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: 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 determines a plurality of scores for a road segment that are related to the total distance traveled when drivers traverse that road segment. The scores are displayed graphically to illustrate the usage of road segments. The scores are also used to determine which road segments to display on a map when determining which roads to display at a given zoom level for a map.

Abstract: Methods and systems for determining a location of a mobile device using a multi-modal Kalman filter are described. According to an example method, a mobile device may maintain multiple approximations of a location of a mobile device. Each approximation includes an estimated geographic location of the mobile device that is determined by filtering a respective subset of location estimates received by the mobile device using a respective Kalman filter, and one of the multiple approximations is designated as an active approximation. The method also involves receiving data indicating an estimate of a geographic location of the mobile device and, based on a distance between the estimate of the geographic location and a given approximation of the multiple approximations, updating the given approximation using the estimate of the geographic location. Additionally, the method involves providing for display a visual indication of an estimated geographic location associated with the active approximation.

Abstract: A map editing system for visually indicating the location of GPS devices on a map and identifying paths from the map. GPS data is received from a plurality of GPS devices. The data is filtered based parameters including the speed of the GPS devices. The filtered GPS data is displayed on a map using representations that visually indicate the location of the GPS devices that the data was received from. The representations can then be used for identifying and creating new paths on the map.

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 mobile computing device may be localized in an indoor area based on the strength of wireless network signals accessible in the indoor area from different access points. For efficiency, the localization may be performed in stages. In a first stage, a general geographic area, such as an “island” as will be described below, in which the mobile device is located is identified. In a second stage, an altitude or building level of the mobile device is identified. In a third stage, a position of the mobile device on the identified building level is determined. At least some of these stages of localization may utilize information received at the mobile device from surrounding access points. For example, the island on which the user is located may be determined by identifying at least one access point on that island. Further, decision trees may be executed using input related to a received signal strength from the surrounding access points, and outputs of the decision trees may indicate the device's location.

Abstract: Maps are created that display representations of GPS data generated from a plurality of GPS devices. The GPS data received from the GPS devices is embodied as a representation having descriptive features that visually indicate the location, direction of travel, and speed of travel of the GPS device, and the representation is associated with a road segment on the map. The display of the GPS data from a plurality of GPS devices can be used for editing information about roads on maps and determining preferred routes.

Abstract: A map editing system for visually indicating the location of GPS devices on a map and identifying paths from the map. GPS data is received from a plurality of GPS devices. The data is filtered based parameters including the speed of the GPS devices. The filtered GPS data is displayed on a map using representations that visually indicate the location of the GPS devices that the data was received from. The representations can then be used for identifying and creating new paths on the map.

Abstract: Decision trees may be built and executed to estimate an indoor location of a mobile device. In particular, a first attribute (e.g., received signal strength indication (RSSI) of one or more access points) is selected, and variations of that attribute throughout an indoor area are identified. These identified variations are mapped to the locations to generate a model. One or more decision trees are built based on the model, and an output of the decision trees estimates a location of a mobile device within the building. According to one aspect, a plurality of such decision trees may be built, and the outputs provided by the plurality of trees may be averaged to provide a more reliable result. Each of the plurality of trees may vary the attribute being analyzed, data values, or an order in which data is analyzed.

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: 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 present disclosure relate generally to indoor localization, for example, where GPS or other localization signals are unavailable. More specifically, aspects relate to using a particle filter in conjunction with a gyroscope and/or accelerometer to identify a current location of a client device with respect to a map. In one example, the map may be based upon a map including a series of walls representing locations where a user may not walk within a building. In another example, the map may be based upon a series of rails representing locations where a user may walk within a building.

Abstract: Aspects of the present disclosure relate generally to indoor localization, for example, where GPS or other localization signals are unavailable. More specifically, aspects relate to using a particle filter in conjunction with one or more orientation devices to identify a location of a client device with respect to a map of an indoor space. This location may then be used to identify the path of the client device through the indoor space.

Abstract: Aspects of the present disclosure relate generally to using position information to grant access. More specifically, wireless network access point data may be used to identify the location of a mobile device in an indoor space. If the identified location is associated with permission information, this information may be used by a permission device to grant or deny the user of the client device some right. For example, the permission information may be used to unlock a door, lock or unlock a feature on the mobile device, delay some action, etc.

Abstract: To localize a mobile device in an indoor area, labels are positioned at locations throughout the indoor area and signal strength is recorded at the label positions from different wireless network access points that are available in the indoor area. As a user traverses the indoor area with the mobile device, individual label identifiers are entered into the mobile device and the strength of the wireless network signals is recorded at each label position. The sampled wireless network signal strength and the corresponding label identifiers and positions are recorded to generate a mapping that identifies wireless network signal strength at each of the different label positions in the indoor area. The mapping may then be accessed to identify the locations of other mobile device users that subsequently enter the indoor area based on the wireless network signal strength from the different access points detected by the other mobile devices.

Abstract: Aspects of the present disclosure relate generally to indoor localization, for example, where GPS or other localization signals are unavailable. More particularly, the estimated location, and in some examples the estimated heading, of a client device may be displayed on a display of the client device. As the device is moved through the indoor space, its location and/or orientation may be estimated based on measurements from one or more orientation devices. Typically, as the client device moves through an indoor space, the location estimation may become less and less accurate. This may be addressed by allowing the user to correct the current location and/or heading. The correction may be logged by the client device and transmitted to a server for further processing.

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: Aspects of the disclosure relate to quality control of survey data used to generate and or supplement map information. A device may be walked through an indoor space in order to collect survey data (accelerometer, gyroscope, wireless network identifiers, etc.). The survey data is then transmitted to a server for further processing to identify the path (or the various locations) of the device in the indoor space. The path may be determined by referring to a map of the indoor location and a localization algorithm, for example, a particle filter or least squares optimizer. The path may be compared to other survey data and paths from the same indoor space as well as the map in order to provide an estimate of the quality of the localization produced for the survey data. Low quality survey data may be flagged for further review or used to make changes to the map.