Abstract: Various embodiments may provide an airborne system for measuring meteorological parameters, including a high altitude unmanned aerial vehicle (UAV) formed completely or partially of closed-cell polyurethane foam. In various embodiments, the UAV may include extendable wings configured to extend and retract as the UAV climbs and descends to different altitude levels. In various embodiments, the UAV may include one or more infrasonic sensors and wind screening configured to measure one or more meteorological parameters, such as wind shear, seismic waves, magnetic storms, magnetohydrodynamic waves, severe weather, tornadoes, hurricanes, meteors, and lighting. The infrasonic sensors may be configured to determine wind shear at the local and regional level. In various embodiments, other meteorological sensors may also be included in/on the UAV in addition to the infrasonic sensors.

Abstract: A monitoring system for a fleet of vehicles includes at least one data acquisition and analysis module (DAAM) mounted on each vehicle in the fleet, a control module on each vehicle in communication with each DAAM, and terminal module located remotely with respect to the vehicles in the fleet. Each DAAM collects/analyzes sensor data to generate analysis results that identify the state of a plurality of systems of the vehicle. Each vehicle's control module collects/analyzes the analysis results from each onboard DAAM to generate vehicle status results that identify potential sources of vehicle anomalies. The terminal module collects/analyzes the analysis results and vehicle status results transmitted from each control module from the fleet of vehicles to identify multiple occurrences of vehicle anomalies and multiple occurrences of those vehicle systems operating at a performance level that is unacceptable.

Abstract: A monitoring system for a fleet of vehicles includes at least one data acquisition and analysis module (DAAM) mounted on each vehicle in the fleet, a control module on each vehicle in communication with each DAAM, and terminal module located remotely with respect to the vehicles in the fleet. Each DAAM collects/analyzes sensor data to generate analysis results that identify the state of a plurality of systems of the vehicle. Each vehicle's control module collects/analyzes the analysis results from each onboard DAAM to generate vehicle status results that identify potential sources of vehicle anomalies. The terminal module collects/analyzes the analysis results and vehicle status results transmitted from each control module from the fleet of vehicles to identify multiple occurrences of vehicle anomalies and multiple occurrences of those vehicle systems operating at a performance level that is unacceptable.