Neural network-guided passive sensor drone inspection system

A method for collecting structural condition data of a structure having an array of passive sensors at various locations on the structure, each passive sensor energized by an energy harvester, the method comprising the steps of:

• providing an unmanned aerial vehicle (UAV) having a UAV navigation system, a UAV image acquisition device, a UAV agile transceiver array, a computer memory, and a drone inspection neural network including a neural compute engine, wherein the neural compute engine is configured to communicate with terrestrial, airborne, or spaceborne communications networks to request and receive neural network weight and configuration file updates in real time in response to anomalies detected in UAV asset inspection data and passive sensor data in real time, classify new anomalies that do not have a database record, and to calculate a revised flight path for further inspection of the asset and anomaly;
• providing a UAV energy transfer module targetable to energize an energy harvester;
• providing a UAV communications device for receiving data from an energized sensor;
• obtaining real time data from one or more of the UAV image acquisition device, the UAV agile transceiver array, or the UAV navigation system;
• using the real time data as inputs to the drone inspection neural network to classify a passive sensor or energy harvester on an asset;
• using the real time data as inputs to the drone inspection neural network to calculate the revised flight path for the UAV system to create a line of sight between the UAV energy transfer module and the energy harvester;
• using the real time data as inputs to the drone inspection neural network to aim the energy transfer module at the energy harvester;
• and
• using the real time data as inputs to the drone inspection neural network to detect anomalies in UAV asset inspection data and passive sensor data in real time.