Abstract:
Methods, systems, and computer program product for determining a building floor level are described. A mobile device can use wireless signal sources and location fingerprint data to determine a level of a building floor on which the mobile device is located. The location fingerprint data can include or be associated with a list and a count of wireless signal sources previously detected on each floor. The mobile device can compare the list and count with wireless signal sources detected by the mobile device, and use results of the comparison to configure a statistical filter that determines a location of the mobile device. The mobile device can then determine the location, including a building floor level, using the statistical filter.
Abstract:
Methods, systems, and computer program products for correcting in-venue location estimation using structural information are described. A mobile device can use wireless location technologies and dead reckoning to determine an estimated location of the mobile device in a venue. The mobile device can compare the estimated location with a map of the venue. Upon determining that the estimated location conflicts with a structural constraint, the mobile device can adjust the location estimation using the structural information. Adjusting the location estimation can include adjusting a statistical filter that provides estimation of the location and changing a heading of the mobile device used in the dead reckoning.
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:
Survey data for an environment is used to predict the accuracy of a position estimate in the environment and whether or not more survey data may improve that accuracy. In some implementations, a user performs a site survey of an environment by observing the strengths of radio frequency signals at various survey points in the environment. An expected positioning accuracy of the surveyed environment can be determined using the new survey data collected and optionally historical survey data for the environment. The user can be informed about the usefulness of collecting additional survey data and/or the expected positioning accuracy in the environment.
Abstract:
Methods, systems, and computer program product for generating location fingerprint data for a venue are described. A sampling device surveying a venue can move inside the venue. While the sampling device moves, the sampling device can record environmental readings including, for example, strengths of signals from multiple radio signal sources. The sampling device can take the recording at fixed or various time intervals. Meanwhile, the sampling device can determine, based on a starting point and motion sensor readings, an estimated location of the mobile device for each time the sampling device takes the recordings. The sampling device can display a motion path of the estimated locations and a user interface item for receiving a user input for correcting the estimated locations. The sample device can tag the recorded environmental readings with the corrected locations, and submit the tagged readings to a server for determining a location fingerprint for the venue.
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
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.
Abstract:
Methods, systems, and computer program product for generating location fingerprint data for a venue are described. A sampling device surveying a venue can move inside the venue. While the sampling device moves, the sampling device can record environmental readings including, for example, strengths of signals from multiple radio signal sources. The sampling device can take the recording at fixed or various time intervals. Meanwhile, the sampling device can determine, based on a starting point and motion sensor readings, an estimated location of the mobile device for each time the sampling device takes the recordings. The sampling device can display a motion path of the estimated locations and a user interface item for receiving a user input for correcting the estimated locations. The sample device can tag the recorded environmental readings with the corrected locations, and submit the tagged readings to a server for determining a location fingerprint for the venue.
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.
Abstract:
Methods, systems, and computer program product for determining a building floor level are described. A mobile device can use wireless signal sources and location fingerprint data to determine a level of a building floor on which the mobile device is located. The location fingerprint data can include or be associated with a list and a count of wireless signal sources previously detected on each floor. The mobile device can compare the list and count with wireless signal sources detected by the mobile device, and use results of the comparison to configure a statistical filter that determines a location of the mobile device. The mobile device can then determine the location, including a building floor level, using the statistical filter.