Abstract: A method and apparatus (3) for operating a rotary milking platform (1) to maximise the number of animals milked per unit time. The milking platform (1) is rotated about a central vertical axis (4) by a variable speed motor (6), and comprises a plurality of animal accommodating locations (5) for the animals being milked. An entry position (7) and an exit position (9) accommodate animals to and from the platform (1). A position sensor (10) monitors the angular position of the platform (1). An RFID sensor (12) reads the identity of animals entering the platform (1). Historical data relating to milking time per milking session and the milk yield per animal per session is stored in an electronic memory (17). A microprocessor (15) reads signals from flow meters (14) which monitor the milk flow from milking clusters of each animal accommodating location (5).

Abstract: A method and apparatus (3) for operating a rotary milking platform (1) to maximise the number of animals milked per unit time. The milking platform (1) is rotated about a central vertical axis (4) by a variable speed motor (6), and comprises a plurality of animal accommodating locations (5) for the animals being milked. An entry position (7) and an exit position (9) accommodate animals to and from the platform (1). A position sensor (10) monitors the angular position of the platform (1). An RFID sensor (12) reads the identity of animals entering the platform (1). Historical data relating to milking time per milking session and the milk yield per animal per session is stored in an electronic memory (17). A microprocessor (15) reads signals from flow meters (14) which monitor the milk flow from milking clusters of each animal accommodating location (5).

Abstract: A rotary milking platform (1) comprises a platform (3) having a circular carrier beam (7) secured to the underside of the platform (3). The carrier beam (7) is supported on a plurality of support elements (10), each of which comprise a freely rotatable roller (35) which is configured to rollably engage an under surface (38) of the carrier beam (7). Each support element (10) comprises an anchor plate (27) adjustably mounted on a corresponding ground engaging element (20) which is secured to the ground. A carrier plate (40) is carried on four guide bolts (50) extending upwardly from the anchor plate (27). Side members (41) extending downwardly from the carrier plate (40) rotatably carry the roller (35). Compression springs (59) acting between abutment washers (55) secured to the guide bolts (50) and the carrier plate (40) urge the carrier plate (40) against heads (53) of the guide bolts (50).

Abstract: A device (1) for determining the mass flow rate of milk turbulently flowing with air in a pipe (2) in pulsed milk slugs comprises sampling a signal from a microphone (8) of the device (1) indicative of sonic signals produced by the milk flow. The sampled signals are read by a microprocessor (15) which applies a Fast Fourier Transform to the sampled signal to produce the frequency domain of the sampled signal. The microprocessor (15) is configured to compute the average energy value of the sampled signal in the frequency bandwidth of 6 kHz to 15 kHz during consecutive monitoring periods. The average energy values are inserted into a calibration equation, which may be a power law equation, a polynomial equation, a logarithmic equation or any other such suitable equation in order to convert the average energy value to a mass flow rate of the milk flowing through the pipe 2 during that predefined monitoring period.

Abstract: A rotary milking platform (3) comprises a plurality of stalls (5) and an RFID animal identifying system (9) for identifying animals entering the stalls (5) of the platform (3). A microprocessor (14) reads signals from an image capturing device (15) and computes a feature vector from the captured image of each animal. A plurality of reference feature vectors comprising respective matrices of metrics already derived from images of the respective animals captured by the image capturing device (15) are stored and cross-referenced with the identity of the respective animals. The microprocessor (14) compares computed feature vectors of each animal with the stored reference feature vectors until a best match has been determined with one of the reference feature vectors. The identity of the animal of that matching reference feature vector is then determined as the identity of the animal of that computed feature vector.

Abstract: An electronic monitoring device for attaching to an animal includes an NFC module facilitating wireless communication between a smart phone and the monitoring device, an accelerometer for monitoring acceleration of the head of the animal, and a microprocessor which determines various states of the animal from signals received from the accelerometer. The smart phone is programmed by a software application which allows an identifying code of the monitoring device to be read from the memory chip and cross-referenced in the smart phone with the identity of an animal, which can be inputted into the smart phone. Data relating to the states(s) of the animal can be read from the microprocessor through the NFC module into the smart phone. Additionally, data relating to the animal stored in a cloud server corresponding to the state or states of the animal is downloaded from the cloud server by the smart phone.

Abstract: A method and apparatus (3) for operating a rotary milking platform (1) to maximise the number of animals milked per unit time. The milking platform (1) is rotated about a central vertical axis (4) by a variable speed motor (6), and comprises a plurality of animal accommodating locations (5) for the animals being milked. An entry position (7) and an exit position (9) accommodate animals to and from the platform (1). A position sensor (10) monitors the angular position of the platform (1). An RFID sensor (12) reads the identity of animals entering the platform (1). Historical data relating to milking time per milking session and the milk yield per animal per session is stored in an electronic memory (17). A microprocessor (15) reads signals from flow meters (14) which monitor the milk flow from milking clusters of each animal accommodating location (5).

Abstract: A rotary milking platform (1) comprises a platform (3) having a circular carrier beam (7) secured to the underside of the platform (3). The carrier beam (7) is supported on a plurality of support elements (10), each of which comprise a freely rotatable roller (35) which is configured to rollably engage an under surface (38) of the carrier beam (7). Each support element (10) comprises an anchor plate (27) adjustably mounted on a corresponding ground engaging element (20) which is secured to the ground. A carrier plate (40) is carried on four guide bolts (50) extending upwardly from the anchor plate (27). Side members (41) extending downwardly from the carrier plate (40) rotatably carry the roller (35). Compression springs (59) acting between abutment washers (55) secured to the guide bolts (50) and the carrier plate (40) urge the carrier plate (40) against heads (53) of the guide bolts (50).

Abstract: A device (5) attached to the neck (6) of an animal (2) includes an accelerometer (28) which produces first and second signals indicative of movement of the animal (2) and the raised and lowered states of the head of the animal. A microprocessor (30) in the device (5) processes the first and second signals to detect ruminating, resting, feeding and three activity states of the animal during respective second predefined time periods of approximately 15 minutes duration. Data indicative of the states of the animal is stored by the microprocessor (30) in the device (5) and periodically transmitted to a cloud computer server which further processes the data to determine various health states and other issues of the animal.

Abstract: A data collection system (1) for monitoring the behaviour and states of a plurality of animals (2) comprises providing the animals (2) with respective monitoring devices (4) for monitoring the behaviour and states of the animals (2). A drone (7) comprising a mobile data collection device (5) secured thereto is configured to fly past the animals (2) at predefined data collection time intervals, typically of six hourly intervals. Each mobile data collection device (5) comprises a first secondary communications module (15) for wirelessly communicating with a second secondary communications module (32) located in the respective monitoring devices (4) for uploading data indicative of the behaviour and states of the animals (2) to a microcontroller (8) in the mobile data collection device (5). The uploaded data indicative of the behaviour and states of the respective animals (2) is written to and stored in a primary memory (17) of the mobile data collection device (5).

Abstract: A device (1) for determining the mass flow rate of milk turbulently flowing with air in a pipe (2) in pulsed milk slugs comprises sampling a signal from a microphone (8) of the device (1) indicative of sonic signals produced by the milk flow. The sampled signals are read by a microprocessor (15) which applies a Fast Fourier Transform to the sampled signal to produce the frequency domain of the sampled signal. The microprocessor (15) is configured to compute the average energy value of the sampled signal in the frequency bandwidth of 6 kHz to 15 kHz during consecutive monitoring periods. The average energy values are inserted into a calibration equation, which may be a power law equation, a polynomial equation, a logarithmic equation or any other such suitable equation in order to convert the average energy value to a mass flow rate of the milk flowing through the pipe 2 during that predefined monitoring period.

Abstract: A device (5) attached to the neck (6) of an animal (2) comprises an accelerometer (17) which produces first and second signals indicative of the raised and lowered state of the head (7) of the animal (2) and movement of the animal (2). A microprocessor (20) in the device (5) processes the first and second signals to determine if the animal is ruminating, resting, feeding or in a highly active state during respective second predefined time periods of approximately 15 minutes duration. Data indicative of the ruminating, resting, feeding and the highly active state of the animal is stored by the microprocessor (20) in the device (5) and is periodically wirelessly communicated to a base station computer which further processes the data to determine various health states of the animal.

Abstract: A device (5) attached to the neck (6) of an animal (2) comprises an accelerometer (28) which produces first and second signals indicative of movement of the animal (2) and the raised and lowered states of the head of the animal. A microprocessor (30) in the device (5) processes the first and second signals to detect ruminating, resting, feeding and three activity states of the animal during respective second predefined time periods of approximately 15 minutes duration. Data indicative of the states of the animal is stored by the microprocessor (30) in the device (5) and periodically transmitted to a cloud computer server which further processes the data to determine various health states and other issues of the animal.

Abstract: The mass flow rate of milk flowing in a pipe in pulsed milk slugs is determined by sampling a signal from a microphone indicative of sonic signals produced by the milk flow. A microprocessor applies a Fast Fourier Transform to the sampled signal to produce the frequency domain of the sampled signal. The microprocessor computes the average energy value of the sampled signal in a relevant frequency band during consecutive monitoring periods. The average energy values are inserted into a calibration equation to convert the average energy value to a mass flow rate. The total mass flow of milk flowing through the pipeline during a period T1-T2 is determined by integrating the determined mass flow rate of milk from T1-T2. Disengagement of a milking cluster from the animal teats during milking is determined when the monitored microphone signal transitions to a continuous relatively high energy noise signal indicative of air.

Abstract: An electronic monitoring device for attaching to an animal includes an NFC module facilitating wireless communication between a smart phone and the monitoring device, an accelerometer for monitoring acceleration of the head of the animal, and a microprocessor which determines various states of the animal from signals received from the accelerometer. The smart phone is programmed by a software application which allows an identifying code of the monitoring device to be read from the memory chip and cross-referenced in the smart phone with the identity of an animal, which can be inputted into the smart phone. Data relating to the states(s) of the animal can be read from the microprocessor through the NFC module into the smart phone. Additionally, data relating to the animal stored in a cloud server corresponding to the state or states of the animal is downloaded from the cloud server by the smart phone.

Abstract: An electronic monitoring device (20) for attaching to an animal (21) for determining a plurality of states of an animal (21). The monitoring device (20) comprises an NFC module (31) which facilitates wireless communication between a smart phone (32) and the monitoring device (20). The monitoring device (20) comprises an accelerometer (27) for monitoring acceleration of the head (25) of the animal (21). A microprocessor (28) determines various states of the animal from signals received from the accelerometer (27). The smart phone (32) is programmed by a software application which allows an identifying code of the monitoring device (20) to be read from the memory chip (36) and cross-referenced in the smart phone (32) with the identity of an animal, which can be inputted into the smart phone (32). Data relating to the state or states of the animal can be read from the microprocessor (28) through the NFC module (31) wirelessly into the smart phone (32).

Abstract: A device (1) for determining the mass flow rate of milk turbulently flowing with air in a pipe (2) in pulsed milk slugs comprises sampling a signal from a microphone (8) of the device (1) indicative of sonic signals produced by the milk flow. The sampled signals are read by a microprocessor (15) which applies a Fast Fourier Transform to the sampled signal to produce the frequency domain of the sampled signal. The microprocessor (15) is configured to compute the average energy value of the sampled signal in the frequency bandwidth of 6 kHz to 15 kHz during consecutive monitoring periods. The average energy values are inserted into a calibration equation, which may be a power law equation, a polynomial equation, a logarithmic equation or any other such suitable equation in order to convert the average energy value to a mass flow rate of the milk flowing through the pipe 2 during that predefined monitoring period.

Abstract: A device (5) attached to the neck (6) of an animal (2) comprises an accelerometer (28) which produces first and second signals indicative of movement of the animal (2) and the raised and lowered states of the head of the animal. A microprocessor (30) in the device (5) processes the first and second signals to detect ruminating, resting, feeding and three activity states of the animal during respective second predefined time periods of approximately 15 minutes duration. Data indicative of the states of the animal is stored by the microprocessor (30) in the device (5) and periodically transmitted to a cloud computer server which further processes the data to determine various health states and other issues of the animal.

Abstract: A device (5) attached to the neck (6) of an animal (2) comprises an accelerometer (17) which produces first and second signals indicative of the raised and lowered state of the head (7) of the animal (2) and movement of the animal (2). A microprocessor (20) in the device (5) processes the first and second signals to determine if the animal is ruminating, resting, feeding or in a highly active state during respective second predefined time periods of approximately 15 minutes duration. Data indicative of the ruminating, resting, feeding and the highly active state of the animal is stored by the microprocessor (20) in the device (5) and is periodically wirelessly communicated to a base station computer which further processes the data to determine various health states of the animal.

Abstract: An electronic monitoring device (20) for attaching to an animal (21) for determining a plurality of states of an animal (21). The monitoring device (20) comprises an NFC module (31) which facilitates wireless communication between a smart phone (32) and the monitoring device (20). The monitoring device (20) comprises an accelerometer (27) for monitoring acceleration of the head (25) of the animal (21). A microprocessor (28) determines various states of the animal from signals received from the accelerometer (27). The smart phone (32) is programmed by a software application which allows an identifying code of the monitoring device (20) to be read from the memory chip (36) and cross-referenced in the smart phone (32) with the identity of an animal, which can be inputted into the smart phone (32). Data relating to the state or states of the animal can be read from the microprocessor (28) through the NFC module (31) wirelessly into the smart phone (32).