Teknologi Automatic Spraying System for Plants based on Leaf Image Detection by Using Raspberry Pi Camera Model V2

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Abstract

The utilization of automated systems to increase crop maintenance efficiency, especially in fertilizer and pesticide application, has been prompted by advancements in precision agriculture technology.  Using a camera module as an automated spraying controller to detect leaf images is one creative method. The integration of the Raspberry Pi v2 Camera Module with digital image processing methods in automated spraying systems is the subject of a comprehensive review of earlier research presented in this article.  Actuator control in the system, analysis of leaf detection techniques, and a review of recent journal literature are some of the techniques employed.  The study's findings show that real-time implementation of this technique which includes color thresholding and texture analysis for leaf detection can be accomplished with good accuracy. The Raspberry Pi v2 Camera Module offers advantages in color image and easy integration with microcontroller. In conclusion, an automated spraying system based on leaf image detection shows great potential in reducing chemical waste and improving spraying precision, although challenges remain related to lighting conditions and crop types. Further research is needed to improve system performance under various field conditions.