ASWIN RATHEESH D K (STM21CS021)
FATHIMA FIZA C P (STM21CS029)
K MUHSIN (STM21CS037)
RENA HARIS V P (STM21CS048)

Coconut farming often requires significant labor to determine the right time for harvesting and to pick the coconuts. This paper presents a new AI-based system designed to make this process easier. The system uses computer vision to analyze images of coconuts,
assessing their ripeness based on color and shape. A Convolutional Neural Network (CNN) classifies coconuts into different stages of maturity to ensure that only the right coconuts are harvested.
The system includes a machine with adjustable arms that can climb trees and pick coconuts at various heights. These arms are manually controlled to guarantee that only mature coconuts are selected. The machine is designed to navigate the tree carefully to
avoid damaging it or the coconuts.
By combining AI with advanced machinery, this system aims to reduce labor costs, improve harvesting efficiency, and lessen the need for human intervention. It offers a more efficient and sustainable solution for coconut farming, enhancing overall productivity.