Trail Ears: Identify Bird Calls in Your Browser, Even With No Signal

Simran Jaiswal — Sat, 10 Oct 2026 14:42:24 +0000

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

What I Built

Trail Ears is a website that identifies bird calls. You record or upload a short clip, and it shows the top 3 likely species with confidence scores. You can log each sighting with a note and export your trail log as a CSV.

It is built to make the screen the shortest part of a walk: It keeps screen time short: record a clip of up to 12 seconds, put the phone away, and check the result and log it when you’re ready. It works for hikers, birders, run clubs, or anyone who has stood outside wondering what that sound is.

Demo

Live site: https://Er-Simran-Jaiswal.github.io/birdnet-web/trail-ears.html

Code

Repo: https://github.com/Er-Simran-Jaiswal/birdnet-web

The new pieces are trail-ears.html (the interface, location filter, and trail log) and sw.js (the offline cache).

How I Built It

Model: BirdNET, an open-source bird sound identification model from the Cornell Lab of Ornithology and Chemnitz University of Technology.
Inference: it runs in the browser with TensorFlow.js, using the open-source browser port georg95/birdnet-web, which I forked.
My part: a new front end with recording and upload, top-3 results, a minimum-confidence slider, an optional location filter that narrows species to the area and time of year, and a local trail log with CSV export.
Offline: a service worker caches the model and page after the first load, so it can keep working with no signal.

Why Does Open Innovation Matter?

No signal needed: a closed API stops working the moment you lose coverage, which on a trail is almost always. With open weights the model lives in the browser's cache.
Privacy: audio and location are processed on the device, so there is no server to send them to.
Cost: no API key, no account, no usage bill.
Hackable: because the model and the browser port are open, I could build a new interface and location filtering on top without asking anyone for permission.

Credits: BirdNET (CC BY-NC-SA 4.0, non-commercial use) and the TensorFlow.js browser port by georg95.

Leaf Detective: Explore Nature, One Leaf at a Time 🍃

Simran Jaiswal — Fri, 09 Oct 2026 11:25:58 +0000

🍃 Leaf Detective: Explore Nature, One Leaf at a Time

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

What I Built

I built Leaf Detective, a nature-themed project designed to encourage people to explore the world beyond their screens. The idea is to make learning about leaves and plants more engaging and interactive.

Instead of spending all your time online, Leaf Detective encourages you to step outside, observe nature, and discover the beauty of the plants around you.

This project is for students, nature lovers, and anyone who wants to reconnect with the outdoors through technology.

Demo

🌐 Try the live website:
https://er-simran-jaiswal.github.io/leaf-detective/

Code

💻 Explore the source code on GitHub:
https://github.com/Er-Simran-Jaiswal/leaf-detective

The project is open source, and you can explore the code, learn from it, and contribute improvements.

How I Built It

I built Leaf Detective as a web project and hosted it using GitHub Pages. I used GitHub to manage and publish the source code and make the website accessible online.

My goal was to combine technology with the natural world and create something that fits the spirit of the Touch Grass challenge.

AI tools and models used: [Add the exact open-source AI model, framework, or agent you used, if applicable.]

Why Does Open Innovation Matter?

Open innovation makes it possible for developers to learn from one another, share ideas, and improve projects collaboratively.

By making projects open source, developers can contribute improvements, discover new approaches, and build better solutions together. It also helps beginners like me gain practical experience, learn from the community, and turn ideas into real projects.

Leaf Detective is a small step toward learning by building and sharing.

My Agent Session

[Optional: Add your DevRelay agent session link here if you have one. Otherwise, remove this section.]

Prize Categories

[Add the applicable partner prize categories based on the official challenge rules. Remove this section if you are not entering any partner categories.]

Thanks for checking out Leaf Detective! 🌿

DEV Community: Simran Jaiswal

Trail Ears: Identify Bird Calls in Your Browser, Even With No Signal

What I Built

Demo

Code

How I Built It

Why Does Open Innovation Matter?

Leaf Detective: Explore Nature, One Leaf at a Time 🍃

🍃 Leaf Detective: Explore Nature, One Leaf at a Time

What I Built

Demo

Code

How I Built It

Why Does Open Innovation Matter?

My Agent Session

Prize Categories