Systems and methods for real-time, multi-factor prediction of emergency landing success probabilities using machine learning
Inventors
Baladhandapani, Gobinathan • Kutuva, Anand Arjunan • Kanagarajan, Sivakumar
Assignees
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Abstract
Embodiments of the present disclosure provide systems and methods for real-time, multi-factor prediction of emergency landing success probabilities using machine learning. In one embodiment, a method includes generating, by one or more processors, a first emergency landing success probability value, the first emergency landing success probability value based at least in part on one or more vehicle state conditions for a vehicle; generating, by the one or more processors, a second emergency landing success probability value, the second emergency landing success probability value based at least in part on one or more environmental state conditions for an operating environment of the vehicle; and generating, by the one or more processors, a third emergency landing success probability value based at least in part on the first emergency landing success probability value and the second emergency landing success probability value.
Core Innovation
The technology provides real-time emergency-landing success prediction using machine-learning models for vehicle state, environmental conditions, landing-port conditions, and communication-link state. These models generate factor-specific probabilities that are subsequently combined into an overall emergency-landing success probability to inform emergency-landing decisions. The abstract and summary sections themselves are not included in the supplied content.
The claim elements retrieve vehicle-state and communication-link conditions, generate separate probability values using corresponding machine-learning models, and apply those values to an emergency-landing machine-learning model to generate an overall probability. This overall probability supports initiation of an emergency-landing procedure, while also supporting periodic or threshold-triggered generation and recommendations to clear obstacles from a potential landing site.
Claims Coverage
The independent claims encompass three inventive features across method claim 1, system claim 8, and apparatus claim 15, each covering generating vehicle-state-related and communication-link-related emergency-landing success probability values, combining them into an overall value, and initiating an emergency-landing procedure based on that value.
Emergency-landing success prediction method
Claim 1 retrieves a vehicle state condition and a communication link condition, applies each condition to its corresponding machine-learning model to generate a respective emergency-landing success probability value, applies both values to an emergency landing machine learning model to generate an overall emergency landing success probability value, and causes initiation of an emergency landing procedure based on that value.
Emergency-landing success prediction system
Claim 8 covers a system comprising a user interface and one or more processors in communication with the user interface, wherein the processors generate vehicle-state-related and communication-link-related emergency landing success probability values, apply both values to an emergency landing machine learning model to generate an overall value, and cause initiation of an emergency landing procedure based on that value.
Emergency-landing success prediction apparatus
Claim 15 covers an apparatus comprising one or more processors and a memory storing instructions that, when executed, cause the apparatus to generate vehicle-state-related and communication-link-related emergency landing success probability values, apply both values to an emergency landing machine learning model to generate an overall value, and cause initiation of an emergency landing procedure based on that value.
The independent claims cover method, system, and apparatus forms of generating an overall emergency-landing success probability from vehicle-state and communication-link probabilities and using the overall value as a basis for initiating an emergency-landing procedure.
Stated Advantages
Not explicitly described in patent.
Documented Applications
Predicting the success probability of an emergency landing and using that probability to inform initiation of an emergency-landing procedure.
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