TOMATO PLANT DISEASES DETECTION SYSTEM USING IMAGE PROCESSING
Objective
This study develops a tomato plant disease detection system using image processing techniques to accurately identify and classify diseases, helping with early intervention and improved crop yield
Abstract
This project employs an Arduino Mega 2560 microcontroller to connect various environmental sensors and a color sensor for tracking temperature, humidity, air quality, and light intensity, along with fruit ripening stages. The system uses MATLAB to process images of tomato leaves and detect disease symptoms. Upon identifying a disease, MATLAB sends an acknowledgment to the Arduino, which activates a GSM module to send SMS alerts to the farmer with the disease name and recommended pesticides. The system continuously monitors environmental factors and assesses plant health, enabling quick response to disease detection and efficient crop management.
NOTE: Without the concern of our team, please don't submit to the college. This Abstract varies based on student requirements.
Block Diagram
Specifications
- - Microcontroller: Arduino Mega 2560
- - Sensors: DHT11, MQ135, LDR, color sensor, moisture sensor
- - Communication Module: GSM
- - Image Processing: MATLAB
- - Water Pump: Controlled by relay
- - Power Supply: 12V adapter
- - Display: LCD
- - Network: NodeMCU
- - Motor: Water pumping motor
Learning Outcomes
- Understanding the architecture and working of the Arduino Mega 2560 microcontroller.
- Setting up and programming environmental sensors for temperature, humidity, air quality, and light intensity monitoring.
- Learning the integration of IoT technology for real-time environmental data collection.
- Understanding the basics of image processing using MATLAB for identifying plant diseases.
- Interfacing Arduino with sensors and MATLAB for seamless data communication.
- Developing skills to send automated SMS alerts using IoT technology.
- Learning how to monitor fruit ripening and detect plant diseases through sensor and image analysis.
- Understanding how to integrate embedded systems and MATLAB for agricultural applications.
Paper Publishing
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