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Cision: AI-Powered Urban Road Safety Platform

Cision Logo

Cursor for City Planning
Transform collision data into actionable, buildable intersection designs in minutes.

Features • Demo • Tech Stack • Getting Started


The Problem

Every year, 1.35 million people die in road traffic accidents globally. In Toronto alone, there are 50,000+ reported collisions annually. The data exists: but it's trapped in spreadsheets, buried in bureaucracy, and disconnected from the planning decisions that could prevent deaths.

  1. Data Gap: Collision data is abstract and scattered with no visual context
  2. Analysis Gap: Safety audits take months and cost thousands of dollars
  3. Communication Gap: Planners can't easily show stakeholders why changes matter

Our Solution

Cision is an AI-powered urban planning platform that transforms raw collision data into interactive 3D visualizations, instant safety audits, and stakeholder-validated redesigns: all in minutes, not months.

How It Works

┌─────────────────┐     ┌─────────────────┐     ┌─────────────────┐     ┌─────────────────┐
│  Collision Data │────▶│  3D Heatmap     │────▶│  AI Safety      │────▶│  AI Redesign    │
│  (Toronto Open  │     │  Visualization  │     │  Audit          │     │  Generator      │
│   Data)         │     │                 │     │  (6 metrics)    │     │                 │
└─────────────────┘     └─────────────────┘     └─────────────────┘     └─────────────────┘
                                                                   │
                                                                   ▼
                                                           ┌─────────────────┐
                                                           │  Voice Agent    │
                                                           │  Stakeholders   │
                                                           │  (Cyclist, Mayor,│
                                                           │   Engineer)     │
                                                           └─────────────────┘

🚀 Features

1. Interactive Collision Heatmap

  • 3D MapGL visualization with clustered hotspots
  • Color-coded by severity (green → red)
  • Filter by collision type: fatalities, cyclist-involved, pedestrian-involved

2. AI Safety Audit

Instant safety audits with:

  • 6 safety metrics (0-100 scale): Signage, Lighting, Crosswalk Visibility, Bike Infrastructure, Pedestrian Infrastructure, Traffic Calming
  • 4-direction Street View composite
  • Identified safety flaws with severity levels
  • Improvement suggestions with priority, cost estimates, and expected impact

3. AI-Powered Intersection Redesign

  • Natural language image generation for intersection transformations
  • Version history carousel to compare designs
  • Iterative refinement workflow

4. Multi-Persona Voice Agents

Three AI stakeholders (powered by ElevenLabs) provide instant feedback:

  • Amogh Merudi: DoorDash Courier & Collision Survivor
  • Olivia Chow: Mayor of Toronto
  • Marcus Chen: Traffic Engineer, P.Eng.

5. Smart Intersection Search

  • Search by intersection name or address with Google Places autocomplete
  • Keyboard navigation and recent search history

6. Collision Statistics Dashboard

  • Date range analysis and victim breakdown
  • Normalized severity scoring vs. city-wide data

🎥 Demo

Watch our 3-minute demo:

Cision Demo


🛠 Tech Stack

Frontend

  • Next.js 16 (App Router, React 19)
  • TypeScript
  • React Map GL / Mapbox (3D mapping)
  • Tailwind CSS + Framer Motion
  • Zustand (state management)
  • Vercel AI SDK

Backend & APIs

  • Next.js API Routes (serverless)
  • MongoDB (collision data storage)
  • Google Gemini (safety audit & image generation)
  • ElevenLabs (voice agents)
  • Google Places API (autocomplete + place details)

AI/ML

  • Nano Banana Pro (image generation for redesigns)
  • OpenAI Vision (Street View analysis)
  • Custom clustering algorithm (collision hotspot detection)

Infrastructure

  • Vercel (deployment)
  • Mapbox (maps)
  • GitHub Actions (CI/CD)

📁 Project Structure

cision/
├── app/
│   ├── api/                # API routes (chat, clusters, safety-audit, etc.)
│   ├── map/                # Main app page
│   └── page.tsx            # Landing page
├── components/
│   ├── map/                # Map components
│   ├── search/             # Search components
│   ├── sidebar/            # Sidebar components (intersection, persona, audit, chat)
│   └── ui/                 # Shared UI components
├── lib/                    # Utilities (clustering, prompts, etc.)
├── stores/                 # State management (Zustand)
└── types/                  # TypeScript type definitions

🚦 Getting Started

Prerequisites

  • Node.js 18+
  • npm / yarn / bun
  • Mapbox API token
  • Google Gemini API key
  • ElevenLabs API key
  • Google Places API key (optional)

Installation

# Clone the repository
git clone <repository-url>
cd cision

# Install dependencies
npm install

# Set up environment variables
# Create .env.local with:
NEXT_PUBLIC_MAPBOX_TOKEN=your_mapbox_token
GOOGLE_GEMINI_API=your_gemini_key
ELEVENLABS_API_KEY=your_elevenlabs_key
NEXT_PUBLIC_GOOGLE_PLACES_API_KEY=your_google_places_key

# Run development server
npm run dev

🙏 Acknowledgments

  • Toronto Open Data Portal for collision data
  • Mapbox for mapping tools
  • ElevenLabs for voice synthesis
  • Google Gemini for AI capabilities
  • DeltaHacks 2026 for the opportunity to build this

Built with ❤️ for safer cities

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