GreenField

dashboard page
config page
statistics page
hardware!

Inspiration

Traditional agriculture is stuck in the past, wasting millions of liters of water relying on rigid schedules. We were inspired to build a system that treats a farm not just as a factory, but as a living ecosystem. We created a precision agriculture tool that replaces guessing with planning, combining data to work with nature, rather than against it.

What it does

GreenField is a full stack IoT platform that combines real-time weather data and live monitoring of soil moisture levels and light to calculate the exact volume of water needed for specific crops.

Precise Hydration: Uses a custom agronomic formula to calculate the exact liters of water needed for 10 different crop types, based on live moisture levels, light deficits, and local weather.
Weather-Aware Watering: Integrates real-time forecasts to automatically suppress watering and mute alerts if heavy rain is expected in the next 6 hours.
Fungus Risk Detection: If a crop is vulnerable and conditions are correct, the system flags a potential fungal risk, warning farmers to check the crops.
Automated Notifications: When critical thresholds are breached, the backend instantly fires off SMTP email alerts and message alerts to the farmer.

How we built it

We built GreenField as an end-to-end IoT platform connecting hardware, cloud, and frontend dashboards:

Hardware: Arduino Uno R4 WiFi equipped with soil moisture and light sensors. The device reads values every few seconds and sends them as JSON to our backend.
Backend: FastAPI server processes incoming readings, calculates water recommendations using a custom agronomic formula, and stores data in SupaBase (PostgreSQL).
Weather Integration: OpenWeather API checks upcoming rain to suppress watering alerts.
Notifications: Email and Telegram alerts automatically notify farmers when thresholds are crossed.
Frontend: Interactive dashboard displays a colour-coded grid of zones. Thresholds dynamically adjust based on crop type.

Challenges we ran into

Hardware Networking: Connecting the Arduino to our backend running in WSL required port forwarding and careful network management.
Live Testing: Coordinating live hardware testing while developing backend and frontend simultaneously.

Accomplishments that we're proud of

Real-time Monitoring: Successfully connected the Arduino sensor node to the backend and visualized live moisture and light readings on the dashboard.
Custom Agronomic Logic: Implemented a formula to calculate the exact water volume required per crop type.
Automated Alerts: Integrated email and Telegram notifications for real-time critical updates.
Dynamic Dashboard: Built a colour-coded grid that adjusts thresholds based on crop type.

What we learned

Building GreenField required coordinating hardware, backend, and frontend development simultaneously, especially managing live IoT devices over WiFI. Connecting external devices like the Arduino highlighted the importance of careful network configuration and reliable communication. We learned that having working sensors is only part of the challenge; transforming raw data into meaningful insights demands data pipelines, real-time processing, and integration with weather and crop-specific logic.

What's next for GreenField

AI-Powered Reports: Use LLM APIs to produce weekly or monthly crop reports summarising soil moisture trends, water usage, and potential risks, advising farmers for their future.
User Integration: Allow farmers to register their own fields, sensors, and crop types, specifying field layout for personalised monitoring and recommendations.
Expanded Sensor Network: Add more nodes per field and additional sensors (temperature, humidity) for finer-grained monitoring.
Automatic Watering: Integrate IoT-controlled irrigation systems to automatically water crops when predicted to be needed.