Harvestgo-A Versatile Weed Identifier Using AI

In today's world, everywhere needs technological development so that the work can be done simultaneously to get good results. In the future, automation will dominate all areas, especially agriculture. Most problems are caused by vegetation surrounding the plants and preventing them from growing. The aim of the project is to create an artificial intelligence-supported weed detection and removal system for coconut farms. We use image processing and sensing tools to install TENSOR-FLOW-based AI models on inexpensive hardware such as Raspberry Pi. The technology instantly collects images, detects weeds growing on coconut trees, and initiates the necessary cleaning process while preserving the coconut plants. Our approach is to improve weed control strategies, increase coconut yields, and improve agricultural sustainability through agricultural automation. The report describes the process, hardware configuration, artificial intelligence model development, and live operation, demonstrating the project's efficiency and productivity potential in agriculture.