Development of Automated Harvest Machine for Precision Farming of Areca Nut
This article provides a comprehensive review and proposes a system design that integrates machine learning with an automated harvesting machine for areca nut classification and collection. Utilizing image processing techniques, the system employs machine learning algorithms to classify areca nuts as ripe, unripe, or rotten based on features such as color, texture, and shape. An IoT-enabled automated mechanism facilitates the selective harvesting of mature nuts, improving efficiency compared to traditional methods. This approach aims to enhance productivity in areca nut farming by automating and optimizing the harvesting process. The article discusses both existing solutions and a system currently being deployed.
Authors
- Mouna Cheggour (ORCID: https://orcid.org/0000-0002-4641-9590)
- A. Geetha Kiran (ORCID: https://orcid.org/0000-0002-6794-4327)
- B Pooja
- J. Mohana Lakshmi
- B.C. Gowda
- N Kotesha
Institutions
- Shri Dharmasthala Manjunatheswara College of Ayurveda and Hospital (IN)
Publication Details
- Published
- 2025-07-04
- DOI
- https://doi.org/10.1109/icctdc64446.2025.11158830
- Primary Topic
- Nuts composition and effects
- Type
- article
- Field-Weighted Citation Impact
- 0.00