DESIGN AND BUILD MONITORING SYSTEM NUMBER OF CHICKEN IN CAGE ON LIVESTOCK BASED IMAGE PROCESSING TO AUTOMATION GIVING FEED
Keywords:
image processing, automation, arduino uno, ultrasonic sensor, haar cascade classiferAbstract
Currently in Indonesia there are many large or small scale chicken breeders. However, sometimes there are still breeders who feed their animals inefficiently, for example, the amount of feed given is not measured and there is no checking of the number of chickens in the cage. With the development of Image Processing, it can help chicken breeders to be able to monitor the number of chickens. Therefore, in this final project, designed an automatic chicken feeding system that uses a proximity sensor to find out the remaining feed in the container and also uses a camera to monitor the number of chickens in the cage. The prototype to be designed is 50x50x50 cm in size, the system being designed consists of a camera, Arduino Uno controller, servo, measurement sensor using ultrasonic and weight sensor. In this prototype has the haar cascade classifer method, where this method is for reading moving objects and the working principle of feeding chickens will be scheduled at a predetermined time, then the amount of feed given to chickens is based on the results of the number of chickens in the cage. The existence of a prototype monitoring system for the number of chickens in the cage on image processing based farms for automation of chicken feeders, the results of the automatic chicken feeding design get a scheduled feeding time, can monitor the number of chickens in the cage and feed according to the number of chickens who are in the cage.
References
[2] A. K. Nasution, A. Trisanto, and E. Nasrullah, “Rancang Bangun Alat Pemberi Pakan dan Pengatur Suhu Otomatis untuk Ayam Pedaging Berbasis Programmable Logic Controller pada Kandang Tertutup,†Rekayasa dan Teknol. Elektro Ranc., vol. 9, no. 2, pp. 86–95, 2015.
[3] Fikriya, Z. A., Irawan, M. I. and Soetrisno., S. (2017) ‘Implementasi Extreme Learning Machine untuk Pengenalan Objek Citra Digital’, Jurnal Sains dan Seni ITS, 6(1). doi: 10.12962/j23373520.v6i1.21754.
[4] Rahman, A. et al. (2015) ‘Rancang Bangun Alat Scoring Keahlian Dalam Tendangan Pinalti Berbasis Image Processing’, pp. 318–323.
[5] Surbakti, bagi K. A. B. (2017) ‘Manajemen Pemeliharaan Ayam Broiler Fase Strarter di CV.Berkah Putra Chicken Desa Tonjong Kecamatan Tajur Halang Kabupaten Bogor Jawa Barat’, pp. 1–52.
[6] Syarif, M. and Wijanarto (2015) ‘Deteksi Kedipan Mata Dengan Haar Cascade Classifier Dan Contour Untuk Password Login’, Techno.com, 14(4), pp. 242–249.