Qualcomm Incorporated

Tourmaline Labs, Inc.

Lukas Daniel Kuhn

Vidya Narayanan

Sanjiv Nanda

Leonard Henry Grokop

Jin Won Lee

Alexandros Manolakos

Li Ding

Shankar Sadasivam

Jinwon Lee

Steven Lloyd Pifko

Christoph Peter Stüber

Pawel Lukowicz

Embodiments of the present disclosure present systems, devices, methods, and computer readable medium for contextual driver evaluation. The disclosed techniques allow for collecting trip data from various sensors integrated in a mobile device for a user. The techniques include segregating the trip motion data into one or more segments associated with one or more populations with distinct features and characteristics. The trip data can be processed to identify event and behavior features that can be used to evaluate a driver's abilities in a contextually appropriate way. The information for a plurality of drivers can be compared to score the driver's ability amount a plurality of drivers.

System and methods for relative driver scoring using contextual analytics

Methods, systems, computer-readable media, and apparatuses for inferring context are provided. In one potential implementation, first context information associated with a first duration is identified, second context information is accessed to determine a context segmentation boundary; and the first context information and the second context information is then aggregated to generate an inferred segmented aggregated context. In a further implementation, the first context information is used to average inferred contexts, and the context segmentation boundary is used to reset a start time for averaging the first context information.

Aggregate context inferences using multiple context streams

One or more mobile devices make measurements while moving along a path. Each measurement may comprise a specific group of identifiers of wireless transmitters, and strengths of corresponding wireless signals. A set of measurements are made in a sequence along a path, and the subsets of the measurements are identified for satisfying a test on a value of a measure of similarity of measurements included in the subset. A new place of relevance is identified, by comparing the just-described subsets of the measurements with similar subsets of additional measurements (e.g. by clustering). Alternatively, a known place of relevance (e.g. having a label) is identified, by comparing the just-described subsets of the measurements with pre-computed model of measurements. Also, the just-described subsets of the measurements may be compared with corresponding subsets of measurements of another path, e.g. to identify common portions therein.

Discovering and automatically sizing a place of relevance

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.

Systems and methods for collecting and transmitting telematics data from a mobile device

Methods, apparatuses and articles of manufacture for use in a mobile device to determine whether a dynamic user profile is to transition from a first state to a second state based, at least in part, on one or more sensed indicators. The dynamic user profile may be indicative of one or more current inferable user behavior contexts for a user co-located with the mobile device. The mobile device may transition a dynamic user profile from a first state to a second state, in response to a determination that the dynamic user profile is to transition from the first state to the second state, and operatively affect one or more functions performed, at least in part, by the mobile device based, at least in part, on the transition of the dynamic user profile to the second state.

Determining a dynamic user profile indicative of a user behavior context with a mobile device

Methods, systems, computer-readable media, and apparatuses for utilizing relationships between places of relevance are presented. In some embodiments, a mobile computing device may obtain information indicative of a micro-place of relevance visited by the mobile device at a first time. The information may be based on measurements taken by the mobile device at the first time. Further, the mobile device may derive an attribute of the visit to the micro-place of relevance based on the obtained information and a place model that associates micro-places of relevance with macro-places of relevance.

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San Diego, CA, United States of America

Lukas Daniel Kuhn