Abstract: Generating a location-specific three-dimensional model in response to a location query can provide users with a better understanding of a location through providing better interactivity, better perspective, and better understanding of dimensionality. Generation of the models can be enabled by leveraging a three-dimensional asset database and segmentation methods. The location-specific models can provide further utility by further including situation specific simulated effects, such as simulated weather or traffic.

Abstract: Generating a location-specific three-dimensional model in response to a location query can provide users with a better understanding of a location through providing better interactivity, better perspective, and better understanding of dimensionality. Generation of the models can be enabled by leveraging a three-dimensional asset database and segmentation methods. The location-specific models can provide further utility by further including situation specific simulated effects, such as simulated weather or traffic.

Abstract: Methods and systems are described herein for presenting an animation of a geographic area based on current conditions within the geographic area. A client device presents a map display of the geographic area via a user interface. In response to determining to present an animation of the geographic area, the client device animates the map display of the geographic area using virtual objects overlaid on the map display which represent the current conditions at the geographic area.

Abstract: Generating a location-specific three-dimensional model in response to a location query can provide users with a better understanding of a location through providing better interactivity, better perspective, and better understanding of dimensionality. Generation of the models can be enabled by leveraging a three-dimensional asset database and segmentation methods. The location-specific models can provide further utility by further including situation specific simulated effects, such as simulated weather or traffic.

Abstract: A system for large-scale crowd sourcing of map data cleanup and correction, comprising an application server that generates image data, sends image data to a user device, receives tagging data provided by the device user, and provides tags to a crowdsourced search and locate server based on tagging data from a user device, a crowdsourced search and locate server that receives tags from an application server, computes agreement and disagreement values and performs expectation-maximization analysis, and a map data server that stores and provides map data, and a method for estimating location and quality of a set of geolocation data.

Abstract: Described herein are methods and systems that help facilitate the summoning and loading of a pickup and delivery unmanned aerial vehicle (UAV). In particular, a computing system may display a graphical interface including an interface feature that indicates UAV assignments. That computing system may receive a message including a UAV identifier that identifies a particular UAV assigned to a particular item based on a UAV-assignment request for the particular item. And the computing system may use the received UAV identifier as a basis for displaying, on the graphical interface, (i) a graphical identifier of the particular UAV assigned to the particular item based on the UAV-assignment request for the particular item and (ii) a graphical identifier of the particular item.

Abstract: Described herein are methods and systems that help facilitate the summoning and loading of a pickup and delivery unmanned aerial vehicle (UAV). In particular, a computing system may display a graphical interface including an interface feature that indicates UAV assignments. That computing system may receive a message including a UAV identifier that identifies a particular UAV assigned to a particular item based on a UAV-assignment request for the particular item. And the computing system may use the received UAV identifier as a basis for displaying, on the graphical interface, (i) a graphical identifier of the particular UAV assigned to the particular item based on the UAV-assignment request for the particular item and (ii) a graphical identifier of the particular item.

Abstract: A system for large-scale crowd sourcing of map data cleanup and correction, comprising an application server that generates image data, sends image data to a user device, receives tagging data provided by the device user, and provides tags to a crowdsourced search and locate server based on tagging data from a user device, a crowdsourced search and locate server that receives tags from an application server, computes agreement and disagreement values and performs expectation-maximization analysis, and a map data server that stores and provides map data, and a method for estimating location and quality of a set of geolocation data.

Abstract: Described herein are methods and systems that help facilitate the summoning and loading of a pickup and delivery unmanned aerial vehicle (UAV). In particular, a computing system may display a graphical interface including an interface feature that indicates UAV assignments. That computing system may receive a message including a UAV identifier that identifies a particular UAV assigned to a particular item based on a UAV-assignment request for the particular item. And the computing system may use the received UAV identifier as a basis for displaying, on the graphical interface, (i) a graphical identifier of the particular UAV assigned to the particular item based on the UAV-assignment request for the particular item and (ii) a graphical identifier of the particular item.

Abstract: Described herein are methods and systems that help facilitate the summoning and loading of a pickup and delivery unmanned aerial vehicle (UAV). In particular, a computing system may display a graphical interface including an interface feature that indicates UAV assignments. That computing system may receive a message including a UAV identifier that identifies a particular UAV assigned to a particular item based on a UAV-assignment request for the particular item. And the computing system may use the received UAV identifier as a basis for displaying, on the graphical interface, (i) a graphical identifier of the particular UAV assigned to the particular item based on the UAV-assignment request for the particular item and (ii) a graphical identifier of the particular item.

Abstract: A system for large-scale crowd sourcing of map data cleanup and correction, comprising an application server that generates image data, sends image data to a user device, receives tagging data provided by the device user, and provides tags to a crowdsourced search and locate server based on tagging data from a user device, a crowdsourced search and locate server that receives tags from an application server, computes agreement and disagreement values and performs expectation-maximization analysis, and a map data server that stores and provides map data, and a method for estimating location and quality of a set of geolocation data.

Abstract: A crowdsourced search and locate platform has been developed and put into practice. A plurality of geospatial images of a geographical region of interest are presented to a plurality of participants in an internet mediated crowdsourcing campaign for the purpose of identifying and tagging specific features of interest to the campaign administrator. An algorithm of the invention, CrowdRank, monitors the identification accuracy of the participants both absolute and compared to other participants calculating a score used to weight each identification made by that user. CrowdRank also chooses images to maximize campaign efficiency and calculates the confidence level of each feature identification.

Abstract: Described herein are methods and systems that help facilitate the summoning and loading of a pickup and delivery unmanned aerial vehicle (UAV). In particular, a computing system may display a graphical interface including an interface feature that indicates UAV assignments. That computing system may receive a message including a UAV identifier that identifies a particular UAV assigned to a particular item based on a UAV-assignment request for the particular item. And the computing system may use the received UAV identifier as a basis for displaying, on the graphical interface, (i) a graphical identifier of the particular UAV assigned to the particular item based on the UAV-assignment request for the particular item and (ii) a graphical identifier of the particular item.

Abstract: A system for large-scale crowd sourcing of map data cleanup and correction, comprising an application server that generates image data, sends image data to a user device, receives tagging data provided by the device user, and provides tags to a crowdsourced search and locate server based on tagging data from a user device, a crowdsourced search and locate server that receives tags from an application server, computes agreement and disagreement values and performs expectation-maximization analysis, and a map data server that stores and provides map data, and a method for estimating location and quality of a set of geolocation data.

Abstract: A crowdsourced search and locate platform, comprising an application server that receives input from a plurality of user devices and navigates to a particular location, sends images of the location to a user device, and receives tagging data provided by the device user, and a client interface application that displays a plurality of interactive elements to a user, receive input from the user, and provide the results of the input to the application server, and methods for operating and administering a crowdsourced search and locate platform.

Abstract: A crowdsourced search and locate platform, comprising an application server and a client interface application. The application server: receives connections from crowdsourcing participants; navigates a first crowdsourcing participant to a specific geospatial location; sends an image corresponding to the geospatial location to the first crowdsourcing participant; receives tagging data from the first crowdsourcing participant, the tagging data corresponding to a plurality of objects and locations identified by the first crowdsourcing participant.

Abstract: A system for large-scale crowd sourcing of map data cleanup and correction, comprising an application server that generates image data, sends image data to a user device, receives tagging data provided by the device user, and provides tags to a crowdsourced search and locate server based on tagging data from a user device, a crowdsourced search and locate server that receives tags from an application server, computes agreement and disagreement values and performs expectation-maximization analysis, and a map data server that stores and provides map data, and a method for estimating location and quality of a set of geolocation data.

Abstract: A crowdsourced search and locate platform has been developed and put into practice. A plurality of geospatial images of a geographical region of interest are presented to a plurality of participants in an internet mediated crowdsourcing campaign for the purpose of identifying and tagging specific features of interest to the campaign administrator. An algorithm of the invention, CrowdRank, monitors the identification accuracy of the participants both absolute and compared to other participants calculating a score used to weight each identification made by that user. CrowdRank also chooses images to maximize campaign efficiency and calculates the confidence level of each feature identification.

Abstract: A system for large-scale crowd sourcing of map data cleanup and correction, comprising an application server that generates image data, sends image data to a user device, receives tagging data provided by the device user, and provides tags to a crowdsourced search and locate server based on tagging data from a user device, a crowdsourced search and locate server that receives tags from an application server, computes agreement and disagreement values and performs expectation-maximization analysis, and a map data server that stores and provides map data, and a method for estimating location and quality of a set of geolocation data.

Abstract: A crowdsourced search and locate platform, comprising an application server and a client interface application. The application server: receives connections from crowdsourcing participants; navigates a first crowdsourcing participant to a specific geospatial location; sends an image corresponding to the geospatial location to the first crowdsourcing participant; receives tagging data from the first crowdsourcing participant, the tagging data corresponding to a plurality of objects and locations identified by the first crowdsourcing participant. The client interface application: displays elements enabling an administrative user to configure a crowdsourced search and locate campaign; displays other elements enabling an administrative user to configure and run a crowdrank algorithm; and upon the user's selecting a particular object type icon, displays tags of the type selected by placing visual indicators at each tagged location of objects of the selected type within the plurality of image strips.