Abstract:
Apparatus and methods for changing one or more functional or operational aspects of a wireless device, such as upon the occurrence of a certain event. In one embodiment, the event comprises detecting that the wireless device is within range of one or more other devices. In another variant, the event comprises the wireless device associating with a certain access point. In this manner, various aspects of device functionality may be enabled or restricted (device “policies”). This policy enforcement capability is useful for a variety of reasons, including for example to disable noise and/or light emanating from wireless devices (such as at a movie theater), for preventing wireless devices from communicating with other wireless devices (such as in academic settings), and for forcing certain electronic devices to enter “sleep mode” when entering a sensitive area.
Abstract:
Methods, systems, and computer program product for location transition determination are described. A mobile device can use location fingerprint data and sensor readings to determine a transition of the mobile device into or out of a portion of a venue by using particle filters. When the mobile device determines that the mobile device is located at a first portion of the venue, e.g., on a given floor, the mobile device can introduce candidate locations, or particles, on a second portion of the venue and candidate locations outside of the venue. If estimated locations at the first portion of the venue do not converge, the mobile device can increase weight of the candidate locations that are outside of the first portion of the venue to detect possible transition to the second portion of the venue or to outside of the venue.
Abstract:
Coarse location estimation for mobile devices is disclosed for detecting mobile device presence at general locations of interest and switching operating modes and services for one or more location context aware applications. In some implementations, sensor data is received from a plurality of data sources at a location. For each data source, a first probability is estimated that the mobile device is at the location based on sensor data from the data sources. A second probability is estimated that the mobile device is not at the location based on sensor data from the data sources. The first and second estimated probabilities are statistically combined to generate a third estimated probability that the mobile device is at the location.
Abstract:
Methods, systems, and computer program product for prefetching location data based on predicted user behavior. A mobile device can request, from a user routine subsystem of the mobile device, a list of locations that a user of the mobile device routinely visits while the user carries the mobile device. The mobile device can determine a cluster of these locations that are within a specified distance between one another. The mobile device can request location data for these locations from a location server, even if the user is not at one of these locations. The location data can include a venue map and a venue location fingerprint. Upon detecting that the user entered a venue at one of these locations, the mobile device can determine a location of the user inside of the venue using the venue location fingerprint. The mobile device can then display the location on a venue map.
Abstract:
Methods, systems, and computer program product for prefetching location data based on predicted user behavior. A mobile device can request, from a user routine subsystem of the mobile device, a list of locations that a user of the mobile device routinely visits while the user carries the mobile device. The mobile device can determine a cluster of these locations that are within a specified distance between one another. The mobile device can request location data for these locations from a location server, even if the user is not at one of these locations. The location data can include a venue map and a venue location fingerprint. Upon detecting that the user entered a venue at one of these locations, the mobile device can determine a location of the user inside of the venue using the venue location fingerprint. The mobile device can then display the location on a venue map.
Abstract:
Coarse location estimation for mobile devices is disclosed for detecting mobile device presence at general locations of interest and switching operating modes and services for one or more location context aware applications. In some implementations, sensor data is received from a plurality of data sources at a location. For each data source, a first probability is estimated that the mobile device is at the location based on sensor data from the data sources. A second probability is estimated that the mobile device is not at the location based on sensor data from the data sources. The first and second estimated probabilities are statistically combined to generate a third estimated probability that the mobile device is at the location.
Abstract:
Apparatus and methods for changing one or more functional or operational aspects of a wireless device, such as upon the occurrence of a certain event. In one embodiment, the event comprises detecting that the wireless device is within range of one or more other devices. In another variant, the event comprises the wireless device associating with a certain access point. In this manner, various aspects of device functionality may be enabled or restricted (device “policies”). This policy enforcement capability is useful for a variety of reasons, including for example to disable noise and/or light emanating from wireless devices (such as at a movie theater), for preventing wireless devices from communicating with other wireless devices (such as in academic settings), and for forcing certain electronic devices to enter “sleep mode” when entering a sensitive area.
Abstract:
Apparatus and methods for changing one or more functional or operational aspects of a wireless device, such as upon the occurrence of a certain event. In one embodiment, the event comprises detecting that the wireless device is within range of one or more other devices. In another variant, the event comprises the wireless device associating with a certain access point. In this manner, various aspects of device functionality may be enabled or restricted (device “policies”). This policy enforcement capability is useful for a variety of reasons, including for example to disable noise and/or light emanating from wireless devices (such as at a movie theater), for preventing wireless devices from communicating with other wireless devices (such as in academic settings), and for forcing certain electronic devices to enter “sleep mode” when entering a sensitive area.
Abstract:
Apparatus and methods for changing one or more functional or operational aspects of a wireless device, such as upon the occurrence of a certain event. In one embodiment, the event comprises detecting that the wireless device is within range of one or more other devices. In another variant, the event comprises the wireless device associating with a certain access point. In this manner, various aspects of device functionality may be enabled or restricted (device “policies”). This policy enforcement capability is useful for a variety of reasons, including for example to disable noise and/or light emanating from wireless devices (such as at a movie theater), for preventing wireless devices from communicating with other wireless devices (such as in academic settings), and for forcing certain electronic devices to enter “sleep mode” when entering a sensitive area.
Abstract:
Methods, systems, and computer program product for deduplicating location fingerprint data for a venue are described. A system including a location server, or a mobile device, or both, can deduplicate the location fingerprint data. Deduplicating the location fingerprint data can include identifying correlated signal sources the signals of which are mutually dependent such that measurements of one signal source can be used to predict measurements of another. The system can determine a mutual information entropy value for each pair of signal sources, and identify the correlated signal sources based on high mutual information entropy value. The system can adjust weights of the correlated signal sources in location determination.