Abstract:
Methods, systems and computer program products for user settlement detection are disclosed. A mobile device configured to perform an action immediately upon entering or exiting a geofenced environment can delay performing the action until a user of the mobile device has settled into the environment. The mobile device can detect a settled user state by observing the environment of the mobile device, including measuring one or more environment variables using one or more sensors of the mobile device. The mobile device can detect a settled user state even when the mobile device is in motion. The mobile device can perform the action upon detecting a settled user state.
Abstract:
Methods, program products, and systems of using a mobile WAP for location and context purposes are disclosed. In general, in one aspect, a server can estimate an effective location of a wireless access gateway using harvested data. The server can harvest location data from multiple mobile devices. The harvested data can include a location of each mobile device and an identifier of a wireless access gateway that is located within a communication range of the mobile device. In some implementations, the server can identify a mobile wireless access gateway based on a distance comparison. Data indicating the mobility of a wireless access gateway can be used by a mobile device to initiate one or more actions, including managing power of the mobile device, modifying entrance and exit conditions of virtual fences and determining a context of the mobile device.
Abstract:
Crowds of people within an environment can be modeled in real time. A multitude of mobile devices located within an environment can periodically transmit their geographical locations over networks to a remote server. The remote server can use these geographical locations to generate a current real-time model of a crowd of people who possess the mobile devices that transmitted the geographical locations. The remote server can transmit the model over networks back to the mobile devices. The mobile devices can use the received model to present useful information to the users of those mobile devices.
Abstract:
A wireless electronic device may include wireless communications circuitry and processing circuitry. The wireless communications circuitry may receive radio-frequency signals from external communications circuitry in a number of frequency channels of a communications band. The processing circuitry may gather received signal quality data such as receive signal strength indicator (RSSI) values from the radio-frequency signals received in each of the frequency channels. The processing circuitry may accumulate respective probability distributions of gathered RSSI values for each frequency channel and may compare each of the probability distributions to generate RSSI offset values for each frequency channel. The processing circuitry may gather additional RSSI values in one or more frequency channels and may adjust the additional RSSI values based on the associated RSSI offset values. The processing circuitry may use the adjusted RSSI values to determine an accurate location of the wireless electronic device.
Abstract:
Methods and computer products can provide personalized content based on historical interaction with a mobile device. A computing device can receive information about a user interaction with an application running on the mobile device at a first time and location. A type of the application can be identified by parsing a description of the application (e.g., using a natural language processing algorithm). An affinity model can be generated that associates the type of the application with the first time and/or location. At a second time and location, it can be determined that the second time corresponds to the first time and/or that the second location corresponds to the first location. Using the affinity model, the second time and/or location can be associated with the type of the application, and the mobile device may then display content related to the type of the application.
Abstract:
Systems, methods, and program products for determining a location of a calendar item are described. A mobile device can receive a calendar item including a description and a time. The mobile device can determine that, at the time specified in the calendar item, the mobile device is located at a location that is estimated to be significant to a user. The mobile device can store the description in association with the significant location. Upon receive a new calendar item containing at least one term in the description, the mobile device can predict that the user will visit the significant location at the time specified in the new calendar item. The mobile device can provide user assistance based on the prediction.
Abstract:
Systems, methods, and program products for providing services to a user by a mobile device based on the user's daily routine of movement. The mobile device determines whether a location cluster indicates a significant location for the user based on one or more hints that indicate an interest of the user in locations in the cluster. The mobile device can perform adaptive clustering to determine a size of area of the significant location based on how multiple locations converge in the location cluster. The mobile device can provide location-based services for calendar items, including predicting a time of arrival at an estimated location of a calendar item. The mobile device can provide various services related to a location of the mobile device or a significant location of the user through an application programming interface (API).
Abstract:
Crowd-sourced localized application usage data is collected from mobile devices at a usage location and sent to a network-based service. The network-based service analyzes the data to determine a single most relevant application correlated to the usage location. Once the most relevant application is determined, a recommendation for the application is sent to client devices operating at the usage location. In some implementations the data is processed to determine whether the usage location is a chained venue, a large venue or an event. Once the usage location has been determined, the most relevant application can be selected for recommendation.
Abstract:
Collocated access point (AP) harvest data is combined with accurate location-tagged harvest data to improve access point location estimates and to estimate the location of access points that could not be previously estimated.
Abstract:
A mobile device enables its user to retroactively “check in,” on social media, to locations to which the device has previously been. The mobile device automatically tracks the locations to which it goes during some time interval. As the mobile device goes to each location, the mobile device stores data that specifies that location. Following the time interval, and potentially in response to a request by the device's user to view the locations previously visited, the mobile device presents a list of at least some of the locations on its display. The device's user can select one or more of the presented locations. The selection of a location causes the mobile device to post, to an Internet-based social media service, information pertaining to the selected location. For example, such information can indicate that the device's user had been at the selected location.