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-Intelligent Plant Disease Detection and Care Advisory System-
Need for the project
Need for the project
Plant diseases significantly affect crop yield and quality. Early detection and accurate diagnosis are critical in mitigating damage, especially for small-scale farmers and home gardeners who may lack expert knowledge. Traditional diagnosis often relies on expert consultations or physical symptoms, which may be delayed and ineffective for new diseases. This system provides an immediate, AI-driven approach to identify diseases and offer actionable care steps, promoting sustainable agriculture and reducing losses.
Objectives of the project
Help users easily detect plant diseases or pests by analysing leaf images through a simple web and mobile interface.
Provide care advice according to the identified plant type, disease, and collected weather data.
Let users keep track of their plants’ health over time.
Foster community-driven knowledge sharing
Scope of the project
The primary users of the system will be farmers and gardeners, and the system will enable the administrator to manage the database.
General Users (Farmers/Gardeners):
Upload leaf images through the web or mobile app to detect diseases and pests.
Receive disease/pest diagnosis and care advice.
View the history of diagnoses and treatments.
Participate in community discussions.
System Admin:
Manage the disease and pest database.
Monitor community content.
Update system parameters, such as CNN model configurations or environmental data integrations.
The system's scope is based on the plants and diseases as follows: (Based on the Plantvillage Dataset
Apple
Apple Scab
Black rot
Cedar Apple Rust
Blue Berry
Cherry
Powdery mildew
Corn (maize)
Cercospora leaf spot
Common Rust
Northern Leaf Blight
Grape
Black rot
Leaf Blight
Orange
Citrus Greening
Peach
Bacterial Spot
Pepper Bell
Bacterial Spot
Potato
Early Blight
Late Blight
Raspberry
Soybean
Squash
Powdery Millow
Strawberry
Leaf Scorch
Tomato
Bacterial Spot
Early Blight
Late Blight
Leaf Mold
Septoria Leaf Spot
Two-spotted Spider Mite
Target Spot
Yellow Leaf Curls
Tomato Mosaic Virus
The PlantVillage Dataset will be used to train the CNN model for plant disease detection
The PlantVillage dataset is a publicly available collection of over 54,000 high-quality images of healthy and diseased crop leaves, designed to support research in plant disease detection using machine learning and computer vision. It covers 14 plant species, including tomato, apple, grape, corn, and potato, and includes images of leaves affected by 26+ different diseases such as early blight, late blight, leaf mold, and bacterial spot, as well as healthy leaves. Captured under controlled conditions, the dataset is widely used for training and evaluating models that classify plant diseases.
Deliverables
Web and Mobile app
Web and Mobile app
A mobile application built with react native and a web application built with React.js for plant disease detection and care advisory.
Community Forum
Community Forum
A community forum for user engagement and knowledge sharing
CNN Model
CNN Model
A trained CNN model capable of classifying a wide variety of plant diseases and pests. (an AI disease detection system)
Advisory System
Advisory System
A plant care advisory module based on plant type, disease, and location
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