Abstract:
Aspects of the subject matter described in this disclosure can be implemented in a fall detection device and method. One or more motion sensors can access a user's acceleration data. The acceleration data can be segmented using a segmentation algorithm to identify a potential fall event. The segmentation algorithm can determine a cumulative sum of the acceleration data, where the cumulative sum is based on acceleration values being greater than or less than an acceleration threshold value, and a potential fall event can be identified where the cumulative sum is greater than a cumulative sum threshold value. Statistical features can be extracted from the segmented acceleration data and aggregated, and a determination can be made as to whether the potential fall event is a fall event based at least in part on the statistical features.
Abstract:
A system and method are disclosed that may selectively switch a station's association from a first AP to a second AP based, at least in part, on whether an indication of first RSSI values for the first AP is greater than an indication of second RSSI values for the second AP by more than a difference value. For some embodiments, the difference value may be dynamically adjusted based, at least in part, on the first RSSI values, on a connection history of the station, and/or on a user selection.
Abstract:
Methods, systems, computer-readable media, and apparatuses for calendar matching of inferred contexts are described. In one potential embodiment, a mobile device may use context information to generate a calendar of inferred contexts. Label information from raw calendar data may be used to update an inferred context within a calendar of inferred contexts. Additionally, the label may be propagated to future contexts and entries in an inferred context calendar.
Abstract:
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.
Abstract:
A method for pruning weights of an artificial neural network based on a learned threshold includes determining a pruning threshold for pruning a first set of pre-trained weights of multiple pre-trained weights based on a function of a classification loss and a regularization loss. Weights are pruned from the first set of pre-trained weights when a first value of the weight is less than the pruning threshold. A second set of pre-trained weights of the multiple pre-trained weights is fine-tuned or adjusted in response to a second value of each pre-trained weight in the second set of pre-trained weights being greater than the pruning threshold.
Abstract:
Some disclosed systems may include a microphone system having two or more microphones, an interface system and a control system. In some examples, the control system may be capable of receiving, via the interface system, audio data from two or more microphones of the microphone system, of determining a gesture location based, at least in part, on the audio data and of controlling one or more settings of the system based on the gesture location.
Abstract:
Aspects of the subject matter described in this disclosure can be implemented in a fall detection device and method. One or more motion sensors can access a user's acceleration data. The acceleration data can be segmented using a segmentation algorithm to identify a potential fall event. The segmentation algorithm can determine a cumulative sum of the acceleration data, where the cumulative sum is based on acceleration values being greater than or less than an acceleration threshold value, and a potential fall event can be identified where the cumulative sum is greater than a cumulative sum threshold value. Statistical features can be extracted from the segmented acceleration data and aggregated, and a determination can be made as to whether the potential fall event is a fall event based at least in part on the statistical features.
Abstract:
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.
Abstract:
A system and method are disclosed that may selectively switch a station's association from a first AP to a second AP based, at least in part, on whether an indication of first RSSI values for the first AP is greater than an indication of second RSSI values for the second AP by more than a difference value. For some embodiments, the difference value may be dynamically adjusted based, at least in part, on the first RSSI values, on a connection history of the station, and/or on a user selection.
Abstract:
The disclosure is directed to using motion to reduce unnecessary scans for local wireless networks. An aspect determines whether or not a motion state change event of a user device indicates a change from a moving motion state to a stationary motion state, and if the motion state change event indicates a change from a moving motion state to a stationary motion state, ignoring the motion state change event. An aspect of the disclosure is directed to using motion to reduce latency of scanning for local wireless networks. An aspect determines whether or not a user device is in motion, determines whether or not a periodic scan timer has expired and/or a received signal strength indicator (RSSI) is below a threshold, and if the user device is in motion and the periodic scan timer has expired or the RSSI is below the threshold, scanning for a local wireless network.