Abstract: A method of computing an orientation of a mobile device in a vehicle includes collecting accelerometer data from the mobile device. The accelerometer data are subdivided into frames, each frame being a quantity of time in which a sample data point is taken. Statistics are calculated for each frame, including (i) a mean and (ii) a standard deviation of the magnitude of the acceleration vectors. Device usage delimiters, marking start and end points of a coherent block, are computed, the coherent block being consecutive frames in which the mobile device stays in the same orientation relative to the vehicle. A gravity vector is estimated using the statistics in coherent blocks. A nullspace is computed from the gravity vector, the nullspace being a plane orthogonal to the gravity vector. The accelerometer data is projected onto the nullspace, resulting in an estimated orientation of the mobile device in the vehicle.

Abstract: A method of analyzing audio signals, such as for a drive monitoring system, includes recording an audio signal from a mobile device, the audio signal including a background audio stream and a residual audio signal. Communication with an audio database is performed to obtain a reference signal. If a match between the background audio stream and the reference signal is determined, a time alignment between the background audio stream and the reference is computed. At least a portion of the recorded audio signal is aligned with the reference signal using the time alignment. The background audio stream is canceled from the recorded audio signal, to result in the residual audio stream. A computer processor is used to determine a driving behavior factor from the residual audio stream.

Abstract: Techniques are described herein for classifying multiple device states using separate Bayesian classifiers. An example of a method described herein includes accessing sensor information of a device, wherein at least some of the sensor information is used in a first feature set and at least some of the sensor information is used in a second feature set; processing the first feature set using a first classification algorithm configured to determine a first proposed state of a first state type and a first proposed state of a second state type; processing the second feature set using a second classification algorithm configured to determine a second proposed state of the first state type and a second proposed state of the second state type; and determining a proposed state of the device as the first proposed state of the first state type and the second proposed state of the second state type.

Abstract: A method of computing an orientation of a mobile device in a vehicle includes collecting accelerometer data from the mobile device. The accelerometer data are subdivided into frames, each frame being a quantity of time in which a sample data point is taken. Statistics are calculated for each frame, including (i) a mean and (ii) a standard deviation of the magnitude of the acceleration vectors. Device usage delimiters, marking start and end points of a coherent block, are computed, the coherent block being consecutive frames in which the mobile device stays in the same orientation relative to the vehicle. A gravity vector is estimated using the statistics in coherent blocks. A nullspace is computed from the gravity vector, the nullspace being a plane orthogonal to the gravity vector. The accelerometer data is projected onto the nullspace, resulting in an estimated orientation of the mobile device in the vehicle.

Abstract: A method of analyzing audio signals, such as for a drive monitoring system, includes recording an audio signal from a mobile device, the audio signal including a background audio stream and a residual audio signal. Communication with an audio database is performed to obtain a reference signal. If a match between the background audio stream and the reference signal is determined, a time alignment between the background audio stream and the reference is computed. At least a portion of the recorded audio signal is aligned with the reference signal using the time alignment. The background audio stream is canceled from the recorded audio signal, to result in the residual audio stream. A computer processor is used to determine a driving behavior factor from the residual audio stream.

Abstract: In a multi-level power transmission scheme, an access point transmits at one power level, while repeatedly transmitting at a burst power level for short periods of time. For example, a femto cell may transmit a beacon with periodic high power bursts of short duration, while the femto cell transmit power also undergoes high power bursts aligned with the beacon bursts. In a network listen-based power control scheme, an access point listens for one or more parameters sent over-the-air by the network and then defines transmit power based on the received parameter(s). In some aspects, beacon transmit power may be set based on a defined outage radius parameter and the total received signal power on a channel. In some aspects, access point transmit power may be set based on a defined coverage parameter and the received energy associated with signals from access points of a certain type.

Abstract: In a multi-level power transmission scheme, an access point transmits at one power level, while repeatedly transmitting at a burst power level for short periods of time. For example, a femto cell may transmit a beacon with periodic high power bursts of short duration, while the femto cell transmit power also undergoes high power bursts aligned with the beacon bursts. In a network listen-based power control scheme, an access point listens for one or more parameters sent over-the-air by the network and then defines transmit power based on the received parameter(s). In some aspects, beacon transmit power may be set based on a defined outage radius parameter and the total received signal power on a channel. In some aspects, access point transmit power may be set based on a defined coverage parameter and the received energy associated with signals from access points of a certain type.

Abstract: Techniques are disclosed for using the hardware and/or software of the mobile device to obscure speech in the audio data before a context determination is made by a context awareness application using the audio data. In particular, a subset of a continuous audio stream is captured such that speech (words, phrases and sentences) cannot be reliably reconstructed from the gathered audio. The subset is analyzed for audio characteristics, and a determination can be made regarding the ambient environment.

Abstract: Techniques are described herein for classifying multiple device states using separate Bayesian classifiers. An example of a method described herein includes accessing sensor information of a device, wherein at least some of the sensor information is used in a first feature set and at least some of the sensor information is used in a second feature set; processing the first feature set using a first classification algorithm configured to determine a first proposed state of a first state type and a first proposed state of a second state type; processing the second feature set using a second classification algorithm configured to determine a second proposed state of the first state type and a second proposed state of the second state type; and determining a proposed state of the device as the first proposed state of the first state type and the second proposed state of the second state type.

Abstract: Techniques are disclosed for using the hardware and/or software of the mobile device to obscure speech in the audio data before a context determination is made by a context awareness application using the audio data. In particular, a subset of a continuous audio stream is captured such that speech (words, phrases and sentences) cannot be reliably reconstructed from the gathered audio. The subset is analyzed for audio characteristics, and a determination can be made regarding the ambient environment.

Abstract: A mobile device may determine a material-type of a surface proximate to the device and/or a distance between the device and the proximate surface, in at least one implementation. In some implementations, proximate material-type information may be used to estimate a distance between a mobile device and a proximate surface. A material class may also be determined for a proximate surface in some implementations. Various context-based applications are disclosed for material-type, material class, and/or distance information in connection with a mobile device.

Abstract: In a multi-level power transmission scheme, an access point transmits at one power level, while repeatedly transmitting at a burst power level for short periods of time. For example, a femto cell may transmit a beacon with periodic high power bursts of short duration, while the femto cell transmit power also undergoes high power bursts aligned with the beacon bursts. In a network listen-based power control scheme, an access point listens for one or more parameters sent over-the-air by the network and then defines transmit power based on the received parameter(s). In some aspects, beacon transmit power may be set based on a defined outage radius parameter and the total received signal power on a channel. In some aspects, access point transmit power may be set based on a defined coverage parameter and the received energy associated with signals from access points of a certain type.

Abstract: In a multi-level power transmission scheme, an access point transmits at one power level, while repeatedly transmitting at a burst power level for short periods of time. For example, a femto cell may transmit a beacon with periodic high power bursts of short duration, while the femto cell transmit power also undergoes high power bursts aligned with the beacon bursts. In a network listen-based power control scheme, an access point listens for one or more parameters sent over-the-air by the network and then defines transmit power based on the received parameter(s). In some aspects, beacon transmit power may be set based on a defined outage radius parameter and the total received signal power on a channel. In some aspects, access point transmit power may be set based on a defined coverage parameter and the received energy associated with signals from access points of a certain type.