Abstract:
Certain embodiments of this disclosure include methods and devices for adjusting the precision of location information. According to one embodiment, a method is provided. The method may include: obtaining a request for location information from an application; determining that the location information needs to be adjusted; obtaining the location information; adjusting the location information, wherein the adjusting includes: (i) adding noise to the location information to obtain noisy location information, (ii) discretizing the noisy location information to obtain discretized location information, and (iii) hysteresizing the discretized location information to obtain adjusted location information. The adjusted location information may then be provided to the requesting application.
Abstract:
Aspects of the disclosure relate generally to localizing mobile devices. In one example, a first location method associated with a first accuracy value may be used to estimate a location of the mobile device. A confidence circle indicative of a level of confidence in the estimation of the location is calculated. The confidence circle may be displayed on a mobile device. When other location methods become available, the size of the displayed confidence circle may be expanded based on information from an accelerometer of the client device or the accuracy of the other available location methods. This may be especially useful when the mobile device is transitioning between areas which are associated with different location methods that may be more or less accurate.
Abstract:
Aspects of the disclosure relate generally to localizing mobile devices. In one example, a first location method associated with a first accuracy value may be used to estimate a location of the mobile device. A confidence circle indicative of a level of confidence in the estimation of the location is calculated. The confidence circle may be displayed on a mobile device. When other location methods become available, the size of the displayed confidence circle may be expanded based on information from an accelerometer of the client device or the accuracy of the other available location methods. This may be especially useful when the mobile device is transitioning between areas which are associated with different location methods that may be more or less accurate.
Abstract:
A wearable computing device is described that detects an indication of movement associated with the wearable computing device when a user of the wearable computing device detected being located within a moving vehicle. Based at least in part on the indication of movement, a determination is made that the user of the wearable computing device is currently driving the moving vehicle. An operation is performed based on the determination that the user of the wearable computing device is currently driving the moving vehicle.
Abstract:
The present disclosure describes methods, systems, and apparatuses for determining the likelihood that two wireless scans of a mobile computing device were performed in the same location. The likelihood is determined by scanning for wireless networks with a computing device. The scanning includes a receiving a plurality of network attributes for each wireless networks within the range of the mobile computing device. Further, the likelihood is determined by comparing the plurality of network attributes from the scanning with a reference set of network attributes. The comparing of network attributes is used to determine an attribute comparison. Finally, the likelihood between a position associated with the reference set of network attributes and the computing device, based on the attribute comparison, determines a position associated with the network.
Abstract:
The present disclosure describes methods, systems, and apparatuses for determining the distance between two wireless scans of a mobile computing device. The distance is determined by scanning for wireless networks with a computing device. The scanning includes a receiving a plurality of network attributes for each wireless networks within the range of the mobile computing device. Further, the distance is determined by comparing the plurality of network attributes from the scanning with a reference set of network attributes. The comparing of network attributes is used to determine an attribute comparison. Finally, the distance between a position associated with the reference set of network attributes and the computing device, based on the attribute comparison, determines a position associated with the network.
Abstract:
A system and method for mapping an indoor environment. A client device may receive an indication of a starting point on a floor plan. The client device may prompt the user to travel in a particular direction and indicate when the user can no longer travel in that direction. As the user travels from the starting point in the designated direction, the client device may gather information about the indoor environment. For example, the client device may gather wireless signal strength data, cellular tower strength data, or video image data while the user travels in the designated direction. The client device may associate the gathered information with the path the user traveled from the starting point to the ending point. The client device may indicate the area for which valid location information is available based on the path the user traveled and the information the user collected.
Abstract:
Methods and apparatus are directed to geofencing-related heuristics for computing devices. A computing device with a plurality of sensors can receive a plurality of heuristics. Each heuristic can be configured to generate command(s) for the sensors based on one or more heuristic inputs. The heuristic input(s) can include an input related to a geofence. The computing device can receive a plurality of signals from the sensors. The computing device can determine, based on the plurality of signals, an activity class for the computing device. The activity class can specify an activity associated with the computing device. The computing device can select a heuristic from the plurality of heuristics at least based on the activity class. The computing device can execute the selected heuristic to generate the command(s) for the sensors.
Abstract:
Aspects of the present disclosure relate generally to using position information to provide advertisements. More specifically, wireless network access point data may be used to identify the position of a mobile device in an indoor space, which, in turn, may be used to identify products within the vicinity of the identified position. Based on the identified products, a server may send advertisements of the same or related products available at other locations to the mobile device.