AI-Powered Precision Farming and Smart Crop Management
Harvest Intelligence – Where AI Meets Agriculture for a Smarter Tomorrow!
Skills you will gain:
About Program:
This 3-day hands-on workshop introduces participants to cutting-edge applications of Artificial Intelligence in agriculture. From analyzing satellite imagery and IoT data to building disease detection models and intelligent crop advisory tools, learners will explore how AI is transforming modern farming. Ideal for students, researchers, agri-tech professionals, and enthusiasts, this program blends theory with project-based learning using platforms like Google Colab and Streamlit.
Aim: To empower participants with the knowledge and practical skills to leverage Artificial Intelligence for precision farming, plant health monitoring, and data-driven crop recommendations, fostering sustainable and efficient agricultural practices.
Program Objectives:
- Introduce participants to the core principles of precision farming and smart crop management
- Train participants in the application of remote sensing and NDVI data in agriculture
- Enable learners to build image classification models for crop disease detection
- Facilitate hands-on development of crop advisory systems using AI logic
- Discuss real-world implementations, challenges, and future potential of AI in agriculture
What you will learn?
Day 1: Data-Driven Agriculture – Foundations of Precision Farming
- Introduction to Precision Farming & Smart Crop Monitoring
- Understanding Data Sources: Satellite Imagery, IoT Sensors, Weather & Soil Data
- NDVI & Remote Sensing Dataset Exploration
- Hands-On: Visualizing Crop Health Data with Google Colab
- Case Studies: Use of Remote Sensing in Real Farms
Day 2: Deep Learning in the Field – Detecting Plant Diseases with AI
- Image-Based Disease Detection in Crops
- PlantVillage Dataset & Common Crop Diseases
- CNN Model for Leaf Disease Classification
- Model Training, Evaluation & Prediction
- Tailoring Models to Specific Crops
Day 3: Smart Decisions – AI-Driven Crop Recommendation Systems
- Overview of AI-Driven Decision Support in Agriculture
- Using Soil, Weather & Historical Data for Crop Recommendation
- Build Your Own: Crop Suggestion Tool using OpenAI or Custom Rules
- Model Deployment via Streamlit or Google Colab
- Use Cases: Crop Planning & Smart Irrigation Systems
Mentor Profile
Fee Plan
Get an e-Certificate of Participation!
Intended For :
- Undergraduate/Graduate students in Agriculture, AI, Computer Science, or related fields
- Professionals from AgriTech, Environment, or Data Science domains
- Researchers or startup founders interested in Smart Farming
- Basic knowledge of Python and machine learning concepts is recommended but not mandatory
Career Supporting Skills
Program Outcomes
- Understand how AI is integrated into modern agriculture systems
- Gain experience in processing satellite and sensor data for crop health monitoring
- Build and evaluate deep learning models for plant disease detection
- Design an AI-powered crop recommendation tool using real-world data
- Learn to deploy AI tools using accessible platforms like Google Colab and Streamlit
- Analyze real case studies of AI use in global agriculture