The invention provides a method for systematically monitoring aircraft
pilot and
air traffic control (ATC)
radio communications to detect predefined
aviation-specific keywords indicative of operational conditions affecting
flight safety or efficiency, such as turbulence,
icing, or
visibility constraints. Detected keywords and semantic equivalents from voice transmissions are transformed into structured data formats. These structured data are correlated with Automatic Dependent Surveillance-Broadcast (ADS-B) data, including precise aircraft position, altitude, heading, and speed. Leveraging this integrated data, the
system generates automated, quantitative visualizations, such as condition-specific heatmaps or other graphical representations, illustrating spatial distributions of reported in-flight phenomena like turbulence,
icing, or hazardous conditions. These visualizations enable air traffic controllers, pilots, and
aviation stakeholders to rapidly assess and disseminate real-time observations and historical patterns of flight hazards, thereby significantly enhancing situational awareness,
operational safety, and decision-making effectiveness without manual input or subjective interpretation, improving overall
aviation operational efficiency and safety.