Abstract: A method of computing a heart rate value compensates for noise derived from the subject, the sensor, the transmission, and/or other variables that can lead to false R-peak detection or missed R-peak detection. The method computes an updated heart rate based on a window of approximately ten seconds of digitized ECG readings broadcast from a sensor. A new value is calculated approximately every second such that the window of ECG readings overlaps considerably between consecutive calculations. The method compensates for noisy data by discarding heart rate samples that differ by more than a threshold amount from a previously calculated heart rate value. The threshold is adjusted based on a standard deviation of differences between heart rate samples. Prior to calculating a heart rate value, a forward-looking, pre-filter logic may be applied in situations where the raw data has an extremely low signal-to-noise ratio.

Abstract: A method of computing a heart rate value compensates for noise derived from the subject, the sensor, the transmission, and/or other variables that can lead to false R-peak detection or missed R-peak detection. The method computes an updated heart rate based on a window of approximately ten seconds of digitized ECG readings broadcast from a sensor. A new value is calculated approximately every second such that the window of ECG readings overlaps considerably between consecutive calculations. The method compensates for noisy data by discarding heart rate samples that differ by more than a threshold amount from a previously calculated heart rate value. The threshold is adjusted based on a standard deviation of differences between heart rate samples. Prior to calculating a heart rate value, a forward-looking, pre-filter logic may be applied in situations where the raw data has an extremely low signal-to-noise ratio.

Abstract: An animal data compliance system includes one or more sources of animal data from one or more targeted individuals wherein the animal data is transmitted electronically. A collecting computing device gathers the animal data. One or more rules related to at least a portion of the animal data are created or modified based upon one or more terms. The one or more rules are associated with at least a portion of the animal data. At least a portion of animal data and the one or more rules are provided to one or more receiving computing devices. The one or more rules informs the one or more receiving computing devices of one or more permissions or restrictions related to the animal data. The one or more receiving computing devices take at least one action based upon the one or more rules.

Abstract: An animal data compliance system includes one or more sources of animal data from one or more targeted individuals wherein the animal data is transmitted electronically. A collecting computing device gathers the animal data. One or more rules related to at least a portion of the animal data are created or modified based upon one or more terms. The one or more rules are associated with at least a portion of the animal data. At least a portion of animal data and the one or more rules are provided to one or more receiving computing devices. The one or more rules informs the one or more receiving computing devices of one or more permissions or restrictions related to the animal data. The one or more receiving computing devices take at least one action based upon the one or more rules.

Abstract: An unmanned aerial vehicle-based data collection and distribution system includes a source of animal data that can be transmitted electronically. The source of animal data includes at least one sensor. The animal data is collected from at least one target individual. The system also includes an unmanned aerial vehicle that receives the animal data from the source of animal data as a first set of received animal data and a home station that receives the first set of received animal data. Characteristically, the unmanned aerial vehicle includes a transceiver operable to receive signals from the source of animal data and to send control signals to the source of animal data.

Abstract: An unmanned aerial vehicle-based data collection and distribution system includes a source of animal data that can be transmitted electronically. The source of animal data includes at least one sensor. The animal data is collected from at least one target individual. The system also includes an unmanned aerial vehicle that receives the animal data from the source of animal data as a first set of received animal data and a home station that receives the first set of received animal data. Characteristically, the unmanned aerial vehicle includes a transceiver operable to receive signals from the source of animal data and to send control signals to the source of animal data.

Abstract: An unmanned aerial vehicle-based data collection and distribution system includes a source of animal data that can be transmitted electronically. The source of animal data includes at least one sensor. The animal data is collected from at least one target individual. The system also includes an unmanned aerial vehicle that receives the animal data from the source of animal data as a first set of received animal data and a home station that receives the first set of received animal data. Characteristically, the unmanned aerial vehicle includes a transceiver operable to receive signals from the source of animal data and to send control signals to the source of animal data.

Abstract: A system for monetizing animal data includes a source of animal data that can be transmitted electronically. Characteristically, the source of animal data includes at least one sensor. An intermediary server receives and collects the animal data such that collected data has attached thereto metadata. The metadata includes at least one of the origination of the animal data or personal attributes of individuals from which the animal data originated. The intermediary server provides requested animal data to a data acquirer for consideration. The requested animal data may include simulated animal data. The intermediary server will also distribute at least a portion of the consideration to at least one stakeholder. The intermediary server includes a single computer server or a plurality of interacting computer servers.

Abstract: A speculation system for providing animal data and predictive indicators thereof includes one or more source sensors that collect animal data from targeted individuals. Characteristically, the animal data can be transmitted electronically. A computing subsystem receives the animal data. At least a portion of the animal data is transformed by the computing subsystem or the one or more sensors into a predictive indicator for a selected targeted individual or a group of targeted individuals. The computing subsystem operable to provide the predictive indicator and optionally at least a portion of the animal data to a user. Advantageously, a transmission subsystem providing transmission of the animal data to the computing subsystem.

Abstract: A method for generating and distributing simulated animal data includes a step of receiving a set of real animal data at least partially obtained from one or more sensors that receive, store, or send information related to one or more targeted individuals. Simulated animal data is generated from at least a portion of real animal data or one or more derivatives thereof. Finally, the simulated animal data is provided to a computing device. Characteristically, one or more parameters or variables of the one or more targeted individuals can be modified.

Abstract: A browser-based biological tracking system connects a computer to a set of wearable sensors. The system includes an application that is automatically downloaded from a server in response to a user accessing a webpage. The application sends data streams from the sensors to the server. The server calculates readings which are then displayed in a webpage. The set of sensors may include multiple types of sensors which utilize different communication interfaces. Some readings, called aggregate insights, are computed based on measurements from multiple sensors.

Abstract: A browser-based biological tracking system connects a computing device to a set of wireless communication-enabled sensors. The system includes a connection application that is automatically downloaded from a server in response to a user accessing a webpage. The connection application sends data streams from the sensors to the server. The server calculates readings which are then displayed in a webpage. The set of sensors may include multiple types of sensors which utilize different communication interfaces. Some readings, sometimes referred to as aggregate insights, are computed based on measurements from multiple sensors.

Abstract: An unmanned aerial vehicle-based data collection and distribution system includes a source of animal data that can be transmitted electronically. The source of animal data includes at least one sensor. The animal data is collected from at least one target individual. The system also includes an unmanned aerial vehicle that receives the animal data from the source of animal data as a first set of received animal data and a home station that receives the first set of received animal data. Characteristically, the unmanned aerial vehicle includes a transceiver operable to receive signals from the source of animal data and to send control signals to the source of animal data.

Abstract: A method of computing a heart rate value compensates for noise derived from the subject, the sensor, the transmission, and/or other variables that can lead to false R-peak detection or missed R-peak detection. The method computes an updated heart rate based on a window of approximately ten seconds of digitized ECG readings broadcast from a sensor. A new value is calculated approximately every second such that the window of ECG readings overlaps considerably between consecutive calculations. The method compensates for noisy data by discarding heart rate samples that differ by more than a threshold amount from a previously calculated heart rate value. The threshold is adjusted based on a standard deviation of differences between heart rate samples. Prior to calculating a heart rate value, a forward-looking, pre-filter logic may be applied in situations where the raw data has an extremely low signal-to-noise ratio.

Abstract: An unmanned aerial vehicle-based data collection and distribution system includes a source of animal data that can be transmitted electronically. The source of animal data includes at least one sensor. The animal data is collected from at least one target individual. The system also includes an unmanned aerial vehicle that receives the animal data from the source of animal data as a first set of received animal data and a home station that receives the first set of received animal data. Characteristically, the unmanned aerial vehicle includes a transceiver operable to receive signals from the source of animal data and to send control signals to the source of animal data.

Abstract: A method of computing a hear rate compensates for noise in data transmission that can lead to false R-peak detection or missed R-peak detection. The method computes an updated heart rate based on a window of approximately ten seconds of digitized ECG readings broadcast from a sensor. A new value is calculated approximately every second such that the window of ECG readings overlaps considerably between consecutive calculations. The method compensates for noisy data by discarding heart rate samples that differ by more than a threshold amount from a previously calculated heart rate value. The threshold is adjusted based on a standard deviation of differences between heart rate samples.