Smart Conveyor Real-Time Sort Rotten Tomatoes With Deep Learning Method Integrated IoT Control

The Indonesian Ministry of Agriculture reported a significant increase in demand for fruits and vegetables in 2024. The share of expenditure on fruits increased by 18.35%, while for vegetables increased by 7.98% in the fourth quarter of 2024. This high demand drives the need for efficiency in the post-harvest process, especially at the sorting stage. Manual processes that rely on labor are time-consuming and risk producing errors in product quality grouping. As a solution, this study developed a smart conveyor system integrated with IoT technology and deep learning to classify tomatoes by grade. This system includes layers of physical devices, connectivity, computing, data processing, and collaboration to optimize performance. The conveyor is driven by a DC motor with a detection accuracy level of 94%. Rotten tomatoes are classified as grade C and directed straight, while red tomatoes (grade A) and green tomatoes (grade B) are directed to certain containers using servos. This innovation leads to manual processes, reduces dependence on labor, and increases efficiency. With this technology, farmers can meet market needs more effectively and ensure accurate and consistent tomato grouping, supporting the transformation of the horticulture sector in Indonesia.

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Publication Details

Journal
JURNAL ILMIAH RESEARCH AND DEVELOPMENT STUDENT
Published
2025-01-22
DOI
https://doi.org/10.59024/jis.v3i1.1135
Primary Topic
Belt Conveyor Systems Engineering
Type
article
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article

Smart Conveyor Real-Time Sort Rotten Tomatoes With Deep Learning Method Integrated IoT Control

Owen Pratama Endramawan, Mochammad Rifki Ulil Albaab, Muhammad Ramadhan, Junia Vitasari et al.
JURNAL ILMIAH RESEARCH AND DEVELOPMENT STUDENT
Belt Conveyor Systems Engineering
article

Smart Conveyor Real-Time Sort Rotten Tomatoes With Deep Learning Method Integrated IoT Control

Owen Pratama Endramawan, Mochammad Rifki Ulil Albaab, Muhammad Ramadhan, Junia Vitasari, Rangga Raditya Nugroho
article en

Abstract

The Indonesian Ministry of Agriculture reported a significant increase in demand for fruits and vegetables in 2024. The share of expenditure on fruits increased by 18.35%, while for vegetables increased by 7.98% in the fourth quarter of 2024. This high demand drives the need for efficiency in the post-harvest process, especially at the sorting stage. Manual processes that rely on labor are time-consuming and risk producing errors in product quality grouping. As a solution, this study developed a smart conveyor system integrated with IoT technology and deep learning to classify tomatoes by grade. This system includes layers of physical devices, connectivity, computing, data processing, and collaboration to optimize performance. The conveyor is driven by a DC motor with a detection accuracy level of 94%. Rotten tomatoes are classified as grade C and directed straight, while red tomatoes (grade A) and green tomatoes (grade B) are directed to certain containers using servos. This innovation leads to manual processes, reduces dependence on labor, and increases efficiency. With this technology, farmers can meet market needs more effectively and ensure accurate and consistent tomato grouping, supporting the transformation of the horticulture sector in Indonesia.

JURNAL ILMIAH RESEARCH AND DEVELOPMENT STUDENTVol. 3(1)
Universitas Jember (ID), Politeknik Negeri Jember
Openalex Percentile: Top 93%
Belt Conveyor Systems Engineering
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