Agri-Nova 🌱

Agri-Nova is an innovative project designed to support farmers in making informed decisions and maximizing agricultural productivity. By providing insights into soil health, plant disease detection, market trend analysis, and sustainable farming practices, Agri-Nova addresses key challenges in the agricultural sector and empowers farmers with actionable data to improve yield and resource efficiency.

PPT LINK: https://stdntpartners-my.sharepoint.com/:p:/g/personal/mohammedsufyaan_talish_studentambassadors_com/EakiQ9EbmZBCtNthSsOO4RMBgFeUWW9B65AFg4VKt6wSTQ?e=t6Nhlc

Problem Statement

Farmers face numerous daily challenges:

• Assessing soil health and nutrient levels.
• Detecting and managing plant diseases in a timely manner.
• Analyzing and responding to market trends.
• Limited access to sustainable and eco-friendly agricultural practices.

These challenges often lead to reduced productivity, inefficient use of resources, and missed opportunities for maximizing crop yield and quality.

Solution Approach

Agri-Nova leverages cutting-edge technologies in AI, IoT, and data analytics to offer a comprehensive solution for modern agriculture:

1. Soil Health Analysis 🌍: Provides insights into soil composition, moisture levels, and nutrient status, enabling farmers to make precise adjustments to soil management practices.
2. Plant Disease Detection 🌾: Uses computer vision and machine learning to detect early signs of diseases in plants, helping farmers take preventive action before significant damage occurs.
3. Market Trend Analysis 📊: Aggregates market data to offer insights on crop demand and pricing trends, supporting better planning and decision-making for crop sales.
4. Sustainable Practice Recommendations 🌎: Offers suggestions on eco-friendly farming practices that align with environmental conservation goals.

Key Features

• Real-Time Soil Health Monitoring: Analyze soil pH, moisture, and nutrient levels with IoT sensors.
• Disease Detection with AI: Upload images of crops to detect diseases using machine learning models.
• Market Data Analytics: Access and visualize market trends to identify the best time for selling crops.
• Sustainable Practices: Provides tips and recommendations for reducing environmental impact while increasing yield.

Tech Stack

• Frontend: Js, HTML, CSS
• Backend: Flask
• Database: MySql
• Machine Learning: Python, TensorFlow, OpenCV
• Cloud Services: Azure/AWS for data processing and storage

Installation

1. Clone the repository:

   git clone https://github.com/yourusername/agri-nova.git
   cd agri-nova