Automated Aircraft Management System

1 . A method for automated aircraft management, the method comprising:

collecting sensor data from sensors associated with an aircraft;

inputting information including the sensor data into a machine learning model for analysis;

outputting, via the machine learning model, an aircraft analysis associated with the sensor data and the aircraft, where the aircraft analysis includes adjustments to mechanisms within the aircraft; and

applying, at least in part, the adjustments from the aircraft analysis to the aircraft.

2 . The method of claim 1 , wherein the machine learning model is a neural network.

3 . The method of claim 1 , wherein the adjustments include adjustments to environmental conditions within an aircraft cabin of the aircraft.

4 . The method of claim 1 , further comprising:

receiving user input from within an aircraft cabin of the aircraft; and

combining the user input into the information including the sensor data prior to inputting the information into the machine learning model.

5 . The method of claim 4 wherein the user input adjusts a component in the aircraft cabin.

6 . The method of claim 1 , further comprising:

detecting, via at least one sensor from the sensors, an activity performed in an aircraft cabin of the aircraft; and

combining the activity into the information including the sensor data prior to inputting the information into the machine learning model.

7 . The method of claim 6 wherein the activity is an individual using an aircraft cabin component.

8 . The method of claim 1 , further comprising:

analyzing the aircraft analysis produced by the machine learning model;

detecting an anomaly associated with a component of the aircraft; and

producing an alert associated with the anomaly, wherein the alert includes data associated with the component.

9 . The method of claim 8 , wherein the anomaly includes indicators of faulty equipment within the aircraft.

10 . The method of claim 1 , further comprising:

analyzing the aircraft analysis produced by the machine learning model;

detecting a condition when the aircraft analysis has exceeded a predetermined threshold; and

producing an alert associated with the condition, wherein the condition includes data associated with an aircraft cabin of the aircraft.

11 . The method of claim 10 , wherein the condition is associated with items within an aircraft cabin of the aircraft.

12 . The method of claim 8 , wherein the alert provides notice to resupply an aircraft cabin component.

13 . The method of claim 1 , further comprising:

detecting, via at least one sensor from the sensors, an individual within an aircraft cabin of the aircraft;

retrieving a user profile associated with the individual, wherein the user profile includes historical data of user preferences; and

combining the historical data into the information including the sensor data prior to inputting the information into the machine learning model.

14 . A system for automated aircraft management, the system comprising:

a detection component configured to detect parameters associated with an aircraft;

a machine learning component configured to provide an aircraft analysis of at least the parameters detected by the detection component; and

an adjustment component configured to adjust aircraft mechanisms associated with at least the aircraft analysis.

15 . The system of claim 14 wherein a storage component stores the aircraft analysis in a profile.

16 . The system of claim 14 wherein when the aircraft analysis includes an anomaly, providing an alert associated with the anomaly.

17 . The system of claim 14 wherein the detection component include pressure, capacitive, temperature, and switch sensing instruments.

18 . A computer program product for automated aircraft management, the computer program product comprising a computer readable storage medium having computer readable instructions stored therein, wherein the computer readable instructions, when executed on a computing device, causes the computing device to:

receive data associated with an aircraft, wherein the data includes sensor data from sensors associated with the aircraft;

analyzing the aircraft by inputting the data into a machine learning model, wherein analyzing the aircraft includes adjustments to aircraft mechanisms; and

implementing the adjustments to the aircraft.

19 . The computer program product of claim 18 further comprising:

analyzing the aircraft inputting data into the machine learning model;

detecting an anomaly associated with a component of the aircraft; and

producing an alert associated with the anomaly, wherein the alert includes data associated with the component.

20 . The computer program product of claim 18 further comprising receiving historical data from a user profile.