RescueSim

RescueSim is a 911 dispatcher training tool that simulates emergency scenarios using text or voice interactions. It provides realistic feedback and performance analysis to enhance user skills.

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RescueSim

What It Does

RescueSim is an advanced training platform for 911 dispatchers, offering realistic emergency scenarios to improve decision-making skills.

How We Built It

  1. Frontend: We designed a responsive user interface using HTML, CSS, and JavaScript to make the platform intuitive and user-friendly.
  2. Backend: Built with Python and FastAPI, our backend processes user inputs, manages simulations, and connects with the frontend.
  3. AI Integration: OpenAI GPT generates realistic victim responses, while Google Cloud Speech-to-Text and Text-to-Speech handle voice interactions for Speech-to-Speech modes.
  4. Deployment: We used Render to deploy the application, ensuring reliability and accessibility for live usage.
  5. Feedback System: A robust evaluation system analyzes dispatcher performance, offering constructive feedback and ratings to help trainees improve.

Challenges We Ran Into

  • API Integration: Ensuring smooth communication between OpenAI, Google Cloud services, and our backend required extensive debugging.
  • Speech Features: Implementing real-time transcription and audio synthesis posed many challenges
  • Deployment Issues: Hosting both the frontend and backend on Render introduced compatibility challenges that we had to overcome. It took a while.

Accomplishments That We're Proud Of

  • Successfully integrating AI and cloud services to enhance realism and interactivity.
  • Building a fully functional platform that provides impactful training for emergency responders.
  • Creating a Speech-to-Speech mode that replicates real-life dispatcher interactions, complete with voice input and feedback.
  • Deploying the application on an accessible platform, making it accessible to a wide audience.

What We Learned

  • The importance of seamless frontend-backend integration for creating a smooth user experience.
  • How to effectively use AI technologies like OpenAI GPT and Google Cloud Speech APIs in practical applications.
  • The value of iterative design and user feedback in developing a realistic and effective training tool.
  • Teamwork and communication are critical in overcoming complex challenges and delivering a polished product.

What's Next for RescueSim

  • Advanced Scenarios: Introducing more specialized training scenarios, such as disaster response and high-risk medical emergencies.
  • Enhanced Analytics: Providing detailed performance metrics and progress tracking for trainees.
  • Mobile App: Developing a mobile-friendly version for on-the-go training.

Note

Because of how render works the link may load for a while, but once it does everything should start going with ease.

In the video system sound was muted by accident. If you go to the website right now you can hear the victim talk to you, if speech-to-speech mode is selected

Thank you for your time!

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