Plane Catcher

Map of Gatwick Airport
My Fleet page
Quests and Offers page
Badges for finding different number of planes
Badge for login
Quest badge "Find plane with <G-XLEE> tail number"
Quest badge "Find plane <Norwegian flight DY1308> which is landing at <Gatwick South Terminal> in 17 minutes"
Quest badge "Capture a plane before it touches down"
Quest badge "QUICK! Capture 10 planes in the next 5 minutes"
BA Boeing 777
EasyJet Airbus A320
Emirates Airbus A380
Emirates Boeing 777
TUI Boeing 737
TUI Boeing 777
B35 Stealth Bomber
Saab 340
Generic Airbus A320
Generic Airbus A380
Generic Boeing 737
Generic Boeing 777
Boieng 787
Airbus A321
Airbus A330
Embraer E145
Embraer E190
Designs for the planes

Inspiration

Inspired by the addictive, location-based gameplay of Pokémon Go, Plane Catcher brings that same thrill to the airport experience — turning the skies into your playing field.

What it does

Plane Catcher is an interactive, gamified flight-tracking app that lets you "catch" real planes flying overhead to unlock real-world rewards such as airport lounge access and Duty-Free discounts. Powered by live flight data and built for the modern traveller.

How we built it

Front end: React, Flask, Sequal, Vite Backend: Python, Flask Database: SQLite / Sequel AI assistance: ChatGPT, Claude, Gemini

Challenges we ran into

Data limitations — we could only simplify and integrate data for EasyJet flights during the hackathon window. Plane scaling issues — plane icons were rendering at incorrect sizes on the map and required careful CSS/canvas tuning. Web scraping hurdles — FlightAware is not a static HTML site, so traditional HTML scraping failed. We overcame this by intercepting and reading network requests directly. Flight path modelling — accurately positioning planes mid-journey was tricky; early builds had all planes snapping back to Gatwick Airport and disappearing.

Accomplishments that we're proud of

Successfully rendered live, real-time plane data on an interactive map Built a full working prototype end-to-end during a hackathon Cracked the challenge of scraping dynamic websites via network request analysis

What we learned

How to extract data from dynamic, JavaScript-rendered websites by intercepting network requests rather than parsing static HTML — a first for the whole team Integrating multiple AI tools (ChatGPT, Claude, Gemini) into a development workflow Handling live geospatial data and rendering it smoothly on a map

What's next for Plane Catcher

Plane Catcher is just getting started:

🌍 Expand to all airlines and airports globally 🏅 More reward tiers and partnerships with airport retailers 👥 Multiplayer and leaderboard features 📱 Native mobile app