Abstract: A robotic delivery system includes a server, a dispatch module, and a robotic delivery vehicle. The dispatch module transmits a suggested item to the dispatch application being executable on a client device operated by a user; and receives, from the dispatch application, a selection of the suggested item from the user of the client device.

Abstract: A robotic delivery system includes a server, a dispatch module, and a robotic delivery vehicle. The dispatch module transmits a suggested item to the dispatch application being executable on a client device operated by a user; transmits an item cost for the suggested item to a dispatch application; receives, from the dispatch application, a selection of the suggested item from the user of the client device; transmits a message directing the robotic delivery vehicle to deliver the suggested item having been selected; and transmits a message to a facility associated with the robotic delivery vehicle.

Abstract: Described in detail herein is an automated fulfilment system including a computing system programmed to receive requests from disparate sources for physical objects disposed at one or more locations in a facility. The computing system can combine the requests, and group the physical objects in the requests based on object types or expected object locations. Autonomous robot devices can receive instructions from the computing system to retrieve a group of the physical objects and deposit the physical objects in storage containers.

Abstract: Described in detail herein are systems and methods for network environment for a dynamic learning system for object matching and substitution using hand-held electronic devices. In exemplary embodiments, a hand-held electronic device may receive a request for physical objects of which a first physical object may be unavailable. The hand-held electronic device may transmit an identifier of the first physical object to a central computing system. The central computing system may query the database to retrieve data associated with the first physical object. The centrally computing system may attempt to match the first physical object to an available physical object based on dynamically learned matching behavior using the retrieved data.

Abstract: Described in detail herein are systems and methods for network environment for a dynamic learning system for object matching and substitution using hand-held electronic devices. In exemplary embodiments, a hand-held electronic device may receive a request for physical objects of which a first physical object may be unavailable. The hand-held electronic device may transmit an identifier of the first physical object to a central computing system. The central computing system may query the database to retrieve data associated with the first physical object. The centrally computing system may attempt to match the first physical object to an available physical object based on dynamically learned matching behavior using the retrieved data.

Abstract: Described in detail herein is an automated fulfilment system including a computing system programmed to receive requests from disparate sources for physical objects disposed at one or more locations in a facility. The computing system can combine the requests, and group the physical objects in the requests based on object types or expected object locations. Autonomous robot devices can receive instructions from the computing system to retrieve a group of the physical objects and deposit the physical objects in storage containers.

Abstract: A robotic delivery system includes a server, a dispatch module, and a robotic delivery vehicle. The dispatch module transmits a suggested item to the dispatch application being executable on a client device operated by a user; transmits an item cost for the suggested item to a dispatch application; receives, from the dispatch application, a selection of the suggested item from the user of the client device; transmits a message directing the robotic delivery vehicle to deliver the suggested item having been selected; and transmits a message to a facility associated with the robotic delivery vehicle.

Abstract: A distributed robotic delivery system includes a mobile application, a server, a dispatch module, and a plurality of robotic delivery vehicles. The mobile application receives suggested items for purchase, the suggested items selected by having a set of properties suitable for delivery by a selected one of the plurality of robotic delivery vehicles, where the set of properties includes product dimensions and weight; receives item costs to be provided to a user for the suggested items; displays the item costs; and transmits a message directing the dispatch module to deploy the selected one of the plurality of robotic delivery vehicles to deliver one or more items of the suggested items selected by the user.

Abstract: A method for tracking an item in a distributed environment is provided. At least one node in a network adds a new block to a first cryptographically verifiable ledger represented by a first sequence of blocks that is stored in one or more non-transitory computer-readable media. The new block added to the first cryptographically verifiable ledger contains a component identifier and a hash of a previous block in the first sequence of blocks. The at least one node in the network adds a new block to a second cryptographically verifiable ledger represented by a second sequence of blocks that is stored in the one or more non-transitory computer-readable media. The new block added to the second cryptographically verifiable ledger contains a destination identifier, the first sequence of blocks, and a hash of a previous block in the second sequence of blocks.

Abstract: Described in detail herein are systems and methods for network environment for a dynamic learning system for object matching and substitution using hand-held electronic devices. In exemplary embodiments, a hand-held electronic device may receive a request for physical objects of which a first physical object may be unavailable. The hand-held electronic device may transmit an identifier of the first physical object to a central computing system. The central computing system may query the database to retrieve data associated with the first physical object. The centrally computing system may attempt to match the first physical object to an available physical object based on dynamically learned matching behavior using the retrieved data.

Abstract: A distributed robotic delivery system includes a mobile application, a server, a dispatch module, and a plurality of robotic delivery vehicles. The mobile application receives suggested items for purchase, the suggested items selected by having a set of properties suitable for delivery by a selected one of the plurality of robotic delivery vehicles, where the set of properties includes product dimensions and weight; receives item costs to be provided to a user for the suggested items; displays the item costs; and transmits a message directing the dispatch module to deploy the selected one of the plurality of robotic delivery vehicles to deliver one or more items of the suggested items selected by the user.

Abstract: Described in detail herein are systems and methods for network environment for a dynamic learning system for object matching and substitution using hand-held electronic devices. In exemplary embodiments, a hand-held electronic device may receive a request for physical objects of which a first physical object may be unavailable. The hand-held electronic device may transmit an identifier of the first physical object to a central computing system. The central computing system may query the database to retrieve data associated with the first physical object. The centrally computing system may attempt to match the first physical object to an available physical object based on dynamically learned matching behavior using the retrieved data.

Abstract: A distributed robotic delivery system includes a mobile application, a server, a dispatch module, and a plurality of robotic delivery vehicles. The mobile application receives an item cost, robotic delivery shipping options, and acquisition factors. The mobile device displays the item cost, robotic delivery shipping options, and the acquisition factors in a user interface. Upon a selection of robotic delivery option, the mobile application notifies the dispatch module to deploy the robotic delivery vehicle with the item to the specified delivery point.

Abstract: Described in detail herein is an automated fulfilment system including a computing system programmed to receive requests from disparate sources for physical objects disposed at one or more locations in a facility. The computing system can combine the requests, and group the physical objects in the requests based on object types or expected object locations. Autonomous robot devices can receive instructions from the computing system to retrieve a group of the physical objects and deposit the physical objects in storage containers.

Abstract: Described in detail herein is an automated fulfilment system including a computing system programmed to receive requests from disparate sources for physical objects disposed at one or more locations in a facility. The computing system can combine the requests, and group the physical objects in the requests based on object types or expected object locations. Autonomous robot devices can receive instructions from the computing system to retrieve a group of the physical objects and deposit the physical objects in storage containers.

Abstract: The present invention extends to methods, systems, and computer program products for developing an item data model for an item. Aspects of the invention can automate the process of data collection of “facts” for “items” that information is needed about. Facts can be organized and normalized to eliminate redundant facts, and interpret what is found. Data requirements extraction and automated modeling using a combination of data virtualization, data analytics, extract, transform, and load (ETL), web crawlers, and reverse engineering systems, can be used along with other technologies to develop an item model. A model owner feeds a curating module with the information for locating the facts to be used, and initiating the modeling process. Existing data structures, websites, vendor input, etc. can be described to the import process, and an item model is produced. The model can be imported into existing modeling tools for viewing, or viewed as XML.

Abstract: Described in detail herein are systems and methods for network environment for a dynamic learning system for object matching and substitution using hand-held electronic devices. In exemplary embodiments, a hand-held electronic device may receive a request for physical objects of which a first physical object may be unavailable. The hand-held electronic device may transmit an identifier of the first physical object to a central computing system. The central computing system may query the database to retrieve data associated with the first physical object. The centrally computing system may attempt to match the first physical object to an available physical object based on dynamically learned matching behavior using the retrieved data.

Abstract: Described in detail herein are methods and systems for performing a physical object assessment. The system entails an automated system to receive, unpack and assess a physical object based on automated determined attributes. The system can determine an element based on the assessment and generate a webpage including the attributes of the physical object and the determined element.

Abstract: Described in detail herein is an automated fulfillment system including a computing system programmed to receive requests from disparate sources for physical objects disposed at one or more locations in a facility. The computing system can combine the requests, and group the physical objects in the requests based on object types or expected object locations. Autonomous robot devices can receive instructions from the computing system to retrieve a group of the physical objects and deposit the physical objects in storage containers.

Abstract: Methodologies, systems, and computer-readable media are provided for dynamic virtual data analysis. A first subset of performance metric data relating to a number of facilities is compared between at least two of the facilities to generate a first level comparison. A second subset of the performance metric data associated with two or more sections of at least one facility is compared to generate a second level comparison. A processor generates a graphical representation of the first level comparison and the second level comparison. A user electronic device can receive input from a user to dynamically navigate between a rendering of the graphical representation of the first level comparison and a rendering of the graphical representation of the second level comparison. The user can also modify the first subset of data or the second subset of data to update the first level comparison or the second level comparison.