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APLIKASI MODUL ESP32-CAM DALAM RANCANG BANGUN SISTEM PEMANTAUAN KEMATANGAN BUAH TOMAT BERBASIS EDGE IMPULS YOLO MODEL

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Penilaian

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This study aims to design and implement an automated system to detect the ripeness level of tomatoes using the ESP32-CAM module and the YOLO algorithm trained through the Edge Impulse platform. The system relies on color parameters extracted from tomato images to classify ripeness into three categories: unripe, semi-ripe, and ripe. Tests were conducted at various distances (10 cm, 20 cm, and 40 cm) and under different lighting conditions (morning and afternoon). The results show that the system can accurately detect ripe tomatoes in all conditions. The highest accuracy was generally obtained at a 20 cm distance, especially for unripe and semi-ripe tomatoes. As a reference, manual classification using the USDA's Tomato Color Chart (TCC) was employed. The automatic detection results show a high degree of conformity with manual classification, demonstrating that this system can be used as an alternative for real-time monitoring of tomato ripeness in modern agriculture. Keywords: ESP32-CAM, YOLO, Edge Impulse, tomato ripeness, tomato color chart, automated detection.

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Availability

Inventory Code	Barcode	Call Number	Location	Status
2507003154	T174047	T1740472025	Central Library (Reference)	Available but not for loan - Not for Loan

Detail Information

Series Title

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Call Number

T1740472025

Publisher

: Prodi Ilmu Fisika, Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Sriwijaya., 2025

Collation

x, 78 hlm.:ilus.; 29 cm

Language

Indonesia

ISBN/ISSN

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Classification

530.07

Content Type

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Media Type

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Carrier Type

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Edition

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Subject(s)

Fisika

Specific Detail Info

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Statement of Responsibility

EM

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