Smart Agriculture Robot for Plant Disease Detection and Spraying - Vaibhav Pansare; Dada Ghalme; Bhushan Rahinj; Prof. Khot J. S.; Dr. Divekar S.N (International Journal of Scientific Research in Science, Engineering and Technology, 2025)
The agricultural sector is rapidly adopting automation and smart technologies to improve crop yield and reduce manual labor. This paper presents the design and implementation of a Smart Agriculture Robot capable of detecting plant diseases using image processing and performing targeted pesticide spraying. The system integrates a Raspberry Pi 3B+ with a 5MP camera module for capturing plant images, which are then analyzed using machine learning techniques to identify symptoms of plant diseases. Detected results are communicated to users via email reports and can be accessed on mobile or laptop devices. The robot’s movement is controlled using an ESP8266 Node MCU and a Node MCU car control app through Wi-Fi connectivity. An L298N motor driver drives four wheels based on remote commands. The system is powered by a 12V battery regulated through an LM7805 module. This integrated setup not only reduces farmers’ exposure to harmful chemicals by automating the spraying process but also facilitates early detection of diseases, thereby improving plant health and crop productivity. The proposed solution demonstrates a low-cost, scalable, and efficient method for precision agriculture using IoT and embedded systems.
Keywords: Smart Agriculture; Plant Disease Detection; Raspberry Pi 3B+; Node MCU ESP8266; Image Processing; IoT; Precision Farming; L298 Motor Driver; Automated Spraying; Machine Learning; Agricultural Robotics; Remote Monitoring