AI-Powered Plant Disease Detection System

Project details

Client: Agritech Research Client
Project: AI Plant Disease Detection System
Type: AI Model
Company: Webnedrix

Status: Completed

AI-Powered Plant Disease Detection System

Agriculture faces one of its biggest challenges in the form of plant diseases that can significantly reduce crop yields and threaten food security. Early and accurate detection is critical for farmers and agricultural enterprises to take timely action. Our client wanted a robust and intelligent solution that could automate plant disease detection using AI.

The Research Problem

This struggle with early detection of plant diseases, often leads to:

Reduced crop yields.

Increased farming costs due to late interventions.

Heavy reliance on manual inspection, which is error-prone and time-consuming.

Our Solution

We developed a Plant Disease Detector powered by Deep Learning that leverages pre-trained Convolutional Neural Networks (CNNs) for image classification.

How It Works:

Image Input: Farmers capture an image of the plant leaf using their smartphone or camera.

Processing: The system preprocesses the image (resizing, normalization, noise reduction).

Deep Learning Model: A fine-tuned pre-trained CNN model analyzes the leaf patterns, texture, and color variations.

Output: The system classifies the condition (e.g., Healthy, Early Blight, Late Blight, Leaf Spot, etc.) and provides recommendations.

Key Features of the Solution:

High Accuracy Detection: Achieved 90%+ accuracy across multiple plant disease categories.

Mobile & Web Support: Farmers can upload images via an app or web interface.

Actionable Insights: Along with detection, the system provides tailored advice for treatment and prevention.

Scalability: Model can be extended to cover multiple plant species and diseases.

Results

High Accuracy: Achieved over 95% accuracy in detecting major plant diseases.

Time Efficiency: Reduced disease identification time from days to seconds.

Scalability: Farmers and agricultural enterprises can now diagnose issues instantly, without waiting for lab tests or experts.

Impact: Improved decision-making, higher crop yields, and lower risk of large-scale losses.

Technology Stack

Machine Learning: CNN (fine-tuned pre-trained model)

Framework: TensorFlow

Language: Python

Deployment: Streamlit

By integrating AI into agriculture, this solution demonstrates how technology can empower farmers, boost food security, and transform traditional farming practices into smarter, more resilient systems.

Looking to harness AI for your industry? At Webnedrix, we specialize in building intelligent, scalable solutions that solve real-world problems. Get in touch with us today to explore how we can design the right innovation for your business.