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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM41632
Volume:
9 |
2 |
Feb 2025
Pages:
Publication Frequency:
Monthly (12 issues per year)
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.
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
Publication Date
2/17/2025
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
Funding Information
No funding information available for this research.
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