Abstract:
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.
Abstract:
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.
Abstract:
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.
Abstract:
System and methods for performing context inference in a computing device are disclosed. In one embodiment, a method of performing context inference includes: determining, at a computing device, a first context class using context-related data from at least one data source associated with a mobile device; and determining, at the mobile device, a fusion class based on the first context class, the fusion class being associated with at least one characteristic that is common to the first context class and a second context class that is different from the first context class.
Abstract:
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 features 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.
Abstract:
Various arrangements for detecting a type of sound, such as speech, are presented. A plurality of audio snippets may be sampled. A period of time may elapse between consecutive audio snippets. A hypothetical test may be performed using the sampled plurality of audio snippets. Such a hypothetical test may include weighting one or more hypothetical values greater than one or more other hypothetical values. Each hypothetical value may correspond to an audio snippet of the plurality of audio snippets. The hypothetical test may further include using at least the greater weighted one or more hypothetical values to determine whether at least one audio snippet of the plurality of audio snippets comprises the type of sound.
Abstract:
Techniques are provided to infer a context associated with a mobile device based on aggregated data from a set of other mobile devices. The set of mobile devices can include mobile devices currently or previously near a location of the mobile device. Each mobile device in the set of other mobile devices can collect sensor data and infer a low-level context (e.g., "sitting" or "standing"). The low-level contexts can be aggregated. Based on the aggregated low-level contexts, a high-level context (e.g., "at a party" or "watching television") associated with the mobile device can be inferred or a low-level context associated with the mobile device can be refined.
Abstract:
Methods, systems, computer-readable media, and apparatuses for determining indoor/outdoor state of a mobile device are presented. In some embodiments, a sensor reading is obtained from a sensor accessible by the mobile device. Contemporaneous information related to a local condition associated with an area where the mobile device is located is obtained. At least the sensor reading and the information related to a local condition are provided as input to an indoor/outdoor detection model selected from a plurality of trained models. Based on the model, the mobile device is classified as indoors or outdoors.
Abstract:
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.