Smart Rescue

Inspiration

Often at times , the emergency call center might be overwhelmed by a lot of people seeking help or may be understaffed , during these situations certain emergency calls might not be entertained or missed . To avoid such cases we introduce our project Smart Rescue

What it does

Whenever there's a busy line from emergency call center , we have smart rescue ai to listen to the emergency , and get the important details from there . It marks an emergency prioritywise and dispatches accordingly.

How we built it

The Features which we have in Smart Rescue:

AI-powered call management: Smart Rescue uses natural language processing (NLP) and machine learning (ML) to identify the urgency of each call and prioritize them accordingly. Call grading based on keywords: Smart Rescue grades each call based on the keywords spoken by the caller. This allows the system to quickly identify urgent calls and transfer them to the emergency handler. Location tracking: Smart Rescue also records the location of each caller and provides this information to the handler. Call transcript: Smart Rescue provides a transcript of each call to the emergency handler, allowing them to quickly and accurately assess the situation and respond accordingly. Automated responses: In some cases, Smart Rescue can provide automated responses to callers to guide them through emergency situations until an emergency handler is available.

Challenges we ran into

Some of the challenges we faced were in the areas of voice recognition, the Ethereum implementation and some of the backend integration with the frontend of our application.

What's next for Smart Rescue

Looking forward to make our project into a real world product

Built With

• assemblyai
• ethereum
• github
• gpt3.5
• metamask
• pythonflash
• react.js
• twiliorestapi