NatureQuest: Gamified Outdoor Exploration Powered by Open AI

This is a submission for the Hacktoberfest Open-Source AI Challenge Week 1: Touch Grass

What I Built

NatureQuest is a web application designed to turn screen time into outdoor exploration. The core concept is simple: to unlock reward coupons and digital badges, users must step away from their screens, go outside, and complete a "Touch Grass Quest."

The quest requires capturing and identifying 10 different elements of nature—such as specific flowers, trees, bird species, or local wildlife. Once the AI verifies 10 unique outdoor finds, the app issues a reward coupon code.

It is built for anyone looking for a fun, gamified motivation to explore local parks, hike, garden, or take active nature walks without staying glued to a screen.

How I Built It

• Open-Source AI Core: Powered by open-weight vision models (e.g., fine-tuned Gemma vision models / Hugging Face Transformers) running local inference via Ollama.
• Frontend & Backend: Next.js web application with a lightweight API route that processes uploaded photos, verifies species, and tracks quest completion.
• Reward Engine: A milestone tracking system that verifies unique nature entries and automatically generates dynamic coupon codes upon reaching 10 verified items.

Why Does Open Innovation Matter?

1. Zero API Charges for Gamified Apps: Closed vision APIs charge per request, making a 10-photo quest cost-prohibitive to scale. Open-weight models allow unlimited photo scans at zero marginal cost.
2. Offline Trail Functionality: Outdoor nature walks often lack stable cellular connectivity. Running local inference enables full identification capabilities deep on hiking trails without cloud internet access.
3. Privacy-First Design: Nature captures don't need to be uploaded or stored on proprietary cloud platforms, keeping user location and camera data private.