Project Kisan – AI Farmer Assistance System

Project Kisan is an AI-driven agricultural assistance prototype designed to support farmers with data-based decision-making. The system provides crop recommendations, fertilizer guidance, basic disease insights, input analysis, and rule-based advisory using machine learning and structured logic.
This repository contains the development notebook and the initial research workflow for building the system.

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1. Overview

The goal of Project Kisan is to demonstrate how AI can simplify agricultural decision-making for farmers by providing precise, data-driven suggestions.
The project explores early-stage prototyping, including:

• Data analysis and preprocessing
• Agricultural feature interpretation
• Rule-based and ML-based recommendation design
• System structure for farmer-centric advisory
• Notebook-based experimentation and documentation

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2. Features

• Crop Recommendation Logic
  Suggests suitable crops based on available environmental or soil features.

• Fertilizer Guidance
  Basic NPK-oriented suggestions using interpreted values.

• Advisory Flow
  Interprets farmer inputs and converts them into meaningful insights.

• Structured Implementation
  Modular notebook with clear sections for preprocessing, feature handling, and logic design.

• Early Research Notebook
  The entire development workflow is archived as a PDF.

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3. Repository Structure

Project-Kisan-AI-Farmer-Assistant/ │ ├── README.md # Project documentation ├── notebook/ │ └── Project-Kisan-Notebook.ipnb # Exported Jupyter Notebook (analysis + prototype) └── assets

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4. Development Notebook

A complete export of the research and initial prototyping is included here:

notebook/Project-Kisan-Notebook.pdf

This document contains:

• Exploratory data analysis
• Feature interpretation
• Logic design
• Observations
• Implementation workflow
• Future improvements

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5. Technologies Used

• Python
• Pandas
• NumPy
• Machine Learning fundamentals
• Decision logic design
• Jupyter Notebook

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6. Future Roadmap