Abstract: A beverage container recycling system has a housing with an advertising display, a user feedback display and a deposit opening. An imaging region is connected to the deposit opening. The imaging region has a camera to take an image of a deposited beverage container. A processor, network interface circuit and memory are associated with the housing. The memory stores instructions executed by the processor to analyze the image of the deposited beverage container to characterize the deposited beverage container as one of glass, aluminum or plastic. A carriage directly deposits a glass beverage container in a glass bin. The carriage directs aluminum and plastic beverage containers to a crusher with a blade to pierce aluminum and plastic beverage containers prior to compaction. The crusher selectively directs compacted beverage containers to a plastic bin and an aluminum bin.

Abstract: Techniques for storing information representing a venue are described. A venue data provider may upload venue data to a venue data service. The venue data can include locations, geometries, and business categories of the buildings and floors. The venue data service can validate the venue data, and request a survey service to survey the venue using the validated venue data. A survey can include recording measurements of an environment variable at various locations of the venue. The location service can generate location fingerprint data from the survey. The location fingerprint data can include expected measurements of the environment variable at various locations of the building. The venue data service can provide the location fingerprint data to a mobile device such that the mobile device can determine a location of the mobile device in the venue using sensor readings of the environment variable.

Abstract: Techniques for storing information representing a venue are described. A venue data provider may upload venue data to a venue data service. The venue data can include locations, geometries, and business categories of the buildings and floors. The venue data service can validate the venue data, and request a survey service to survey the venue using the validated venue data. A survey can include recording measurements of an environment variable at various locations of the venue. The location service can generate location fingerprint data from the survey. The location fingerprint data can include expected measurements of the environment variable at various locations of the building. The venue data service can provide the location fingerprint data to a mobile device such that the mobile device can determine a location of the mobile device in the venue using sensor readings of the environment variable.

Abstract: Techniques for storing information representing a venue are described. A venue data provider may upload venue data to a venue data service. The venue data can include locations, geometries, and business categories of the buildings and floors. The venue data service can validate the venue data, and request a survey service to survey the venue using the validated venue data. A survey can include recording measurements of an environment variable at various locations of the venue. The location service can generate location fingerprint data from the survey. The location fingerprint data can include expected measurements of the environment variable at various locations of the building. The venue data service can provide the location fingerprint data to a mobile device such that the mobile device can determine a location of the mobile device in the venue using sensor readings of the environment variable.

Abstract: Content Management Systems (CMSs) can be configured to edit available content. The CMS can be provided as a web interface so that content can be rapidly updated. User data can be collected associated with an individual user or one or more specific locations. Examples include information related to venue traffic, efficacy of floor plan and layout, store placement, advertising rates as a function of location, lease rates, user demographics, user purchasing habits, and other user profiles.

Abstract: Techniques for storing information representing a venue are described. A system can represent a venue as a set of one or more nested data objects. A top layer of the nested data objects can include a venue data object that stores coarse information of the venue, including an identifier, a name, and a geometry of the venue. A second layer of data objects that are nested in the venue data object can include one or more building data objects that have finer granularity than the venue data object. Each building data object can store information on a building located at the venue, including name of the building, address of the building, and a geometry of the building. Additional layers of data objects representing further details of each building.

Abstract: Techniques for storing information representing a venue are described. A venue data provider may upload venue data to a venue data service. The venue data can include locations, geometries, and business categories of the buildings and floors. The venue data service can validate the venue data, and request a survey service to survey the venue using the validated venue data. A survey can include recording measurements of an environment variable at various locations of the venue. The location service can generate location fingerprint data from the survey. The location fingerprint data can include expected measurements of the environment variable at various locations of the building. The venue data service can provide the location fingerprint data to a mobile device such that the mobile device can determine a location of the mobile device in the venue using sensor readings of the environment variable.

Abstract: Techniques for validating venue data are described. The venue data can include records describing physical features of a venue and records describing conceptual features of the venue. A validation engine can detect conflicts between records in the venue data or conflicts between records in the venue data and external data. The conflict can include a physical conflict between two physical features, e.g., when a floor of a building is larger than a footprint of the building, a conceptual conflict between two occupants of a venue, e.g., when an airport baggage claim area is located next to a high school, or a relationship conflict between an occupant and a venue in which the occupant is allegedly located, e.g., ski resort located in an office building. The conflict can be defined in conflict rules. The validation engine can learn the conflict rules from historical venue data and truth references.

Abstract: Techniques for enriching venue data are described. The venue data can include records describing physical features of a venue and records describing conceptual features of the venue. A data enrichment engine can enrich the venue data using probe data by automatically correcting inconsistencies in the venue data or adding additional information to the venue data. The probe data can include crowd-sourced data from multiple mobile devices. The probe data can include motion sensor data, application launch data, and site survey data.

Abstract: Private or closed networks configured to provide location or venue specific content or other localization information to mobile computing devices are based on periodic or other reassignments of network access point identifiers. Authorized network subscribers and applications can determine accurate mobile device location based on updated access point identifiers and RF signatures provided by mobile devices. Appropriate venue-based content or services can then be provided to mobile devices, while non-authorized subscribers and applications are hindered in their ability to determine mobile device location.

Abstract: Content Management Systems (CMSs) can be configured to edit available content. The CMS can be provided as a web interface so that content can be rapidly updated. User data can be collected associated with an individual user or one or more specific locations. Examples include information related to venue traffic, efficacy of floor plan and layout, store placement, advertising rates as a function of location, lease rates, user demographics, user purchasing habits, and other user profiles.