Smart Field was inspired by the need to support small farmers who often lack access to advanced agricultural tools and real-time environmental data.
We saw the potential of AI and open satellite datasets to revolutionize farming by making precision agriculture accessible, sustainable, and practical for everyone.
We were also motivated by the increasing challenges of climate change, which threaten crop yields and resource availability. Smart Field empowers farmers to adapt and thrive in changing environmental conditions.
Smart Field is an AI-powered precision agriculture platform that uses open satellite imagery and environmental data from NASA, NOAA, and ESA.
👨🌾 Farmers can:
- 🌍 Register and add their fields by entering coordinates
- 🧠 Receive AI-driven recommendations and talk with AI for irrigation, fertilization, and pest control
- 🛰️ View satellite-based maps of soil health and vegetation
- 📊 Access dashboard for real-time decision-making
By promoting sustainable farming practices, Smart Field reduces environmental impact and supports climate resilience.
We combined cutting-edge web technologies, open data APIs, and AI models to bring Smart Field to life:
| Layer | Technology / Tools |
|---|---|
| 🌐 Frontend | React.js, Vite, Tailwind CSS |
| ⚙️ Backend | Node.js, Express, Python |
| 🧭 Mapping | Leaflet.js, OpenStreetMap |
| ☁️ Data Sources | NASA EarthData, NOAA Climate Data, ESA Copernicus - AWS Open Data |
| 🤖 AI Engine | Python ML models for environmental and crop insights |
Our architecture connects real-time open data streams with AI analysis to deliver actionable insights directly to farmers through an intuitive, visual interface.
Smart Field reduces inequalities by giving small farmers free access to AI and satellite data tools normally available only to large farms. By democratizing technology and focusing on climate resilience, it helps vulnerable communities adapt to climate change, improve crop yields, and strengthen economic stability.
- Integrating multiple open data APIs (NASA, NOAA, ESA) into one seamless platform
- Ensuring AI-generated recommendations were accurate and meaningful for diverse regions
- Designing a user-friendly frontend that simplifies complex environmental data
- Balancing technical complexity with ease of use for non-technical users
-- REMINDER THAT I DELETED ORIGINAL GIBR2 FILE BECAUSE OF FILE SIZE, but there is extracted json and csv
Throughout building Smart Field, we learned to:
- Handle large-scale open datasets efficiently
- Create intuitive UIs for data visualization and AI interaction
- Design systems that promote social impact and sustainability
- Combine AI, climate data, and user experience into a single cohesive platform
Documentation can be found here: https://docs.google.com/document/d/1kc-hT8DfLuSM2BV6jmFQAbUzxXptyhbuI9VwouP1wVs/edit?usp=sharing
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- Node.js (v18+)
- npm or yarn
- Clone the repository
- npm install
- .\start_frontend.bat
- .\start_frontend.bat