Abstract: Route planning for an unmanned aerial vehicle (UAV) is disclosed. A map of a region is partitioned into geographic cells, data about flight conditions in each cell is aggregated, and a cost for each cell is calculated based on weighted flight condition factors. A plurality of flight paths from a first point to a second point are determined, and a cost for each flight path is determined by summing the cost of each cell traversed by the flight path. An optimal flight path is selected from the plurality of flight paths in dependence upon the total cost of each flight path. When new information is obtained that affects the cost of the cells the flight path, the cost of the current flight path is recalculated along with the costs of alternative flight paths to determine whether a route should be altered.

Abstract: Methods, systems, apparatuses, and computer program products for providing malware protection on a UAV are disclosed. In a particular embodiment, a method of providing malware protection on a UAV includes a malware defense controller initiating, on an unmanned aerial vehicle (UAV) in response to a malware defense event, a malware defense scan of at least one file stored on the UAV. In this embodiment, the malware defense controller also implements, in dependence upon a result of a malware detection analysis, a malware defense operation.

Abstract: In a particular embodiment, coordinating an aerial search among unmanned aerial vehicles is disclosed that includes receiving, by a server in a UAV transportation ecosystem, search area data, accessing, by the server, UAV parameters for a type of UAV, determining, by the server in dependence upon the search area data and the UAV parameters, a number of UAVs needed to complete a coordinated aerial search of a search area within a time limit, and partitioning, by the server, the search area into a plurality of partitions, wherein the number of partitions is equal to the number of UAVs.

Abstract: Methods, systems, apparatuses, and computer program products for fulfilling a request associated with operational aspects of an unmanned aerial vehicle (UAV) mission are disclosed. In a particular embodiment, fulfilling a request associated with operational aspects of a UAV mission includes a fulfillment controller presenting to a first set of providers of a plurality of providers, a request for offers to perform a first set of operational aspects of a UAV mission. In this embodiment, the fulfillment controller also includes receiving from each provider of a second set of providers of the plurality of providers, an offer to perform a second set of operational aspects of the first set of operational aspects of the UAV mission. In addition, the fulfillment controller also selects from a first set of offers received from the second set of providers, a first offer to accept.

Abstract: Methods, systems, apparatuses, and computer program products for automated preflight evaluation of an unmanned aerial vehicle (UAV) configuration are disclosed. In a particular embodiment, automated preflight evaluation of an UAV configuration includes a preflight controller retrieving information about a UAV configuration selected to perform a mission in accordance with one or more mission parameters. In this embodiment, the preflight controller uses the retrieved information to assess an ability of the UAV configuration to perform the mission in accordance with the one or more mission parameters.

Abstract: In a particular embodiment, decentralized oracles in an unmanned aerial vehicle (UAV) transportation ecosystem includes: receiving, by an oracle node of a plurality of oracle nodes, from a validating node of a plurality of validating nodes of a UAV transportation ecosystem, a request for data for fulfillment of a smart contract, wherein the plurality of oracle nodes are communicatively coupled via an overlay network implemented using a network communicatively coupling the plurality of validating nodes; generating, based on responses to the request from the plurality of oracle nodes, the data for fulfillment of the smart contract; and providing the data for fulfillment of the smart contract.

Abstract: In a particular embodiment, blockchain-based hybrid authentication is disclosed that includes receiving, by a smart contract controller, an invocation of a smart contract and accessing, by the smart contract controller, one or more parameters associated with a client account. In this embodiment, the smart contract determines whether the one or more parameters fulfill the smart contract. In response to determining that the one or more parameters fulfill the smart contract, the smart contract provides an attestation of an identity associated with the client account.

Abstract: Methods, systems, apparatuses, and computer program products for geofence management with an unmanned aerial vehicle (UAV) are disclosed. In a particular embodiment, a method of geofence management with a UAV includes a geofence manager utilizing a first set of sensor data collected by a first set of in-flight UAVs of the UAV system to detect a first object. In this embodiment, the geofence manager also utilizes the first set of sensor data to determine a first location of the detected first object and determines whether the first location of the detected first object is within a geofence of an area.

Abstract: Methods, systems, apparatuses, and computer program products for displaying electromagnetic spectrum information for UAV navigation are disclosed. In a particular embodiment, a method of displaying electromagnetic spectrum information for UAV navigation includes an electromagnetic spectrum awareness controller, of a control device associated with a UAV, that generates a first map layer based on electromagnetic spectrum map data; and displays, on a display of the control device, the first map layer overlaid on a base image.

Abstract: In a particular embodiment, parallel deconfliction processing of unmanned aerial vehicles (UAVs) is disclosed that includes a UAV control system partitioning the airspace over a geographic region into a plurality of airspace regions. In this example embodiment, the UAV control system includes a plurality of deconfliction controllers. For each deconfliction controller in the plurality of deconfliction controllers, the UAV control system assigns to the deconfliction controller, one or more airspace regions of the plurality of airspace regions. The UAV control system also inputs, in parallel, flight path data for a plurality of unmanned aerial vehicles (UAVs) to the plurality of deconfliction controllers. This embodiment also includes processing, in parallel by the plurality of deconfliction controllers, the flight path data to identify a flight conflict between two or more UAVs. Each deconfliction controller outputs a deconfliction result for each airspace region.

Abstract: Methods, systems, apparatuses, and computer program products for incentivizing UAV use are disclosed. In a particular embodiment, incentivizing UAV use includes UAV pilot recommendation by a computing system. In this embodiment, the computing system receives at least one parameter related to a prospective UAV mission and retrieves UAV flight records of a plurality of UAV pilots. According to this embodiment, the computing system recommends, based on the at least one parameter and the UAV flight records, at least one UAV pilot for the prospective UAV flight.

Abstract: Methods, systems, apparatuses, and computer program products for UAV module management are disclosed. In a particular embodiment, UAV module management includes software module library management by a computing system. In this embodiment, the computing system presents information representing a plurality of UAV software modules, receives information representing a UAV software module selection, and adds the UAV software module identified by the information representing a UAV software module selection to a UAV software module library. According to this embodiment, the computing system adds, based on a selection of a UAV software module, the selected UAV module to a UAV software module library.

Abstract: In a particular embodiment, parallel deconfliction processing of unmanned aerial vehicles (UAVs) is disclosed that includes a UAV control system partitioning the airspace over a geographic region into a plurality of airspace regions. In this example embodiment, the UAV control system includes a plurality of deconfliction controllers. For each deconfliction controller in the plurality of deconfliction controllers, the UAV control system assigns to the deconfliction controller, one or more airspace regions of the plurality of airspace regions. The UAV control system also inputs, in parallel, flight path data for a plurality of unmanned aerial vehicles (UAVs) to the plurality of deconfliction controllers. This embodiment also includes processing, in parallel by the plurality of deconfliction controllers, the flight path data to identify a flight conflict between two or more UAVs. Each deconfliction controller outputs a deconfliction result for each airspace region.

Abstract: Methods, systems, apparatuses, and computer program products for predictive maintenance of an unmanned aerial vehicle (UAV) are disclosed. In a particular embodiment, a method of predictive maintenance of a UAV includes a maintenance controller detecting a deviation in an expected behavior of a UAV and determining whether to attribute the deviation to any environmental interferences. In this example embodiment, after determining to not attribute the deviation to any environmental interferences, the maintenance controller schedules the UAV for maintenance.

Abstract: Methods, systems, apparatuses, and computer program products for increasing awareness of an environmental condition for an unmanned aerial vehicle (UAV) are disclosed. In a particular embodiment, a method of increasing awareness of an environmental condition for a UAV includes an environmental awareness controller utilizing data associated with a first UAV to detect an environmental condition at a location associated with the first UAV. In this embodiment, the environmental awareness controller also updates environmental condition information associated with the location to indicate detection of the environmental condition at the location and provides the updated environmental condition information to a device associated with second UAV.

Abstract: In a particular embodiment, recording data associated with an unmanned aerial vehicle (UAV) is disclosed that includes a blockchain manager receiving a transaction message associated with a UAV. The particular embodiment also includes the blockchain manager using the information within the transaction message to create a block of data. In this particular embodiment, the blockchain manager stores the created block of data in a blockchain data structure associated with the UAV.

Abstract: A method includes receiving, at a mobile hub device, communications including location-specific risk data and a task assignment. The method also includes generating an output indicating dispatch coordinates. The dispatch coordinates identifying a dispatch location from which to dispatch, from the mobile hub device, one or more unmanned vehicles to perform a task of the task assignment.

Abstract: Methods, apparatuses, system, devices, and computer program products for unmanned aerial vehicle (UAV) response to object detection are disclosed. In a particular embodiment, a detection response controller receives data generated by one or more sensors of a UAV. Based on the generated data, the detection response controller determines a presence and an identification of an object in a proximity of the UAV. Based on the presence and the identification of the object, the detection response controller determines one or more actions for the UAV to perform.

Abstract: In a particular embodiment, parallel deconfliction processing of unmanned aerial vehicles (UAVs) is disclosed that includes a UAV control system partitioning the airspace over a geographic region into a plurality of airspace regions. In this example embodiment, the UAV control system includes a plurality of deconfliction controllers. For each deconfliction controller in the plurality of deconfliction controllers, the UAV control system assigns to the deconfliction controller, one or more airspace regions of the plurality of airspace regions. The UAV control system also inputs, in parallel, flight path data for a plurality of unmanned aerial vehicles (UAVs) to the plurality of deconfliction controllers. This embodiment also includes processing, in parallel by the plurality of deconfliction controllers, the flight path data to identify a flight conflict between two or more UAVs. Each deconfliction controller outputs a deconfliction result for each airspace region.

Abstract: Methods, systems, apparatuses, and computer program products for automated mission planning and execution for an unmanned aerial vehicle (UAV) are disclosed. In a particular embodiment, automated mission planning and execution for a UAV includes a computing device receiving from a user, mission parameters for planning a mission and identifying, based on the mission parameters, constraints on the mission. In this example embodiment, the computing device determines, based on the identified constraints, a set of pairs of UAVs and flight paths. Each pair includes a flight path and a UAV that is available and capable to perform the flight path in accordance with the mission parameters. The computing device selects from the set of pairs to assign to the mission, a pair of a particular UAV and a particular flight path.