Agriculture plays a critical role in feeding the growing global population. However, one of the major challenges faced by farmers today is the early and accurate detection of plant diseases. Traditional methods of disease monitoring involve manual inspection, which is time-consuming, labor-intensive, and often unreliable due to human error or lack of expertise. If plant diseases go undetected or are treated too late, they can lead to significant crop loss and reduced agricultural productivity.

In addition to disease detection, the indiscriminate use of pesticides poses a serious threat to the environment and human health. Excessive pesticide application leads to soil and water contamination, pest resistance, and unnecessary expenses. There is a growing need for a smarter and more sustainable solution that targets pesticide usage only when necessary.

This project proposes a solution that leverages Artificial Intelligence (AI) and IoT technology to monitor plant health and perform automatic pesticide spraying only when required. The system is built using a Raspberry Pi, which processes images of plant leaves using a machine learning model to detect signs of disease. It also collects environmental data using sensors such as temperature, humidity, soil moisture, and light intensity to provide additional context for plant health assessment.

If a disease is detected, the Raspberry Pi activates a spraying mechanism using a pump or valve controlled through GPIO pins and a relay. The system also integrates with IoT platforms like Blynk or ThingSpeak, allowing farmers to monitor plant conditions and spraying activity in real-time through a smartphone or web dashboard.

By combining AI, image processing, sensors, and automation, this project offers a cost-effective, scalable, and eco-friendly solution for smart agriculture. It enhances crop health monitoring accuracy, reduces pesticide wastage, and empowers farmers with real-time data to make informed decisions.

Component Used:

. Camera Module 

. Raspberry Pi 

. Environmental Sensors

• DHT11/DHT22
• Soil Moisture Sensor
• Light Intensity Sensor Pesticide Spraying Mechanism

. Pesticide Spraying Mechanism

• Water Pump/Submersible Pump
• Spray Nozzles
• DC Motors/Stepper Motors
• Relay Module

 . Power Supply Unit