The Development of Chicken Coop Automatic Remote Visual Monitoring System
(1) Department of Computer Science, IPB University, Indonesia
(2) Department of Computer Science, IPB University, Indonesia
(3) Department of Computer Science, IPB University, Indonesia
(4) Department of Computer Science, IPB University, Indonesia
Abstract
Purpose: A remote visual monitoring system will be very helpful for chicken farmers to monitor their cages, that usually located away from their houses. This system needs adequate bandwidth in transmitting the video over the internet, which is usually very limited in urban areas. The main goal of this research is to develop an automatic chicken coop remote monitoring system and define the optimum video resolution to be transmitted.
Methods: We used an 8 MP Raspberry Pi camera V2 to record the video and send the results to Google Drive by utilizing the GDrive API. Furthermore, a live streaming video from the chicken coop is accessible through a simple HTTP web page utilizing ngrok as a tunneling software so that the live streaming video can be publicly accessed from anywhere using a web browser. Three video resolutions of 640x480, 800x600, 1024x768 with 15 and 30 framerates were used in our experiments. Each scenario has a duration of five minutes and takes 12 times.
Result: The experiment results showed, resolutions that provide a stable video recording and streaming are 640x480 and 800x600. The resulting system succeeded in performing live streaming along with the process of data acquisition.
Value: The Google Drive infrastructure is used because of its popularity and convenience by people with limited digital literacy such as smallholder chicken farmers. Furthermore, the video produced by this system can be used in supporting research of chicken behavior pattern identification to build a system notification of an emergency situation in the cage.
Keywords
Full Text:
PDFReferences
Directorate General of Livestock and Animal Health Statistics 2018, Livestock and Animal Health Statistics 2018. Ministry of Agricuture, 2018.
Directorate General of Livestock and Animal Health Ministry of Agriculture of the Republic of Indonesia, Performance Report of the Directorate General of Livestock and Animal Health 2018. Ministry of Agriculture, 2018.
J. A. Azeez and C. Akbay, “An Economic Analysis of Broiler Chicken Production for Different Production Rotations in the Northern Region of Iraq,” TEAD, vol. 7, no. 2, pp. 76–89, 2021.
M. W. Yu and F. E. Robinson, “The Application of Short-Term Feed Restriction to Broiler Chicken Production: A Review,” J. Appl. Poult. Res., vol. 1, no. 1, pp. 147–153, 1992.
A. Ahyari, Pengendalian Produksi. Yogyakarta: BPFE, 1979.
R. Fadilah, Super Lengkap Beternak Ayam Broiler. Jakarta: AgroMedia, 2013.
S. Pakage, B. Hartono, Z. Fanani, B. A. Nugroho, and D. A. Iyai, “Analisis Struktur Biaya dan Pendapatan Usaha Peternakan Ayam Pedaging dengan Menggunakan Closed House System dan Open House System,” Indones. J. Anim. Sci., vol. 20, no. 3, p. 193, 2018.
H. van Meirhaeghe, A. Schwarz, J. Dewulf, B. Venbeselaere, and M. de Gussem, Biosecurity in Animal Production and Veterinary Medichine. Den Haag: Acco Leuven, 2019.
A. Mazick, S. Ethelberg, E. M. Nielsen, K. Molbak, and M. Lisby, “An Outbreak of Campylobacter Jejuni Associated with Consumption of Chicken, Copenhagen, 2005,” Eurosurveillance, vol. 11, no. 5, pp. 7–8, 2006.
S. Friel and L. Ford, “Systems, Food Security and Human Health,” Food Sec., vol. 7, no. 2, pp. 437–451, 2015.
R. Somya, A. Ardaneswari, D. A. Saputro, and H. D. Purnomo, “Perancangan Sistem Pemantauan Pertumbuhan Ayam Pada Peternakan Ayam Broiler Dengan Pola Kemitraan,” in Proc. Semin. Nas. Teknol. Inf. dan Multimed. 2015, pp. 4.3-1–4.3-5.
T. van Hertem, T. Norton, D. Berckmans, and E. Vranken, “Predicting Broiler Gait Scores from Activity Monitoring and Flock Data,” Biosyst Eng, vol. 173, pp. 93–102, 2018.
J. Khairunnisa, S. Wahjuni, I. R. H. Soesanto, and W. Wulandari, “Detecting Poultry Movement for Poultry Behavioral Analysis using The Multi-Object Tracking (MOT) Algorithm,” in 2021 8th Int. Conf. Comput. Commun. Eng. (ICCCE), 2021, pp. 265–268.
Z. H. C. Soh, M. H. Ismail, F. H. Otthaman, M. K. Safie, M. A. A. Zukri, and S. A. C. Abdullah, “Development of Automatic Chicken Feeder using Arduino Uno,” in 2017 Int. Conf. Electr. Electron. Syst. Eng. (ICEESE), 2017, pp. 120–124.
R. Agarwala, A. Leube, and S. Wahl, “Utilizing Minicomputer Technology for Low-Cost Photorefraction: A Feasibility Study,” Biomed. Opt. Express, vol. 11, no. 11, p. 6108, 2020.
L. C. Bishnoi, D. Singh, and S. Mishra, “Simulation of Video Transmission Over Wireless IP Network in Fedora Environment,” IP Multimed. Commun. A Spec. Issue from IJCA, vol. 10, pp. 9–14, 2011.
N. A. Samudera, “Perancangan Sistem Keamanan Ruangan Menggunakan Raspberry Pi (bagian: Aplikasi),” eProceedings Eng., vol. 2, no. 2, pp. 37–43, 2015.
A. U. Bokade and V. R. Ratnaparkhe, “Video Surveillance Robot Control using Smartphone and Raspberry Pi,” in Proceedings of 2016 Int. Conf. Commun. Signal Process. (ICCSP), 2016, pp. 2094–2097.
M. T. Trenchanchez, A. P. Pujol, T. P. Palleja, P. M. Partinez, E. C. Clotet, and J. P. Palacin, “An Inexpensive Wireless Smart Camera System for IoT Applications Based On An ARM Cortex-M7 Microcontroller,” J. Ubiquitous Syst. Pervasive Netw., vol. 11, no. 2, pp. 1–8, 2019.
N. Boyko and Kryvenchuk, Application of Сloud Services for Processing of Information Flows, EasyChair. EasyChair, 2019.
R. van Rousslet, Pro Microsoft Teams Development: A Hands-on Guide to Building Custom Solutions for the Teams Platform, 1st ed. APress, 2021.
S. Sundararajana, U. Meyer-Baese, and G. Botella, “Custom Instruction for NIOS II Processor FFT Implementation for Image Processing,” in Sens. Anal. Technol. Biomed. Cogn. Appl. 2016, 2016, pp. 31–42.
K. Srijakkot, I. Kanjanasurat, N. Wiriyakrieng, and C. Benjangkaprasert, “The Comparison of Faster R-CNN and Atrous Faster R-CNN in Different Distance and Light Condition,” J. Phys. Conf. Ser., vol. 1475, no. 1, pp. 012–015, 2020.
A. Rego, A. Canovas, J. M. Jimenez, and J. Lloret, “An Intelligent System for Video Surveillance in IoT Environments,” IEEE Access, vol. 6, pp. 31580–31598, 2018.
K. Janard and W. Marurngsith, “Accelerating Real-time Face Detection on a Raspberry Pi Telepresence Robot,” in Proc. 5th Int. Conf. Innov. Comput. Technol. (INTECH 2015), 2015, pp. 136–141.
S. Nurtini, M. A. U. Muzayyanah, F. T. Haryadi, and A. Hakim, “Performance of Broiler Farmer in Partnerships System at Surakarta, Indonesia,” J. Adv. Agric. Technol., vol. 4, no. 2, pp. 196–199, 2017.
W. Liu, “SSD: Single Shot MultiBox Detector,” in Computer Vision – ECCV 2016, 2016, pp. 21–37.
Refbacks
- There are currently no refbacks.
Scientific Journal of Informatics (SJI)
p-ISSN 2407-7658 | e-ISSN 2460-0040
Published By Department of Computer Science Universitas Negeri Semarang
Website: https://journal.unnes.ac.id/nju/index.php/sji
Email: [email protected]
This work is licensed under a Creative Commons Attribution 4.0 International License.