Monitoring system for an electric aircraft and a method for its use

1. An aircraft monitoring system for an electric aircraft, wherein

the aircraft monitoring system comprises:

at least a sensor configured to generate a failure datum, wherein the failure datum includes a datum regarding a condition of an electric motor;

a crew alerting system (CAS) in electronic communication with the at least a sensor, wherein the CAS is comprised of at least a computing device, wherein the at least a computing device is configured to:

generate a checklist comprising a plurality of branches, each branch comprising a plurality of remedy data configured to address the failure datum for the electric motor;

determine a first branch of the plurality of branches as a function of the failure datum;

display the plurality of remedy data for the first branch using a pilot display, wherein the plurality of remedy data is displayed with increasing intrusiveness from a least intrusive remedy that is expected to be the least intrusive to a flight plan or operation of the aircraft to a most intrusive remedy that is expected to be the most intrusive to a flight plan or operation of the aircraft;

prompt a pilot to apply a remedy datum of the plurality of remedy data for the first branch using the pilot display as a function of the plurality of remedy data, wherein correlations between the failure datum and the remedy datum are generated from past failure data and past remedy data;

apply the remedy datum; and

provide an indication of the condition of the electric motor using the pilot display as a function of the application of the remedy datum.

2. The monitoring system of claim 1 , wherein the computing device is further configured to generate the remedy datum as a function of the indication of the condition of the electric motor.

3. The monitoring system of claim 1 , wherein the indication comprises a failure score.

4. The monitoring system of claim 1 , wherein applying the remedy datum comprises engaging a plurality of temperature regulating devices.

5. The monitoring system of claim 4 , wherein the plurality of temperature regulating elements comprises heating elements.

6. The monitoring system of claim 4 , wherein the plurality of temperature regulating elements includes cooling elements.

7. The monitoring system of claim 1 , wherein the plurality of remedy data is generated using a machine learning model, wherein the machine learning model is trained using training data comprising correlations between a set of failure datum and a set of remedy datum.

8. The monitoring system of claim 1 , wherein the plurality of remedy data is generated using a fuzzy logic.

9. The monitoring system of claim 1 , wherein the failure datum includes a datum regarding a condition of an energy source.

10. The monitoring system of claim 9 , wherein the CAS is further configured to provide an indication of the condition of the energy source using the pilot display as a function of the application of the remedy datum.

11. A method of use for a monitoring system for an electric aircraft, wherein the method comprises:

generating, using at least a senor, a failure datum wherein the failure datum includes a datum regarding a condition of an electric motor;

generating, using a crew alerting system (CAS), a checklist comprising a plurality of branches, each branch comprising a plurality of remedy data configured to address the failure datum for the electric motor;

determining, using the CAS, a first branch of the plurality of branches a function of the failure datum;

displaying, using the CAS, the plurality of remedy data for the first branch using a pilot display, wherein the plurality of remedy data is displayed with increasing intrusiveness from a least intrusive remedy that is expected to be the least intrusive to a flight plan or operation of the aircraft to a most intrusive remedy that is expected to be the most intrusive to a flight plan or operation of the aircraft;

prompting, using the CAS, a pilot to apply a remedy datum of the plurality of remedy data for the first branch using the pilot display as a function of the plurality of remedy data, wherein correlations between the failure datum and the remedy datum are generated from past failure data and past remedy data;

applying, using the CAS, the remedy datum; and

providing, using the CAS, an indication of the condition of the electric motor using the pilot display as a function of the application of the plurality of remedy data.

12. The method of claim 11 , wherein the computing device is further configured to generate the remedy datum as a function of the indication of the condition of the electric motor.

13. The method of claim 11 , wherein the indication comprises a failure score.

14. The method of claim 11 , wherein applying the remedy datum comprises engaging a plurality of temperature regulating devices.

15. The method of claim 14 , wherein the plurality of temperature regulating elements comprises heating elements.

16. The method of claim 14 , wherein the plurality of temperature regulating elements includes cooling elements.

17. The method of claim 11 , wherein the plurality of remedy data is generated using a machine learning model, wherein the machine learning model is trained using training data comprising correlations between a set of failure datum and a set of remedy datum.

18. The method of claim 11 , wherein the plurality of remedy data is generated using a fuzzy logic.

19. The method of claim 11 , wherein the failure datum includes a datum regarding a condition of an energy source.

20. The method of claim 19 , wherein the CAS is further configured to provide an indication of the condition of the energy source using the pilot display as a function of the application of the remedy datum.