2. INTRODUCTION
• This system is a guide to paddy farmers for disease
identification and giving instructions and solutions to protect
the paddy, based on AI.
3. COMPANY INFO
• Botanic expert- Chamath nisansala
External lecture (University of Peradeniya)
0771865905
• AI Researcher – Roshan Rolanka
(Colombo and Moratuwa university)
0714453500
4. CONTEXT DIAGRAM
MMS(Photo/image)
User(Farmer) Mobile device
Signal Tour Image processing System
Botanic expert Mobile device
Data uploading(knowledge)
Agriculture officer
Register botanic expert data uploading
5. ARCHITECTURE DIAGRAM (AI PART)
Image Processing
Module
Case
Identification
Module
Solution Process Module
MMS(Image)
Solution SMS
Mobile Device
Reject image SMS
System
6. LITERATURE REVIEW
• Image processing system.
• fertilized recommendation systems.
• Artificial neural network .
• Kohonen neural network training method.
• Pattern and color base image processing.
7. PROJECT INFRASTRUCTURE
• Project Management tool – MS project
• Unit testing framework – Math lab
• Source control – GitHub
• Build server – Jenkins
• Error Logging – Log4m
8. DATA FLOW DIAGRAM
Leaf image
Database
Preprocessing
Leaf Edge detection
Histogram Equalization
Classifier
Send the Result
Feature Extraction
Thresholding
Feature vector
Database
Input
Training
10. ER DIAGRAM
Farmer Agriculture officer
Phone number
user name
Password
NIC number
JOB Post
Diseases
Disease name
Disease Date
Disease Features
Image
Image ID
Image colour
Message
Text
Pestiside
Quantity
Product name
Refure
Take Look
Give Send
1
M
M
1
1
1
M
M
1
M
1
