Abstract:
A system comprises a plurality of sensors, a sensor processor, and a sampling rate engine. The sensor processor is coupled to an output of each sensor of the plurality of sensors. The sensor processor estimates user dynamics in response to a first output signal of a first sensor of the plurality of sensors. The sampling rate engine is coupled to an output of the sensor processor. The sampling rate engine determines a sampling rate value of a second sensor of the plurality of sensors in response to a user dynamics value from the sensor processor. The second sensor comprises a selectable sampling rate. The selectable sampling rate is configured in response to the sampling rate value determined by the sampling rate engine.
Abstract:
A system comprises a plurality of sensors, a sensor processor, and a sampling rate engine. The sensor processor is coupled to an output of each sensor of the plurality of sensors. The sensor processor estimates user dynamics in response to a first output signal of a first sensor of the plurality of sensors. The sampling rate engine is coupled to an output of the sensor processor./ The sampling rate engine determines a sampling rate value of a second sensor of the plurality of sensors in response to a user dynamics value from the sensor processor. The second sensor comprises a selectable sampling rate. The selectable sampling rate is configured in response to the sampling rate value determined by the sampling rate engine.
Abstract:
Method including detecting low user dynamics by a first MEMS sensor is provided. A first sensor determines sampling rate value corresponding to the low user dynamics. The first sensor sampling rate value is less than a second sensor sampling rate value corresponding to high user dynamics. A sampling rate of a second MEMS sensor is adjusted to the first sensor sampling rate value.
Abstract:
A system comprises a plurality of sensors, a sensor processor, and a sampling rate engine. The sensor processor is coupled to an output of each sensor of the plurality of sensors. The sensor processor estimates user dynamics in response to a first output signal of a first sensor of the plurality of sensors. The sampling rate engine is coupled to an output of the sensor processor. The sampling rate engine determines a sampling rate value of a second sensor of the plurality of sensors in response to a user dynamics value from the sensor processor. The second sensor comprises a selectable sampling rate. The selectable sampling rate is configured in response to the sampling rate value determined by the sampling rate engine.
Abstract:
Method including detecting low user dynamics by a first MEMS sensor is provided. A first sensor determines sampling rate value corresponding to the low user dynamics. The first sensor sampling rate value is less than a second sensor sampling rate value corresponding to high user dynamics. A sampling rate of a second MEMS sensor is adjusted to the first sensor sampling rate value.
Abstract:
A system comprises a plurality of sensors, a sensor processor, and a sampling rate engine. The sensor processor is coupled to an output of each sensor of the plurality of sensors. The sensor processor estimates user dynamics in response to a first output signal of a first sensor of the plurality of sensors. The sampling rate engine is coupled to an output of the sensor processor./ The sampling rate engine determines a sampling rate value of a second sensor of the plurality of sensors in response to a user dynamics value from the sensor processor. The second sensor comprises a selectable sampling rate. The selectable sampling rate is configured in response to the sampling rate value determined by the sampling rate engine.
Abstract:
Several methods and systems for location estimation are disclosed. In an embodiment, the method includes performing a primary wireless scan to identify a first set of access points at a user location associated with a first user location estimate. A secondary wireless scan is performed at pre-defined time intervals subsequent to the primary wireless scan. A set of access points is identified corresponding to each secondary wireless scan. The method further comprises detecting a presence or an absence of user motion based on a number of shared access points between the first set of access points and a set of access points corresponding to each secondary wireless scan. A current user location is estimated to be the first user location estimate if the user motion is detected to be absent, or a second user location estimate computed based on geolocation signals if the user motion is detected to be present.
Abstract:
Several methods and systems for location estimation are disclosed. In an embodiment, the method includes performing a primary wireless scan to identify a first set of access points at a user location associated with a first user location estimate. A secondary wireless scan is performed at pre-defined time intervals subsequent to the primary wireless scan. A set of access points is identified corresponding to each secondary wireless scan. The method further comprises detecting a presence or an absence of user motion based on a number of shared access points between the first set of access points and a set of access points corresponding to each secondary wireless scan. A current user location is estimated to be the first user location estimate if the user motion is detected to be absent, or a second user location estimate computed based on geolocation signals if the user motion is detected to be present.
Abstract:
At least some of the embodiments are methods including detecting low user dynamics by a first MEMS sensor, determining a first sensor sampling rate value corresponding to the low user dynamics wherein the first sensor sampling rate value is less than a second sensor sampling rate value corresponding to high user dynamics, and adjusting a sampling rate of a second MEMS sensor to the first sensor sampling rate value.
Abstract:
At least some of the embodiments are methods including detecting low user dynamics by a first MEMS sensor, determining a first sensor sampling rate value corresponding to the low user dynamics wherein the first sensor sampling rate value is less than a second sensor sampling rate value corresponding to high user dynamics, and adjusting a sampling rate of a second MEMS sensor to the first sensor sampling rate value.