Artificial intelligence for emergency assistance with human feedback for machine learning

A method for providing emergency assistance comprising:

• receiving audio, visual, or text data about an ongoing emergency at a public safety answering point comparing said audio, visual, or text data about said ongoing emergency with a database of other emergencies using an artificial intelligence engine;
• recognizing key words and patterns in aggregated and correlated data by the artificial intelligence engine;
• generating appropriate audio, visual, and text output for a human operator to respond to said ongoing emergency;
• and
• generating feedback to the artificial intelligence engine to aid in machine learning, wherein said feedback includes one or more of the following:
• (i) continue drawing this conclusion;
• and (ii) stop drawing this conclusion.

A method for providing emergency assistance comprising:

• receiving audio, visual, or text data about an ongoing emergency at a public safety answering point;
• comparing said audio, visual, or text data about said ongoing emergency with a database of other emergencies using an artificial intelligence engine;
• recognizing key words and patterns in aggregated and correlated data by the artificial intelligence engine;
• generating appropriate audio, visual, and text output for a human operator to respond to said ongoing emergency;
• and
• generating feedback to the artificial intelligence engine to aid in machine learning, wherein said feedback includes one or more of the following:
• (i) a reason why the message was correct;
• and (ii) a reason why the message was incorrect.

A method for managing and processing data from a plurality of public safety answering points comprising:

• receiving audio data, visual data, and text data related to a plurality of ongoing emergencies being received at a plurality of public safety answering points;
• comparing said audio data, visual data, and text data about said plurality of ongoing emergencies with one or more databases storing relevant data from a plurality of other emergencies using an artificial intelligence engine;
• identifying a plurality of key words and a plurality of patterns among the compared data by the artificial intelligence engine;
• generating appropriate audio, visual, and text output for a plurality of human operators to respond to said plurality of ongoing emergencies;
• and
• generating continuously feedback to the artificial intelligence engine to aid in machine learning based on the generated output;
• and
• wherein said feedback includes whether the message was correct or not, and wherein said feedback includes one or more of the following:
• (i) continue drawing this conclusion;
• and (ii) stop drawing this conclusion.

A method for managing and processing data from a plurality of public safety answering points comprising:

• receiving audio data, visual data, and text data related to a plurality of ongoing emergencies being received at a plurality of public safety answering points;
• comparing said audio data, visual data, and text data about said plurality of ongoing emergencies with one or more databases storing relevant data from a plurality of other emergencies using an artificial intelligence engine;
• identifying a plurality of key words and a plurality of patterns among the compared data by the artificial intelligence engine;
• generating appropriate audio, visual, and text output for a plurality of human operators to respond to said plurality of ongoing emergencies;
• and
• generating continuously feedback to the artificial intelligence engine to aid in machine learning based on the generated output;
• and
• wherein said feedback includes whether the message was correct or not, and wherein said feedback includes one or more of the following:
• (i) a reason why the message was correct;
• and (ii) a reason why the message was incorrect.

A method for managing and processing data from a plurality of public safety answering points comprising:

• receiving audio data, visual data, and text data related to a plurality of ongoing emergencies being received at a plurality of public safety answering points;
• comparing said audio data, visual data, and text data about said plurality of ongoing emergencies with one or more databases storing relevant data from a plurality of other emergencies using an artificial intelligence engine;
• identifying a plurality of key words and a plurality of patterns among the compared data by the artificial intelligence engine;
• generating appropriate audio, visual, and text output for a plurality of human operators to respond to said plurality of ongoing emergencies;
• and
• generating continuously feedback to the artificial intelligence engine to aid in machine learning based on the generated output;
• and
• wherein said feedback includes whether the message was correct or not, and wherein said feedback includes one or more of the following:
• (i) the message was correct;
• continue drawing this conclusion;
• and (ii) the message was wrong;
• do not continue drawing this conclusion.

A method for managing and processing data from a plurality of public safety answering points comprising:

• receiving audio data, visual data, and text data related to a plurality of ongoing emergencies being received at a plurality of public safety answering points;
• comparing said audio data, visual data, and text data about said plurality of ongoing emergencies with one or more databases storing relevant data from a plurality of other emergencies using an artificial intelligence engine;
• identifying a plurality of key words and a plurality of patterns among the compared data by the artificial intelligence engine;
• generating appropriate audio, visual, and text output for a plurality of human operators to respond to said plurality of ongoing emergencies;
• and
• generating continuously feedback to the artificial intelligence engine to aid in machine learning based on the generated output;
• and
• wherein said feedback includes whether the message was correct or not, wherein said feedback includes one or more of the following:
• (i) the message was correct because of X;
• continue drawing this conclusion;
• and (ii) the message was wrong because of Y;
• do not continue drawing this conclusion.