Sky Sense

A real-time Canadian flight analytics platform to detect mid-air conflicts and visualize multi-aircraft conflicts, hotspots, and waypoint traffic patterns in a fully interactive dashboard.

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SkySense

Real-Time Flight Conflict & Airspace Intelligence

Problem

Canada’s airspace is becoming increasingly complex as flight volumes continue to rise. Traditional tools mainly offer static flight tracking or post-incident monitoring, leaving critical gaps:

  • Early detection of mid-air conflicts
  • Understanding traffic congestion around high-density waypoints
  • Visualizing how multiple aircraft interact dynamically within shared airspace

There is no accessible, lightweight platform that enables real-time conflict analysis, multi-aircraft visualization, or waypoint-level traffic insights.

Our Solution

Flight Analytics Dashboard is a real-time airspace analysis platform that combines a Python-based flight simulation engine with an interactive React + Leaflet visualization dashboard. The system simulates 250–1000 Canadian flights, detects multi-aircraft conflicts, identifies airspace hotspots, and lets users explore each conflict in detail on a dynamic map. Our goal was to build something lightweight, visual, and analytical, giving users a clear view of how aircraft share the sky.

Why It Matters

Air traffic management is moving toward proactive safety, requiring tools that can:

  • Visualize aircraft interactions before incidents occur
  • Analyze airspace congestion in real time
  • Scale with rising air traffic density
  • Support training, research, and automated conflict-avoidance systems

Our platform shows how simulation + analytics + visualization can work together to provide immediate insight into complex airspace behavior. This foundation can evolve into:

  • Real-time integration with ADS-B feeds
  • Predictive conflict resolution
  • AI-assisted risk scoring
  • Airspace optimization tools

How It Works

Flight Simulation & Conflict Detection (Python)

We built a custom Python engine (FlightPath.py) that:

  • Simulates aircraft trajectories over time
  • Detects conflicts involving two or more aircraft
  • Calculates the time (in seconds after departure) when conflicts occur
  • Outputs structured conflict data in conflicts.json
  • Re-generates results every time the user runs an analysis

This gives us a fresh, accurate conflict snapshot on demand.

Interactive Dashboard (React + Vite)

Our dashboard visualizes the entire dataset with:

  • Total flights
  • Time-of-day distribution
  • Altitude histograms
  • Aircraft type breakdown
  • Top routes
  • Live hotspot identification
  • Conflict table with deep-dive navigation

A single click — Run Analysis — re-simulates all trajectories and updates the results instantly.

Conflict Resolver (Leaflet Map)

Clicking any conflict opens a dedicated map view that:

  • Visualizes every aircraft involved (2–6+)
  • Draws complete trajectories: departure airport → all waypoints → arrival airport
  • Assigns each aircraft a unique color
  • Shows the exact moment the conflict occurs
  • Allows users to compare paths and understand why the conflict happened

Hotspot Detection

Using route parsing and a dynamically generated waypoint → list of ACID codes dictionary, our system:

  • Counts traffic at each waypoint
  • Determines hotspots using a dataset-adaptive threshold
  • Highlights overloaded or high-risk waypoints

This works for any dataset size, from hundreds to thousands of flights.

Key Technical Features

  • True multi-aircraft conflict detection (not limited to pairs)
  • Live integration between Python and React via a custom Vite API endpoint
  • Dataset-agnostic hotspot algorithm
  • Full multi-waypoint route visualizations
  • Centralized state sharing (React Context)
  • Scales from 250 to 1000+ flights without structural changes

Tech Stack

  • Frontend: React, Vite, Leaflet
  • Backend / Simulation: Python, Javascript (custom trajectory engine)
  • Data Handling: Node.js, JSON
  • Version Control: GitHub
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