EmberAI

An open‑source, AI‑powered mapping dashboard for tracking wildfires and shelter locations in real time.

EmberAI combines lightning‑fast search with meaningful AI insights to equip communities, first responders, and volunteers with the information they need to act quickly during fire emergencies.

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🚀 Key Features

• Geo‑Aware Search with Algolia MCP

  • Unified proxy for multiple indices (fires, shelters, aqi).
  • Instant insideBoundingBox filtering for map viewport queries.
  • High‑performance faceting (e.g. severity:4+, state:CA).

• AI Enrichment via n8n Workflows

  • Fire Severity Classification: Automated LLM calls convert raw satellite data into a 1–5 urgency score and one‑sentence summary.
  • Shelter Capacity Forecasting: Time‑series API + LLM or ARIMA predicts near‑future capacity risks (boolean flag).
  • Modular workflows in n8n, no additional server code required.

• Real‑Time Data Ingestion

  • MODIS / VIIRS fire data from NASA FIRMS (7‑day CSV feeds).
  • FEMA shelter locations via open data API.
  • Optional Air Quality Index (AQI) from AirNow.
  • Secure, batch indexing into Algolia with a Python pipeline (update_indices.py).

• Interactive Map UI

  • React + Leaflet front‑end with colored circle markers: scale up severity from green→purple.
  • Popups display date, confidence, AI summary, and capacity forecasts.
  • Search bar for date, confidence, and full‑text queries.
  • Responsive design for desktop and tablet use.

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📦 Getting Started

Follow these steps to run EmberAI locally. No paid hosting or accounts required.

1. Clone the repository

git clone https://github.com/devinnicholson/emberAI.git
cd emberAI

2. Configure environment

Create a .env file based on .env.example:

cp .env.example .env

Fill in at minimum:

ALGOLIA_APP_ID=your_algolia_app_id
ALGOLIA_ADMIN_KEY=your_algolia_admin_key
# Optional (for AQI): AIRNOW_API_KEY=your_airnow_api_key
# Optional (for severity workflows): OPENAI_API_KEY=your_openai_api_key
# n8n Webhook URL: "http://n8n:5678/webhook/fire-severity"
N8N_FIRE_WEBHOOK_URL=http://n8n:5678/webhook/fire-severity

3. Launch with Docker Compose

docker-compose up --build -d

Services:

• backend (Python indexer + Algolia MCP proxy on port 4000)
• frontend (React UI on port 5173)
• n8n (AI workflow engine on port 5678)

4. Run initial data ingest

docker-compose exec backend python /app/update_indices.py

5. Access the dashboard

• UI: http://localhost:5173
• n8n Editor: http://localhost:5678 (no signup or payment required)

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📈 Architecture Overview

flowchart LR
  subgraph Ingestion
    F(FIRE CSVs) -->|fetch_fires| B[index_records]
    S(SHELTER API) -->|fetch_shelters| B
    A(AQI API) -->|fetch_aqi| B
    B -->|batch to Algolia| Algolia[(Algolia MCP)]
    B -->|batch webhook| n8nWebhook((n8n Webhook))
  end

  subgraph Enrichment
    n8nWebhook --> LLM[LLM Classification]
    LLM -->|severity & summary| Algolia
    Cron[Hourly Cron] -->|shelter series| LLM2[Capacity Forecast]
    LLM2 -->|capacityRisk| Algolia
  end

  subgraph Frontend
    Algolia -->|search + facets| Map[React + Leaflet UI]
  end

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🤝 Contributing & Next Steps

I welcome contributions to:

• Add regional filters and custom alerts (e.g. SMS/email hooks).
• Integrate reverse‑geocoding for human‑readable locations.
• Enhance UI/UX with chart overlays and data exports.

Let's build stronger wildfire response tools together 🌍🔥