🌱 Building an AI-Driven Community Agriculture Assistant

Inside the development of a climate-smart gardening AI for South Florida

This is a behind-the-scenes update for premium subscribers. You’re supporting the growth of a project that combines AI, climate resilience, and food sovereignty, thank you.

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Why This Project Matters

Urban agriculture in South Florida faces unique challenges: unpredictable weather, soil variations, and a disconnect between landowners and community growers.

At the same time, there’s a growing movement to localize food systems, reclaim unused land, and share knowledge between gardeners and small-scale farmers.

So, I’m building an AI-powered planting assistant for a Miami-based non-profit, a tool designed to help community gardens and small growers make better planting decisions, connect with each other, and adapt to our local climate conditions.

This isn’t just about automation. It’s about empowering local communities with intelligent, climate-aware tools.

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What I’ve Built So Far

The first version of the prototype is live!

I created a Streamlit-based interface that lets users:

• Upload an Excel file containing planting or harvest data,

• Automatically clean and structure the data, and

• Ask questions in natural language, like:

"Which crops had the highest yield in sandy soil during the summer?"

"What’s the average harvest time for tomatoes planted in raised beds?"

The assistant uses AI to analyze your data, summarize insights, and provide actionable answers in context.

Current Tech Stack

• Streamlit for the web interface

• Pandas for data handling

• OpenAI API for intelligent Q&A on datasets

• Data source: local Excel files collected from gardens and growers

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Data Cleaning