Automated harvest machine for precision farming

Automated harvest machine for precision farming

Mouna C1, Pooja B S2, Kotesha N3, Punith Gowda B K4, Geetha Kiran A5, Mohana Lakshmi J6

1,2,5Department of Computer Science and Engineering, Malnad College of Engineering, Hassan

3,4,6Department of Electrical and Electronics Engineering, Malnad College of Engineering, Hassan

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Abstract— This article proposes a review and a system design that integrates machine learning and an automated machine for automatic areca nut classification and harvesting. Analyzing images through machine learning, the system classifies nuts as ripe, unripe, or rotten based on characteristics such as color, texture, and shape. The hardware system enables selective picking of mature nuts, through an IoT based automated machine. Replacing conventional practices, this approach enhances productivity in areca nut collection. This article presents an overall review of the available system and a system under deployment.

Keywords— Areca Nut Classification, Machine Learning, Image Processing, Raspberry Pi, Agricultural Automation, Ripeness Detection, Precision Agriculture