Penerapan Metode Color Based Detection Menggunakan Platform ESP32-Cam Sebagai Alat Pendeteksi Ikan Betta Varian Albino

Abstract

This research aims to overcome the problems that arise in identifying Betta fish variants, especially Albino variants, which are often difficult to distinguish by ordinary people due to difficulties in distinguishing visual differences. This problem encourages the need to develop a tool that is able to automatically distinguish Betta Albino fish variants. This research presents the concept of implementing the ESP32-Cam platform as a Betta Albino fish variant detection tool. The novelty of this research lies in the use of the ESP32-Cam platform which is an innovation as a detection tool. The urgency of this research lies in the need for a tool that can help ordinary people in identifying Betta Albino fish variants easily without requiring knowledge of Betta fish species. The method used in this research is colour-based detection using the eloquent surveillance library. The image capture process is done through an ESP32-Cam camera by utilising the concept of object detection and image processing. This research also involves the application of components such as TCS 3200, LM393, and LCD 1602 I2C to support the function of the detection tool. The results show that the Betta Albino fish variant object detection device is able to identify colour differences accurately. Through the ESP32-Cam platform, this tool successfully creates an automated solution that can distinguish Betta Albino fish variants well. In conclusion, this study confirms that the use of the ESP32-Cam platform in designing the Betta Albino fish variant detection tool can be practically applied. This tool has the potential to contribute in facilitating the accurate identification of Betta Albino fish variants to the general public.