Claims:1. A system (100) for cattle health monitoring comprising:
a cattle attribute tracking device (110) coupled to at least one body part of a cattle, wherein the cattle attribute tracking device (110) is configured to track a plurality of behavioural attributes and a plurality of physiological attributes of the cattle;
a cattle attribute data processing subsystem (120) located on a remote server, wherein the cattle attribute data processing subsystem (120) is configured to:
receive cattle attribute data representative of the plurality of the plurality of behavioural attributes and a plurality of physiological attributes of the cattle via a communication protocol; and
filter the cattle attribute data received in one or more formats into a structured format of cattle attribute data by using a data filtration technique;
a cattle health analysis subsystem (130) operatively coupled to the cattle attribute data processing subsystem (120), wherein the cattle health analysis subsystem (130) is configured to:
select one or more optimal features from the structured format of the cattle attribute data for a predetermined time interval upon filtering by using a feature selection technique;
evaluate one or more attribute metric of each of the one or more optimal features selected from the cattle attribute data for the predetermined time interval;
compare the one or more attribute metric of each of the one or more optimal features evaluated for the predetermined time interval with corresponding one or more historical attribute metric records associated with the cattle;
detect existence of one or more health associated abnormalities of the cattle based on a comparison of the one or more attribute metric with the one or more historical attribute metric records; and
utilize a trained health analysis classifier to analyse a health state of the cattle for informing one or more caretakers of the cattle based on the existence of the one or more health associated abnormalities detected; and
a cattle health recommendation generation subsystem (140) operatively coupled to the cattle health analysis subsystem (130), wherein the cattle health recommendation generation subsystem (140) is configured to generate a plurality of health and nutrition-oriented recommendations for the one or more caretakers of the cattle based on the health state of the cattle analysed.
2. The system (100) as claimed in claim 1, wherein the cattle attribute tracking device comprises at least one of a neck band, an ear tag, a tail tag, an ankle tag or a combination thereof.
3. The system (100) as claimed in claim 1, wherein the cattle attribute tracking device comprises one or more sensing devices comprising at least one of a triaxial accelerometer, a magnetometer, a positioning sensor, a gyroscope, a temperature sensor or a combination thereof.
4. The system (100) as claimed in claim 1, wherein the behavioural attributes comprises at least one of a posture attribute, a grazing habit, a grazing pattern, a feeding duration, a rumination, a drinking habit, a migration pattern, a sleeping schedule, a lying time, a reproductive activity, a congregation activity, a proximity to a neighbouring animal, a proximity of a stationary device or a combination thereof.
5. The system (100) as claimed in claim 1, wherein the physiological attributes comprises at least one of a temperature rate, a heart rate, a urination rate, a respiration rate, a lactation duration, a bowel movement, a body measurement, a calving activity or a combination thereof.
6. The system (100) as claimed in claim 1, wherein the cattle health analysis subsystem (130) is configured to utilize a computation technique comprising at least one of a sum, an average, a median or a mode for evaluation of the one or more attribute metric for the predetermined time interval.
7. The system (100) as claimed in claim 1, wherein the one or more health associated abnormalities comprises at least one of delay in reproduction cycle of the cattle, one or more diseases or a combination thereof.
8. The system (100) as claimed in claim 1, comprising a caretaker management subsystem (150) operatively coupled to the health analysis subsystem (130), wherein the caretaker management subsystem (150) is configured to conduct and coordinate one or more training programs for the one or more caretakers to maintain wellbeing of the cattle based on the health state of the cattle analysed.
9. The system (100) as claimed in claim 1, comprising a veterinary service management subsystem (160) configured to collaborate one or more veterinary service providers within an integrated platform to provide one or more cattle welfare services upon identification of a requirement based on the health state of the cattle analysed.
10. A method (300) comprising:
tracking, by a cattle attribute tracking device, a plurality of behavioural attributes and a plurality of physiological attributes of the cattle (310);
receiving, by a cattle attribute data processing subsystem, cattle attribute data representative of the plurality of the plurality of behavioural attributes and a plurality of physiological attributes of the cattle via a communication protocol (320);
filtering, by the cattle attribute data processing subsystem, the cattle attribute data received in one or more formats into a structured format of cattle attribute data by using a data filtration technique (330);
selecting, by a cattle health analysis subsystem, one or more optimal features from the structured format of the cattle attribute data for a predetermined time interval upon filtering by using a feature selection technique (340);
evaluating, by the cattle health analysis subsystem, one or more attribute metric of each of the one or more optimal features selected from the cattle attribute data for the predetermined time interval (350);
comparing, by the cattle health analysis subsystem, the one or more attribute metric of each of the one or more optimal features evaluated for the predetermined time interval with corresponding one or more historical attribute metric records associated with the cattle (360);
detecting, by the cattle health analysis subsystem, existence of one or more health associated abnormalities of the cattle based on a comparison of the one or more attribute metric with the one or more historical attribute metric records (370);
utilising, by the cattle health analysis subsystem, a trained health analysis classifier to analyse a health state of the cattle for informing one or more caretakers of the cattle based on the existence of the one or more health associated abnormalities detected (380); and
generating, by a cattle health recommendation generation subsystem, a plurality of health and nutrition-oriented recommendations for informing the one or more caretakers of the cattle based on the health state of the cattle analysed (390).
Dated this 15th day of December 2020

Signature

Harish Naidu
Patent Agent (IN/PA-2896)
Agent for the Applicant
, Description:BACKGROUND
[0001] Embodiments of the present disclosure relate to a health monitoring system and more particularly to a system and a method for cattle health monitoring.
[0002] Cattle is one of an important asset for any cattle farms. Good health and wellbeing of the cattle is essential to raise and maintain the asset of the cattle farms for purpose of producing meat, milk or eggs. With increasing awareness of health-related issues concerning the cattle and significant losses that arise from poor fertility management, the farming industry has been forced to adapt in maintaining accurate records of the cattle. Gradually, as the size of the cattle farms increase, day to day monitoring of the cattle condition and an ability of a stockman to keep records and track individual cattle becomes increasingly difficult. As a result, various automated monitoring systems are designed for tracking the cattle condition and effectively monitoring the cattle welfare.
[0003] Conventionally, the monitoring systems which are available for tracking the condition of the assets of the cattle farms include a range of sensors for monitoring one or more physical parameters of the cattle. However, such a conventional system requires the range of sensors to be invasively attached to the cattle which is not only distressing to the cattle but also requires involvement of one or more skilful veterinary experts. In addition, the involvement of the veterinary experts for observing the cattle condition increases time consumption and also makes the overall process expensive. Also, such an attachment with the range of sensors have a limited ability for observing one or more social activities of the cattle and fertility monitoring of the cattle especially during parturition period. Moreover, such a conventional system is capable of handling only a limited population of the cattle and thus creates difficulty in detailed health analysis and providing valuable precautionary measures for the cattle welfare in case of large population of the cattle.
[0004] Hence, there is a need for an improved system and a method for cattle health monitoring in order to address the aforementioned issues.

BRIEF DESCRIPTION
[0005] In accordance with an embodiment of the present disclosure, a system for cattle health monitoring is disclosed. The system includes a cattle attribute tracking device coupled to at least one body part of a cattle. The cattle attribute tracking device is configured to track a plurality of behavioural attributes and a plurality of physiological attributes of the cattle. The system also includes a cattle attribute data processing subsystem located on a remote server. The cattle attribute data processing subsystem is configured to receive cattle attribute data representative of the plurality of the plurality of behavioural attributes and a plurality of physiological attributes of the cattle via a communication protocol. The cattle attribute data processing subsystem is also configured to filter the cattle attribute data received in one or more formats into a structured format of cattle attribute data by using a data filtration technique. The system also includes a cattle health analysis subsystem operatively coupled to the cattle attribute data processing subsystem. The cattle health analysis subsystem is configured to select one or more optimal features from the structured format of the cattle attribute data for a predetermined time interval upon filtering by using a feature selection technique. The cattle health analysis subsystem is also configured to evaluate one or more attribute metric of each of the one or more optimal features selected from the cattle attribute data for the predetermined time interval. The cattle health analysis subsystem is also configured to compare the one or more attribute metric of each of the one or more optimal features evaluated for the predetermined time interval with corresponding one or more historical attribute metric records associated with the cattle. The cattle health analysis subsystem is also configured to detect existence of one or more health associated abnormalities of the cattle based on a comparison of the one or more attribute metric with the one or more historical attribute metric records. The cattle health analysis subsystem is also configured to utilise a trained health analysis classifier to analyse a health state of the cattle for informing one or more caretakers of the cattle based on the existence of the one or more health associated abnormalities detected. The system also includes a cattle health recommendation generation subsystem operatively coupled to the cattle health analysis subsystem. The cattle health recommendation generation subsystem is configured to generate a plurality of health and nutrition-oriented recommendations for informing the one or more caretakers of the cattle based on the health state of the cattle analysed.
[0006] In accordance with another embodiment of the present disclosure, a method for cattle health monitoring is disclosed. The method includes tracking, by a cattle attribute tracking device, a plurality of behavioural attributes and a plurality of physiological attributes of the cattle. The method also includes receiving, by a cattle attribute data processing subsystem, cattle attribute data representative of the plurality of the plurality of behavioural attributes and a plurality of physiological attributes of the cattle via a communication protocol. The method also includes filtering, by the cattle attribute data processing subsystem, the cattle attribute data received in one or more formats into a structured format of cattle attribute data by using a data filtration technique. The method also includes selecting, by a cattle health analysis subsystem, one or more optimal features from the structured format of the cattle attribute data for a predetermined time interval upon filtering by using a feature selection technique. The method also includes evaluating, by the cattle health analysis subsystem, one or more attribute metric of each of the one or more optimal features selected from the cattle attribute data for the predetermined time interval. The method also includes comparing, by the cattle health analysis subsystem, the one or more attribute metric of each of the one or more optimal features evaluated for the predetermined time interval with corresponding one or more historical attribute metric records associated with the cattle. The method also includes detecting, by the cattle health analysis subsystem, existence of one or more health associated abnormalities of the cattle based on a comparison of the one or more attribute metric with the one or more historical attribute metric records. The method also includes utilising, by the cattle health analysis subsystem, a trained health analysis classifier to analyse a health state of the cattle for informing one or more caretakers of the cattle based on the existence of the one or more health associated abnormalities detected. The method also includes generating, by a cattle health recommendation generation subsystem, a plurality of health and nutrition-oriented recommendations for informing the one or more caretakers of the cattle based on the health state of the cattle analysed.
[0007] To further clarify the advantages and features of the present disclosure, a more particular description of the disclosure will follow by reference to specific embodiments thereof, which are illustrated in the appended figures. It is to be appreciated that these figures depict only typical embodiments of the disclosure and are therefore not to be considered limiting in scope. The disclosure will be described and explained with additional specificity and detail with the appended figures.
BRIEF DESCRIPTION OF THE DRAWINGS
The disclosure will be described and explained with additional specificity and detail with the accompanying figures in which:
[0008] FIG. 1 is a block diagram of a system for cattle health monitoring in accordance with an embodiment of the present disclosure;
[0009] FIG. 2 is a block diagram representation of an embodiment of a system for cattle health monitoring in accordance with an embodiment of the present disclosure.
[0010] FIG. 3 is a block diagram of an exemplary system for cattle health monitoring in accordance with an embodiment of the present disclosure;
[0011] FIG. 4 illustrates a block diagram of a computer or a server of FIG. 1 in accordance with an embodiment of the present disclosure; and
[0012] FIG. 5 is a flow chart representing the steps involved in a method for cattle health monitoring of FIG. 1 in accordance with the embodiment of the present disclosure.
[0013] Further, those skilled in the art will appreciate that elements in the figures are illustrated for simplicity and may not have necessarily been drawn to scale. Furthermore, in terms of the construction of the device, one or more components of the device may have been represented in the figures by conventional symbols, and the figures may show only those specific details that are pertinent to understanding the embodiments of the present disclosure so as not to obscure the figures with details that will be readily apparent to those skilled in the art having the benefit of the description herein.
DETAILED DESCRIPTION
[0014] For the purpose of promoting an understanding of the principles of the disclosure, reference will now be made to the embodiment illustrated in the figures and specific language will be used to describe them. It will nevertheless be understood that no limitation of the scope of the disclosure is thereby intended. Such alterations and further modifications in the illustrated system, and such further applications of the principles of the disclosure as would normally occur to those skilled in the art are to be construed as being within the scope of the present disclosure.
[0015] The terms "comprises", "comprising", or any other variations thereof, are intended to cover a non-exclusive inclusion, such that a process or method that comprises a list of steps does not include only those steps but may include other steps not expressly listed or inherent to such a process or method. Similarly, one or more devices or sub-systems or elements or structures or components preceded by "comprises... a" does not, without more constraints, preclude the existence of other devices, sub-systems, elements, structures, components, additional devices, additional sub-systems, additional elements, additional structures or additional components. Appearances of the phrase "in an embodiment", "in another embodiment" and similar language throughout this specification may, but not necessarily do, all refer to the same embodiment.
[0016] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which this disclosure belongs. The system, methods, and examples provided herein are only illustrative and not intended to be limiting.
[0017] In the following specification and the claims, reference will be made to a number of terms, which shall be defined to have the following meanings. The singular forms “a”, “an”, and “the” include plural references unless the context clearly dictates otherwise.
[0018] Embodiments of the present disclosure relate to a system and a method for cattle health monitoring. The system includes a cattle attribute tracking device coupled to at least one body part of a cattle. The cattle attribute tracking device is configured to track a plurality of behavioural attributes and a plurality of physiological attributes of the cattle. The system also includes a cattle attribute data processing subsystem located on a remote server. The cattle attribute data processing subsystem is configured to receive cattle attribute data representative of the plurality of the plurality of behavioural attributes and a plurality of physiological attributes of the cattle via a communication protocol. The cattle attribute data processing subsystem is also configured to filter the cattle attribute data received in one or more formats into a structured format of cattle attribute data by using a data filtration technique. The system also includes a cattle health analysis subsystem operatively coupled to the cattle attribute data processing subsystem. The cattle health analysis subsystem is configured to select one or more optimal features from the structured format of the cattle attribute data for a predetermined time interval upon filtering by using a feature selection technique. The cattle health analysis subsystem is also configured to evaluate one or more attribute metric of each of the one or more optimal features selected from the cattle attribute data for the predetermined time interval. The cattle health analysis subsystem is also configured to compare the one or more attribute metric of each of the one or more optimal features evaluated for the predetermined time interval with corresponding one or more historical attribute metric records associated with the cattle. The cattle health analysis subsystem is also configured to detect existence of one or more health associated abnormalities of the cattle based on a comparison of the one or more attribute metric with the one or more historical attribute metric records. The cattle health analysis subsystem is also configured to utilise a trained health analysis classifier to analyse a health state of the cattle for informing one or more caretakers of the cattle based on the existence of the one or more health associated abnormalities detected. The system also includes a cattle health recommendation generation subsystem operatively coupled to the cattle health analysis subsystem. The cattle health recommendation generation subsystem is configured to generate a plurality of health and nutrition-oriented recommendations for informing the one or more caretakers of the cattle based on the health state of the cattle analysed.
[0019] FIG. 1 is a block diagram of a system (100) for cattle health monitoring in accordance with an embodiment of the present disclosure. The system (100) includes a cattle attribute tracking device (110) coupled to at least one body part of a cattle. The cattle attribute tracking device is configured to track a plurality of behavioural attributes and a plurality of physiological attributes of the cattle. As used herein, the term ‘cattle attribute tracking device’ is defined as a wearable device which is attached to an animal body for tracking and acquiring one or more characteristics in real-time. In one embodiment, the cattle may include, but not limited to, a cow, a buffalo, a sheep, a goat, a horse, a donkey and the like. In some embodiment, the at least one body part of the cattle for coupling the cattle attribute tracking device may include but not limited to, a neck of the cattle, an ear of the cattle, a tail of the cattle, an ankle of the cattle and the like. In one embodiment, the cattle attribute tracking device may include at least one of a neck band, an ear tag, a tail tag, an ankle tag or a combination thereof. In some embodiment, the cattle attribute tracking device may include a radium light strap which is visible at night in absence of electricity. In such embodiment, the cattle attribute tracking device may include a plurality of sensing devices including but not limited to, at least one of a triaxial accelerometer, a magnetometer, a positioning sensor, a gyroscope, a temperature sensor or a combination thereof. The triaxial accelerometer measures motion data associated with a given cattle. Similarly, the magnetometer and the gyroscope measure the head tilt of the cattle. The positioning sensor tracks a real-time location of the cattle. Again, the temperature sensor measures the body temperature of the cattle. The cattle attribute tracking device also includes a battery, a microcontroller equipped with the plurality of sensing devices and a wireless transceiver. In one embodiment, the wireless transceiver may include, but not limited to, a Bluetooth R low energy (BLE) compatible radio transceiver, a Bluetooth compatible transceiver, a radio frequency identification (RFID) transceiver, a near field communication (NFC) transceiver, a Wi-Fi (wireless fidelity) transceiver and the like.
[0020] The system (100) also includes a cattle attribute data processing subsystem (120) located on a remote server. The cattle attribute data processing subsystem (120) is configured to receive cattle attribute data representative of the plurality of the plurality of behavioural attributes and a plurality of physiological attributes of the cattle via a communication protocol. In one embodiment, the remote server may include a cloud server. In such embodiment, the cloud server may include a cloud storage repository to store information of the cattle, information of the cattle farm, the cattle attribute data, details of one or more caretakers and the like. In one embodiment, the plurality of behavioural attributes may include, but not limited to, a posture attribute, a grazing habit, a grazing pattern, a feeding duration, a rumination, a drinking habit, a migration pattern, a sleeping schedule, a lying time, a reproductive activity, a congregation activity, a proximity to a neighbouring animal, a proximity of a stationary device or a combination thereof. In another embodiment, the plurality of physiological attributes may include, but not limited to, a temperature rate, a heart rate, a urination rate, a respiration rate, a lactation duration, a bowel movement, a body measurement, a calving activity or a combination thereof. In a specific embodiment, the communication protocol may include, but not limited to, Bluetooth, RFID, NFC, Wi-fi and the like.
[0021] The cattle attribute data processing subsystem is also configured to filter the cattle attribute data received in one or more formats into a structured format of cattle attribute data by using a data filtration technique. The data filtration technique filters raw data received from the cattle attribute tracking device in the one or more formats by removing one or more noises, duplicate values, null values and the like. In one embodiment, the data filtration technique may include a median filtering technique, a Kalman filtering technique or a low pass filtering technique. In one embodiment, the filtered data may include data for one animal of the cattle, multiple animals among the cattle and the like. In another embodiment, the filtered data may include data associated with cattle of a particular time interval from a particular geographical location.
[0022] The system (100) also includes a cattle health analysis subsystem (130) operatively coupled to the cattle attribute data processing subsystem (120). The cattle health analysis subsystem (130) is configured to select one or more optimal features from the structured format of the cattle attribute data for a predetermined time interval upon filtering by using a feature selection technique. In one embodiment, the feature selection technique may include but not limited to, a chi-squared feature selection technique, a Pearson correlation feature selection technique, a recursive feature elimination technique, a lasso feature selection technique, a tree-based feature selection technique.
[0023] The cattle health analysis subsystem is also configured to evaluate one or more attribute metric of each of the one or more optimal features selected from the cattle attribute data for the predetermined time interval. The evaluation of the one or more attribute metric of each of the optimal features includes utilization of a computation technique, wherein the computation technique includes at least one of a sum, an average, a median or a mode for evaluation of the one or more attribute metric for the predetermined time interval. The one or more attribute values for each of the one or more optimal features are collected for the predetermined time interval such as an hour, a day, a week, a period of ten days, a period of fifteen days, a month and the like. Each of the one or more attribute values collected for each of the corresponding one or more optimal features over the predetermined time interval are further evaluated using the computation technique to obtain the one or more attribute metric.
[0024] The cattle health analysis subsystem is also configured to compare the one or more attribute metric of each of the one or more optimal features evaluated for the predetermined time interval with corresponding one or more historical attribute metric records associated with the cattle. In one embodiment the one or more historical attribute metric records associated with the cattle may include a sample behavioural and physiological attribute data of the cattle obtained from an external source. The cattle health analysis subsystem is also configured to detect existence of one or more health associated abnormalities of the cattle based on a comparison of the one or more attribute metric with the one or more historical attribute metric records. In one embodiment, the one or more health associated abnormalities may include at least one of delay in reproduction cycle of the cattle, one or more diseases or a combination thereof. For example, upon comparison, if temperature metric of the cattle for the predetermined interval is higher than the historical average temperature of the cattle, then the one or more health associated abnormalities such as fever or onset of other diseases are detected.
[0025] The cattle health analysis subsystem is also configured to utilize a trained health analysis classifier to analyse a health state of the cattle for informing one or more caretakers of the cattle based on the existence of the one or more health associated abnormalities detected. In one embodiment, the trained health analysis classifier may include a machine learning technology-based classifier. In such embodiment, the machine learning technology-based classifier may include, but not limited to, a decision tree classifier, a random forest classifier, a support vector machine (SVM) classifier, an artificial neural network (ANN) classifier and the like. The trained health analysis classifier is configured to correlate the one or more attributes of the dataset to a particular health state of the cattle. For example, the trained health analysis classifier correlates multiple physiological and/or behaviour attributes to a particular health state of the cattle. In one embodiment, the health state of the cattle may include a healthy state of the cattle, an unhealthy state of the cattle, a pre-diseased state of the cattle and the like.
[0026] The system (100) also includes a cattle health recommendation generation subsystem (140) operatively coupled to the cattle health analysis subsystem (130). The cattle health recommendation generation subsystem (140) is configured to generate a plurality of health and nutrition-oriented recommendations for informing the one or more caretakers of the cattle based on the health state of the cattle analysed. In one embodiment, the one or more caretakers may include, but not limited to, a farmer, a cattle farm owner, a stockman, a veterinary doctor, a veterinary health department and the like. In a specific embodiment, the plurality of health and nutrition-oriented recommendation may include at least one of a customized diet recommendation, a nutrition recommendation during pre-pregnancy and post-pregnancy period, a separate housing recommendation for fresh and sick animals of the cattle, a regular health examination recommendation and the like. In a specific embodiment, the plurality of health and nutrition-oriented recommendations and health status of the cattle are notified to the one or more caretakers in real-time via a plurality of notification means. In such embodiment, the plurality of notification means may include, but not limited to, a text message, an electronic mail, a call, a voice message, a pop-up notification and the like.
[0027] FIG. 2 is a block diagram representation of an embodiment of a system (100) for cattle health monitoring in accordance with an embodiment of the present disclosure. As described in aforementioned FIG. 1, the system includes a cattle attribute tracking device (110), a cattle attribute data processing subsystem (120), a cattle health analysis subsystem (130) and a cattle health recommendation generation subsystem (140). In addition, the system (100) also includes a caretaker management subsystem (150) operatively coupled to the health analysis subsystem (130). The caretaker management subsystem (150) is configured to conduct and coordinate one or more training programs for the one or more caretakers to maintain wellbeing of the cattle based on the health state of the cattle analysed. In one embodiment, the one or more training programs are conducted for mutual knowledge sharing by the one or more caretakers to maintain the wellbeing of the cattle. In another embodiment, the one or more training programs are conducted for knowledge sharing by one or more veterinary experts with the one or more caretakers to maintain the wellbeing of the cattle. In some embodiment, the one or more training programs may be conducted in regular time intervals corresponding to different health state of the cattle analysed. In such embodiment, the one or more training programs may include at least one of an online training program, an offline training program or a combination thereof.
[0028] In a preferred embodiment, the system (100) further includes a veterinary service management subsystem (160) operatively coupled to the cattle health analysis subsystem. The veterinary service management subsystem is configured to collaborate one or more veterinary service providers within an integrated platform to provide one or more cattle welfare services upon identification of a requirement based on the health state of the cattle analysed. In one embodiment, the one or more veterinary service providers may include, but not limited to, a veterinary doctor, a veterinary hospital authority, a veterinary lab, a veterinary service blogger, veterinary pharmacist and the like. In such embodiment, the one or more veterinary services may include, but not limited to, a health check-up service for the cattle, a diagnostic test service for the cattle, a nutritional consultation service for the cattle and the like. The one or more veterinary service providers upon analysis of the health state of the cattle are notified in real-time for providing corresponding one or more veterinary services through the integrated platform.
[0029] FIG. 3 is a block diagram of an exemplary system (100) for cattle health monitoring in accordance with an embodiment of the present disclosure. The system (100) is an automated, IoT-based health monitoring system designed to monitor the health of cattle. The system (100) is composed of hardware devices, a cloud system, an end-user application, and innovative techniques of data measurements and data analysis. The system (100) is useful for real-time tracking and health monitoring of the cattle of a cattle farm from a remote environment. Considering an example, wherein a dairy farm has large population of dairy cows. The large population of the dairy cows of the cattle farm has ineffective breeding activity and gradually with continuous degradation of the breeding activity, milk productivity by remaining number of the dairy cows also gets affected. One or more stockmen of the cattle farm are also unable to manage and share health information of the large population of the dairy cows. In order to overcome and mange such aforementioned issues of the cattle farm, computerised health monitoring system (100) is deployed for managing day to day activity of the cattle farm. The system (100) helps in handling, tracking and health monitoring of the large population of the dairy cows from the remote environment without involving manual intervention.
[0030] For example, suppose the cattle farm has 50 dairy cows (105), then the system (100) is capable of monitoring each of the 50 dairy cows individually. Each of the dairy cows (105) of the cattle farm are tagged with a cattle attribute tracking device (110). In the example used herein, the cattle attribute tracking device includes a neck collar. The neck collar is a wearable device for the cattle which includes a plurality of sensing devices, a battery, a microcontroller and a wireless transceiver. The neck collar also includes a radium light strap which is visible at night in absence of electricity. For example, the plurality of sensing devices may include at least one of a triaxial accelerometer, a magnetometer, a positioning sensor, a gyroscope, a temperature sensor or a combination thereof. Again, the wireless transceiver may include a Wi-Fi (wireless fidelity) transceiver for transmitting cattle attribute data to a remote server.
[0031] The system (100) also includes a cattle attribute data processing subsystem (120) located on the remote server. For example, the remote server may include a cloud server (125). The cloud server (125) may include a cloud storage repository (128) which includes information about the one or more stockmen such as identification number, name, credentials, information of the cattle farm such as size, GPS coordinates, information of the number of dairy cows for example cow id, group number, information of the cattle attribute tracking device for example device id, mac address, the cattle attribute data and the like. The cattle attribute data processing subsystem (120) receives the cattle attribute data representative of the plurality of the plurality of behavioural attributes and a plurality of physiological attributes of the cattle via a communication gateway such as Wi-Fi gateway (135). For example, the plurality of behavioural attributes received may include, but not limited to, a posture attribute, a grazing habit, a grazing pattern, a feeding duration, a rumination, a drinking habit, a migration pattern, a sleeping schedule, a lying time, a reproductive activity, a congregation activity, a proximity to a neighbouring animal, a proximity of a stationary device or a combination thereof. Similarly, the plurality of physiological attributes may include, but not limited to, a temperature rate, a heart rate, a urination rate, a respiration rate, a lactation duration, a bowel movement, a body measurement, a calving activity or a combination thereof.
[0032] Once, the cattle attribute data is received, the cattle attribute data processing subsystem filters the cattle attribute data received in one or more formats into a structured format of cattle attribute data by using a data filtration technique. The data filtration technique used herein, filters raw data received from the cattle attribute tracking device by removing one or more noises, duplicate values, null values and the like. For example, the data filtration technique may include a median filtering technique, a Kalman filtering technique or a low pass filtering technique.
[0033] Upon data filtration, a cattle health analysis subsystem (130) hosted on the server, selects one or more optimal features from the structured format of the cattle attribute data for a predetermined time interval by using a feature selection technique. For example, the feature selection technique may include but not limited to, a chi-squared feature selection technique, a Pearson correlation feature selection technique, a recursive feature elimination technique, a lasso feature selection technique, a tree-based feature selection technique. The feature selection technique helps in extracting relevant features from huge volume of data ad further helps in accurate and efficient data analysis. The cattle health analysis subsystem also evaluates one or more attribute metric of each of the one or more optimal features selected from the cattle attribute data for the predetermined time interval. Each of the one or more attribute values collected for each of the corresponding one or more optimal features over the predetermined time interval are further evaluated using the computation technique to obtain the one or more attribute metric. For example, the computation technique may include at least one of a sum, an average, a median or a mode for evaluation of the one or more attribute metric for the predetermined time interval. In the example used herein, the predetermined time interval may include a period of ten days.
[0034] Upon evaluation of the computation metric, the cattle health analysis subsystem (130) compares the one or more attribute metric of each of the one or more optimal features evaluated for the predetermined time interval with corresponding one or more historical attribute metric records associated with the cattle. The cattle health analysis subsystem also detects existence of one or more health associated abnormalities of the cattle based on a comparison of the one or more attribute metric with the one or more historical attribute metric records. For example, if the temperature metric of the dairy cow for the period of ten days is higher than the historical average temperature of the dairy cow, then the one or more health associated abnormalities such as fever or prediction of onset of other diseases are determined in advance. Also, if the reproduction cycle of the dairy cow of a particular age group is found as irregular from the average historical reproduction cycle data upon analysis, then a health associated abnormality such as a delay in the reproduction cycle is detected. Again, for detailed health analysis through a computational approach, the cattle health analysis subsystem utilizes a trained health analysis classifier to analyse a health state of the cattle for informing one or more caretakers of the cattle based on the existence of the one or more health associated abnormalities detected. Here, the trained health analysis classifier may include a decision tree classifier implemented based on the machine learning technology. Again, the health state of the cattle may include a healthy state of the cattle, an unhealthy state of the cattle, a pre-diseased state of the cattle and the like.
[0035] Once, the health state of the cattle is analysed, a cattle health recommendation generation subsystem (140) generates a plurality of health and nutrition-oriented recommendations for informing the one or more caretakers (145) of the cattle based on the health state of the cattle analysed. Here, the one or more caretakers may include, but not limited to, a cattle farm owner, the one or more stockmen, and a veterinary doctor. In the example used herein, as the dairy cow is detected with delay in the reproduction cycle and fever like condition, so the corresponding caretakers of the cow are informed in real-time with the plurality of health and nutrition-oriented recommendations via a message or a pop-up notification. For example, the plurality of health and nutrition-oriented recommendation may include at least one of a customized diet recommendation, a nutrition recommendation during pre-pregnancy and post-pregnancy period, a separate housing recommendation for fresh and sick animals of the cattle, a regular health examination recommendation and the like.
[0036] Further, the system (100) also includes a caretaker management subsystem (150) conducts and coordinates one or more training programs for the one or more caretakers to maintain wellbeing of the cattle based on the health state of the cattle analysed. The one or more training programs are conducted for mutual knowledge sharing by the one or more caretakers or one or more veterinary experts with the one or more caretakers to maintain the wellbeing of the cattle. Moreover, the system (100) also includes a veterinary service management subsystem (160) to collaborate one or more veterinary service providers within an integrated platform to provide one or more cattle welfare services upon identification of a requirement based on the health state of the cattle analysed. For example, the one or more veterinary service providers may include, but not limited to, a veterinary doctor, a veterinary hospital authority, a veterinary lab, a veterinary service blogger, veterinary pharmacist and the like. Here, the collaboration of the multiple veterinary service providers helps in easily contacting and outsourcing for providing an essential and desired veterinary service corresponding to the health state of the cattle readily without any hassle. Thus, the overall health monitoring system helps in tracking, analysing, detecting the health state and providing the desired veterinary service from an overall single integrated platform which not only saves time but also effort and expenses.
[0037] FIG. 4 illustrates a block diagram of a computer or a server of FIG. 1 in accordance with an embodiment of the present disclosure. The server (200) includes processor(s) (230), and memory (210) operatively coupled to the bus (220). The processor(s) (230), as used herein, means any type of computational circuit, such as, but not limited to, a microprocessor, a microcontroller, a complex instruction set computing microprocessor, a reduced instruction set computing microprocessor, a very long instruction word microprocessor, an explicitly parallel instruction computing microprocessor, a digital signal processor, or any other type of processing circuit, or a combination thereof.
[0038] The memory (210) includes several subsystems stored in the form of executable program which instructs the processor (230) to perform the method steps illustrated in FIG. 1. The memory (210) has following subsystem: a cattle attribute data processing subsystem (120), a cattle health analysis subsystem (130) and a cattle health recommendation generation subsystem (140).
[0039] The cattle attribute data processing subsystem (120) is configured to receive cattle attribute data representative of the plurality of the plurality of behavioural attributes and a plurality of physiological attributes of the cattle via a communication protocol. The cattle attribute data processing subsystem (120) is also configured to filter the cattle attribute data received in one or more formats into a structured format of cattle attribute data by using a data filtration technique. The cattle health analysis subsystem (130) is configured to select one or more optimal features from the structured format of the cattle attribute data for a predetermined time interval upon filtering by using a feature selection technique. The cattle health analysis subsystem (130) is also configured to evaluate one or more attribute metric of each of the one or more optimal features selected from the cattle attribute data for the predetermined time interval. The cattle health analysis subsystem (130) is also configured to compare the one or more attribute metric of each of the one or more optimal features evaluated for the predetermined time interval with corresponding one or more historical attribute metric records associated with the cattle. The cattle health analysis subsystem (130) is also configured to detect existence of one or more health associated abnormalities of the cattle based on a comparison of the one or more attribute metric with the one or more historical attribute metric records. The cattle health analysis subsystem (130) is also configured to analyse a health state of the cattle for informing one or more caretakers of the cattle based on the existence of the one or more health associated abnormalities detected. The cattle health recommendation generation subsystem (140) is configured to generate a plurality of health and nutrition-oriented recommendations for the one or more caretakers of the cattle based on the health state of the cattle analysed.
[0040] The bus (220) as used herein refers to be internal memory channels or computer network that is used to connect computer components and transfer data between them. The bus (220) includes a serial bus or a parallel bus, wherein the serial bus transmits data in bit-serial format and the parallel bus transmits data across multiple wires. The bus (220) as used herein, may include but not limited to, a system bus, an internal bus, an external bus, an expansion bus, a frontside bus, a backside bus and the like.
[0041] FIG. 5 is a flow chart representing the steps involved in a method (300) for cattle health monitoring of FIG. 1 in accordance with the embodiment of the present disclosure. The method (300) includes tracking, by a cattle attribute tracking device, a plurality of behavioural attributes and a plurality of physiological attributes of the cattle in step 310. In one embodiment, tracking the plurality of behavioural attributes and the plurality of physiological attributes of the cattle may include tracking the plurality of behavioural attributes and the plurality of physiological attributes by the cattle attribute tracking device including at least one of a neck band, an ear tag, a tail tag, an ankle tag or a combination thereof. In such embodiment, the cattle attribute tracking device may include a plurality of sensing devices including but not limited to, at least one of a triaxial accelerometer, a magnetometer, a positioning sensor, a gyroscope, a temperature sensor or a combination thereof.
[0042] The method (300) also includes receiving, by a cattle attribute data processing subsystem, cattle attribute data representative of the plurality of the plurality of behavioural attributes and a plurality of physiological attributes of the cattle via a communication protocol in step 320. In one embodiment, receiving the cattle attribute data representative of the plurality of behavioural attributes and the plurality of physiological attributes of the cattle may include receiving the plurality of behavioural attributes including, but not limited to, a posture attribute, a grazing habit, a grazing pattern, a feeding duration, a rumination, a drinking habit, a migration pattern, a sleeping schedule, a lying time, a reproductive activity, a congregation activity, a proximity to a neighbouring animal, a proximity of a stationary device or a combination thereof. In another embodiment, receiving the plurality of physiological attributes of the cattle may include receiving at least one of a temperature rate, a heart rate, a urination rate, a respiration rate, a lactation duration, a bowel movement, a body measurement, a calving activity or a combination thereof. In some embodiment, receiving the plurality of behavioural attributes and the plurality of physiological attributes of the cattle via the communication protocol may include receiving the plurality of behavioural attributes and the plurality of physiological attributes of the cattle via Bluetooth, RFID, NFC, Wi-fi and the like.
[0043] The method (300) also includes filtering, by the cattle attribute data processing subsystem, the cattle attribute data received in one or more formats into a structured format of cattle attribute data by using a data filtration technique in step 330. In one embodiment, filtering the cattle attribute data received in the one or more formats may include filtering the cattle attribute data by a median filtering technique, a Kalman filtering technique or a low pass filtering technique.
[0044] The method (300) also includes selecting, by a cattle health analysis subsystem, one or more optimal features from the structured format of the cattle attribute data for a predetermined time interval upon filtering by using a feature selection technique in step 340. In one embodiment, selecting the one or more optimal features from the structured format of the cattle attribute data for a predetermined time interval may include selecting the one or more optimal features from the structured format of the cattle attribute data by using a chi-squared feature selection technique, a Pearson correlation feature selection technique, a recursive feature elimination technique, a lasso feature selection technique, a tree-based feature selection technique.
[0045] The method (300) also includes evaluating, by the cattle health analysis subsystem, one or more attribute metric of each of the one or more optimal features selected from the cattle attribute data for the predetermined time interval in step 350. In one embodiment, evaluating the one or more attribute metric of each of the one or more optimal features may include evaluating the one or more attribute metric of each of the one or more optimal features by utilization of a computation technique such as at least one of a sum, an average, a median or a mode. The method (300) also includes comparing, by the cattle health analysis subsystem, the one or more attribute metric of each of the one or more optimal features evaluated for the predetermined time interval with corresponding one or more historical attribute metric records associated with the cattle in step 360. In one embodiment, the predetermined time interval may include, but not limited to, an hour, a day, a week, a period of ten days, a period of fifteen days, a month and the like.
[0046] The method (300) also includes detecting, by the cattle health analysis subsystem, existence of one or more health associated abnormalities of the cattle based on a comparison of the one or more attribute metric with the one or more historical attribute metric records in step 370. In one embodiment, detecting the existence of the one or more health associated abnormalities of the cattle may include detecting at least one of delay in reproduction cycle of the cattle, one or more diseases or a combination thereof.
[0047] The method (300) also includes utilising, by the cattle health analysis subsystem, a trained health analysis classifier to analyse a health state of the cattle for informing one or more caretakers of the cattle based on the existence of the one or more health associated abnormalities detected in step 380. In one embodiment, utilising the trained health analysis classifier to analyse the health state of the cattle may include utilising a machine learning technology-based classifier. In such embodiment, the machine learning technology-based classifier may include, but not limited to, a decision tree classifier, a random forest classifier, a support vector machine (SVM) classifier, an artificial neural network (ANN) classifier and the like. In some embodiment, utilizing the trained health analysis classifier to analyse the health state of the cattle may include utilizing the health analysis classifier to analyse a healthy state of the cattle, an unhealthy state of the cattle, a pre-diseased state of the cattle and the like.
[0048] The method (300) also includes generating, by a cattle health recommendation generation subsystem, a plurality of health and nutrition-oriented recommendations for informing the one or more caretakers of the cattle based on the health state of the cattle analysed in step 390. In one embodiment, generating the plurality of health and nutrition-oriented recommendations for informing the one or more caretakers of the cattle may include generating the plurality of health and nutrition-oriented recommendation including at least one of a customized diet recommendation, a nutrition recommendation during pre-pregnancy and post-pregnancy period, a separate housing recommendation for fresh and sick animals of the cattle, a regular health examination recommendation and the like.
[0049] In a specific embodiment, the method (300) further includes conducting, by a caretaker management subsystem, and coordinating one or more training programs for the one or more caretakers to maintain wellbeing of the cattle based on the health state of the cattle analysed. In one embodiment, the one or more training programs are conducted for mutual knowledge sharing by the one or more caretakers to maintain the wellbeing of the cattle. In another embodiment, the one or more training programs are conducted for knowledge sharing by one or more veterinary experts with the one or more caretakers to maintain the wellbeing of the cattle.
[0050] In a particular embodiment, the method (300) further includes collaborating, by a veterinary service management subsystem, one or more veterinary service providers within an integrated platform to provide one or more cattle welfare services upon identification of a requirement based on the health state of the cattle analysed. In one embodiment, collaborating the one or more service providers may include collaborating the one or more veterinary service providers including, but not limited to, a veterinary doctor, a veterinary hospital authority, a veterinary lab, a veterinary service blogger, veterinary pharmacist and the like. In such embodiment, the one or more veterinary services may include, but not limited to, a health check-up service for the cattle, a diagnostic test service for the cattle, a nutritional consultation service for the cattle and the like.
[0051] Various embodiments of the present disclosure provide an internet of things technology-based health monitoring system which collects real-time attributes data of the cattle and performs real-time analysis from a remote environment without involving manual intervention. Thus, helps in saving time and effort.
[0052] Moreover, the present disclosed system includes a systematised approach by utilising a classification technique for detection of the one or more health associated abnormalities of the cattle which further helps in avoiding human errors generated during manual observation of the cattle health condition.
[0053] Furthermore, the present disclosed system also provides health and nutrition-oriented recommendations to the one or more caretakers in real-time which helps in maintaining well-being of the cattle easily without any difficulty. Also, the recommendations generated by the system considers valuable opinions of the veterinary experts and customises the recommendation by considering each of the health state of the cattle.
[0054] It will be understood by those skilled in the art that the foregoing general description and the following detailed description are exemplary and explanatory of the disclosure and are not intended to be restrictive thereof.
[0055] While specific language has been used to describe the disclosure, any limitations arising on account of the same are not intended. As would be apparent to a person skilled in the art, various working modifications may be made to the method in order to implement the inventive concept as taught herein.
[0056] The figures and the foregoing description give examples of embodiments. Those skilled in the art will appreciate that one or more of the described elements may well be combined into a single functional element. Alternatively, certain elements may be split into multiple functional elements. Elements from one embodiment may be added to another embodiment. For example, the order of processes described herein may be changed and are not limited to the manner described herein. Moreover, the actions of any flow diagram need not be implemented in the order shown; nor do all of the acts need to be necessarily performed. Also, those acts that are not dependent on other acts may be performed in parallel with the other acts. The scope of embodiments is by no means limited by these specific examples.