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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM41632

Automated harvest machine for precision farming

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM41632

Volume:

9 |

2 |

Feb 2025

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM41632

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

MC

Mouna C1

PBS

Pooja B S2

KN

Kotesha N3

PGBK

Punith Gowda B K4

GKA

Geetha Kiran A5

MLJ

Mohana Lakshmi J6

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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

Cite This Article

Mouna C1, Pooja B S2, Kotesha N3, Punith Gowda B K4, Geetha Kiran A5, Mohana Lakshmi J6, "Automated harvest machine for precision farming," International Journal of Scientific Research in Engineering and Management, vol. 9, no. 2, Feb 2025. https://doi.org/10.55041/IJSREM41632

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Publication Date

2/17/2025

Peer Review Type

Double-Blind Peer Review

Review Rounds: 2

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5

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The authors declare no conflict of interest related to this research work.

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