Abstract: Flight path deconfliction among unmanned aerial vehicles is disclosed. Telemetry data received from an unmanned aerial vehicle (UAV) and air traffic data received from a server or other data sources are analyzed, using deconfliction circuitry, to determine whether a flight path conflict indicative of a potential collision exists. The deconfliction circuitry reroutes the flight path of the UAV to avoid the flight path conflict, and transmits, in dependence upon the rerouted flight path, navigation instructions to the UAV for avoiding the potential collision. The deconfliction circuitry includes hardware-implemented logic optimized for processing the navigation data.

Abstract: A method includes determining, based at least in part on parameters of a software defined radio (SDR), waveform data descriptive of an electromagnetic waveform. The method also includes obtaining sensor data distinct from the waveform data. The method further includes generating feature data based on the sensor data and the waveform data and providing the feature data as input to a first machine learning model and initiating a response action based on an output of the first machine learning model.

Abstract: An autonomous underwater device includes one or more receiver arrays. Each receiver array includes a plurality of receiver elements, and each receiver element is configured to generate a signal responsive to detecting sound energy in an aquatic environment. The autonomous underwater device also includes one or more processors coupled to the one or more receiver arrays and configured to receive signals from the receiver elements, to generate input data based on the received signals, and to provide the input data to an on-board machine learning model to generate model output data. The model output data includes sonar image data based on the sound energy, a label associated with the sonar image data, or both.

Abstract: A method includes obtaining route information at an unmanned aerial vehicle (UAV). The route information indicates a plurality of zones between an origin and a destination and a corresponding set of mobile devices for each zone. The method includes receiving first control data at the UAV from a first mobile device while in a first zone of the plurality of zones. The first mobile device is included in a first set of mobile devices corresponding to the first zone. The method further includes receiving second control data at the UAV from a second mobile device while in a second zone of the plurality of zones. The second mobile device is included in a second set of mobile devices corresponding to the second zone.

Abstract: A method includes determining, based at least in part on parameters of a software defined radio (SDR), waveform data descriptive of an electromagnetic waveform. The method also includes generating feature data based on the waveform data. The method further includes providing the feature data as input to a first machine learning model to predict a future action of a device associated with at least a portion of the electromagnetic waveform and initiating a response action based on the predicted future action.

Abstract: A method includes determining, based at least in part on parameters of a software-defined radio (SDR), waveform data descriptive of an electromagnetic waveform. The method also includes generating feature data based on the waveform data and based on one or more symbols decoded from the electromagnetic waveform. The method further includes providing the feature data as input to a first machine-learning model and initiating a response action based on an output of the first machine-learning model.

Abstract: Flight path deconfliction among unmanned aerial vehicles is disclosed. Telemetry data received from an unmanned aerial vehicle (UAV) and air traffic data received from a server or other data sources are analyzed, using deconfliction circuitry, to determine whether a flight path conflict indicative of a potential collision exists. The deconfliction circuitry reroutes the flight path of the UAV to avoid the flight path conflict, and transmits, in dependence upon the rerouted flight path, navigation instructions to the UAV for avoiding the potential collision. The deconfliction circuitry includes hardware-implemented logic optimized for processing the navigation data.

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: Making a determination regarding consensus using proofs of altitude of unmanned aerial vehicles (UAVs), including: receiving a request for a consensus from a pool of Unmanned Aerial Vehicles (UAVs), wherein membership in the pool of UAVs is based on an altitude threshold; sending, to each UAV in the pool of UAVs, a transaction request associated with the request for the consensus; receiving, from each UAV in the pool of UAVs, a corresponding response of a plurality of responses to the transaction request; and generating, based on the plurality of responses, a determination for the consensus.

Abstract: A method includes obtaining route information at an unmanned aerial vehicle (UAV). The route information indicates a plurality of zones between an origin and a destination and a corresponding set of mobile devices for each zone. The method includes receiving first control data at the UAV from a first mobile device while in a first zone of the plurality of zones. The first mobile device is included in a first set of mobile devices corresponding to the first zone. The method further includes receiving second control data at the UAV from a second mobile device while in a second zone of the plurality of zones. The second mobile device is included in a second set of mobile devices corresponding to the second zone.

Abstract: A method includes determining a trainable model to provide to a trainer, the trainable model determined based on modification of one or more models of a plurality of models. The plurality of models is generated based on a genetic algorithm and corresponds to a first epoch of the genetic algorithm. Each of the plurality of models includes data representative of a neural network. The method also includes providing the trainable model to the trainer. The method further includes adding a trained model, output by the trainer based on the trainable model, as input to a second epoch of the genetic algorithm, the second epoch subsequent to the first epoch.

Abstract: A caliper pig for detecting geometrical deformation of a pipeline is disclosed. The caliper pig includes a body and a first sensor arm assembly. The first sensor arm assembly includes a primary caliper sensor ring adapted to be mounted on the body. Further, the first sensor arm assembly includes a plurality of sensor arms adapted circumferentially distributed on the primary caliper sensor ring. Each of the plurality of sensor arms includes a sensing arm adapted to be in contact with an internal surface of the pipeline and a pair of magnets adapted to rotate along the sensing arm. Each of the plurality of sensor arms includes a sensing unit configured to detect a change in magnetic field based on the movement of the sensing arm. The sensing unit is configured to generate an output indicative of an angle of deflection of the sensing arm while traversing on the internal surface of the pipeline.

Abstract: In a particular embodiment, monotonic partitioning in unmanned aerial vehicle (UAV) search and surveillance is disclosed that includes receiving, by server, a request for search route information, the request including a geographical search area, transforming the geographical search area into a plurality of monotonic partitions, determining, for each monotonic partition, a sweep search pattern for UAV navigation, and generating, in dependence upon the search patterns, search route information for one or more UAVs.

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: 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: In a particular embodiment, methods, systems, apparatuses, and computer program products for utilizing an unmanned aerial vehicle for emergency response are disclosed that include determining, by a UAV, a disinfection area; flying, by the UAV, over the determined disinfection area; and releasing, by the UAV, a disinfectant while flying over the determined disinfection area.

Abstract: The present invention provides a composition and a method for mitigating formation or activity of a corrosion-associated biofilm on metal surfaces of pipelines. The pipelines are first treated with pigs i.e. bi-di pigs for removing/disturbing biofilm, followed by microbial treatment i.e. application of microbecidal composition. The microbecidal composition comprising at least one alcohol, one corrosion inhibitor, one surfactant, one biocide and a lignin-based nanoparticle. The lignin-based nano particle is functionalized with amine functionalizing agent. The present composition and method is eco-friendly, as low concentration is sufficient and further, regular dosing is not required for MIC control.

Abstract: Methods and devices for confirmation of successful delivery by an unmanned aerial vehicle (UAV) are disclosed. A UAV is configured to navigate to a delivery destination, authenticate a receiving zone at the delivery destination, release, in dependence upon authentication of the receiving zone, the package into the receiving zone, capture, by a camera of the UAV, an image of the receiving zone, and generate delivery confirmation data including the image the receiving zone. A recipient device is configured to detect, by the device disposed in a receiving zone for receiving a package, a UAV in proximity to a receiving zone, authenticate the UAV, detect delivery of the package in the receiving zone, capture, by a camera of the device, an image of the package, and generate delivery confirmation data including the image the package and location data obtained from a GPS sensor in the device.

Abstract: A method includes determining a trainable model to provide to a trainer, the trainable model determined based on modification of one or more models of a plurality of models. The plurality of models is generated based on a genetic algorithm and corresponds to a first epoch of the genetic algorithm. Each of the plurality of models includes data representative of a neural network. The method also includes providing the trainable model to the trainer. The method further includes adding a trained model, output by the trainer based on the trainable model, as input to a second epoch of the genetic algorithm, the second epoch subsequent to the first epoch.

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.