I myself have come across this situation where my power button on the mobile phone is long pressed and the 911 call is been called and the 911 dispatcher has to call back to attend the situation which was a mistake using Natural Language Processing and Machine Learning I have developed an AI software which will understand such miss calls and call back the person and proceeds with asking whether it was a mistake or real situation if it was a mistake it attends the call acknowledge the person and disconnect the call and if it was real emergency situation it proceeds with more situational questions like what is the emergency etc or in the other hand it has a function to transferring the call to real 911 dispatcher.

What it does

it collects the voice data on the real-time and does NLP and responds in a human voice understanding the problem situation using ML

How I built it

I used Dialogflow by Google to develop the NLP module of the system which is deployed on and processing is carried out on google cloud and TensorFlow by google.

Challenges I ran into

Understanding the different types of case Intends and Entities of dialogflow

What I learned

converting real-life issue solution using NLP

What's next for AI and NLP based 911 Dispatcher

now it is just on a prototype level , it will require more dataset to train it on so that it can understand every situation and all different languages

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