008] According to a first aspect of the subject matter of this disclosure, a system is provided for assessing the degree of disturbance caused by a flying insect to multiple animals located in a given area. The system includes a processing circuitry configured to: obtain one or more ear movement patterns associated with at least one ear of at least one of the multiple animals, each ear movement pattern being associated with a corresponding ear movement feature; for at least a portion of the one or more ear movement patterns, determine whether the corresponding ear movement feature of the one or more ear movement patterns satisfies a predefined rule; and determine whether multiple ear movement patterns whose ear movement features satisfy the predefined rule satisfy a motion requirement rule.

[0009] In one embodiment of the subject matter of this disclosure and / or its embodiments, each of one or more ear movement patterns is associated with its own characteristics.

[0010] In one embodiment of the subject matter of this disclosure and / or its embodiments, one or more ear movement patterns are associated with features common to all ear movement patterns.

[0011] In one embodiment of the subject matter of this disclosure and / or its embodiments, the action requirement rule is one of the following: (a) the number of ear movement patterns whose features satisfy a predefined rule is higher than a first harassment threshold, and (b) the percentage of ear movement patterns from multiple animals whose features satisfy a predefined rule is higher than a second harassment threshold.

[0012] In one embodiment of the subject matter of this disclosure and / or its embodiments, after an action requirement rule is met, the processing circuitry is configured to indicate that action needs to be taken to reduce the number of flying insects in a given area.

[0013] In one embodiment of the subject matter of this disclosure and / or its embodiments, the action includes at least one of the following: installing insect paper, installing an insect trap, installing an insect strip that releases insecticide, using an insect repellent spray, using an insect predator, or any combination thereof.

[0014] In one embodiment of the subject matter of this disclosure and / or its embodiments, the action is intended to address one or more health conditions.

[0015] In one embodiment of the subject matter of this disclosure and / or its embodiments, the ear movement pattern of at least one ear is obtained via at least one corresponding accelerometer coupled to at least one ear.

[0016] In some cases, at least one corresponding accelerometer is part of at least one corresponding ear tag attached to at least one ear of at least one animal.

[0017] In one embodiment of the subject matter of this disclosure and / or its embodiments, the flying insect is any one of the housefly, stable fly, blowfly, flesh fly, tuft fly, or any combination thereof.

[0018] In one embodiment of the subject matter of this disclosure and / or its embodiments, one or more animals are any of livestock, domesticated animals, wild animals, and combinations thereof.

[0019] In one embodiment of the subject matter of this disclosure and / or its embodiments, one or more animals are dairy cows.

[0020] In one embodiment of the subject matter of this disclosure and / or its embodiments, a given area is a controlled environment.

[0021] According to a second aspect of the subject matter of this disclosure, a method is provided for assessing the degree of disturbance caused by a flying insect to multiple animals located in a given area, the method comprising: obtaining one or more ear movement patterns associated with at least one ear of at least one of the multiple animals, each ear movement pattern being associated with a corresponding ear movement feature; determining, for at least a portion of the one or more ear movement patterns, whether the corresponding ear movement feature of the one or more ear movement patterns satisfies a predefined rule; and determining whether the multiple ear movement patterns whose ear movement features satisfy the predefined rule satisfy a motion requirement rule.

[0022] In one embodiment of the subject matter of this disclosure and / or its embodiments, one or more ear movement patterns are associated with features common to all ear movement patterns.

[0023] In one embodiment of the subject matter of this disclosure and / or its embodiments, each of one or more ear movement patterns is associated with its own characteristics.

[0024] In one embodiment of the subject matter of this disclosure and / or its embodiments, the action requirement rule is one of the following: (a) the number of ear movement patterns whose features satisfy a predefined rule is higher than a first harassment threshold, and (b) the percentage of ear movement patterns from multiple animals whose features satisfy a predefined rule is higher than a second harassment threshold.

[0025] In one embodiment of the subject matter of this disclosure and / or its embodiments, the method involves instructing that action needs to be taken to reduce the number of flying insects in a given area after an action requirement rule has been met.

[0026] In one embodiment of the subject matter of this disclosure and / or its embodiments, the action includes at least one of the following: installing insect paper, installing an insect trap, installing an insect strip that releases insecticide, using an insect repellent spray, using an insect predator, or any combination thereof.

[0027] In one embodiment of the subject matter of this disclosure and / or its embodiments, the ear movement pattern of at least one ear is obtained via at least one corresponding accelerometer coupled to at least one ear.

[0028] In one embodiment of the subject matter of this disclosure and / or its embodiments, at least one corresponding accelerometer is part of at least one corresponding ear tag attached to at least one ear of at least one animal.

[0029] In one embodiment of the subject matter of this disclosure and / or its embodiments, the flying insect is any one of the housefly, stable fly, blowfly, flesh fly, tuft fly, or any combination thereof.

[0030] In one embodiment of the subject matter of this disclosure and / or its embodiments, one or more animals are any of livestock, domesticated animals, wild animals, and combinations thereof.

[0031] In one embodiment of the subject matter of this disclosure and / or its embodiments, one or more animals are dairy cows.

[0032] In one embodiment of the subject matter of this disclosure and / or its embodiments, a given area is a controlled environment.

[0033] According to a third aspect of the subject matter of this disclosure, a non-transitory computer-readable storage medium is provided having computer-readable program code embodied therein, the computer-readable program code being executable by at least one processor to perform a method for assessing the degree of disturbance caused by a flying insect to a plurality of animals located in a given area, the disturbance assessment comprising one or more components, the method comprising: obtaining one or more ear movement patterns associated with at least one ear of at least one of the plurality of animals, each ear movement pattern being associated with a corresponding ear movement feature; determining, for at least a portion of the one or more ear movement patterns, whether the corresponding ear movement feature of the one or more ear movement patterns satisfies a predefined rule; and determining whether the plurality of ear movement patterns whose ear movement features satisfy the predefined rule satisfy a motion requirement rule.

[0034] According to a fourth aspect of the subject matter of this disclosure, a system for determining animal population welfare is provided, the system comprising: one or more monitoring devices configured to monitor parameters of animal population members; a data repository including one or more records, each record (i) associated with a corresponding member of the member, and (ii) including one or more parameters of the corresponding member monitored over time by at least one monitoring device; and a processing circuit system configured to: acquire at least one subset of the records, the subset being associated with a first group of members of the animal population; calculate: (A) based on the subset of the records For each given member of the first group, at least two of the following are true: (a) a health score indicating the health status of the corresponding member, (b) a natural life score indicating that the behavior pattern of the corresponding member conforms to the expected natural behavior pattern, or (c) an emotion / happiness score indicating that the emotion / happiness measure of the corresponding member conforms to the expected emotion / happiness measure; and (B) a welfare score of the animal population, based on at least two of the following: (a) a health score calculated for the members of the first group, (b) a natural life score calculated for the members of the second group, or (c) an emotion / happiness score calculated for the members of the third group.

[0035] In one embodiment of the subject matter of this disclosure and / or its embodiments, the parameters include one or more of the following behavioral parameters: (a) the percentage of exercise time of a given member in a first time period, (b) the percentage of eating time of a given member in a second time period, or (c) the percentage of social behavior time of a given member in a third time period; and wherein a natural life score of a given member is determined based on the behavioral parameters.

[0036] In one embodiment of the subject matter of this disclosure and / or its embodiments, the natural life score of a given member is determined based on the consistency of the values ​​of at least some parameters over time.

[0037] In one embodiment of the subject matter of this disclosure and / or its embodiments, there is consistency in the measured values ​​based on reference parameters.

[0038] In one embodiment of the subject matter of this disclosure and / or its embodiments, reference parameters are measured from a reference animal.

[0039] In one embodiment of the subject matter of this disclosure and / or its embodiments, the parameters include one or more of the following affective / happiness parameters: (a) the respiratory level of a given member, (b) the percentage of rumination time of a given member in a fourth time period, or (c) the percentage of eating time of a given member in a fifth time period; and wherein the affective / happiness score of a given member is determined based on the affective / happiness parameters.

[0040] In one embodiment of the subject matter of this disclosure and / or its embodiments, a given member’s emotion / happiness score is determined based on the consistency of the values ​​of at least some parameters over time.

[0041] In one embodiment of the subject matter of this disclosure and / or its embodiments, there is consistency in the measured values ​​based on reference parameters.

[0042] In one embodiment of the subject matter of this disclosure and / or its embodiments, reference parameters are measured from a reference animal.

[0043] In one embodiment of the subject matter of this disclosure and / or its embodiments, the welfare score is calculated based on the change between the emotion / happiness scores of the first group of members.

[0044] In one embodiment of the subject matter of this disclosure and / or its embodiments, at least two of the first, second, and third groups are the same group.

[0045] In one embodiment of the subject matter of this disclosure and / or its embodiments, the second and third groups include healthy members from the first group whose health scores are above a threshold.

[0046] In one embodiment of the subject matter of this disclosure and / or its embodiments, the record also includes one or more environmental parameters to indicate the environmental state of the respective member, and wherein the determination of (a) the natural life score of the respective member or (b) the emotional / happiness score of the respective member is also based on the environmental parameters.

[0047] In one embodiment of the subject matter of this disclosure and / or its embodiments, the monitoring device includes one or more of the following: an accelerometer, a temperature sensor, a position sensor, a pedometer, or a heart rate sensor.

[0048] In one embodiment of the subject matter of this disclosure and / or its embodiments, at least some records also include descriptive data associated with the respective members, wherein the descriptive data is not obtained from the monitoring device.

[0049] In one embodiment of the subject matter of this disclosure and / or its embodiments, descriptive data includes one or more of the following: the age of the corresponding member, the sex of the corresponding member, the treatment history of the corresponding member, or genetic information associated with the corresponding member.

[0050] In one embodiment of the subject matter of this disclosure and / or its embodiments, the processing circuitry is also configured to suggest actions to be taken for an animal population based on welfare scores.

[0051] In one embodiment of the subject matter of this disclosure and / or its embodiments, the action is one or more of the following: treating an animal population, changing the ambient temperature of an animal population, changing the feed for an animal population, or changing the schedule of an animal population.

[0052] In one embodiment of the subject matter of this disclosure and / or its embodiments, at least a subset of the records is all records of the animal population.

[0053] In one embodiment of the subject matter of this disclosure and / or its embodiments, the animal population is located in one or more geographical locations.

[0054] In one embodiment of the subject matter of this disclosure and / or its embodiments, at least some monitoring devices are attached monitoring devices that are attached to the respective members.

[0055] In one embodiment of the subject matter of this disclosure and / or its embodiments, the attached monitoring device is a monitoring tag or monitoring collar.

[0056] In one embodiment of the subject matter and / or embodiments of this disclosure, the animal population is a population of ruminants or companion animals.

[0057] In one embodiment of the subject matter of this disclosure and / or its embodiments, recommendations are given when the welfare score is below a welfare threshold.

[0058] In one embodiment of the subject matter of this disclosure and / or its embodiments, the welfare threshold is determined based on statistical analysis of historical welfare scores.

[0059] In one embodiment of the subject matter of this disclosure and / or its embodiments, the welfare threshold is geographic location-specific.

[0061] According to a fifth aspect of the subject matter of this disclosure, a method for determining animal population welfare is provided, the method comprising: obtaining, by means of a processing circuit system, at least a subset of one or more records, each record (i) associated with a corresponding member of a member, and (ii) including one or more parameters of the corresponding member monitored over time by at least one of a set of one or more monitoring devices configured to monitor parameters of members of an animal population, wherein a portion thereof is associated with a first group of members of the animal population; calculating, by means of the processing circuit system: (A) based on the subset of records, for each given member of the first group of members, at least two of the following: (a) a health score indicating the health status of the corresponding member, (b) a natural life score indicating that the behavior pattern of the corresponding member conforms to a desired natural behavior pattern, or (c) an emotion / happiness score indicating that the emotion / happiness measure of the corresponding member conforms to a desired emotion / happiness measure; and (B) a welfare score of the animal population, based on at least two of the following: (a) a health score calculated for members of the first group, (b) a natural life score calculated for members of the second group, or (c) an emotion / happiness score calculated for members of the third group.

[0062] In one embodiment of the subject matter of this disclosure and / or its embodiments, the parameters include one or more of the following behavioral parameters: (a) the percentage of exercise time of a given member in a first time period, (b) the percentage of eating time of a given member in a second time period, or (c) the percentage of social behavior time of a given member in a third time period; and wherein a natural life score of a given member is determined based on the behavioral parameters.

[0063] In one embodiment of the subject matter of this disclosure and / or its embodiments, the natural life score of a given member is determined based on the consistency of the values ​​of at least some parameters over time.

[0064] In one embodiment of the subject matter of this disclosure and / or its embodiments, there is consistency in the measured values ​​based on reference parameters.

[0065] In one embodiment of the subject matter of this disclosure and / or its embodiments, reference parameters are measured from a reference animal.

[0066] In one embodiment of the subject matter of this disclosure and / or its embodiments, the parameters include one or more of the following affective / happiness parameters: (a) the respiratory level of a given member, (b) the percentage of rumination time of a given member in a fourth time period, or (c) the percentage of eating time of a given member in a fifth time period; and wherein the affective / happiness score of a given member is determined based on the affective / happiness parameters.

[0067] In one embodiment of the subject matter of this disclosure and / or its embodiments, a given member’s emotion / happiness score is determined based on the consistency of the values ​​of at least some parameters over time.

[0068] In one embodiment of the subject matter of this disclosure and / or its embodiments, there is consistency in the measured values ​​based on reference parameters.

[0069] In one embodiment of the subject matter of this disclosure and / or its embodiments, reference parameters are measured from a reference animal.

[0070] In one embodiment of the subject matter of this disclosure and / or its embodiments, the welfare score is calculated based on the change between the emotion / happiness scores of the first group of members.

[0071] In one embodiment of the subject matter of this disclosure and / or its embodiments, at least two of the first, second, and third groups are the same group.

[0072] In one embodiment of the subject matter of this disclosure and / or its embodiments, the second and third groups include healthy members from the first group whose health scores are above a threshold.

[0073] In one embodiment of the subject matter of this disclosure and / or its embodiments, the record also includes one or more environmental parameters indicating the environmental state of the respective member, and wherein the determination of (a) the natural life score of the respective member or (b) the emotional / happiness score of the respective member is also based on the environmental parameters.

[0074] In one embodiment of the subject matter of this disclosure and / or its embodiments, the monitoring device includes one or more of the following: an accelerometer, a temperature sensor, a position sensor, a pedometer, or a heart rate sensor.

[0075] In one embodiment of the subject matter of this disclosure and / or its embodiments, at least some records also include descriptive data associated with the respective members, wherein the descriptive data is not obtained from the monitoring device.

[0076] In one embodiment of the subject matter of this disclosure and / or its embodiments, descriptive data includes one or more of the following: the age of the corresponding member, the sex of the corresponding member, the treatment history of the corresponding member, or genetic information associated with the corresponding member.

[0077] In one embodiment of the subject matter of this disclosure and / or its embodiments, the method further includes suggesting actions to be taken for the animal population based on welfare scores.

[0078] In one embodiment of the subject matter of this disclosure and / or its embodiments, the action is one or more of the following: treating an animal population, changing the temperature of the animal population's environment, changing the animal population's feed, or changing the animal population's schedule.

[0079] In one embodiment of the subject matter of this disclosure and / or its embodiments, at least a subset of the records are all records of the animal population.

[0080] In one embodiment of the subject matter of this disclosure and / or its embodiments, the animal population is located in one or more geographical locations.

[0081] In one embodiment of the subject matter of this disclosure and / or its embodiments, at least some monitoring devices are attached monitoring devices that are attached to the respective members.

[0082] In one embodiment of the subject matter of this disclosure and / or its embodiments, the attached monitoring device is a monitoring tag or monitoring collar.

[0083] In one embodiment of the subject matter and / or embodiments of this disclosure, the animal population is a population of ruminants or companion animals.

[0084] In one embodiment of the subject matter of this disclosure and / or its embodiments, recommendations are given when the welfare score is below a welfare threshold.

[0085] In one embodiment of the subject matter of this disclosure and / or its embodiments, the welfare threshold is determined based on a statistical analysis of historical welfare scores.

[0086] In one embodiment of the subject matter and / or embodiments of this disclosure, the welfare threshold is geographically specific.

[0087] According to a sixth aspect of the subject matter of this disclosure, a non-transitory computer-readable storage medium is provided having computer-readable program code embodied therein, the computer-readable program code being executable by at least one processing circuitry system of a computer to perform a method for determining animal population welfare, the method comprising: obtaining, by the processing circuitry system, at least a subset of a set of one or more records, each record (i) associated with a corresponding member of a member, and (ii) including, monitoring, over time, one or more parameters of the corresponding member by at least one of a set of one or more monitoring devices configured to monitor parameters of animal population members, wherein a portion thereof is associated with a first... The member groups are associated; the processing circuit system calculates: (A) based on a subset of records, for each given member of the first group, at least two of the following: (a) a health score indicating the health status of the corresponding member, (b) a natural life score indicating that the behavior pattern of the corresponding member conforms to the expected natural behavior pattern, or (c) an emotion / happiness score indicating that the emotion / happiness measure of the corresponding member conforms to the expected emotion / happiness measure; and (B) a welfare score of the animal population, based on at least two of the following: (a) a health score calculated for the first group of members, (B) a natural life score calculated for the second group of members, or (c) an emotion / happiness score calculated for the third group of members. Attached Figure Description

[0088] To understand the subject matter of this disclosure and how it can be implemented in practice, the subject matter will now be described by way of non-limiting example only, with reference to the accompanying drawings, wherein:

[0089] Figure 1 This is a schematic diagram of an environment in which a system for assessing the level of disturbance caused by flying insects to multiple animals within a given area operates, in accordance with the subject matter of this disclosure.

[0090] Figure 2 This is a block diagram, schematically illustrating an example of a system for assessing the level of disturbance caused by flying insects to multiple animals in a given area, in accordance with the subject matter of this disclosure.

[0091] Figure 3 This is a flowchart illustrating an example of a series of operations performed by a system for assessing the degree of disturbance caused by flying insects to multiple animals in a given area, in accordance with the subject matter of this disclosure.

[0092] Figures 4A-4B It is a percentage distribution of Moran cattle exhibiting ear movement patterns over 24 hours and 11 days, respectively, in accordance with the subject matter of this disclosure, with ear movement rates satisfying predefined rules for ear movement rates;

[0093] Figure 5 This is a flowchart illustrating another example of a series of operations performed by a system for assessing the degree of disturbance caused by flying insects to multiple animals in a given area, in accordance with the subject matter of this disclosure;

[0094] Figure 6 This is a schematic diagram illustrating the components of the welfare score of an animal population, based on the subject matter of this disclosure.

[0095] Figure 7 This is a block diagram, schematically illustrating an example of a welfare determination system for determining the welfare of an animal population, in accordance with the subject matter of this disclosure.

[0096] Figure 8 This is a flowchart illustrating an example of a series of operations used to determine animal population welfare in accordance with the subject matter of this disclosure;

[0097] Figure 9 This is a diagram illustrating the determination of animal population welfare KPI scores based on the subject matter of this disclosure;

[0098] Figure 10A This is an illustration of an example graphical user interface (GUI) for a welfare determination system, in accordance with the subject matter of this disclosure;

[0099] Figure 10B This is an illustration of another example of a GUI for a welfare determination system, based on the subject matter of this disclosure;

[0100] Figure 11 This is a diagram illustrating the determination of welfare thresholds for different countries based on the subject matter of this disclosure;

[0101] Figure 12 This is a diagram illustrating the impact of weather and season on welfare scores, based on the subject of this disclosure.

[0102] Figure 13 This is a schematic diagram illustrating an exemplary comparison, based on the subject matter of this disclosure, of welfare scores determined by human auditors with welfare KPI scores determined by a system across various facilities; and

[0103] Figure 14 This is a schematic diagram illustrating an example of consistency between benefit scores determined by human auditors and benefit KPI scores determined by the system, based on the subject matter of this disclosure. Detailed Implementation

[0104] Numerous specific details are set forth in the following detailed description in order to provide a thorough understanding of the subject matter of this disclosure. However, those skilled in the art will understand that the subject matter of this disclosure can be practiced without these specific details. In other instances, well-known methods, procedures, and components have not been described in detail so as not to obscure the subject matter of this disclosure.

[0105] In the accompanying drawings and description, the same reference numerals indicate those components common to different embodiments or configurations.

[0106] Unless otherwise expressly stated, it will become apparent from the following discussion that terms such as “obtain,” “determine,” “instruct,” “insert,” “analyze,” “provide,” “calculate,” and “suggest” are used throughout the discussion of this specification to refer to the actions and / or processes of a computer that operate and / or convert data into other data, represented as physical quantities, such as electronic quantities, and / or data representing the physical object. The terms “computer,” “processor,” “processing resource,” “processing circuit system,” and “controller” should be broadly interpreted to encompass any type of electronic device with data processing capabilities, including, by way of non-limiting example, personal desktop / laptop computers, servers, computing systems, communication devices, smartphones, tablets, smart TVs, processors (e.g., digital signal processors (DSPs), microcontrollers, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), etc.), a group of multiple physical machines sharing various task capabilities, a virtual server residing on a single physical machine, any other electronic computing device, and / or any combination thereof.

[0107] The operations taught herein can be performed by a computer specifically constructed for the desired purpose, or by a general-purpose computer whose computer program, stored in a non-transitory computer-readable storage medium, is specifically configured for the desired purpose. The term "non-transitory" is used herein to exclude transient propagating signals, but includes any volatile or non-volatile computer storage technology suitable for the application.

[0108] As used herein, the phrases “for example,” “such as,” “as an example,” and variations thereof describe non-limiting embodiments of the subject matter of this disclosure. References to “one case,” “some cases,” “other cases,” or variations thereof in the specification are intended to indicate that a particular feature, structure, or characteristic described in relation to an embodiment is included in at least one embodiment of the subject matter of this disclosure. Therefore, the appearance of the phrases “one case,” “some cases,” “other cases,” or variations thereof does not necessarily refer to the same embodiment.

[0109] It should be understood that, unless otherwise expressly stated, for clarity, certain features of the subject matter of this disclosure described in the context of a single embodiment may also be provided in combination in that single embodiment. Conversely, for brevity, various features of the subject matter of this disclosure described in the context of a single embodiment may also be provided individually or in any suitable sub-combination.

[0110] In embodiments of the subject matter of this disclosure, a comparison can be performed. Figure 3 , Figure 5 and Figure 8 The fewer, more, and / or different stages shown. In embodiments of the subject matter of this disclosure, Figure 3 , Figure 5 and Figure 8 One or more phases shown may be executed in different orders and / or one or more groups of phases may be executed simultaneously. Figure 2 and Figure 7 A general schematic diagram of a system architecture according to an embodiment of the subject matter of this disclosure is shown. Figure 2 and Figure 7 Each module in this document may consist of any combination of software, hardware, and / or firmware that perform the functions defined and explained herein. Figure 2 and Figure 7 The modules in the system can be concentrated in one location or distributed across more than one location. In other embodiments of the subject matter of this disclosure, the system may include more than Figure 2 and 7 The fewer, more, and / or different modules shown.

[0111] Any reference to the method in the specification shall be modified as necessary for use on a system capable of executing the method, and shall be modified as necessary for use on a non-transitory computer-readable medium storing instructions that, once executed by a computer, would cause the method to be executed.

[0112] Any references to the system in the specification shall be modified as necessary to apply to methods that can be executed by the system, and shall be modified as necessary to apply to non-transitory computer-readable media storing instructions that can be executed by the system.

[0113] Any reference in this specification to a non-transitory computer-readable medium shall be modified as necessary to apply to a system capable of executing instructions stored in a non-transitory computer-readable medium, and as necessary to a method capable of being executed by a computer that reads instructions stored in a non-transitory computer-readable medium.

[0114] The subject matter of this disclosure aims to provide systems and methods for assessing levels of flying insect nuisance. Based on such assessments, the subject matter of this disclosure is capable of measuring the actual number of insects in a flying insect population, assessing the distribution of a given disease in an animal population, preventing disease, preventing adverse health conditions, improving animal welfare, and / or preventing nuisance.

[0115] With this in mind, please note Figure 1 , Figure 1 A schematic diagram of an environment is shown in which a system (which may also be referred to herein as the "system") for assessing the degree of disturbance of multiple animal pairs by flying insects within a given area operates in accordance with the subject matter of this disclosure.

[0116] As illustrated in the diagram, environment 100 includes an area 102 containing an animal population of multiple animals 104 (e.g., livestock, domesticated animals, wild animals, etc.) and a population of multiple flying insects 106 (e.g., mosquitoes, flies such as houseflies, stable flies, blowflies, flesh flies, tuft flies, etc.) dispersed throughout area 102, surrounding the multiple animals 104. The dispersion of multiple flying insects 106 throughout area 102 exposes the multiple animals 104 to potential insect infestation and / or irritation, related diseases, and health conditions. As an example, area 102 may be a controlled environment (e.g., a controlled fence, a controlled barn, etc.) configured to maintain optimal growth conditions for the multiple animals 104 throughout their development and / or lifespan. As another example, area 102 may also be an uncontrolled environment (e.g., grassland, field, etc.).

[0117] Disturbance and / or irritation may involve, for example, biting, pricking, blood-sucking, and may elicit one or more deworming behaviors in multiple animals104, such as ear movements (e.g., ear shaking), head shaking, foot stomping, tail wagging, etc. Related diseases may include, for example, Rift Valley fever, trypanosomiasis, bluetongue, transient fever, keratoconjunctivitis (pink eye), summer mastitis, etc.

[0118] Of the multiple animals 104 found in region 102, one or more animals may be associated with one or more components (e.g., accelerometers, gyroscopes, etc.) and / or one or more systems (e.g., visual systems, etc.) capable of recognizing and / or monitoring different types of ear movement patterns. For example, each of the one or more animals may be attached with one or more accelerometers 108 (e.g., microelectromechanical systems (MEMS) three-dimensional accelerometers or any other type of three-dimensional accelerometer). The three-dimensional accelerometers 108 may optionally be coupled to one or both ears of the animal in various ways. For example, in some cases, each three-dimensional accelerometer 108 may be a separate device attached to the animal's ear, while in other cases, it may be part of an ear tag attached to the animal's ear. It should be noted that the three-dimensional accelerometers 108 may be attached to the animal in other ways (e.g., as part of a neck monitoring tag attached to the animal via a collar), wherein the placement of the accelerometers 108 is capable of determining the movement of the ears of the animal to which they are attached.

[0119] Each given accelerometer unit of one or more three-dimensional accelerometers 108 can be instructed to detect one or more ear movement patterns associated with harassment and / or stimulation caused by multiple flying insects 106, based on Figure 3 and Figure 5 A further detailed explanation is needed.

[0120] By way of example, an animal population consisting of nine cows 104 is located in a controlled barn 102. Each of the nine cows 104 has a three-dimensional accelerometer 108 coupled to its right ear and is surrounded by a plurality of stable flies 106 dispersed throughout the controlled barn 102. The corresponding three-dimensional accelerometer 108 for each cow is designed to detect specific ear movement patterns in the cow's right ear, indicating disturbances and / or stimuli caused by the plurality of stable flies 106.

[0121] Now let’s turn our attention to the components of the system to assess the level of disturbance caused by 200 flying insects to multiple animals in a given area.

[0122] Figure 2 This is a block diagram, schematically illustrating an example of a system for assessing the degree of disturbance to multiple animals by flying insects in a given area 200, in accordance with the subject matter of this disclosure.

[0123] According to the subject matter of this disclosure, a system for assessing the level of disturbance caused by flying insects to multiple animals in a given area 200 (which may also be referred to herein as "system 200") may include a network interface 206. The network interface 206 (e.g., a network interface card, Wi-Fi client, Li-Fi client, 3G / 4G client, or any other communication component) enables system 200 to communicate with external systems via a network and to process inbound and outbound communications from these systems. For example, system 200 may obtain ear movement patterns, ear movement pattern thresholds, and / or disturbance thresholds through the network interface 206.

[0124] System 200 may also include or be associated with a data repository 204 (e.g., a database, storage system, memory including read-only memory (ROM), random access memory (RAM), or any other type of memory) configured to store data. Some examples of data that may be stored in data repository 204 include:

[0125] Ear movement patterns;

[0126] Characteristics of ear movement patterns (e.g., ear movement rate, ear movement frequency, etc.);

[0127] Historical patterns;

[0128] Thresholds (e.g., disturbance threshold, ear movement rate threshold, pattern threshold, amplitude threshold, etc.);

[0129] Predefined rules;

[0130] Data associated with an individual (e.g., an individual cow) or a group of individuals (e.g., a herd of cows);

[0131] The aim is to reduce the level of flight movement in a given area; etc.

[0132] Data repository 204 can be further configured to retrieve and / or update and / or delete stored data. It should be noted that, in some cases, data repository 204 can be distributed, and system 200 can access the information stored therein, for example, via a wired or wireless network that system 200 can connect to (using its network interface 206).

[0133] System 200 also includes a processing circuitry system 202. The processing circuitry system 202 may be one or more processing units (e.g., a central processing unit), a microprocessor, a microcontroller (e.g., a microcontroller unit (MCU)), or any other computing device or module, including multiple and / or parallel and / or distributed processing units adapted to independently or collaboratively process data to control associated system 200 resources and enable operations associated with system 200 resources.

[0134] Processing circuitry system 202 includes an interference assessment module 208 configured to perform an interference assessment process, as further detailed herein, among other things, refer to Figure 3 and 5 .

[0135] Go to Figure 3 The flowchart shown illustrates an example of a series of operations performed by the system to assess the level of disturbance to multiple animals by flying insects in a given area 200, in accordance with the subject matter of this disclosure.

[0136] Therefore, a system for assessing the level of disturbance caused by flying insects to multiple animals in a given area 200 can be configured to perform a disturbance assessment process 300, for example, using a disturbance assessment module 208.

[0137] Therefore, based on and following the reference Figure 1 The system described herein, used to assess the degree of harassment of multiple animals by flying insects in a given area 200, acquires one or more ear movement patterns (such as tapping, flicking, twisting, etc.) associated with at least one ear of at least one of at least one of multiple animals 104 (box 302). One or more ear movement patterns can be determined by analyzing three-dimensional accelerometer data acquired by corresponding three-dimensional accelerometers 108 attached to at least one ear of at least one of the multiple animals 104. For example, the three-dimensional accelerometer data acquired by each three-dimensional accelerometer 108 can be analyzed to identify multiple repetitions of ear acceleration mutation events over a set period of time. This number can then be compared to a predefined threshold, which can serve as an indication of the ear movement pattern associated with the flying insect harassment; once the predefined threshold is exceeded, the system 200 can acquire the data. In a more specific example, where the three-dimensional accelerometer is part of an ear tag coupled to the animal's ear, the repetition of mutation events can be so rapid due to the continuous movement of the ear that the tag's sensor may become saturated, and the tag's activity may be restricted. Visual confirmation revealed that these conditions were associated solely with the presence of flying insects, enabling the identification of the correlation between sudden changes in events and the presence of insects.

[0138] One or more ear movement patterns can be associated with their own characteristics, such as ear movement rate as a function of time, and / or have common characteristics of all ear movement patterns (or specific subgroups), which can be treated similarly.

[0139] After obtaining one or more ear movement patterns, system 200 determines whether, for at least a portion of the one or more ear movement patterns, their corresponding ear movement characteristics (e.g., ear movement rate) satisfy predefined rules (e.g., exceeding an ear movement rate threshold, pattern threshold, amplitude threshold, following a certain pattern over time, differing from historical patterns of a single animal and / or an animal population, etc.) (box 304). For example, the predefined rules can be defined by one or more of the following: (a) comparing one or more ear movement patterns with empirical evidence of the presence of flies, (b) using historical patterns associated with animals in an animal population or groups of animals in an animal population, (c) comparing one or more ear movement patterns with specifications from database system 200, (d) the ability to correct thresholds / rules based on time of day, weather, animal type, geographic location, climate, (e) using external verification, such as visual confirmation (as described above), (f) using other factors that can empirically confirm an overabundance of flies, etc.

[0140] When predefined rules are based on thresholds, the threshold can be a definite value, a range of values, etc., representing the degree of stimulation or disturbance. The resulting stimulation or disturbance is considered to have a negative impact on milk production, growth rate, etc.

[0141] Then, system 200 determines whether several ear movement patterns whose features satisfy a predefined rule at box 304 meet an action requirement rule (box 306). The action requirement rule may be, for example, (a) the number of ear movement patterns whose features satisfy the predefined rule at box 304 is higher than a first disturbance threshold (e.g., a defined value, a range of values, etc.), (b) the percentage of ear movement patterns from multiple animals whose features satisfy the predefined rule at box 304 is higher than a second disturbance threshold (e.g., a percentage value), or (c) any other rule that determines that action is required to reduce the level of disturbance caused by flying insects.

[0142] For example, Figure 4A and 4B Percentage distribution of Moran cattle exhibiting ear movement patterns over 24 hours and 11 days, respectively, with ear movement rates conforming to predefined rules for ear movement rates;

[0143] like Figure 4A As shown, between 00:00 and 06:00, the percentage of Moran cattle exhibiting ear movement patterns and whose ear movement rates conform to predefined rules is approximately zero. This percentage increases between 06:00 and 15:00 (peaking at 40%), decreases between 15:00 and 19:30, reaches approximately zero around 19:30, and remains there until 00:00.

[0144] Turn attention Figure 4B , Figure 4B The figure illustrates the percentage distribution of Moran cattle exhibiting ear movement patterns over 11 consecutive days, with ear movement rates conforming to a predefined rule. As shown, the percentage distribution of Moran cattle exhibiting ear movement patterns, whose ear movement rates conform to the predefined rule, remained constant for 9 out of the 11 days. However, on the remaining two days (May 5th and June 5th), the percentage distribution changed dramatically due to rain (which is known to be the cause of the reduced fly population).

[0145] In some cases, such as Figure 5 As shown, after the action requirement rules are met, system 200 instructs actions to reduce the number of flying insects in a given area (box 308). This action may involve, for example, installing insect paper, installing insect traps, installing insect strips that release insecticide, using insect repellent sprays, using insect predators, etc. Alternatively or additionally, system 200 may instruct actions related to a given disease (e.g., checking for the presence of the disease and / or treating the disease, etc.) and / or actions aimed at addressing the health status of one or more animals in the population (e.g., providing tailored care, providing appropriate medication, etc.).

[0146] Through examples and based on the description in this article, Figure 1 As a related example, system 200 obtains the ear movement pattern of the right ear of each of nine cows 104, measured by the corresponding three-dimensional accelerometer 108 for each ear. The ear movement pattern of the right ear of each of the nine cows 104 is associated with its own ear movement rate as a function of time.

[0147] Of the 9 cows 104, 4 cows were found to have a right ear movement pattern with a rate of 50 ear movements per minute, while the remaining 5 cows had a right ear movement pattern with a rate of 30 ear movements per minute. The system 200 can then determine whether the ear movement rate of each of the 9 cows 104 exceeds the ear movement rate threshold of 40 ear movements per minute. For example, if 5 different cows 104 have 5 right ears with a movement rate of 50 ear movements per minute, exceeding the 40 ear movement rate threshold, then the number of ear movement patterns exceeding the threshold is determined to be 5.

[0148] After determining the number of ear movement patterns exceeding the ear movement rate threshold (5), the system 200 can determine whether the percentage of ear movement patterns exceeding the ear movement rate threshold from the 9 cows 104 is higher than a disturbance threshold of 30% (as an example). Since this percentage is higher than the threshold in this example, i.e. 55.55% (5 (cows) / 9 (total number of cows)). (100 = 55.55%), which is higher than the harassment threshold, so system 200 sends an instruction that stable fly traps should be installed throughout the controlled livestock shed 102 area.

[0149] It is worth noting that the reference in the example above is intended to handle combinations of all types of actions (such as tapping the ear, flicking the ear, twisting the ear, etc.), but in other cases, only a single type of action or a subgroup of selected motion types can be considered. In these cases, alternatively or additionally using an accelerometer (e.g., a microelectromechanical system (MEMS) 3D accelerometer or any other type of 3D accelerometer), the system can utilize components such as gyroscopes and / or methods such as image processing to achieve ear motion type recognition.

[0150] It should be further pointed out that any comparison of ear movement rate with threshold is merely an example, and other types of rules may exist, such as pattern-based rules (e.g., the incidence of various types of ear movements, trends in ear movement rate, etc.).

[0151] It should also be noted that, in some cases, in addition to indicating the need for action to reduce the number of flying insects in a given area, or as an alternative, system 200 may also indicate the level of disturbance caused by the flying insect population. For example, an indication may be provided indicating whether there is low-level, moderate-level, or high-level disturbance caused by flying insects to animal populations. As an alternative, a numerical indication may be provided indicating the level of disturbance on a scale (e.g., 1-100). As another alternative, raw data may be provided (e.g., how many animals exhibit ear movement patterns exceeding a threshold, optionally indicating which specific animals, etc.).

[0152] Based on certain examples of the subject matter of this disclosure, system 200 may associate a disturbance level (determined as described above) with one or more other parameters associated with the animal, such as the animal's milk production, feed intake, health, welfare (or components thereof, as further described below), etc. In some cases, system 200 may use this association to optionally dynamically (e.g., periodically) set the rules used at box 304 and / or the action requirement rules at box 308. It should be noted that different animal populations may have different disturbance tolerances in some cases; therefore, the ability to associate a disturbance level with the other parameters described herein may also determine population-specific rules for the disturbance level.

[0153] As previously mentioned, in certain circumstances, the assessment of the previously disclosed harassment levels can also be utilized by a welfare determination system, which will be described in detail later, to determine the welfare of multiple animal populations (104). Welfare can be determined by calculating a welfare score, as described below, which may be influenced by information obtained during the assessment of harassment levels, as described below.

[0154] Figure 6 This is a schematic diagram of the components of an animal population welfare score according to the subject matter of this disclosure.

[0155] Before proceeding to describe the diagram, it should be noted that the terms emotion and well-being are used interchangeably in this text for the positive or negative effects of the environment on an animal population or its parts and / or for indications of the mental and / or emotional state of an animal population or its parts.

[0156] Turning to the diagram, based on the illustration shown, a welfare score for an animal population (or a portion thereof) can be determined based on at least one of the following welfare key performance indicators (KPIs): health score 420, emotional / well-being score 430, and natural life score 440. It is worth noting that welfare KPIs may include additional or alternative elements to help determine the welfare score, such as an assessment of the level of fly harassment, as well as... Figure 3 and Figure 5 Related description. When using harassment level to determine welfare score, the score may be negatively correlated with the harassment level; that is, the higher the harassment level, the lower the welfare score, and vice versa.

[0157] The calculation of the health score (420), emotional / well-being score (430), and natural life score (440) is based on data associated with members of the animal population. The data used to calculate the welfare KPIs may be descriptive data (e.g., member's age, member's sex, member's treatment history, genetic information associated with the member, etc.) and / or monitoring data (e.g., parameters of animal population members monitored over time using one or more monitoring devices, at least some of which may be selectively attached to members), and / or data from other resources, as further detailed herein.

[0158] Monitoring data relating to each member of an animal population may include one or more of the following: location information (indicating the member’s geographic location), body temperature, breathing type, breathing level, rumination time, movement type, movement time, feeding time, social time, elimination behavior, internal rumen environment parameters (e.g., monitored using rumen pellets), etc.

[0159] Monitoring data can be obtained from sensors within the monitoring device, such as: one or more accelerometers, temperature sensors, location sensors (e.g., a Global Positioning System (GPS) receiver, included in the monitoring device attached to a member), thermal sensors, pedometers, animal identification components (e.g., identification (ID) tags), heart rate sensors, biosensors, or any other sensors capable of monitoring one or more parameters of a member of an animal population.

[0160] It is important to note that in some cases, at least some monitoring data can be measured over time. For example, rumination time, activity time, feeding time, and socialization time can all be the duration of the corresponding activity from start to finish. For instance, if a member of an animal population begins feeding at 10:00 AM and ends feeding at 10:30 AM, the feeding time is 30 minutes. It is also important to note that in some cases, at least some monitoring data can be measured periodically, almost continuously, or continuously, or in some combination (some data are collected periodically, while others are collected continuously or almost continuously). For example, body temperature, location, heart rate, etc., can be measured periodically (e.g., every minute, every 10 minutes, etc.) or continuously.

[0161] It should be noted that whenever continuous, nearly continuous, real-time or close to real-time is mentioned, the time interval for obtaining the measurement can be milliseconds, seconds, minutes, hours or days. It should also be noted that, compared to current technical solutions using human auditors, even a time constant of days cannot be maintained, let alone the time constants of hours, minutes, seconds or less envisioned under the subject matter of this disclosure.

[0162] It should be further noted that in some cases, only a portion of the data used to calculate the welfare score or its components is measured periodically (e.g., every minute, every 10 minutes, etc.), or continuously or nearly continuously. However, since each such newly acquired measurement can potentially affect the welfare score and / or its components, the welfare score and / or its components can be recalculated whenever a new measurement is obtained. This keeps the welfare score and / or its components updated in a similar periodic, or continuous or nearly continuous, manner.

[0163] In some cases, by analyzing optical information, such as images and / or videos that include at least a portion of the member, at least some data related to the member can be extracted. Optical analysis can be used to determine the member's external impression, to assess the relationship between the member and their caregiver, and even to determine the member's position relative to known landmarks in the images / videos.

[0164] Monitoring data can be used for objective and general welfare assessments, and even if it cannot replace subjective human audits, it can at least supplement them. Furthermore, monitoring data can be used to achieve automated animal welfare assessments in real-time or near real-time, based on collected monitoring data.

[0165] Monitoring devices collect at least some data related to an animal population by monitoring parameters of members over time. In some cases, at least part of the monitoring device may be attached to a given member (e.g., in the form of a monitoring tag, monitoring collar, etc.) to collect monitoring data of the given member (continuously, or nearly continuously, or periodically, or in some combination of ways (some of which is collected periodically, and some of which is collected continuously or nearly continuously).

[0166] Additionally or alternatively, at least some of the monitoring equipment may not be attached to a specific member, but rather placed in locations that allow simultaneous or sequential monitoring of one or more members. For example, at least some of the monitoring equipment may be manual monitoring equipment (operated by a human operator), fixed monitoring equipment (e.g., monitoring when a member passes through a gate), autonomously driven monitoring equipment (e.g., carried by an autonomous drone), monitoring equipment integrated into a mobile device or computer, etc.

[0167] It should be noted that at least a portion of the data collected by the monitoring equipment is associated with the corresponding member from which the data was collected. For this purpose, in some cases, at least some members of the animal population, and in other cases, all members of the animal population, may have identification (ID) means (such as, but not limited to, ID tags such as EID tags or visual ID tags) attached to or associated with them.

[0168] ID means can be a tag that uniquely identifies a member of an animal population to which it is attached. In some cases, ID means are part of a monitoring device attached to a member. Alternatively, however, ID means can be another type of device used to identify members using known and / or proprietary methods and / or technologies, including electronic identification, visual identification, camera-based identification, facial or body part identification, barcodes, identification tags, etc.

[0169] As previously mentioned, various systems / devices / methods / techniques can be used to identify each member of an animal population, including ID tags, identification markers (e.g., numbers, letters, symbols, or any combination thereof), readable barcodes, facial (or other body part) recognition, etc. When read by an appropriate reading device (e.g., an ID tag reader), the ID device is able to determine at least one unique animal identifier, thereby uniquely identifying the member.

[0170] It is important to note that in some cases, one or more identification methods can be passive identification methods, such as passive tagging. For example, a tag can be an identifier printed on the animal to be identified, a sticker of a visual identifier attached to the animal, or a mark drawn on the animal. In this case, the tag is visually identifiable (e.g., a barcode), and the corresponding tag reading device can be, for example, a camera capable of acquiring an image in the spectrum of the visual tag.

[0171] Monitoring data collected by monitoring equipment can be stored in records within a data repository. Each record can be associated with a corresponding member of the animal population and can contain different types of data, including descriptive data, monitoring data, combinations of descriptive and monitored data, and optional other types of data.

[0172] For example, the record may include (a) descriptive data that is not necessarily collected by the monitoring device (e.g., the age of the member, the sex of the member, the treatment history of the member, the genetic information associated with the member, etc.), and (b) monitoring data (e.g., the body temperature of the member, the exercise time of the member, the feeding time of each member, the social time of the member, the respiratory level of the member, the rumination time of the member, etc.).

[0173] As described above, such monitoring data can be monitored continuously, nearly continuously, periodically, or in some combination using monitoring equipment (some of which is collected periodically, and some is collected continuously or nearly continuously). Therefore, when monitoring data is monitored continuously, nearly continuously, or periodically, or in some combination (where some data is collected periodically, and some is collected continuously or nearly continuously), the corresponding records can be updated accordingly (e.g., by updating existing records associated with the corresponding member, or by adding additional records indicating newly acquired values). In some cases, updates to at least some parameters form records associated with the corresponding member, which can be achieved by averaging the values ​​of the corresponding parameters over time or by performing any mathematical and / or statistical calculations on them.

[0174] Now draw attention to the calculation of a health score 420 for a given member of an animal population, which can form part of the welfare score calculation, as illustrated herein. The health score 420 for a given member of an animal population is determined based on basic health and functional criteria for that given member, specifically including freedom from disease and injury. In some embodiments, the health score 420 may be calculated at least in part based on identifying symptoms that may be associated with health-related problems, such as disease, injury, etc. In some cases, the health score 420 is determined based on finding a statistically significant correlation between the identified symptoms and the disease or injury. In some cases, the strength of this correlation between symptoms indicating disease and / or injury is also used to determine the health score 420.

[0175] These symptoms can be identified by monitoring rumination and / or energy levels in individual members, groups of members, or the entire animal population. Additionally or alternatively, symptoms can be identified, at least in part, by monitoring visual indicators associated with health problems and / or monitoring respiratory patterns in individual members, groups of members, or the entire animal population.

[0176] Energy levels can be measured, for example, by detecting the movement of a given member over a given time period (e.g., a day) and inferring the amount of energy the given member needs to perform those movements (optionally based on specific characteristics of the given animal). The movement can be monitored, for example, by monitoring acceleration signals obtained from an accelerometer within a monitoring device attached to the given member.

[0177] Rumination can be measured, for example, by detecting rumination activity in a given member over a given time period (e.g., a day). This can be achieved by analyzing an obtained acceleration signal, such as an acceleration signal obtained from an accelerometer within a monitoring device attached to the given member, and detecting a signal associated with a reference signal known to be associated with rumination activity.

[0178] For example, a respiratory pattern can be determined by detecting various respiratory patterns in a given member over a given time period (e.g., a day). This can be achieved by analyzing, for example, acceleration signals obtained from an accelerometer within a monitoring device attached to the given member and detecting signals associated with reference signals known to be associated with a particular respiratory pattern. This can determine whether the given animal is exhibiting suspicious behavior (e.g., whether it is breathing more heavily than usual and / or exceeding a predetermined threshold, etc.).

[0179] Image analysis of images and / or videos of animal population members can identify visual indicators associated with health problems. For example, image and / or video analysis can be used to identify scratches or irritations related to symptoms of disease.

[0180] It should be noted that these are merely examples of symptoms that may be associated with health-related problems, and additional and / or alternative data may be used to identify the symptoms indicated above, or other symptoms that may be associated with health-related problems.

[0181] The health score 420 of an animal population can be used to calculate a health index that indicates the overall health level of the population. In some cases, the health index can be used to identify the level of morbidity in an animal population. For example, a health index showing that the health score 420 of animals in the population exceeding a threshold (e.g., about 5%) is below the threshold may indicate an developing health problem in the population. A health index showing that the health score 420 of animals in the population exceeding a second threshold (e.g., about 10%) is below the threshold may serve as an indicator of a widespread health problem. A health index showing that the health score 420 of animals in the population exceeding a third threshold (e.g., about 20%) is below the threshold may indicate a pandemic.

[0182] It is worth noting that analysis of the health score 420 can identify a given animal in the population that has a certain health problem (e.g., disease, lameness, estrus, etc.). In some cases, analysis of the health index (generated based on the health scores 420 of animal population members) can identify at the population level whether the overall health level of the animal population is above an acceptable predetermined health threshold.

[0183] Now draw attention to the calculation of the affective / happiness score 430 for a given member of an animal population. The calculation of the affective / happiness score 430 for a given member of an animal population can be based on the given member's state, such as: distress, sadness, depression, happiness, etc. The affective / happiness score 430 can reflect how a given animal is affected by its environment and experiences (whether it is positively or negatively affected by its environment). In some cases, the calculation of the affective / happiness score 430 for a given member of an animal population is based on the degree of distress of the given animal; therefore, the more distress identified, the lower its affective / happiness score 430.

[0184] For example, the state or distress level of a given member can be determined based on variations in its breathing patterns, rumination activity, feeding activity, or some combination thereof. For instance, measuring the variability of rumination and feeding times, as well as the level of severe breathing among members of an animal population, optionally once daily, can provide a basis for the emotional / wellness score of 430.

[0185] As a specific example of a measure that can determine the affective / wellness score 430, the consistency of rumination variability (RV) in an animal population over a ten-day period is used. This analysis shows that reduced ration digestibility leads to an increased risk of metabolic problems and reduced consistency, and that optimal intake will be reflected by consistent, low levels of RV.

[0186] Another measure that can determine the affective / wellness score 430 is heavy breathing. Analysis of respiratory levels among members of an animal group indicates that heavy breathing indicates heat stress (discomfort). Notably, when analyzing heavy breathing behavior at the group level, increased heavy breathing implies overall heat stress in the animal population.

[0187] A non-restrictive example of a situation that affects the sentiment / happiness score 430 of a ruminant population includes: increased competition among a given group of members in a ruminant population (e.g., increased competition for food due to a lack of bedding space), which would lead to greater variability in rumination and feeding times among members of a given group and result in a lower sentiment / happiness score 430 for that ruminant population group.

[0188] Additional examples of environmental factors that influence the emotional / wellness score of 430 include: the condition of bedding for animal population members, lighting conditions, the number of square feet per square meter of animal population members (to avoid over-storage of animals), the availability of water and feed (e.g., queuing at water troughs indicates that not all animal population members are meeting their needs), the results of a milk spectrometer for animal population members (for dairy animals), image analysis of feed and feeding areas, and feed that is only eaten by the more dominant members of the animal population, which may indicate problems with feed levels and / or social issues among animal population members.

[0189] In some cases, problems can be inferred from the affective / wellness score 430. For example, if an increasing inconsistency or difference is found among members of an animal population in the affective / wellness score 430 based on animal housing conditions, it can be concluded that there are problems with the condition of bedding supplies (which is part of housing conditions) for these members.

[0190] Moving to the Natural Life Score of 440, its calculation is based on an analysis of behaviors that demonstrate a given animal's ability to lead a reasonably natural life by performing natural behaviors and acquiring natural elements in its environment. These specific behaviors can include feeding activities, grazing activities, activity levels (e.g., the amount and intensity of movement of a given animal), walking activities, etc. For example, these behaviors can be used to verify whether an animal has sufficient time and opportunity to feed, whether it exhibits a normal high level of activity, whether it is not forced to walk too much, or whether it is restricted to an appropriate amount of movement / walking. A non-restrictive example related to the natural life behavior of dairy cows is that on a dairy farm, calves may be periodically separated from their mothers on the first day after birth and fed milk from buckets, typically twice a day. Due to the infrequent feedings, the total milk intake is limited, so the calf does not ingest too much milk at once. In contrast, under natural conditions, dairy cows are kept in relatively close proximity to their calves for the first two weeks, and the calves are fed multiple times a day in small meals. Adjusting the feeding system to more closely resemble the animal's natural behavior (close to the mother and fed frequently, but in relatively small amounts) will result in a higher Natural Life Score of 440 for the calf. Additional examples related to natural living behaviors include the time grazing animals spend searching for food in pastures, which can indicate the need for a redistribution of fencing.

[0191] As further detailed herein, a single welfare KPI (e.g., one of the health score 420, emotional / well-being score 430, or natural life score 440) or any combination of welfare KPIs can be used to determine the welfare of an animal population, a subgroup of a population, or an individual member of an animal population, and optionally recommend actions to be taken for members of an animal population. These actions may include treating members, moving members, examining members, separating members from the rest of the animal population, altering the feeding conditions of at least some members, altering the drinking conditions of at least some members, altering the bedding conditions of at least some members, etc.

[0192] Using the teachings of this paper, the welfare of animal population members can be automatically determined, welfare scores can be calculated without the presence of a human auditor, and over time intervals impossible for a human operator (optionally even in real-time or near real-time). Welfare KPI scores can also take into account large amounts of data, including historical trends, whereas human audits are limited by their ability to gather and derive insights from large datasets. Furthermore, since the determination of welfare KPI scores is not done manually, it is not influenced by human bias. Personal impressions and audit proficiency have no impact on the automatic determination of welfare KPI scores according to the teachings of this paper. It is worth noting that in some cases, audits are conducted on a six-month basis, or even over longer time intervals; clearly, in such cases, potential problems may not have been noticed or assessed at all within six months.

[0193] The automated determination of animal welfare disclosed herein can also be used to improve the welfare of a given animal or group of animals in a real-time or near-real-time manner. For example, the systems and methods disclosed herein can make it possible to identify declining animal conditions in individual animals or groups of animals within an animal population. Furthermore, the systems and methods disclosed herein can provide animal caregivers and / or regulatory bodies (such as government organizations) with information that can be used to take real-time or near-real-time actions to improve animal welfare, such as by providing access to veterinary care or treatment for health problems, such as infectious diseases, ectoparasites, and / or reproductive problems.

[0194] Furthermore, based on the systems and methods disclosed herein, benchmarks can be established for one or more locations or facilities of an animal population. Over time, these benchmarks can be used as a reference to automatically determine the compliance of a facility or location with expected levels of animal welfare. These benchmarks can be measured and adjusted, and optionally continuously.

[0195] Furthermore, the systems and methods disclosed herein can empirically determine welfare scores using objectively, automatically, and optionally continuously collected information, thereby enhancing or replacing traditional manual auditing methods for animal welfare. Thus, the systems and methods disclosed herein can provide an unbiased, fraud-free, and universal model for assessing animal welfare.

[0196] The animal welfare disclosed herein can be used to set standards (optionally industry-wide standards) and benchmarks across different animal populations and / or members of one or more animal populations, and optionally to provide real-time administrative or veterinary support to mitigate and reduce emerging risks. The animal welfare disclosed herein can also be used by insurers and / or financial providers to assess risks in insurance and / or financing related to animal populations.

[0197] For example, the animal welfare (including animal welfare KPI scores) disclosed herein can be used to set minimum animal welfare standards for various types of animal caregivers, whether institutional (such as farms that raise cattle, pigs, horses, or any other type of animal for slaughter, milk production, or any other purpose) or private animal owners (such as pet owners). Having such standards enables regulation (allowing governments or other regulatory bodies to ensure animal welfare meets required standards and to quickly identify any violations), value and / or risk assessment (allowing insurance companies, lenders, or other types of financial institutions, industry associations, customers, or any other entity interested in the valuation and / or risk assessment of animals or their products, such as milk, meat, etc.), and more. For example, the increased objectivity, consistency, frequency, and reliability of the welfare systems and methods described herein allow for more accurate and precise comparisons between different farms / animal facilities, which is one advantage enabling entities to generate effective standards setting, risk assessment regulation, and more.

[0198] In some cases, animal welfare scores can also serve as a measure for providing animal welfare certification, similar to the Marine Stewardship Council (MSC) certification used in fisheries.

[0199] It is noteworthy that the system disclosed herein possesses a powerful and significant capability to monitor animal welfare of animal populations in a continuous (or nearly continuous) reliable, consistent, and objective manner (utilizing animal welfare KPI scores). The monitoring described herein enables all stakeholders—animal caregivers, regulatory bodies, financial institutions, industry associations, dairy processors, meat processors, retail chains, end customers, or any other entity potentially interested in animal welfare—to receive relevant information to make decisions in real-time or near real-time based on reliable, consistent, and objective information that is continuously or nearly continuously updated (e.g., in milliseconds, seconds, minutes, hours, or days)—as opposed to existing technologies lacking such information. Several non-limiting examples of using animal welfare according to the subject matter of this disclosure include: financial institutions can assess risk based on relevant information indicating animal welfare when making decisions; regulatory bodies can act upon discovering violations rather than in retrospect; retail chains, dairy processors, meat processors, end customers, or any other consumers of products from that animal population can access animal welfare information about the animal population from which the product originates; veterinarians can proactively act based on the need to identify animal welfare; and dairy and / or meat producers can compare farms based on animal welfare so they can make informed purchasing decisions.

[0200] In some cases, welfare scores can also be determined based on sustainability indices and / or greenhouse gas indices. In such cases, sensors that collect relevant information (e.g., water and / or energy resource use, waste generation, freshwater use, air gases, etc.) can be used to obtain the information upon which these indices are based.

[0201] It is important to note that the welfare scores determined according to the teachings of this article are based on (at least in part) direct analysis of animal behavior and physiological signals, rather than on artificial interpretation.

[0202] exist Figure 9 The diagram illustrates a non-restrictive example of determining animal population welfare KPI scores, where assessments of animal population freedom are achieved through the continuous collection of surveillance and descriptive data associated with the animal population (as detailed in this paper). Welfare KPI scores are determined based on the collected data.

[0203] It is important to note that Figure 9 The examples of monitoring data types provided are non-limiting, and the types of monitoring data may differ for different types of animal populations. For example, for companion animals, monitoring data may include play behavior, social activities with other animals, etc. For livestock, monitoring data may include activity levels, feeding times, walking time, rumination time, heavy breathing, health-related parameters (such as body temperature), living conditions, carrying capacity, feeding time behavior, play behavior, socialization with other animals, fly infestation (e.g., determined by ear movement patterns), etc.

[0204] It should be further noted that the welfare of companion animals is observed more at the individual animal level, while the welfare of livestock is observed more at the population level.

[0205] In some cases, animal populations may reside in one or more facilities (e.g., farms, enclosures, etc.). In such cases, welfare scores can be calculated at the facility level by analyzing welfare KPI scores associated with members of the animal population within that facility. For example, different farms may have their own welfare scores for comparison between farms.

[0206] Furthermore, welfare KPI scores can be used to monitor the well-being of animal population members, thus providing human caregivers with tools for long-term monitoring and more economical population management. The welfare KPI scores described in this article offer numerous benefits to animals and animal caregivers. For example, animal management can use welfare KPI scores internally, such as on farms, to achieve hierarchical balance by managing and eliminating feeding and social stresses from individual animals or groups of animals by moving specific members or groups between enclosures within the farm. As discussed in this article, welfare KPI scores can also provide reliable, objective, consistent, and continuous information for decision-making by all stakeholders—animal caregivers, regulatory bodies, financial institutions, industry associations, milk processors, meat processors, retail chains, end customers, or any other entity that may be interested in animal welfare.

[0207] As a non-restrictive example of utilizing welfare KPI scores, these scores can help animal caregivers maintain farm sustainability by identifying specific operational aspects requiring attention, such as bedding, feeding, milking, processing, or any other part of the farm. In this non-restrictive example, animal caregivers can monitor overall morbidity in the animal population, observing members collapsing due to being pushed beyond their metabolic capacity or mismanagement, which can impact productivity and prevent them from reaching optimal production levels. Animal caregivers can also examine housing conditions, identify historical trends within the animal population, and create benchmarks for continuous measurement and adjustment of their farm. These benchmarks can be any combination of animal welfare scores and / or health scores 420, emotional / well-being scores 430, or natural life scores 440, and, as described herein, any one benchmark, or any combination of two or more benchmarks, can be updated manually or automatically.

[0208] Welfare KPIs can also be used by regulatory entities or sourcing companies to monitor regulated or supplier farms, develop procedures with the animal care providers they regulate or source, manage public and customer feedback, and ensure they maintain transparency regarding brand names and brand values.

[0209] Furthermore, welfare KPI scores can be used to improve the health of a given member or the overall health of the animal population by identifying conditions and recommending treatments for veterinary problems, even before external signs of disease are detected. Because some animals do not exhibit disease symptoms, welfare KPIs can express changes in the animal population that indicate health problems in certain members. This allows for earlier and more effective treatment of health problems—for example, saving on the costs of more invasive medications and treatments; treatment can be initiated earlier due to earlier warnings compared to other methods, which in turn reduces the number of sick animals, the length of time the animal population is affected by any health problem, and so on. Early identification of problems can also prevent changes in members' daily routines that could lead to discomfort among members of the animal population. By analyzing welfare KPI scores over a specific time period, daily routines (e.g., feeding times, activity cycles, rumination, and social behavior schedules) of individual members and / or groups of members and / or the entire animal population can be identified. Once consistent daily routines are identified, changes in welfare KPI scores can be used as early warning signals of changes in consistent daily routines before they collapse.

[0210] For example, if a given group of members in an animal population has a health score 420 below a certain threshold (e.g., a health score 420 indicates that the percentage of diseased members in the animal population is greater than or equal to 10% of the population), and a natural life score 440 below a second threshold (e.g., the percentage of recorded feed availability and / or daytime walking distance and / or high activity levels that are above or below historical levels), this measurement can indicate infectious disease problems within the population (e.g., respiratory diseases, gastrointestinal diseases, or reproductive diseases).

[0211] These infectious diseases in cattle can include, for example, one or more of the following: respiratory diseases, where the pathogens involved are bacteria, including Mansonia solani, Pasteurella multocida, Mycoplasma bovis, and Histolytica silicosis; and viruses, including bovine coronavirus (BCV), parainfluenza-3 (PI3) virus, bovine respiratory syncytial virus (BRSV), bovine viral diarrhea virus (BVDV), and bovine herpesvirus 1 (BHV1), the latter causing infectious bovine rhinotracheitis (IBR). Other diseases, where the additional immune-active components are based on or derived from microorganisms pathogenic to ruminants. Examples of these microorganisms include, for cattle (bovine animals are taurine cattle, zebu cattle, buffalo, bison, yaks, or European bison): Neosporidia, Diflagellates, Cryptosporidia, Bovine hornworms, bovine rotavirus, bovine viral diarrhea virus, bovine coronavirus, bovine infectious rhinotracheitis virus (bovine herpesvirus type 1), bovine paraparainfluenza virus, bovine respiratory syncytial virus, rabies virus, bluetongue virus, Escherichia coli, Salmonella, Staphylococcus, Mycobacterium, Pyogenic Eomycetes, Brucella, Clostridium, Pasteurella, Mansell's disease, Haemophilus, Leptospira, Fusobacterium, Bovine Mycobacterium, and Pyogenic Eomycetes. For sheep and goats (goats, sheep): Toxoplasma gondii, peste des petits ruminants virus, bluetongue virus, Schmalenburg virus, mycobacteria, Brucella, Clostridium, Kose, Escherichia coli, Chlamydia, Clostridium, Pasteurella, and Manskovitis. For deer: Epidemic hemorrhagic disease virus, bluetongue virus, papillomavirus, Borrelia burgdorferi, Mycobacterium bovis, and Pyogenic E. pyogenic diseases such as: mastitis, Staphylococcus and Streptococcus, genital tract infections, Pyogenic E. pyogenic E. pyogenic, E. coli and Clostridium, and Clostridium necrophorum.

[0212] Infectious diseases in pigs can include, for example, one or more enteric pathogens, including: Salmonella, especially Salmonella Typhimurium and Salmonella Choleraesuis; Lawsonia intracellularis; astroviruses; rotaviruses; transmissible gastroenteritis viruses; short spirochetes, especially *S. spp.* and *S. spp.*; Clostridium, especially *Clostridium difficile*, *Clostridium perfringens* types A, B, and C, *Clostridium neoformans*, *Clostridium septicemia*, and *Clostridium tetanus*; porcine enteric microRNA viruses; porcine enteric-coated caliciviruses; respiratory pathogens, including: *Actinomyces pleuropneumoniae*; *Bordetella* spp. bronchial septicemia; *Erysipelothrix rhusiopathiae*; and *Haemophilus parasuis*, especially types 1 and 7. 14 subtypes; Pasteurella multocida, especially Pseudomonas multocida; Mycoplasma, especially Mycoplasma pneumoniae and Mycoplasma hyopneumoniae; swine influenza virus; PRRS virus; PED virus; porcine circovirus, especially PCV2 and PCV3; porcine parvovirus; pseudorabies virus; porcine mycoplasma virus; mycobacteria, especially Mycobacterium avium, Mycobacterium intracellulare, and Mycobacterium bovis; swine respiratory coronavirus; Mycobacterium pyogenes; swine adenovirus; classical swine fever virus; swine cytomegalovirus; African swine fever virus; or other pathogens, including Escherichia coli, streptococci, especially Streptococcus suis, Streptococcus suis, and Streptococcus hypogalactiae, preferably subcocci. Horse-like bacteria; *Brucella suis*, especially variants 1, 2, and 3; *Leptospira*, especially *Leptospira australis*, *Leptospira canis*, *Leptospira typhus*, *Leptospira pomona*, *Leptospira icterus*, *Leptospira tortis*, *Leptospira tarasovie*, *Leptospira harjoi*, *Leptospira seroilae*; encephalomyelitis virus; hemagglutinating encephalomyelitis virus; Japanese encephalitis virus; West Nile virus; reovirus; rubella virus; Menanger virus; Nipah virus; vesicular stomatitis virus; swine vesicular herpesvirus; swine pox virus; swine herpesvirus; and *Staphylococcus*.

[0213] Then action can be taken, for example, as detailed further in this article, among other things, referring to Figure 8 To address this situation, actions can be recommended based on the overall welfare score and / or health score (420) of the animals in the population, and / or emotional / well-being score (430) and / or natural score (440).

[0214] Having described the components of the welfare score, now please note Figure 7 . Figure 7 This is a block diagram, schematically illustrating an example of a welfare determination system for determining the welfare of an animal population in accordance with the subject matter of this disclosure.

[0215] The welfare determination system 500 includes a network interface 520 (e.g., a network interface card, WiFi client, LiFi client, 3G / 4G client, or any other component) enabling the welfare determination system 500 to communicate with external systems via a network to obtain monitoring parameters and / or descriptive data associated with animal population members. The external system may be a monitoring device configured to monitor member parameters, or any other intermediate system that obtains information about members from a monitoring device (e.g., a computerized system managing at least a portion of the animal population members).

[0216] The welfare determination system 500 also includes, or is associated with, a data repository 510 (e.g., a database, storage system, including read-only memory (ROM), random access memory (RAM), or any other type of memory), configured to store data, optionally including, among other things, animal information records. Each information record is associated with a different member of the animal population and may include descriptive data of that member (e.g., age of the different member, sex of the different member, treatment history of the different member, genetic information associated with the different member, etc.) and monitoring data and / or monitoring parameters (e.g., health parameters, behavioral parameters, emotional / welling parameters, etc.) of the different members monitored over time by monitoring devices. The data repository 510 may be further configured to retrieve and / or update and / or delete the stored data. It should be noted that, in some cases, the data repository 510 may be distributed, and the welfare determination system 500 may access the information stored therein, for example, via a wired or wireless network (using its network interface 520) to which the welfare determination system 500 can connect.

[0217] The welfare determination system 500 also includes a processing circuitry system 530. The processing circuitry system 530 may be one or more processing units (e.g., a central processing unit), a microprocessor, a microcontroller (e.g., a microcontroller unit (MCU)), or any other computing device or module, including multiple and / or parallel and / or distributed processing units adapted to independently or collaboratively process data to control associated welfare determination system 500 resources and enable operations associated with welfare determination system 500 resources.

[0218] The processing circuit system 530 may include a welfare KPI determination module 540. The welfare KPI determination module 540 can be configured to determine the welfare KPIs of an animal population (or groups within that population), as further detailed herein, among other things, refer to [reference needed]. Figure 8 .

[0219] Turning Figure 8 The diagram illustrates a flowchart of an example of a series of operations performed to determine the welfare of an animal population, in accordance with the subject matter of this disclosure.

[0220] According to the subject matter of this disclosure, the benefits determination system 500 can be configured to perform a benefits KPI determination process 600 (optionally in real-time or near real-time), for example, using a benefits KPI determination module 540.

[0221] As described in this article, refer to Figure 6 Welfare KPIs are determined based on data associated with members of the animal population. This data can come from various sources, both internal and / or external to the system. For example, some data can be descriptive (e.g., age of different members, sex of different members, treatment history of different members, genetic information associated with different members, etc.), while other data can be monitoring data, such as animal parameters (e.g., temperature, activity time, feeding time, social behavior time, respiratory level, rumination time, etc.), which are monitored over time using one or more monitoring devices.

[0222] Data collected from monitoring devices is stored in records within a data repository. Each record is associated with a corresponding member of the animal population and contains descriptive data obtained from the monitoring devices (e.g., age, sex, treatment history, and associated genetic information of the corresponding member) and monitoring data, such as animal parameters (e.g., temperature, activity time, feeding time, social behavior time, respiratory level, rumination time, etc.). Monitoring data can be collected continuously, almost continuously, periodically, or in a combination thereof (some data are collected periodically, and some are collected continuously or almost continuously).

[0223] The welfare determination system 500 is configured to obtain at least a subset of the records associated with the first member group of the animal population (box 610). In some cases, all records of the animal population are obtained by the welfare determination system 500. In other cases, the first member group may consist of subpopulations of the animal population, selected based on one or more criteria (e.g., sex, age, location, treatment history, etc.). For example, the animal population may be dairy cows on a given farm, and the subpopulations may be all dairy cows that received a given treatment last year. It is important to note that the animal population may be located at one or more geographic sites and / or specific locations within these sites (e.g., fences, pastures, treatment areas, etc.).

[0224] The animals in this population can be, for example, ruminants, livestock, pigs, companion animals, or any other type of non-human animal.

[0225] After obtaining at least a subset of the records, the welfare determination system 500 is further configured to, based on the subset of records, calculate at least one of the following for at least some members of the first member group: (a) a health score 420, indicating the health status of the corresponding member; (b) a natural life score 440, indicating that the behavior pattern of the corresponding member conforms to the expected natural behavior pattern; or (c) an affective / happiness score 430, indicating that the affective / happiness measurement of the corresponding member conforms to the expected affective / happiness measurement (box 620).

[0226] For calculating the Health Score 420, parameters that can be used may include, for example, a given member's energy level and / or a given member's rumination time. Rumination, energy level, heavy breathing, chewing, core temperature, image analysis identifying indicators of health problems, and optional additional and / or alternative indicators from the member can determine whether the member has a health impairment (e.g., disease and / or injury). The Health Score 420 can be calculated based on the absolute values ​​of these parameters, the changes of these monitored parameters over time, the relative values ​​of these parameters (such as percentages), or a combination thereof.

[0227] For example, a health score for a given member can be determined based on the consistency of at least some parameter values ​​over time (e.g., their consistency over a rolling average over a given period, such as a 10-day rolling average). In some cases, the consistency of values ​​can be measured against a reference parameter, such as a reference parameter measured from a reference animal. Actual members of an animal population (other than the given member) or members from another population can serve as reference animals. Historical data can also be used as a reference. In some cases, a reference can be a theoretical reference on how a hypothetical reference animal should behave.

[0228] For the calculation of the Emotional / Happiness Score 430, parameters that can be used for calculation may include, for example, one or more of the following: (a) respiratory activity, including the respiratory level of a given member (e.g., the respiratory level suggests a panting animal or heavy breathing); (b) rumination activity, including the percentage of time a given member ruminates within a given time period, e.g., the time a given member ruminates within a given time period (e.g., a day); (c) feeding activity, including the percentage of time a given member feeds within a specific time period, e.g., the time a given member feeds within a given time period (e.g., a day); or (d) the external impression of a given member (e.g., images and / or videos using automated image analysis, which include at least a portion of the given member).

[0229] The calculation of the sentiment / happiness score 430 can be based on the values ​​of these parameters and / or the changes in the values ​​of these monitored parameters over time. For example, the sentiment / happiness score 430 of a given member can be determined based on the consistency of at least some parameter values ​​over time (e.g., their consistency over a rolling average over a given time period, such as a 10-day rolling average). In some cases, the consistency of values ​​can be measured against a reference parameter, such as a reference parameter measured from a reference animal. Actual members of an animal population (other than the given member) or members from another population can serve as reference animals. Historical data can also serve as a reference. In some cases, the reference can be a theoretical reference on how the hypothetical reference animal should behave.

[0230] For the calculation of the natural life score 440, parameters that can be used for calculation may include, for example, one or more of the following: (a) locomotor activity, including the percentage of time a given member spends locomotor activity over a given period (e.g., a given member is active for 20% of the time in a given day, or a given animal has a certain amount of high-activity locomotor activity over a given period), (b) feeding activity, including the percentage of time a given member spends feeding over a given period (e.g., a given member spends 25% of the time feeding over a given day), (c) social activity, including the percentage of time a given member spends socializing over a given period (e.g., the time a given member spends interacting with another animal) (e.g., a given member spends 10% of the time engaging in social interaction over a given day), or (d) chronological activity, the variation of a given member’s chronological schedule relative to a historical chronological schedule (e.g., if feeding four times a day is the norm, but feeding less or more than four times a day in a given day).

[0231] The calculation of the natural life score 440 can be based on the values ​​of these parameters and / or the changes in the values ​​of these monitored parameters over time. For example, the natural life score 440 of a given member can be determined based on the consistency of at least some parameter values ​​over time (e.g., the consistency of the percentage of daytime activity time of a rolling average over a given time period, such as a 10-day rolling average). In some cases, the consistency of values ​​can be measured against reference parameters, such as those measured from reference animals. Actual members of an animal population (other than the given member) or members from another population can serve as reference animals. Historical data can also serve as a reference. In some cases, the reference can be a theoretical reference on how the hypothetical reference animal should behave.

[0232] It should be noted that, in some cases, the determination of the natural life score 440 and / or emotional / happiness score 430 of the corresponding members is also based on one or more environmental parameters to indicate the state of the environment.

[0233] Non-limiting examples of such environmental parameters include weather conditions in the animal's area, the animal's geographical location, and the ambient temperature around the animal, all of which can affect the calculation of the natural life score 440 and / or the affective / well-being score 430. For example, on cold days, animals are expected to stay indoors, thus reducing movement and social interaction. Therefore, system 200 will consider ambient temperature when determining the natural life score 440 and / or the affective / well-being score 430. Lower levels of movement on cold days can be assigned a lower weight, for example, relative to the weight assigned to lower levels of movement on warm days.

[0234] It should be noted that environmental parameters may include one or more general environmental parameters that are unrelated to a specific member of the animal population, and / or one or more specific member environmental parameters that are associated with a specific member of the animal population. In the latter case, the specific member's environmental parameters may be included in the record associated with that specific member of the animal population.

[0235] After calculating at least one of the health score 420, natural life score 440, or emotional / well-being score 430 for the first member group, the welfare determination system 500 calculates the welfare score of the animal population based on any one or any combination of the following: (a) the health score 420 calculated for the first member group, (b) the natural life score 440 calculated for the second member group, or (c) the emotional / well-being score 430 calculated for the third member group (box 630).

[0236] In some cases, the welfare score can be the sum of the averages of the health score (420), the natural life score (440), and the emotional / well-being score (430). In other cases, different weights can be assigned to each average score based on various considerations, such as the level of confidence of the score used to calculate the corresponding average, the variability of the score used to calculate the corresponding average, etc. In some cases, the welfare score can be normalized to a value between 0 and 100.

[0237] In some cases, the first, second, and third groups are identical, and the scores of all members in the group are used for calculation. In other cases, the welfare score is calculated by considering the natural life score 440 and / or the emotional / well-being score 430, which are calculated only for healthy members of the first group, such as those whose health scores exceed the threshold 420.

[0238] It should be noted that in some cases, the welfare score of an animal population or any of its subgroups is calculated based on variations between or within individual scores (e.g., health score 420, emotional / well-being score 430, and natural life score 440) calculated for members of the animal population or its subgroups.

[0239] For the effect of intra-individual variance on the affective / wellness score 430 of the first member group, or the variables used in its calculation, a non-restrictive example is that when variance is below one or more threshold ranges (e.g., for dairy cows, one or more of the following: rumination variability below the range of 16-20%, and / or rumination time-variability below the threshold of 20-30 minutes, and / or heavy breathing-respiratory level variability below the range of 15-20%, etc.) is considered good (and therefore this does not adversely affect the overall welfare score of the animal population), and changes in one or more threshold ranges (e.g., for dairy cows, one or more of the following: rumination variability above the range of 16-20%, and / or rumination time-variability above the threshold of 20-30 minutes, and / or heavy breathing-respiratory level variability above the range of 15-20%, etc.) will result in a decrease in the welfare score. It is worth noting that in this example, one or more threshold ranges are referenced, but this is by no means a limitation. These variations can be compared with one or more sliding scales calculated based on historical values ​​of the first member group’s sentiment / happiness score of 430 or the variables used in its calculation.

[0240] It is worth noting that all the calculations mentioned above can be performed in real-time or near real-time, for example, within a very short time interval, almost instantaneously, or within a few seconds. Alternatively, the calculations may take several minutes or longer to complete.

[0241] In some cases, a graphical user interface (GUI) can be used to present the calculated welfare score of an animal population or any subpopulation to users of system 200. Non-limiting examples of GUI screens that system 200 might use are shown below. Figure 10A and 10B As shown. The GUI can display current (optionally real-time or near real-time) and / or historical welfare KPI scores, including charts and reports based on these current and / or historical welfare KPI scores.

[0242] Check Figure 10AThe diagram illustrates a non-limiting GUI example, including: a map 810 GUI component, a list 820 GUI component, and a timeline 830 GUI component. Map 810 displays one or more facilities (e.g., farms) with animal populations monitored by welfare determination system 500. List 820 displays information in tabular form regarding facility welfare KPI scores within a given timeframe (e.g., calendar month, year, etc.). The columns of list 820 include data for each facility within the given timeframe (e.g., average welfare KPI score, average health score 420, average emotional / happiness score 430, average natural life score 440, etc.). These components are interconnected—when a user of system 500 selects one or more facilities using map 810 or list 820, the welfare KPI score, health score 420, emotional / happiness score 430, and natural life score 440 for the selected facility within the given timeframe are presented in timeline 830. Furthermore, the GUI can also display historical trends in the calculation of welfare KPI scores to the user within the timeline 830 GUI component. Users of the Welfare Calculation System 500 can use the GUI to generate representations of welfare scores calculated across different timelines and / or regions. The GUI can present data for single or multiple groups in a comparative manner. One or more groups can be associated with one or more facilities, allowing the GUI to present welfare KPI scores for specific facilities or groups of facilities. For example, the GUI can present multiple charts (within the Timeline 830 GUI component) showing the welfare KPI scores for all facilities from multiple geographic locations selected from Map 810 last year, thus providing users of the Welfare Determination System 500 with a tool to easily compare welfare KPI scores across different geographic locations.

[0243] Check Figure 10BAnother non-limiting GUI example is shown, which is a dashboard-style GUI including: a map 850 GUI component and one or more dashboard 840 GUI components. The dashboard 840 GUI components can display different colors to indicate the relative welfare KPI scores of animals at one or more locations, interactively selected by the user of system 500 from the map 850 GUI component. For example, the number of animals with welfare KPI scores above a given threshold is marked in green, the number of animals with welfare KPI scores within the given threshold is marked in yellow, and the number of animals with welfare KPI scores below the given threshold is marked in red. Additional dashboard 840 GUI elements can also use similar color coding to display information such as the health score 420, emotional / happiness score 430, and natural life score 440 of animals at the selected location. Additionally, the symbols for facilities on the map can also be color-coded in a similar way. For example, facilities with welfare KPI scores below a given threshold can be marked in red, facilities with welfare KPI scores above the given threshold can be marked in green, and facilities with welfare KPI scores within the given threshold can be marked in yellow.

[0244] After calculating the welfare score, the welfare determination system 500 can be optionally configured to recommend actions to the animal population based on the welfare score (box 640). Actions can be taken on a given member of the animal population, a given group of members of the animal population (e.g., members of the animal population located in a specific location, such as a farm), or the entire animal population.

[0245] This action could, for example, be advising animal caregivers to change the human-animal relationship or the animal's living environment and / or condition. The advice may also be additionally or alternatively made to regulatory bodies (such as government organizations) to take action in cases of inadequate animal welfare (note that in some cases, regulatory bodies may provide welfare scores for animal populations under their supervision periodically or continuously, enabling them to enforce animal welfare requirements in a reliable, objective, repeatable, and unbiased manner). The advice may also be additionally or alternatively made to financial institutions to ensure the fulfillment of animal caregivers' obligations to them. The advice may also be additionally or alternatively made to retail chains, dairy processors, or meat processors to prioritize products from one animal population over others (based on animal welfare scores calculated for multiple animal populations, or for multiple groups of animals from a single animal population). The advice may also be additionally or alternatively made to veterinarians to proactively take action based on identified animal welfare needs.

[0246] In some cases, this action can be performed automatically by an automated treatment system that can change the treatment of the animal after receiving a suggested action from the welfare determination system 500.

[0247] It is important to note that actions can be any actions that affect one or more members of an animal population. Examples include: treating one or more animal populations (vaccinating uninfected populations, providing antibiotics, antiviral drugs, analgesics, anti-inflammatory drugs, vitamins, and other general health promoters and hormones such as steroids); altering the ambient temperature to which one or more animal population members are exposed; changing the feeding parameters of one or more animal population members; altering the schedules or daily routines of one or more animal population members; altering the sleep parameters of one or more animal population members; separating one or more animal population members from the rest of the population; improving feed quality and availability to one or more animal population members; reducing the carrying capacity of barns, bedding, or both; improving the housing / shelter conditions of one or more animal population members (e.g., by changing environmental condition controls, bedding surfaces, walking routes, etc.); updating the farm's standard operating procedures (SOPs) to better meet the needs of the animal population; promptly identifying and taking action against outbreaks, and so on.

[0248] Actions can also be suggested based on the health score (420) and / or emotional / happiness score (430) and / or natural life score (440) of members of an animal population or its subgroups.

[0249] Actions can be recommended based on the identification of potential causes for lower-than-expected welfare scores, for example, using rules that associate potential causes with welfare scores and / or their components (health score 420 and / or emotional / happiness score 430 and / or natural life score 440 for members of the animal population or its subgroups). It is understood that certain potential causes (feed problems, bedding, social stress, ambient temperature, production stress) are correlated with lower welfare scores (or lower health score 420 and / or emotional / happiness score 430 and / or natural life score 440). Therefore, the welfare decision system 500 can recommend one or more actions to animal caregivers based on these scores, and provide reasons for providing such recommendations.

[0250] Underlying causes can be identified by relating the behavior of animal group members to environmental or procedural conditions (e.g., environmental conditions, operational conditions, relationship with humans, etc.) that influence one of the scores described herein (health score 420 and / or affective / well-being score 430 and / or natural life score 440). For example, a potential cause of increased variability in rumination and feeding among animal group members might be nutritional or feed problems, bedding problems, or social stress experienced by the animal group members. These causes can be correlated with the welfare score. Similarly, a plausible cause of increased variability in heavy breathing and rumination and feeding among animal group members could be excessively high ambient temperatures or disease among the animal group members.

[0251] Note the non-restrictive example: in addition to using welfare scores to recommend actions, welfare KPIs are also used: when (a) the animal population's welfare score is below a first threshold, (b) the animal population's health score 420 is below a second threshold, and (c) the animal population's natural life score 440 is below a third threshold, the welfare determination system 500 may recommend action to screen the animal population for infectious diseases. Alternatively, if only one or both of the welfare score, health score 420, or natural life score 440 are below the thresholds, the welfare determination system 500 may recommend another action—such as implementing treatment for a potential infectious disease.

[0252] In some cases, it is recommended to take action when welfare KPI scores fall below a welfare threshold. The welfare threshold can be determined based on statistical analysis of historical welfare KPI scores (e.g., using box plots, regression analysis, etc.). Historical welfare KPI scores can be used to identify trends within and / or between animal populations. The welfare threshold can be determined for one or more facilities (e.g., farms), geographical locations (e.g., territories, countries, etc.), etc.

[0253] It is important to note that different locations / regions may have different regulatory and / or environmental conditions in some cases. Therefore, adjustable welfare thresholds can take into account local regulations, local climate, local animal needs, local historical welfare scores, and other relevant factors to produce more realistic and useful welfare thresholds that can be adopted by different local stakeholders in different locations / regions.

[0254] Figure 11 A non-limiting example is shown, illustrating graphs of the average welfare scores of animal populations in four different countries over a year, as determined by Welfare Determination System 500. These graphs demonstrate the applicability of the welfare score model used by Welfare Determination System 500 to various geographic regions, areas, and countries with different environmental and seasonal conditions. The behavior of the welfare scores determined by Welfare Determination System 500 matches known seasonal variations. For example, the decline in welfare scores in country C during May and September corresponds to the extreme heat conditions measured in that country. Welfare scores for different countries are used to determine corresponding welfare thresholds. Welfare thresholds for a given geographic region, area, or country can be statistically determined based on past welfare scores for that given geographic region, area, or country. Statistical determination can be based on the mean, median, box plot, or any other statistical method. Non-limiting examples of using box plots (e.g., Box Plot A 910-a, Box Plot B 910-b, Box Plot C 910-c, Box Plot D 910-d, etc.) to determine welfare thresholds for countries are shown below. Figure 11 As shown, Figure 11This illustrates welfare thresholds determined for four different countries within a given timeframe. A box plot is a known statistical method used to graphically depict groups of numerical data using quartiles. For example, box plot A910-a has four vertical quartiles (colored white, light gray, dark gray, and white). The first quartile is the lowest part of box plot A910-a, preserving the median of the lower half of the dataset. In this example, the threshold is set to the first quartile—welfare scores above the first quartile are above the welfare threshold, while welfare scores below the first quartile are below the welfare threshold. This method generates different welfare thresholds for different countries and can be used to determine different welfare thresholds for different time periods within the same country. It is understandable that the welfare thresholds for the four countries are different.

[0255] It's important to note that Welfare Determination System 500 allows for setting different thresholds for different locations, such as: different animal species, different climates, different customs, different regulations and rules, different laws, and different requirements for animals. The continuous, uninterrupted monitoring of Welfare Determination System 500 enables its users (e.g., animal caregivers) to set appropriate thresholds for their specific locations. Each location can be, for example, a farm, farm group, region, territory, or country.

[0256] It is important to note that welfare thresholds can also vary dynamically (e.g., based on weather) and / or periodically (e.g., seasonally). Regarding seasonally related variations, it is important to note that analysis of historical welfare scores can identify periods within a year when an animal population's welfare score is affected by weather conditions, the seasons, or other locally variable factors. It is readily understood that seasonal variation is geographically dependent and may differ between different countries, or even between different geographic regions within a single country.

[0257] It's important to note that Welfare Determination System 500 can set different thresholds for different locations, taking into account factors such as different animal types, climates, customs, regulations and rules, laws, and animal requirements. The continuous, uninterrupted monitoring provided by Welfare Determination System 500 allows users (e.g., animal caregivers) to set appropriate thresholds for their specific locations. Each location can be, for example, a farm, farm group, region, territory, or country.

[0258] It is important to note that welfare thresholds can also vary dynamically (e.g., based on weather) and / or cyclically (e.g., seasonally). Regarding seasonal variations, it is important to note that analysis of historical welfare KPI scores can identify periods within a year when an animal population's welfare KPI score is affected by weather conditions, the seasons, or other local variables. It is readily understood that seasonal variation is geographically dependent and can differ between different countries, and even between different geographic regions within a single country.

[0259] Figure 12 A non-limiting example is shown, illustrating data collected from four countries. In Country A, animals were exposed to conditions affecting the emotional / well-being score 430 between January and March and October and December, with more issues affecting the natural life score 440 between April and August. This could be due, for example, to the tropical climate and the effects of the wet and dry seasons in Country A. In Country B, the natural life score 440 improved between April and October once animals were allowed into enclosures due to better conditions compared to overgrazing in captivity. The emotional / well-being score 430 varied more significantly during the same period due to the effects of feed quality and climate conditions. Furthermore, in Countries C and D, the charts depict the effects of extreme conditions: extreme heat stress in May and September lowered the overall welfare KPI score, even though the animal environment remained unchanged. Human auditors might overlook these weather and seasonal effects because they would obviously be unable to notice the smaller, more subtle effects of climate, condition, and environmental changes that can be identified using the Welfare Determination System 500.

[0260] The welfare KPI scores of the Welfare Determination System 500 have been validated against those of human auditors, and the welfare KPI scores generated by System 500 have been found to be effective and useful. For example, the welfare scores determined by the Welfare Determination System 500 show a good correlation with the welfare scores of the same animal determined by human auditors. Additionally, the Welfare Determination System 500 provides more insights, more accurate insights, and more complete insights than human-led audits. This provides a current example of an improvement over existing technologies.

[0261] In some exemplary studies, welfare KPI scores generated by the Welfare Determination System 500 were blindly compared to human audits of representative farm operations. One example involved a herd of grazing cattle. Human auditors gave lower overall welfare KPI scores due to observed deficiencies in facilities and poor feeding conditions. In contrast, the System 500 welfare KPI scores for the same grazing cattle were higher. To demonstrate the greater accuracy of the Welfare Determination System 500 scores, several indicators were examined: lack of signs of disease (the group of cows was disease-free), no lameness observed in these cows, and persistent feeding behavior; additionally, the somatic cell counts (SCC) of the milk from these cows were tested and found to be at constant and adequate levels, and consistent yield levels—all indicators of adequate cow welfare—as noted by the human auditors. In fact, because dairy cows are inherently low-yielding, they maintained good welfare despite the human auditors' assessment that external conditions were detrimental to their welfare. Human auditors cannot directly measure cow welfare and determine whether these external conditions adversely affect it. In contrast, this can be achieved by using a welfare determination system 500 to perform a more direct measurement of animal welfare. Therefore, this is an example of the welfare determination system 500 described in this paper, which provides a more accurate determination of the welfare of dairy cows on a farm.

[0262] Another example involves a high-producing dairy herd fed a total mixed ration (TMR) diet. Human auditors found low welfare KPI scores due to inadequate housing facilities, problematic stocking rates, and dirty cows. The Welfare Determination System 500, however, yielded relatively high welfare KPI scores for the same high-producing herd because it considered consistent TMR, sufficient bedding space, effective cooling protocols for the cows, and acceptable health scores. Because animal responses to forced conditions are multifactorial, human auditors often struggle to grasp these factors without more frequent or continuous monitoring. Human auditors typically only notice external declines in animal performance—often by then, it's too late. This is another example of human auditors relying on external observations without benefiting from direct and continuous measurement of cow welfare, as is currently the case with the publicly available Welfare Determination System 500.

[0263] Figure 13 This paper depicts some non-restricted examples of welfare scores determined by human auditors (marked with +) and welfare scores from the Welfare Determination System 500 (marked with solid lines) for many given facilities within parallel timeframes. Areas with thicker welfare score lines correlate with times when welfare scores more frequently fall below a set welfare threshold. It is important to note that... Figure 13 The data in the data is actual data monitored using the Welfare Determination System 500, which verifies the welfare KPI scores generated by the System 500.

[0264] In some cases, a human auditor may determine a lower welfare score for a given animal population than the welfare KPI score determined by Welfare Determination System 500 for the same given animal population. This may be because the data and analysis available to the human auditor (e.g., production levels, visual inspections of the animal environment, etc.) are not as readily available as the data in Welfare Determination System 500, which can be obtained through continuous monitoring and analysis of the behavior of animal population members (e.g., feeding levels, rumination time, activity and energy levels, etc.) to accurately determine their welfare KPI scores. A higher score given by Welfare Determination System 500 may also be the result of comparing measured behavior to a rolling baseline and adjusting for the impact of extreme events or slowly deteriorating conditions—situations that are not easily identified through infrequent human audits. Without the ability to compare to a rolling baseline and adjust for the impact of factors such as weather (e.g., seasonal weather, extreme weather), slowly changing conditions (e.g., slowly declining animal facilities), or subtle changes over time, a human auditor may determine a lower welfare score than Welfare Determination System 500 would have for the same animal population under similar conditions. In a real-life example, the farm received a low to medium welfare score from the human auditor because the animal living quarters were unclean, food supplies were limited, and productivity was low, but received a high welfare KPI score from the welfare determination system 500, which was in line with the animals' actual welfare—the animals were under less stress due to low productivity expectations, and the living quarters actually provided the animals with opportunities to rest and cool off.

[0265] A non-restrictive example of an audit score being higher than the welfare KPI score calculated by the Welfare Determination System 500 is when environmental conditions change (e.g., extreme weather conditions) but the animals' living conditions remain unchanged. Human auditors' scores are biased towards the living conditions observed by the auditor, thus assigning a higher audit score. The Welfare Determination System 500 monitors (optionally continuously) the impact of changes in environmental conditions on the animals, thus assigning a lower welfare KPI score that more accurately reflects the animals' reality.

[0266] Another non-restrictive example of an audit score higher than the welfare KPI score calculated by System 500 is when animals are under high physiological stress (e.g., high productivity stress, high workload stress, etc.). Human auditors may be impressed with animal productivity and the physical condition of the farm, but System 500's continuous monitoring of animal behavior detects high stress and the animals' responses to this stress, resulting in a lower welfare KPI score.

[0267] The discrepancy between human-audited welfare scores and System 500 welfare KPI scores (based on automated and optional continuous monitoring) stems from the fact that System 500 also considers historical trends, while human audits rely solely on assessments performed during the audit period. In System 500's welfare KPI score determination, there is no human bias—no personal impressions, no repeatability issues, and no consideration of audit proficiency. System 500 determines welfare status based on animal physiological signals, not human interpretation. System 500 can provide greater sensitivity for long-term conditions (such as overgrazing) or extreme conditions (such as severe heat stress). System 500 can provide greater specificity in situations where animals can manage the stressful environment because it relies less on productivity or condition.

[0268] Figure 14 The study depicts the consistency between the benefit scores determined by human auditors and the benefit KPI scores determined by the Benefit Determination System 500. Figure 14 The upper right and lower left sections of the chart (where most validation measures are found) show a general consistency between the human auditors' benefit scores and the benefit KPI scores determined by the Benefits Determination System 500. The size of the icons in the chart is correlated with the benefit KPI scores, which more frequently fall below the benefit threshold.

[0269] Human auditing has limitations due to inconsistencies, credibility, and accuracy issues. Benefits Determination System 500 mitigates these limitations by providing accurate and optional continuous benefits KPI scores.

[0270] These comparative studies found that System 500, due to its optional 24 / 7 coverage and individual monitoring performance used to calculate welfare KPI scores, more accurately reflects the actual situation of animal populations. For example, System 500 handles scenarios such as uneven operational consistency, extreme weather conditions, and oscillation-related morbidity better. The studies found that production demand significantly impacts welfare responses, meaning that lower output makes worse conditions more tolerable. Based on proven insights, the calculated monitoring welfare scores provide an objective (non-human interpretation) view of animal population conditions.

[0271] It should be noted that the reference Figure 3 , Figure 5 and Figure 8 Some of these boxes can be integrated into a single box, or they can be broken down into several boxes, and / or additional boxes can be added. It should be further noted that some of these boxes are optional. It should also be noted that although the flowcharts are described with reference to the system elements that implement them, this is by no means binding, and these boxes can be executed by elements other than those described herein.

[0272] It should be understood that the subject matter of this disclosure is not limited to the details described herein or shown in the accompanying drawings. The subject matter of this disclosure may have other embodiments and can be practiced and implemented in various ways. Therefore, it should be understood that the wording and terminology used herein are for descriptive purposes and should not be considered limiting. Consequently, those skilled in the art will understand that the concepts upon which this disclosure is based can be readily used as the basis for designing other structures, methods, and systems for performing the purposes of the subject matter of this disclosure.

[0273] It will also be understood that a system according to the subject matter of this disclosure can be implemented, at least in part, as a properly programmed computer. Similarly, the subject matter of this disclosure contemplates a computer-readable computer program for performing the disclosed methods. The subject matter of this disclosure also contemplates a machine-readable storage medium specifically containing a program of machine-executable instructions capable of being used to perform the disclosed methods.

Claims

1. A system for establishing group-specific harassment rules for at least a subset of animals in an animal population, the system comprising: One or more monitoring devices are configured to monitor parameters of one or more members of the animal population; A data repository comprising one or more records, each associated with a corresponding member of the animal population, and including one or more monitored parameters of the member monitored over time by at least one corresponding monitoring device among the monitoring devices; and The processing circuit system is configured as follows: Obtain at least one subset of records from the records that are associated with the member group of the animal population; For each given member in the group, a harassment score is calculated, indicating the level of harassment or stimulation caused by the flying insects to that given member; and Based on the harassment score and at least one other monitored parameter, group-specific harassment rules are determined for the member group and are associated with the group's harassment tolerance.

2. The system of claim 1, wherein, based on the group-specific harassment rules, the processing circuitry is further configured to: limit or weight the data obtained from the monitoring device for the group of members to take into account the masking effect of fly load.

3. The system of claim 1, wherein the disturbance score is calculated based on one or more ear movement patterns caused by disturbance or stimulation from flying insects, and wherein each ear movement pattern includes a corresponding ear movement feature.

4. The system of claim 3, wherein each of the one or more ear movement patterns is associated with its own characteristics.

5. The system of claim 1, wherein the at least one other monitored parameter is one of the following: milk production, feed intake, and health status.

6. A system for monitoring the status of at least a subset of animals in an animal population, the system comprising: One or more monitoring devices are configured to monitor parameters of one or more members of the animal population; A data repository comprising one or more records, each associated with a corresponding member of the animal population, and including one or more monitored parameters of the member monitored over time by at least one corresponding monitoring device among the monitoring devices; and The processing circuit system is configured as follows: Obtain at least one subset of records from the records that are associated with the member group of the animal population; For each given member in the group of members, calculate (a) a harassment score, which indicates the level of harassment or stimulation caused by the flying insects to the given member, and (b) at least one additional animal condition score, which indicates the physiological or behavioral state of the given member. For the aforementioned member group, based on at least one of the harassment scores and at least one of the additional animal condition scores, the impact of flying insect harassment on at least one of the monitored parameters is analyzed. Based on the aforementioned impact, identify whether the member group exhibits any undesirable conditions requiring attention; and, When such undesirable situations are identified, actions aimed at improving or maintaining animal welfare are recommended.

7. The system according to claim 6, wherein, Following the analysis, the processing circuitry is further configured to filter or adjust at least one of the monitored parameters to account for disturbance-related noise.

8. The system of claim 6, wherein the animal condition score is at least one of: (i) a health score indicating the health status of the given member; (ii) a natural life score indicating that the behavior pattern of the given member conforms to the expected natural behavior pattern; or (iii) an emotion / happiness score indicating that the emotion / happiness measurement of the given member conforms to the expected emotion / happiness measurement.

9. The system of claim 6, wherein the monitored parameter includes one or more of the following behavioral parameters: (a) the percentage of exercise time of the given member in a first time period, (b) the percentage of eating time of the given member in a second time period, or (c) the percentage of social behavior time of the given member in a third time period; and wherein the natural life score of the given member is determined based on the behavioral parameters.

10. The system of claim 8, wherein the natural life score for the given member is determined based on the consistency of the values ​​of at least some of the parameters over time.

11. The system of claim 6, wherein the parameter includes one or more of the following emotion / happiness parameters: (a) the respiratory level of the given member, (b) the percentage of rumination time of the given member in a fourth time period, or (c) the percentage of eating time of the given member in a fifth time period; and wherein the emotion / happiness score of the given member is determined based on the emotion / happiness parameter.

12. The system of claim 8, wherein the emotion / happiness score for the given member is determined based on the consistency of the values ​​of at least some of the parameters over time.

13. The system of claim 8, wherein the welfare score is calculated based on the change between the emotion / happiness scores of the members in the first group.

14. The system of claim 6, wherein the record further comprises one or more environmental parameters indicating the state of the environment of the respective member, and wherein determining (a) the natural life score of the respective member or (b) the emotional / happiness score of the respective member is also based on the environmental parameters.

15. The system of claim 6, wherein the action is one or more of the following: treatment of an animal population, alteration of the temperature of the environment of the animal population, alteration of the feed of the animal population, or alteration of the schedule of the animal population.

16. A system comprising: One or more monitoring devices are configured to monitor parameters of one or more members of an animal population; A data repository comprising one or more records, each associated with a corresponding member of the animal population, and including one or more monitored parameters of the member monitored over time by at least one corresponding monitoring device among the monitoring devices; and The processing circuit system is configured as follows: Obtain at least one subset of records from the records that are associated with the member group of the animal population; For each given member in the group of members, a harassment score is calculated, which indicates the level of harassment or stimulation caused by the flying insects to the given member; For the aforementioned member group, based on the harassment score and at least one monitored parameter, perform at least one of the following: (a) identify whether the member group exhibits an undesirable situation requiring attention, or (b) determine a group-specific harassment rule associated with the group's harassment tolerance based on the harassment score and at least one other monitored parameter; and, When such undesirable situations are identified, actions aimed at improving or maintaining animal welfare are recommended.

17. The system of claim 16, wherein, based on the group-specific harassment rules, the processing circuitry is further configured to: limit or weight the data obtained from the monitoring device for the group of members to take into account the masking effect of fly load.

18. The system of claim 16, wherein the disturbance score is calculated based on one or more ear movement patterns caused by disturbance or stimulation from flying insects, and wherein each ear movement pattern includes a corresponding ear movement feature.

19. The system of claim 18, wherein each of the one or more ear movement patterns is associated with its own characteristics.

20. The system of claim 16, wherein the at least one other monitored parameter is one of the following: milk production, feed intake, and health status.

21. The system of claim 16, wherein the action is one or more of the following: administering treatment to an animal population, changing the temperature of the environment of the animal population, changing the feed of the animal population, or changing the schedule of the animal population.

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