OutsideIRL: Less Scrolling, More Living | Touch Grass Challenge

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

OutsideIRL: Less Scrolling, More Living 🌿

What I Built

OutsideIRL is a web app built around a simple idea: technology should help us experience the real world, not keep us stuck in front of a screen.

As students, we spend a lot of time on our laptops and phones for classes, assignments, and entertainment. Sometimes, we forget to take a break, step outside, and notice what's happening around us.

OutsideIRL encourages people to take small steps toward a more active and mindful lifestyle through simple outdoor missions.

Users can explore missions, filter activities by category, use a timer, track completed activities, and record personal reflections.

The goal isn't to spend more time using the app. It's to use the app as a starting point, put the phone away, and actually experience the activity.

Demo

Live Demo: https://anushkabajpaigarg10-debug.github.io/OUTSIDEIRL/

Code

GitHub Repository: https://github.com/anushkabajpaigarg10-debug/OUTSIDEIRL.git

The project currently uses HTML, CSS, and JavaScript, with browser local storage for supported progress data.

How I Built It

I built OutsideIRL using HTML for the structure, CSS for the design and responsive layout, and JavaScript for the interactive features.

The current prototype includes predefined outdoor missions, category filters, a mission timer, progress tracking, and personal reflections.

For this first version, I focused on creating a working frontend prototype that demonstrates the core experience.

Integrating an open-weight AI model to generate personalized outdoor missions is a planned next step. I want to explore running an open-source model locally so the experience can become more adaptive while giving users greater control over their data.

Why Does Open Innovation Matter?

I believe open innovation matters because useful technology should be something people can explore, understand, adapt, and improve.

For OutsideIRL, open-source AI could make it possible to generate outdoor activities based on a person's interests, available time, and surroundings without depending entirely on a closed AI service.

Local inference could also offer more control over personal data and allow developers to experiment with models on their own devices.

I haven't implemented that AI integration yet, but it's an important part of where I want to take this project.

For me, the bigger idea is that AI doesn't always have to give people another reason to stay online. It can help them discover reasons to step outside.

Prize Categories

I'll add the applicable partner categories after confirming which ones my implementation qualifies for.