A method of perceiving an airport scene is disclosed. The method comprises receiving an image of at least part of an airport and processing (304) said image using a first machine learning algorithm to identify at least one segment (402) in said image and determine an initial estimate of a category of airport feature present in said segment. The method also comprises determining (310) one or more real-world coordinates or dimensions associated with the segment, applying (312) one or more predetermined logical tests to the initial estimate of the category of airport feature present in the segment and the real-world coordinates or dimensions of the segment to determine a reviewed estimate of the category of airport feature present in the segment, and outputting (320) said reviewed estimate.

A system (100) for planning a flight path for a survey of a ROI comprises at least one UAV (102). a flight control unit (104) and a flight planning unit (106). Flight planning unit (106) creates a main flight path (302) covering the ROI, identifies an area of interest based on trigger data within the ROI, creates a boundary (304) around the identified area of interest, and creates an additional flight path (306), which is contiguous to the main flight path (302), for the identified area of interest. The trigger data may be captured during the main flight path using sensors mounted on the UAV and the flight path planned/generated in real-time during the flight, or may be fed by user. The main flight path (302) and the additional flight path (306) are any of a back-and-forth linear paths or spiral path flight paths.

A system (100) for planning a flight path for a survey of a ROI comprises at least one UAV (102). a flight control unit (104) and a flight planning unit (106). Flight planning unit (106) creates a main flight path (302) covering the ROI, identifies an area of interest based on trigger data within the ROI, creates a boundary (304) around the identified area of interest, and creates an additional flight path (306), which is contiguous to the main flight path (302), for the identified area of interest. The trigger data may be captured during the main flight path using sensors mounted on the UAV and the flight path planned/generated in real-time during the flight, or may be fed by user. The main flight path (302) and the additional flight path (306) are any of a back-and-forth linear paths or spiral path flight paths.

A pilot notification system includes multiple sensors, multiple modules, and a large language model (LLM). The modules processes inputs to determine the cognitive state of the pilot, the current pilot workload, and the current flight conditions of the aircraft. These modules send this information to other modules which process this information and send the information to the LLM. The structure of the LLM is modified to reflect the pilot's current cognitive state, the pilot's current workload, and the current flight conditions. The LLM generates a pilot alert message to alert the pilot of import information while considering the current circumstances.

In some aspects, a voice to text decoding module receives audio data indicating one or more flight commands for an aircraft and from an air traffic control system, converts the audio data into text data indicating the one or more flight commands, analyzes the text data to determine the one or more flight commands, provides for display on a screen the determined one or more flight commands, receives a confirmation signal of the displayed one or more flight commands, modifies a flight plan of the aircraft so the aircraft complies with the confirmed one or more flight commands, and transmits flight control instructions corresponding to the modified flight plan to a control system of the aircraft.

In some aspects, a voice to text decoding module receives audio data indicating one or more flight commands for an aircraft and from an air traffic control system, converts the audio data into text data indicating the one or more flight commands, analyzes the text data to determine the one or more flight commands, provides for display on a screen the determined one or more flight commands, receives a confirmation signal of the displayed one or more flight commands, modifies a flight plan of the aircraft so the aircraft complies with the confirmed one or more flight commands, and transmits flight control instructions corresponding to the modified flight plan to a control system of the aircraft.

Examples relate to a fatigue detection system to monitor and assess pilot fatigue levels during flight operations. An example system includes a wearable biometric sensor (WBS) integrated into a wristband that captures biometric data from the pilot. A processor analyzes the captured data to determine the pilot's fatigue level. When this level exceeds a predetermined threshold, the system provides an alert to the pilot through a haptic feedback mechanism in the wristband. Additionally, the system generates personalized fatigue mitigation advice, which is displayed on an electronic flight bag (EFB) application accessible to the pilot. The advice may include recommendations for taking a controlled rest, consuming caffeine, or engaging in physical activity. The system enhances flight safety by providing real-time alerts and actionable advice to combat pilot fatigue.

Examples relate to a fatigue detection system to monitor and assess pilot fatigue levels during flight operations. An example system includes a wearable biometric sensor (WBS) integrated into a wristband that captures biometric data from the pilot. A processor analyzes the captured data to determine the pilot's fatigue level. When this level exceeds a predetermined threshold, the system provides an alert to the pilot through a haptic feedback mechanism in the wristband. Additionally, the system generates personalized fatigue mitigation advice, which is displayed on an electronic flight bag (EFB) application accessible to the pilot. The advice may include recommendations for taking a controlled rest, consuming caffeine, or engaging in physical activity. The system enhances flight safety by providing real-time alerts and actionable advice to combat pilot fatigue.

A turbulence notification system and method are described that include receiving airflow reports that are generated by multiple aircraft while the aircraft are in flight. The airflow reports include a geographic location of a respective aircraft that generated the airflow report, an altitude of the respective aircraft, and an airflow condition experienced by the respective aircraft. The system and method generate a profile map that plots at least a first flight path of a first aircraft on a scheduled route of the first aircraft and graphic indicia representing the airflow conditions included in at least some of the airflow reports. The profile map has a vertical axis representing altitude and a horizontal axis representing one of time, location, or distance. The system and method display the profile map on a display device for observation by an operator associated with the first aircraft.

A display system displays, on a display, positions of a work vehicle and one or more unmanned aerial vehicles flying around the work vehicle. The display system includes a processor configured or programmed to obtain position information of the work vehicle and the unmanned aerial vehicles, and, based on the position information, display the positions of the work vehicle and the unmanned aerial vehicles in a field shown on the display.