Systems And Methods For Disturbance Detection And Identification Based On Disturbance Analysis

A method of implementing an intelligent disturbance detection system, the method comprising:

• capturing a disturbance comprising a sound, an image, or combinations thereof via an application tool on a mobile smart device of the intelligent disturbance detection system remote from a user;
• extracting features from the disturbance to generate one or more extracted features;
• comparing the one or more extracted features to one or more disturbance labels of a disturbance set in a comparison by a disturbance detection neural network model of the application tool;
• generating a disturbance label from the one or more disturbance labels when the one or more extracted features match the disturbance label in the comparison;
• training the disturbance detection neural network model to generate a custom disturbance label associated with the one or more extracted features when the one or more extracted features do not match the one or more disturbance labels in the comparison;
• and
• generating an automatic alert via the mobile smart device to transmit an identification of the disturbance to the user based on the disturbance label, the custom disturbance label, or combinations thereof.

A method of implementing an intelligent disturbance detection system, the method comprising:

• capturing a disturbance comprising a sound, an image, or combinations thereof via an application tool on a mobile smart device of the intelligent disturbance detection system remote from a user;
• extracting features from the disturbance to generate one or more extracted features;
• comparing the one or more extracted features to one or more disturbance labels of a disturbance set in a comparison by a disturbance detection neural network model of the application tool;
• generating a disturbance label from the one or more disturbance labels when the one or more extracted features match the disturbance label in the comparison;
• training the disturbance detection neural network model to generate a custom disturbance label associated with the one or more extracted features when the one or more extracted features do not match the one or more disturbance labels in the comparison;
• and
• generating an automatic alert via the mobile smart device to transmit an identification of the disturbance to the user based on the disturbance label, the custom disturbance label, or combinations thereof, wherein the automatic alert comprises a timestamp and a confidence level associated with the identification of the disturbance.