Abstract
This work presents an AI-driven modularized low-cost spot spraying system that uses threshold-based decision-making to dynamically adjust herbicide application in real-time. The system integrates OAK-D for weed detection, Jetson Orin Nano for plant classification, and Arduino Mega for spray control. Simulations demonstrate that this approach significantly reduces herbicide consumption, improves spray precision, and effectively adapts to varying environmental conditions, making it a scalable solution for precision agriculture.