slower.

💎 Idea

In today's fast-paced world, people are overwhelmed and need a break. Planning such a break often causes even more stress. Our project solves this paradox by offering a simple, automated, and personalized solution that removes the need for planning and allows you to truly relax. Easily, effortlessly, and without stress.

🛰️ EU Space Technologies

The project uses data collected from the Copernicus to develop a computer vision-based image detection model. The system goal is to automatically identify and classify regions and surface features that align with the concept of slow travel. By combining advanced image analysis with Earth observation data, the project seeks to create a tool that bridges scientific data processing with real-world applications in exploration, tourism, and environmental awareness.

Our team:

Karol Kowal – Project Manager & Product Owner

Leads the project and coordinates cross-functional collaboration. Oversees product strategy, technical roadmap, and integration of satellite-based solutions. Ensures alignment between design, data, and infrastructure while maintaining focus on innovation and sustainability.

Zuzanna Marciniak – UX Strategist & Designer

Conducts user research and contributes to the conceptual and interaction design. Ensures that the product remains intuitive, human-centered, and aligned with user needs.

Katarzyna Kuczyńska – UX/UI Designer

Designs intuitive and visually cohesive interfaces. Responsible for prototypes, usability, and aesthetic consistency across platforms.

Jan Domański & Piotr Niemiec – Front-end Developers

Build responsive and interactive user interfaces, turning design into seamless digital experiences for both web and mobile platforms.

Szymon Gazdowicz – Data Scientist (Earth Observation)

Integrates and analyzes Copernicus satellite data, focusing on spatial modeling and environmental insights to enhance travel recommendations and awareness.

Kacper Gałan – Data Scientist (Machine Learning)

Develops models that combine satellite, environmental, and contextual data to deliver personalized, sustainable travel suggestions.