This is a submission for the Hacktoberfest Open-Source AI Challenge Week 1: Touch Grass
What I Built
VerdantEcho is an offline-first, zero-signal backcountry trail scout and bioacoustics neural classifier designed with a single goal: to make screen time the shortest part of your outdoor experience.
When hiking through deep mountain hollows, dense old-growth woods, or national parks, cellular reception completely drops. Cloud AI APIs fail with network timeouts. Worse, typical apps keep your eyes glued to glass while you walk past magnificent autumn canopies.
VerdantEcho changes this by running open-weight AI directly on-device:
- 🔊 On-Device Bioacoustics Scout: Uses the Web Audio API to render a live waterfall spectrogram and extracts spectral centroids and harmonic ratios to classify bird calls (Black-capped Chickadees, American Robins, Red-tailed Hawks, Song Sparrows) and autumn field crickets.
- 🍁 Autumn Foliage & Flora Vision: Analyzes canopy senescence, anthocyanin pigmentation ratios, and leaf morphology. Includes a dedicated hazard alert for Poison Ivy (Toxicodendron radicans) with high-contrast trail warnings.
- ❄️ Frost & Soil Almanac: Calculates first expected frost dates and tells you what to sow (hardneck garlic, winter spinach, winter rye) or harvest before the freeze based on offline date and coordinates.
- 🌲 "Touch Grass" Pocket Mode: Switches the device to an ultra-low-power AMOLED HUD. When an animal or plant is detected, synthesized speech announces the finding directly into your earphones, then instructs you to put the phone back in your pocket.
- 📍 Zero-Cloud Field Journal & GPX Exporter: Logs observations with offline GPS waypoints locally in IndexedDB and exports standard
.gpxor.geojsonfiles ready for Gaia GPS, AllTrails, or OpenStreetMap. - 🤖 Gemma 2B Naturalist Companion: Formatted for Google's open-weight Gemma 2B model, delivering concise 2-sentence ecological insights paired with a firm reminder to put the screen away.
Demo
The app runs locally in the browser or offline on mobile devices via PWA service workers.
Key Screenshots & Live Features:
- Real-time Bioacoustics Spectrogram: 2048-point FFT waterfall analyzer visualizes animal calls between 200 Hz and 12 kHz in real time.
- Sunlight HUD & Pocket Mode: A high-contrast sunlight theme for bright daylight, plus an AMOLED Pocket Mode that automatically dims the screen and reads observations aloud.
- Botanical Safety Detector: Instant warnings for trail hazards (Poison Ivy urushiol oil warnings) and autumn canopy color stages.
Code
ayushraaj-01
/
verdantecho
Zero-signal offline trail scout & bioacoustics AI companion that gets you off the screen and into nature.
🌿 VerdantEcho: Zero-Signal Trail Scout & Bioacoustics AI
"Build something with open-source AI at its core that gets people off the screen and into the world. The best builds here should make the screen the shortest part of the experience."
— Hacktoberfest Open-Source AI Challenge: Week 1 (Touch Grass)
🍃 Overview
VerdantEcho is an offline-first, backcountry trail scout and bioacoustics neural classifier engineered for one primary purpose: to minimize your screen time and immerse you in the natural world.
When hiking through deep backcountry valleys, national parks, or remote woodlands, cell towers disappear. Cloud-based AI APIs (OpenAI, Claude, cloud computer vision) fail with timeout errors. Even worse, typical mobile apps encourage you to stare at a glowing piece of glass while walking through magnificent old-growth canopies.
VerdantEcho fundamentally re-engineers outdoor exploration using open-weight AI:
- 🔊 On-Device Bioacoustics Scout: Real-time Web Audio API FFT spectrogram + neural audio pattern extraction…
GitHub Repository: https://github.com/ayushraaj-01/verdantecho
Includes complete source code:
-
index.html&styles.css: Vanilla HTML/CSS high-contrast forest design system. -
app.js: Web Audio API FFT analyzer, canvas camera pipeline, and GPX exporter. -
ai-worker.js: Web Worker for non-blocking bioacoustics inference. -
gemma_field_scout.py: Python CLI for offline Gemma 2B turn-based field guidance. -
sw.js: Service worker for 100% airplane-mode offline caching. -
render.yaml&Dockerfile: 1-click cloud deployment configurations.
How I Built It
VerdantEcho was constructed using a lightweight, resilient, and offline-first architecture:
1. Web Worker Thread Isolation
Running audio spectrogram FFT calculations and image tensor analysis on the main UI thread causes dropped frames and unresponsiveness. Following proven patterns, we offloaded spectral math to an isolated Web Worker (ai-worker.js), ensuring silky smooth 60fps performance even on low-power mobile devices.
2. High-Contrast Sunlight & Pocket HUD
Standard web apps wash out under direct outdoor sunlight. VerdantEcho provides:
- A high-contrast Sunlight HUD with dark emerald accents.
- A Touch Grass Pocket Mode with automatic screen dimming, audio chimes, and Web Speech API synthesis so you never have to look down at the display.
3. Open-Weight Gemma 2B Naturalist Engine
We built a local Python CLI (gemma_field_scout.py) that demonstrates turn-based inference using Gemma's prompt format:
bash
python gemma_field_scout.py --species "Sugar Maple" --notes "High crimson saturation on ridge line"
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