🌿 LeafQuest uses AI-powered nature quests to get people outdoors, explore nature, and spend less time on screens! #Hacktoberfest

Surbhi Srivastav — Mon, 12 Oct 2026 02:22:36 +0000

🌿 LeafQuest — Turn Screen Time Into Outside Time

What I Built

LeafQuest is an outdoor exploration game designed around a simple idea:

Use technology to help people spend less time using technology.

Instead of opening another app to scroll, LeafQuest gives users small real-world nature challenges.

For example:

🍃 Find a unique leaf
🌳 Discover a tree
🌸 Find a flower
🪵 Photograph an interesting natural texture
🐦 Look for signs of wildlife
🔎 Discover something in nature you've never noticed before

The user chooses how long they want to explore, receives a set of challenges, and then puts their phone away and goes outside.

When they return, they can photograph their discovery. The AI analyzes the image and helps determine whether it matches the challenge.

Completed discoveries earn points and are added to the user's Nature Passport, creating a record of their outdoor exploration.

The goal isn't to maximize screen time.

The goal is to make the screen useful for a few seconds and the real world interesting for much longer.

Demo

🌐 Live Demo:

https://leaf-quest-nature-adventure-app--surbhisrivasta7.replit.app

The complete application was developed and deployed using Replit.

I used Replit's development environment to build the frontend, backend, AI integration, and deployment workflow in one place.

How I Built It

I built LeafQuest as a full-stack web application with an offline-first mindset and a modular AI recognition system.

🖥️ Development & Deployment

Replit was used throughout the development process for:

Writing and generating the application code
Building the frontend and backend
Testing the application
Debugging and iterating
Managing the project environment
Deploying the final application

This made it possible to go from the initial idea to a working, deployed prototype without maintaining a complicated local development setup.

Frontend

The application provides:

Quest selection
Nature challenges
Image capture/upload
Progress tracking
Discovery history
Nature Passport
Responsive mobile experience

Backend

The backend manages:

Quest generation
Discovery processing
AI recognition requests
Verification logic
User progress
Discovery data

🤖 AI Recognition

LeafQuest uses an open-source/open-weight AI approach for recognizing objects in nature photographs.

The AI recognition layer is separated from the rest of the application so that the underlying model can be replaced or upgraded without redesigning the entire application.

The basic flow is:

Choose a Quest
      ↓
Go Outside 🌿
      ↓
Find Something
      ↓
Take a Photo 📸
      ↓
AI Recognition
      ↓
Challenge Verification
      ↓
Earn Points ⭐
      ↓
Nature Passport

This architecture also leaves room for future contributors to experiment with different open models and improve recognition accuracy.

Why Does Open Innovation Matter?

For LeafQuest, open innovation isn't just about making the code public.

It gives the project flexibility, transparency, and room for experimentation.

🔐 Privacy

Nature photographs can contain contextual or location information. An open/local AI approach can reduce dependence on sending every image to a closed third-party AI service.

🔄 Model Freedom

A closed API can lock a project into one provider.

With an open-weight model and a modular AI layer, developers can experiment with different models, fine-tune them, or replace them as better models become available.

🌐 Accessibility

Open-source technologies make it easier for students and independent developers to experiment without needing access to expensive proprietary AI infrastructure.

🛠️ Community Contributions

Because the project is open, contributors can improve different parts of LeafQuest independently:

Better nature recognition
New outdoor challenges
Improved verification
New badges
Better offline functionality
New AI models

That is what makes open innovation especially interesting for this project: the AI isn't meant to be a black box. It's a component that the community can experiment with and improve.

My Agent Session

Optional — add your DevRelay agent session here.

Agent Session: [Add DevRelay session link]

Prize Categories

🌿 Hacktoberfest Open-Source AI Challenge — Week 1: Touch Grass

Theme:

Using open-source/open-weight AI to encourage people to spend more time exploring the physical world and less time behind screens.

Development & Deployment:

Built and deployed using Replit.

🌱 The Idea Behind LeafQuest

Most digital products compete for our attention.

LeafQuest tries to do the opposite.

It uses technology to create a reason to leave the screen, walk outside, look around, and notice the world.

The best LeafQuest session isn't one where someone spends an hour inside the app.

It's one where they open it, get a challenge, put the phone away, explore, and come back with a discovery.

Sometimes the best use of technology is knowing when to put it down. 🌿

DEV Community: Surbhi Srivastav