Abstract: Techniques described herein provide multi-factor authentication based on positioning data. Generally described, configurations disclosed herein enable a system to authorize a particular action using positioning data, and possibly other data, associated with an identity. For example, when a user wishes to change a password or access a secured account, the system can authenticate a user if a device associated with the user is located in the secure area. The system can authenticate a user if a requested operation and/or a predetermined pattern of movement associated with the user is detected. For instance, the system allows the user to change the password when the user's computer has followed a predetermined pattern of movement, and when one or more verification procedures meets one or more criteria while the location of the computing device is within the predetermined area.

Abstract: Techniques described herein provide multi-factor authentication based on positioning data. Generally described, configurations disclosed herein enable a system to authorize a particular action using positioning data, and possibly other data, associated with an identity. For example, when a user wishes to change a password or access a secured account, the system can authenticate a user if a device associated with the user is located in the secure area. The system can authenticate a user if a requested operation and/or a predetermined pattern of movement associated with the user is detected. For instance, the system allows the user to change the password when the user's computer has followed a predetermined pattern of movement, and when one or more verification procedures meets one or more criteria while the location of the computing device is within the predetermined area.

Abstract: Techniques described herein provide location-based access control to secured resources. Generally described, configurations disclosed herein enable a system to dynamically modify access to secured resources based on one or more location-related actions. For example, techniques disclosed herein can enable a computing system to control access to resources such as computing devices, display devices, secured locations, and secured data. In some configurations, the techniques disclosed herein can enable controlled access to secured resources based, at least in part, on an invitation associated with a location and positioning data indicating a location of a user.

Abstract: Techniques described herein provide multi-factor authentication based on positioning data. Generally described, configurations disclosed herein enable a system to authorize a particular action using positioning data, and possibly other data, associated with an identity. For example, when a user wishes to change a password or access a secured account, the system can authenticate a user if a device associated with the user is located in the secure area. The system can authenticate a user if a requested operation and/or a predetermined pattern of movement associated with the user is detected. For instance, the system allows the user to change the password when the user's computer has followed a predetermined pattern of movement, and when one or more verification procedures meets one or more criteria while the location of the computing device is within the predetermined area.

Abstract: A system and method for calculating a position in response to a position request. Observed beacon data associated with the request is used to select a calculation method based on available data for a venue and device capabilities. If sufficient venue data based on previously verified beacon positions is available, a position calculation can resolve floor and venue information. If insufficient previously observed data is available for a venue, the position is calculated using 2D data based on GPS observations. Following the choice a calculation model, the calculation position is returned in response to the position request.

Abstract: Techniques described herein provide multi-factor authentication based on positioning data. Generally described, configurations disclosed herein enable a system to authorize a particular action using positioning data, and possibly other data, associated with an identity. For example, when a user wishes to change a password or access a secured account, the system can authenticate a user if a device associated with the user is located in the secure area. The system can authenticate a user if a requested operation and/or a predetermined pattern of movement associated with the user is detected. For instance, the system allows the user to change the password when the user's computer has followed a predetermined pattern of movement, and when one or more verification procedures meets one or more criteria while the location of the computing device is within the predetermined area.

Abstract: The description relates to receiver gain offset. One example can obtain data sensed by a mobile device at a position. The example can evaluate the sensed data and survey data to identify a venue proximate to the position. The survey data of the venue can be organized into regions and then individual regions can be organized into sub-regions. The example can compare signal strengths of the sensed data to signal strengths of the survey data to identify the position relative to an individual region. The comparison can utilize a receiver gain offset estimation between the mobile device and another device that acquired the survey data. The example can refine the receiver gain offset estimation and attempt to identify the position relative to an individual sub-region within the individual region utilizing the refined receiver gain offset estimation.

Abstract: A system and method for calculating a position in response to a position request. Observed beacon data associated with the request is used to select a calculation method based on available data for a venue and device capabilities. If sufficient venue data based on previously verified beacon positions is available, a position calculation can resolve floor and venue information. If insufficient previously observed data is available for a venue, the position is calculated using 2D data based on GPS observations. Following the choice a calculation model, the calculation position is returned in response to the position request.

Abstract: Techniques described herein provide multi-factor authentication based on positioning data. Generally described, configurations disclosed herein enable a system to authorize a particular action using positioning data, and possibly other data, associated with an identity. For example, when a user wishes to change a password or access a secured account, the system can authenticate a user if a device associated with the user is located in the secure area. The system can authenticate a user if a requested operation and/or a predetermined pattern of movement associated with the user is detected. For instance, the system allows the user to change the password when the user's computer has followed a predetermined pattern of movement, and when one or more verification procedures meets one or more criteria while the location of the computing device is within the predetermined area.

Abstract: Techniques described herein generate indoor map data. Generally described, configurations disclosed herein generate indoor map data using positioning data and interaction data associated with the movement and interactions of user computing devices. For example, techniques disclosed herein can enable a computing system to identify floors of a building, hallways, offices, doors, common areas, and other resources, including computing resources, based on the movement of users and the interaction of the users with resources within the indoor environment.

Abstract: A system and method for calculating a position in response to a position request. Observed beacon data associated with the request is used to select a calculation method based on available data for a venue and device capabilities. If sufficient venue data based on previously verified beacon positions is available, a position calculation can resolve floor and venue information. If insufficient previously observed data is available for a venue, the position is calculated using 2D data based on GPS observations. Following the choice a calculation model, the calculation position is returned in response to the position request.

Abstract: Techniques described herein provide location-based access control to secured resources. Generally described, configurations disclosed herein enable a system to dynamically modify access to secured resources based on one or more location-related actions. For example, techniques disclosed herein can enable a computing system to control access to resources such as computing devices, display devices, secured locations, and secured data. In some configurations, the techniques disclosed herein can enable controlled access to secured resources based, at least in part, on an invitation associated with a location and positioning data indicating a location of a user.

Abstract: A determination of whether a mobile computing device is indoors or outdoors can incorporate any of a variety of factors to make an efficient and accurate determination of indoor-outdoor status. Such a status can be useful for use in conjunction with positioning services. Features such as bounding boxes, activity determination, and the like can be used to strike a balance between power consumption and accuracy. A positive user experience with fewer false detections can result.

Abstract: Embodiments adjust device error radiuses associated with inferred device positions produced by positioning systems. Inferred beacon positions and associated beacon radiuses are accessed for beacons in a beacon fingerprint from an observing computing device. The beacon radiuses are associated with a pre-defined confidence level (e.g., an in-circle percentage). A Kalman filter is applied to at least one of the beacons using the inferred beacon positions and the beacon radiuses associated therewith to infer a device position for the computing device and to compute a device error radius for the inferred device position. The computed device error radius is adjusted as a function of the quantity of beacons input to the Kalman filter to achieve the pre-defined confidence level.

Abstract: Embodiments infer position information using captured content items. A computing device such as a mobile computing or a cloud service analyzes one or more content items to generate information describing the content items. For content items that include photographs, for example, the photographs are processed to identify faces, objects, places, text, etc. The generated information is compared to reference content items (e.g., image comparison), user data (e.g., calendar data, contact information, etc.), and/or public data (e.g., address information, event information, etc.) to identify at least one match. Location information associated with the matched reference content items, user data, and/or public data is obtained. A position is determined for the content items based on the location information obtained from the matched reference content item, user data, and/or public data.

Abstract: This document describes policies for digital rights management that enable distribution of full-function versions of applications that, while fully functional, have functions limited by an associated policy. A policy may be replaced or updated, thereby enabling use of previously limited functions without distribution of another version of the application.

Abstract: A determination of whether a mobile computing device is indoors or outdoors can incorporate any of a variety of factors to make an efficient and accurate determination of indoor-outdoor status. Such a status can be useful for use in conjunction with positioning services. Features such as bounding boxes, activity determination, and the like can be used to strike a balance between power consumption and accuracy. A positive user experience with fewer false detections can result.

Abstract: Embodiments infer position information using captured content items. A computing device such as a mobile computing or a cloud service analyzes one or more content items to generate information describing the content items. For content items that include photographs, for example, the photographs are processed to identify faces, objects, places, text, etc. The generated information is compared to reference content items (e.g., image comparison), user data (e.g., calendar data, contact information, etc.), and/or public data (e.g., address information, event information, etc.) to identify at least one match. Location information associated with the matched reference content items, user data, and/or public data is obtained. A position is determined for the content items based on the location information obtained from the matched reference content item, user data, and/or public data.

Abstract: A system and method for calculating a position in response to a position request. Observed beacon data associated with the request is used to select a calculation method based on available data for a venue and device capabilities. If sufficient venue data based on previously verified beacon positions is available, a position calculation can resolve floor and venue information. If insufficient previously observed data is available for a venue, the position is calculated using 2D data based on GPS observations. Following the choice a calculation model, the calculation position is returned in response to the position request.

Abstract: The description relates to receiver gain offset. One example can obtain data sensed by a mobile device at a position. The example can evaluate the sensed data and survey data to identify a venue proximate to the position. The survey data of the venue can be organized into regions and then individual regions can be organized into sub-regions. The example can compare signal strengths of the sensed data to signal strengths of the survey data to identify the position relative to an individual region. The comparison can utilize a receiver gain offset estimation between the mobile device and another device that acquired the survey data. The example can refine the receiver gain offset estimation and attempt to identify the position relative to an individual sub-region within the individual region utilizing the refined receiver gain offset estimation.