🌱 AgriScope

AgriScope is a Streamlit-based sustainability dashboard that helps track, visualize, and forecast agricultural sustainability metrics — including emissions, technology adoption trends, and key performance indicators — with an interactive scenario planner for exploring future outcomes.

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Overview

AgriScope brings together sustainability data into a single, interactive dashboard designed for clarity and decision-making. It combines real-time KPI tracking, emissions visualization, and adoption trend analysis with a forward-looking scenario planner, enabling users to model different sustainability pathways and their potential impact.

Built in Python and deployed on Azure, AgriScope is designed to be lightweight, extensible, and easy to run both locally and in the cloud.

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Features

• 📊 KPI Dashboard — At-a-glance view of key sustainability metrics, updated dynamically as data changes.
• 🌍 Emissions Charts — Visual breakdowns of emissions data across time periods, sources, or categories.
• 📈 Adoption Trends — Track the uptake of sustainable practices or technologies over time.
• 🔮 Scenario Planner — Interactive tool to model hypothetical scenarios and forecast their effects on sustainability outcomes.
• ⚡ Interactive & Responsive UI — Built with Streamlit for a fast, intuitive user experience.
• ☁️ Cloud-Deployed — Hosted on Azure for reliable, scalable access.

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Tech Stack

Layer	Technology
Language	Python
Dashboard/UI	Streamlit
Data Processing	Pandas, NumPy
Visualization	Plotly / Matplotlib
Deployment	Microsoft Azure
Version Control	Git & GitHub

(Update this table to match your exact dependencies — see requirements.txt for the full list.)

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Project Structure

agriscope/
├── dashboard/       # Streamlit app pages and UI components
├── data/            # Data files (not tracked in version control)
├── logs/            # Application logs (not tracked in version control)
├── notebooks/       # Exploratory analysis and prototyping
├── reports/         # Generated reports and exports
├── scripts/         # Utility and automation scripts
├── src/             # Core application source code
├── requirements.txt # Python dependencies
└── README.md

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Setup Instructions

Prerequisites

• Python 3.9+
• pip
• (Optional) An Azure account, if deploying to the cloud

1. Clone the repository

git clone https://github.com/Joey665/agriscope.git
cd agriscope

2. Create and activate a virtual environment

python3 -m venv venv
source venv/bin/activate      # On Windows: venv\Scripts\activate

3. Install dependencies

pip install -r requirements.txt

4. Run the dashboard locally

streamlit run dashboard/app.py

(Adjust the path if your entry point file has a different name/location.)

The app should now be available at http://localhost:8501.

5. Deploying to Azure

AgriScope is deployed on Azure. For deployment, typical options include:

• Azure App Service (recommended for Streamlit apps)
• Azure Container Instances (if containerized with Docker)

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Contact

Project Maintainer: Joseph Bright 📧 Email: josephbright342@gmail.com 🔗 GitHub: https://github.com/Joey665

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