Skripsi

SISTEM DETEKSI API DAN OBJEK BERBASIS METODE HSV DAN YOLOV3 DENGAN PENYIMPANAN DATA DI CLOUD

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Fire is a serious threat that can cause significant material and human losses. Early detection of fire and identification of surrounding objects is crucial to minimize risk. In this final project, a real-time fire and object detection system was developed using HSV-based image processing to identify the typical colors of fire, and the YOLOv3 algorithm to detect various objects such as humans and animals. The system employs the ESP32-CAM module as the monitoring device and uses Cloudinary as the cloud-based storage for automatically saving detection results. Tests were conducted under various lighting conditions, both day and night, and showed that the system achieved an 86.67% success rate in detecting fire and an average accuracy of 73% in object recognition.

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Availability

Detail Information

Series Title

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Call Number

T1902262025

Publisher

Indralaya : Prodi Teknik Komputer dan Jaringan, Fakultas Ilmu Komputer Universitas Sriwijaya., 2024

Collation

59 hlm.; ilus.; 29 cm

Language

Indonesia

ISBN/ISSN

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Classification

006.370 7

Content Type

Text

Media Type

unmediated

Carrier Type

-

Edition

-

Subject(s)

Prodi Teknik Komputer dan Jaringan
ESP32-CAM

Specific Detail Info

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Statement of Responsibility

KA

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