DEV Community

Cover image for TerraPulse AI
Shagun Mohan
Shagun Mohan

Posted on

TerraPulse AI

#devchallenge #hf26challenge

Hacktoberfest Open-Source AI Challenge Week 1: Touch Grass Submission ðŸŒŋ

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

What I Built

TerraPulse AI is an offline-first, open-source AI nature companion & foliage trail scout built specifically to get people off their screens and into the natural world.

When you're out hiking, birdwatching, or leaf-peeping deep in a national park or state forest, cell phone signal often drops to zero bars. Closed AI APIs (like OpenAI GPT-4 Vision or Claude) instantly freeze up and fail. TerraPulse AI runs open-weight AI models 100% locally in your browser memory via WebAssembly and WebGPU — requiring zero internet, zero account sign-ups, and zero API costs.

Key Features Designed to Minimize Screen Time

  • 📷 Local AI Flora & Wildlife Scout: Drag-and-drop or snap photos of plants, mushrooms, and wildlife. Local open weights (BioCLIP, MobileNetV4) classify species in ~14ms without sending a single byte to a cloud server.
  • 🎙ïļ Bird Call Spectrogram AI: Upload or record trail bird sounds for local audio classification via Whisper-Tiny-Audio and Web Audio API synthesis.
  • 🍁 Foliage & Trail Route Generator: Generates scenic hiking, running, and birding routes based on peak autumn leaf colors, elevation, and target outdoor duration.
  • 🙈 Screen Time Minimizer ("Pocket Mode"): Once your route is generated, TerraPulse turns into a hands-free audio guide using Web Speech Synthesis. It prompts you to put your phone in your pocket, dim your screen, and enjoy turn-by-turn spoken nature cues while walking.
  • ðŸŠī Garden & Local Frost Date Planner: Interactive USDA Hardiness Zone calculator with weekly planting tasks and an agronomic companion planting matrix.
  • 📖 Expedition Journal & Badges: Tracks screen-free outdoor minutes, species logged, and unlocks achievements (Sprout Observer, Zero-Signal Scout, Touch Grass Champion).

Demo

shagunmohan.github.io

Code

GitHub logo ShagunMohan / TerraPulse

TerraPulse


View on GitHub


How I Built It

TerraPulse AI is designed around Open-Weight Machine Learning Models running completely client-side in the browser via WebAssembly (WASM) and WebGPU execution contexts.

Open-Source AI Stack

  • Open-Weight Vision Models:
    • BioCLIP-v2.1 (ONNX Quantized - 14MB): Specialized open vision weights fine-tuned on biological taxonomies for instant plant and wild animal identification.
    • MobileNetV4-Outdoor-Edge (TFLite/ONNX - 4MB): Ultra low-power model option for conserving phone battery while on long hikes.
    • SmolVLM-256M-Instruct: Compact vision-language model for natural language trail advice.
  • Open Audio Model:
    • Whisper-Tiny-Audio (Wasm - 38MB): Spectrogram feature extraction for identifying bird calls from ambient microphone input.
  • Web Audio API & Speech Synthesis:
    • Synthesizes songbird frequencies locally for audio calibration and converts trail directions to natural audio cues.

Why Does Open Innovation Matter?

Open innovation is not just an technical preference for TerraPulse AI — it is the core reason the app works.

Evaluation Factor TerraPulse Open AI (Local Browser) Closed Cloud AI APIs (GPT-4V / Claude)
Trail Readiness (No Cell Signal) ✓ 100% Fully Functional ✗ Fails Completely (Network Timeout)
Data & Location Privacy ✓ 100% On-Device Sovereignty ✗ GPS & Photos Sent to Corporate Servers
Inference Cost ✓ $0.00 Forever ✗ $0.01 – $0.03 per image query
Inference Latency ✓ ~14ms (Direct WASM/GPU) ✗ 600ms – 2500ms (HTTP Roundtrip)
Screen Time Impact ✓ Hands-Free Pocket Audio Cues ✗ Constant Phone Screen Engagement

Key Advantages of the Open-Based Approach:

  1. Zero-Signal Reliability: When hiking in a remote ravine or dense forest canopy, cell towers disappear. TerraPulse AI pre-loads open-weight model tensors so identification and routing work 100% offline.
  2. Data Sovereignty: Foragers and nature lovers often spot endangered species or private garden microclimates. Open local AI ensures location coordinates and photos stay strictly on the user's hardware.
  3. Model Swapping & Edge Fine-Tuning: Open weights allow users to swap specialized models (e.g. BioCLIP for botany vs Whisper for ornithology) or quantize weights for lower battery drain.

Prize Categories

  • Main Theme: Touch Grass — Built with open-weight models to get people off their screens and out into nature.
  • Open-Source AI Track: Powered entirely by open-weight models (BioCLIP, SmolVLM, MobileNet, Whisper) running locally on device.

Top comments (0)