About SoilSense

A comprehensive soil health monitoring system built in 30 hours, bridging the gap between traditional farming and modern technology.

System Architecture

Frontend

React 18
Next.js 15
TypeScript
Tailwind CSS
Framer Motion

Sensors & IoT

Arduino
ESP32
Raspberry Pi
Bluetooth LE
WiFi Modules

Satellite Data

Google Earth Engine
Sentinel-2
Landsat 8
MODIS
Planet API

AI & ML

TensorFlow Lite
OpenCV
scikit-learn
PyTorch
Computer Vision

Backend

Node.js
Express
PostgreSQL
Redis
WebSocket

Cloud & Deployment

Vercel
AWS
Docker
GitHub Actions
Supabase
30-Hour Development Timeline
0-2h
Project Setup & Architecture
2-8h
Core UI Components & Landing Page
8-16h
Dashboard & Sensor Simulation
16-24h
AI Analysis & Educational Features
24-30h
Testing, Polish & Deployment
Multi-User Approach

Target Users:

  • • Children learning about soil health
  • • Elderly gardeners with accessibility needs
  • • Urban balcony gardeners
  • • Small-scale farmers
  • • Industrial agricultural operations
Innovation Highlights

Key Innovations:

  • • Multi-scale monitoring (pot to satellite)
  • • AI-powered soil photo analysis
  • • Educational voice assistance
  • • Accessibility-first design
  • • Real-time IoT sensor integration
Technical Achievements
100%
Responsive Design
3
Monitoring Scales
30
Hours to Build
Future Development Roadmap

Phase 1: Mobile Enhancement (Weeks 1-2)

Convert to React Native, implement actual camera integration, add offline functionality

Phase 2: IoT Integration (Weeks 3-4)

Arduino/ESP32 sensor networks, real-time alerts, Bluetooth/WiFi connectivity

Phase 3: AI & Satellite (Weeks 5-6)

Google Earth Engine integration, ML models for crop recommendations, predictive analytics

Phase 4: Community Features (Weeks 7-8)

User accounts, data sharing, expert consultation, farmer networking