Are you a true magellan

The Problem: The Unsustainable and Uninspired Traveler

The current travel ecosystem faces two major interconnected problems:

1. High Carbon Footprint: Tourism accounts for a significant portion of global greenhouse gas emissions, primarily from air travel. Many travelers wish to be more sustainable but lack actionable, personalized guidance to reduce their environmental impact.

2. Travel Fatigue and Homogeneity: Existing travel recommendations are often generic, driven purely by commercial partnerships, or based on shallow data (e.g., "People who went to X also went to Y"). This leads to repetitive itineraries, overcrowding of popular destinations ("overtourism"), and missed opportunities for unique, personalized experiences.

The Solution: "True Magellan" – The Sustainable, Personalized Navigator

"True Magellan" is an AI-powered travel planning service that acts as a user's personal, sustainable navigator. It solves the problems by:

• Deep Personalization (The "True" Part): By analyzing a user's past travel data (e.g., photos, social media check-ins, purchase history, flight/train records, ratings) and stated preferences (e.g., nature vs. city, budget, pace), the platform builds a "Travel DNA" profile.

• Carbon Footprint Optimization (The "Magellan" Part): The core innovation is a sophisticated algorithm that matches the "Travel DNA" to a destination while simultaneously minimizing the projected carbon footprint of the entire trip.

How it Solves It:

1. Data-Driven Destination Selection: Instead of suggesting another flight across the globe, it prioritizes alternative, closer, or rail-accessible destinations that align with the user's true interests. For example, if a user loves the rugged coastlines of Norway, but lives in Central Europe, the algorithm might suggest the lesser-known, equally stunning coastline of the Scottish Highlands, accompanied by a low-emission rail/ferry route.

2. Integrated Low-Carbon Routing: The platform doesn't just suggest a destination; it suggests the entire journey. It maps out the most carbon-efficient path (trains, electric buses, localized public transport) and provides the associated real-time carbon budget for the whole trip, empowering the user to make an informed, sustainable choice.

3. Combating Overtourism: The platform can use spatial data (including EU space data) to suggest under-utilized or emerging destinations that offer similar experiences to overcrowded hotspots, helping to distribute tourist flow more evenly.

Challenge link:

This algorithm uses space innovation (Copernicus, Galileo) to analyze user history and environmental data. It redefines travel by providing personalized, low-impact destinations and optimal low-CO2 routes, perfectly matching the "Beyond Horizons" challenge.

The Team:

👩‍💻 Developer, responsible for the tooling kit, data access, and technical integration– Nishant

🎨Data Set Research, Data Analysis, UI/UX Prototyping, and Final UI/UX - Sweta 

👨‍🔬Data Set Research, Data Analysis, and Parameter Identification. - Sarah 

💼 Business Lead – Partnerships & Strategy - Nishant & Sweta

Data used:

1. Copernicus Atmosphere Monitoring Service (CAMS):
   • Fetch regional data for key air quality indicators.
   • Metrics: Average concentrations of Particulate Matter (PM2.5, PM10), Nitrogen Dioxide (NO2), and ground-level Ozone (O3).
   • Logic: Lower concentrations = better score.
2. Copernicus Land Monitoring Service (CLMS):
   • Fetch data on land use and quality.
   • Metrics: Use the Urban Atlas to find the percentage of "Green Urban Areas" (parks, forests) within a city. Use water quality data for coastal/lake destinations.
   • Logic: Higher percentage of green space = better score.

Code Repo:

https://github.com/kurtesy/magellan-cassini-hackathon25

This innovative blend of AI personalization and objective space-derived data transforms travel planning from a commercial transaction into a mission-driven exercise—making the user a True Magellan who explores sustainably, responsibly, and authentically.