Qualcomm Incorporated

Shankar Sadasivam

Leonard Henry Grokop

Ashwin Deepak Swaminathan

Jin Won Lee

Edward Harrison Teague

Li Ding

Mahesh Ramachandran

Carlos Manuel Puig

George Cherian

Santosh Paul Abraham

Vidya Narayanan

Disha Ahuja

Bhuwan Dhingra

Alexandros Manolakos

Sundar Subramanian

Sanjiv Nanda

Xinzhou Wu

Lei Zhang

Jonathan Kies

Aditya Narain Srivastava

Rashmi Kulkarni

Vitor R Carvalho

Vitor Rocha De Carvalho

Tadeusz Jarosinski

Abhijeet Bisain

Rajeev Jain

Sherman Sebastian Antao

Lukas Daniel Kuhn

Sichao Yang

Suhas H Sheshadri

Ryan Michael Carey

Jinwon Lee

Muralidhar Reddy Akula

Piero Zappi

Siddika Parlak Polatkan

Santiago Mazuelas

Qing Xu

Vitor Carvalho

Jonathan Karl Kies

Disclosed is an apparatus and method for classifying a motion state of a mobile device comprising: determining a first motion state associated with a highest probability value and with a first confidence level greater than a first threshold; entering the first motion state; while the first motion state is active, determining a second motion state associated with a highest probability value and with a second confidence level greater than the first threshold, the second motion state being different from the first motion state; determining whether the second motion state is to be entered; and in response to determining that the second motion state is to be entered, entering the second motion state.

Smartphone motion classifier

A method of operating a shared resource in a mobile device includes extracting a set of features from a plurality of subsystems of the mobile device. The set of features may be extracted from each subsystem of the plurality of subsystems requesting services from one or more shared resources of the mobile device. One or more parameter of the shared resource(s) may be determined based on the extracted set of features from the plurality of subsystems. The shared resource(s) may be operated based on the determined parameter(s).

Power state control of a mobile device

Disclosed is an apparatus and method for power efficient processor scheduling of features. In one embodiment, features may be scheduled for sequential computing, and each scheduled feature may receive a sensor data sample as input. In one embodiment, scheduling may be based at least in part on each respective feature's estimated power usage. In one embodiment, a first feature in the sequential schedule of features may be computed and before computing a second feature in the sequential schedule of features, a termination condition may be evaluated.

Sequential feature computation for power efficient classification

A method of controlling power consumption of a voice activation system in a mobile platform includes monitoring one or more sensors of the mobile platform. Next, it is determined whether a microphone of the mobile platform is concealed or obstructed in response to the monitoring of the one or more sensors. If so, the mobile platform transitions one or more components of the voice activation system from a normal power consumption power state to a low power consumption state.

Sensor activated power reduction in voice activated mobile platform

Methods, systems, computer-readable media, and apparatuses for determining indoor/outdoor state of a mobile device are presented. In some embodiments, a mobile device may maintain an indoor/outdoor state. The mobile device may include at least one first sensor and at least one second sensor, the first sensor associated with higher power consumption than the second sensor. The mobile device may gate off the first sensor and using the second sensor to obtain a sensor reading, if the second sensor can generate a reading indicative of the indoor/outdoor state of the mobile device. The mobile device may use the first sensor to obtain a sensor reading, if the second sensor cannot generate a reading indicative of the indoor/outdoor state of the mobile device. The mobile device may update the indoor/outdoor state of the mobile device based on a reading received from one of the first and the second sensors.

Low power always-on determination of indoor versus outdoor state

Systems and methods for applying and using context labels for data clusters are provided herein. A method described herein for managing a context model associated with a mobile device includes obtaining first data points associated with a first data stream assigned to one or more first data sources; assigning ones of the first data points to respective clusters of a set of clusters such that each cluster is respectively assigned ones of the first data points that exhibit a threshold amount of similarity and are associated with times within a threshold amount of time of each other; compiling statistical features and inferences corresponding to the first data stream or one or more other data streams assigned to respective other data sources; assigning context labels to each of the set of clusters based on the statistical features and inferences.

Context labels for data clusters

System and methods are disclosed to use information available on the state of mobile devices in a heuristics-based approach to improve motion state detection. In one or more embodiments, information on the WiFi connectivity of mobile devices may be used to improve the detection of the in-transit state. The WiFi connectivity information may be used with sensor signal such as accelerometer signals in a motion classifier to reduce the false positives of the in-transit state. In one or more embodiments, information that a mobile device is connected to a WiFi access point (AP) may be used as heuristics to reduce the probability of falsely classifying the mobile device in the in-transit state when mobile device is actually in the hand of a relatively stationary user. Information on the battery charging state or the wireless connectivity of the mobile devices may also be used to improve the detection of in-transit state.

In-transit detection using low complexity algorithm fusion and phone state heuristics

Systems and methods share context information on a neighbor aware network. In one aspect, a context providing device receives a plurality of responses to a discovery query from a context consuming device, and tailors services it offers to the context consuming device based on the responses. In another aspect, a context providing device indicates in its response to a discovery query which services or local context information it can provide to the context consuming device, and also a cost associated with providing the service or the local context information. In some aspects, the cost is in units of monetary currency. In other aspects, the cost is in units of user interface display made available to an entity associated with the context providing device in exchange for the services or local context information offered to the context consuming device.

Systems and methods for sharing context information in a neighbor aware network

Embodiments of the present invention are directed toward providing intelligent sampling strategies that make efficient use of an always-on camera. To do so, embodiments can utilize sensor information to determine contextual information regarding the mobile device and/or a user of the mobile device. A sampling rate of the always-on camera can then be modulated based on the contextual information.

Always-on camera sampling strategies

Disclosed is an apparatus and method for classifying a motion state of a mobile device. In one embodiment, accelerometer data representing acceleration components along orthogonal x, y, and z axes of the mobile device are collected. A presence or absence of a half-step frequency relationship between the accelerometer data is determined. Last, the motion state of the device is determined based at least in part on the presence or absence of the half-step frequency relationship.

Half step frequency feature for reliable motion classification

A context aware system, for use in a mobile device, includes a context change detector (CCD) coupled to a context classifier (CCL). The CCD is configured to receive sensor data and to detect a change in a current context state of the mobile device based on the received sensor data. The CCL is configured to transition from a low power consumption mode to a normal power consumption mode in response to the CCD detecting the change in the current context state. The CCL is further configured to determine a next context state of the mobile device while in the normal power consumption mode.

Context aware system with multiple power consumption modes

Sensor data from a sensor system of a mobile device may be used for determining a level of pressure exerted by a user on the mobile device. The sensor system may include one or more types of sensors, such as a microphone and one or more inertial sensors. The inertial sensors may include one or more gyroscopes and/or accelerometers. Based on the inertial sensor data, it may be determined whether and/or how the mobile device is being held. A process for determining a level of pressure exerted by a user on the mobile device may be adapted based, at least in part, on whether and/or how the mobile device is being held. The pressure-determining process may be adapted according to various other criteria, such as a position of a touch target in a display, ambient noise levels, etc.

Optimizing the use of sensors to improve pressure sensing

The disclosure is directed to modifying the operation of one or more hardware subsystems when a new context awareness service begins. An aspect determines a power budget for a plurality of operating context awareness services including the new context awareness service, wherein the power budget is based on a power requirement for each of the plurality of context awareness services, and wherein the power requirement for each of the plurality of context awareness services is based on power utilizations of the one or more hardware subsystems corresponding to the plurality of context awareness services, and allocates power resources to the one or more hardware subsystems based on importances of the plurality of context awareness services and/or the one or more hardware subsystems, wherein the allocation of the power resources is performed within the power budget.

Dynamic power management of context aware services

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

Systems and methods share context information on a neighbor aware network. A method for communicating data in a wireless communications network is disclosed. The method includes receiving, by a device, a first message from a station, decoding the message to determine service information, the service information identifying a service provided by the station, generating a second message, wherein the second message is generated to indicate the service provided by the station and service information of the device, and transmitting, by the device, the second message to a remote station.

Growing community of inventors

San Diego, CA, United States of America

Shankar Sadasivam