Teknologi Computer Vision untuk melakukan Deteksi dan Penentuan Kualitas Bibit Ayam Day Old Chicks

Abstrak

This research is motivated by the importance of chicken animal protein for child growth, development, immunity, intelligence, and the prevention of stunting. This research aims to design and implement an object detection system using a series of 4 nodes, namely Raspberry Pi, ESP32-CAM, Arduino, and ESP32, to identify chickens based on their physical characteristics. This research utilizes computer vision and artificial intelligence methodology, particularly the Convolutional Neural Network approach, to detect characteristics of DOC chickens, such as feathers, eyes, and legs. The implementation results show that the object detection system built using these four nodes can detect objects according to the existing labels. This system can identify DOC chickens with characteristics such as clean feathers, bright eyes, and bright and undamaged legs. Testing was conducted under various movement conditions of the detection objects, and the results show that the system can work well in recognizing the target objects. In the trial section, the objects used were chickens that fit the DOC characteristic category. The trial results show that the built object detection system can detect DOC chickens with suitable physical characteristics. This can assist farmers in selecting and cultivating quality chickens. Five trial tests were conducted, which showed varying detection performance.