Apparatuses, computer-implemented methods, and computer program products for clear air turbulence detection

An apparatus comprising at least one processor and at least one non-transitory memory having computer-coded instructions stored thereon that, in execution with at least one processor, cause the apparatus to:

• receive, from a vehicle, real-time biometric data for at least one subject aboard the vehicle in response to the real-time biometric data for the at least one subject aboard the vehicle meeting at least one biometric abnormality threshold;
• generate a first subset of weighted biometric data at least in part by application of a first weight value to at least a first subset of the real-time biometric data determined to correspond to at least one passenger aboard the vehicle;
• generating a second subset of weighted biometric data at least in part by application of a second weight value to at least a second subset of the real-time biometric data determined to correspond to at least one crewmember aboard the vehicle, wherein the first weight value represents a greater impact value than the second weight value;
• determine the vehicle has encountered a monitored vehicle event representing clear air turbulence (CAT), wherein the determination that the vehicle has encountered the monitored vehicle event is based at least in part on the first subset of weighted biometric data and the first weight value and the second subset of weighted biometric data and the second weight value;
• obtain vehicle data associated with the vehicle;
• generate a predicted event location corresponding to the monitored vehicle event based at least in part on the vehicle data;
• and
• provide the predicted event location to at least one additional vehicle.

A computer program product comprising at least one non-transitory computer-readable storage medium having computer program code stored thereon that, in execution with at least one processor, is configured to:

• receive, from a vehicle, real-time biometric data for at least one subject aboard the vehicle in response to the real-time biometric data for the at least one subject aboard the vehicle meeting at least one biometric abnormality threshold;
• generate a first subset of weighted biometric data at least in part by application of a first weight value to at least a first subset of the real-time biometric data determined to correspond to at least one passenger aboard the vehicle;
• generate a second subset of weighted biometric data at least in part by application of a second weight value to at least a second subset of the real-time biometric data determined to correspond to at least one crewmember aboard the vehicle, wherein the first weight value represents a greater impact value than the second weight value;
• determine the vehicle has encountered a monitored vehicle event representing clear air turbulence (CAT), wherein the determination that the vehicle has encountered the monitored vehicle event is based at least in part on the first subset of weighted biometric data and the first weight value and the second subset of weighted biometric data and the second weight value;
• obtain vehicle data associated with the vehicle;
• generate a predicted event location corresponding to the monitored vehicle event based at least in part on the vehicle data;
• and
• provide the predicted event location to at least one additional vehicle.