Emergent: AI-Powered Crisis Simulation Platform

Emergent is a web-based, AI-powered Tabletop Exercise (TTX) platform that allows emergency managers to simulate disaster scenarios and their impact on a community. It provides a safe, controlled, and highly detailed environment to practice, test, and refine emergency plans, with a focus on improving communication with vulnerable populations.

The Problem

In a crisis, effective communication can save lives. However, testing communication strategies, especially for reaching diverse and vulnerable communities, is incredibly challenging. Traditional tabletop exercises are often static and resource-intensive. Emergent aims to solve this by providing a dynamic, AI-driven simulation environment that models complex human behaviors and communication patterns.

Key Features

• AI-Powered Scenario Generation: Use Google's Gemini model to dynamically generate realistic disaster scenarios and narrative injects.
• Interactive Simulation: Run exercises on an interactive GIS map, with events unfolding over a structured timeline.
• Persona-Based Modeling: Simulate a diverse community with unique "personas" that react differently to events based on their demographics and roles using Google Gemini's ADK and Parallel Agents
• AI Chat Interaction: Engage with an Gemini AI-powered chatbot to get situational updates and test communication strategies by seeing how personas react.
• Comprehensive After-Action Reporting: Generate detailed reports after each simulation, including an executive summary, deep-dive analytics, and an interactive timeline replay.
• Modern, Intuitive Interface: A clean and responsive UI built with Next.js, Tailwind CSS, and shadcn/ui.

Technology Stack

• Framework: Next.js 14+
• Language: TypeScript
• AI: Google Gemini via @google/generative-ai
• Styling: Tailwind CSS with shadcn/ui
• Mapping: React Leaflet
• 3D Visualization: React Three Fiber & Drei

Getting Started

Follow these instructions to get a local copy of the project up and running for development and testing.

Prerequisites

• Node.js (v20.x or later recommended)
• npm or yarn

Installation

1. Clone the repository:

   git clone https://github.com/your-username/your-repository-name.git
   cd your-repository-name

2. Install dependencies:

   npm install

3. Set up environment variables:

   This project requires an API key for the Google Gemini AI service.

   Create a file named .env.local in the root of the project and add your API key:

   GOOGLE_API_KEY="YOUR_API_KEY_HERE"
   

4. Run the development server:

   npm run dev

   Open http://localhost:3000 with your browser to see the result.

Other Scripts

• Build for production:

  npm run build

• Run production server:

  npm run start

• Run linter:

  npm run lint

Project Structure

The codebase is organized to keep a clean separation of concerns.

• app/: Contains the core application logic, pages, and API routes, following the Next.js App Router structure.
  • app/api/: Backend API endpoints for AI generation, chat, etc.
  • app/components/: The majority of the React components that make up the UI.
  • app/(pages)/: Different top-level pages like /editor, /simulation-v2, etc.
• components/ui/: Core UI components from shadcn/ui.
• lib/: Contains utility functions, type definitions, and state management stores.
  • lib/stores/: State management logic (e.g., Zustand stores).
  • lib/types/: TypeScript type definitions for data structures like scenarios and personas.
• public/: Static assets like images and icons.

Contributing

Contributions are welcome! If you have a suggestion or find a bug, please open an issue to discuss it.

License

This project is licensed under the MIT License. See the LICENSE file for details.