A vertical takeoff and landing aircraft capable of six degree-of-freedom motion where lift, pitch, and roll are provided by multirotors oriented vertically, lateral translation is provided by a cyclorotor oriented vertically, and yaw is provided by a combination of the cyclorotor and the multirotors. The invention includes a frame, which supports the multirotors and cyclorotors. The frame also supports a payload and battery which are positioned at the extreme ends of the frame. The aircraft is capable of hovering precisely to position a payload close to or touching a target surface in the air.

Methods, systems, apparatuses, and computer program products for multi-objective mission planning and execution for an unmanned aerial vehicle (UAV) are disclosed. In a particular embodiment, multi-objective mission planning and execution for a UAV includes a computing device detecting a mode change event associated with a UAV executing a mission in a first mission mode. In this embodiment, the computing device determines, based on the mode change event, a second mission mode for the UAV and switches a current mission mode of the UAV from the first mission mode to the second mission mode.

A method and system for determining the rate of growth of a wildfire.

A system for asset failure and replacement management is disclosed. The system includes a communication interface and processor(s) configured to: receive an indication that the drone is part of a set of assets, wherein the set of assets are tasked with performing element(s) of task(s), and the set of assets comprises a plurality of drones; determine that at least one drone has experienced a failure; in response to a determination that the at least one drone has experienced the failure, update a plan to an updated plan to perform the task(s); and communicate, via the communication interface, information pertaining to the updated plan, wherein the information pertaining to the updated plan is communicated with at least one remaining drone of the set of assets.

Methods, apparatuses, system, devices, and computer program products for updating airspace awareness for unmanned aerial vehicles are disclosed. In a particular embodiment, the classification of a detected object is identified based on sensor data collected by an in-flight unmanned aerial vehicle (UAV). The location of the object is determined based on the sensor data. An airspace awareness controller generates, in dependence upon the classification of the object and the location of the object, an airspace awareness update concerning the object.

Embodiments describe a computer-implemented method for design compliance monitoring, comprising obtaining, via a remote deployable transient sensory system, sensory information associated with a built site indicative of a construction feature in the built site, receiving, via a processor, from a remote deployable transient sensory system, the sensory information, comparing the sensory information with an electronic design file indicative of a built site design, and determining, via the processor, and based on the sensory information and the electronic design file, that the construction feature does not comply with a design feature of the electronic design file. The construction feature is associated with energy efficiency of the built site. The method further includes generating, via the processor, a C.sup.2 BEM based on the sensory information associated with the built site indicative of the construction feature in the built site.

A system for providing a smart, self-healing blockchain-based data exchange data storage device within a self-healing node centric blockchain mesh network, a smart self-healing data exchange device being within one or more universal computing nodes within a self-healing node centric blockchain mesh network is disclosed. The smart self-healing data exchange device being contained within one or more universal computing nodes within a self-healing node-centric blockchain mesh network. The smart self-healing blockchain data exchange device includes a blockchain processor for storing and maintaining a set of blockchain data records stored within a blockchain ledger, each blockchain data record within the set of blockchain data records having a blockchain ID, a universal computing node ID, a bundle of digital access rights, and content data, and an instantiation of the blockchain ledger communicatively coupled to the blockchain processor is stored within a plurality of the one or more universal computing nodes within a self-healing node centric blockchain mesh network. The bundle of digital access rights provides for rights and privileges associated with blockchain data records that can be divided by use, terms, and ownership.

The present invention is directed to methods and systems for enforcing at least one rule within a geofence. The rule is enforced by a fencing agent on an unmanned aerial vehicle (UAV). The geofence is defined by a plurality of geographic designators, with the plurality of geographic designators each being associated with an Internet Protocol (IP) address, preferably an IPv6 address.

A computer receives a hotspot and a corresponding incentive, where the hotspot is a geolocation for collecting the weather data. The computer presents the received hotspot and the corresponding incentive to a user. The computer receives the weather data from the drone, transmits the weather data to a server, and updates a scorecard with the incentive corresponding to the hotspot based on determining that the drone reached the hotspot.

A system for localization of a safe landing zone comprises at least one image-capture device onboard an aerial vehicle, and an onboard processor coupled to the image-capture device. The processor is operative to execute instructions to perform a method that comprises: receive, from the image-capture device, two or more overlapping images of a landscape underneath the aerial vehicle; generate, based on the overlapping images, a landing zone heatmap of the landscape; identify, based on the landing zone heatmap, one or more regions of the landscape having potential landing zones and obstacles; and determine a location of a safe landing zone using a distance transform of the one or more regions of the landscape. The location of the safe landing zone is in an area within one of the potential landing zones that is farthest from the obstacles. The location of the safe landing zone is then stored in a database.