Pemanfaatan Aplikasi Deteksi Birahi Sapi Perah dan Monitoring Suhu Kandang Berbasis IoT Pada UD. Dewi Sri Desa Ranuklindungan Kecamatan Grati, Kabupaten Pasuruan
DOI:
https://doi.org/10.70609/icom.v4i4.5526Keywords:
Optimalisasi produktivitas sapi perah, Deteksi birahi sapi; Pemantauan suhu dan kelembaban, Internet of ThingAbstract
The main challenges in optimising dairy farm productivity are lambing and managing barn temperature and humidity. Timely detection of lambing is key to successful reproduction. IoT-based app detects oestrus and monitors barn temperature. The system calculates the cow's fertile period and alerts the farmer for timely insemination, increasing the chances of reproductive success. IoT-connected sensors monitor barn temperature and humidity, maintaining a stable environment for the cows and increasing productivity.
References
Berckmans, D. (2017). Precision livestock farming technologies for welfare management in intensive livestock systems. Rev. Sci. Tech., 36(1), 189-196. https://doi.org/10.20506/rst.36.1.2622
Cardoso, C. S., von Keyserlingk, M. A. G., Hötzel, M. J., & Robbins, J. A. (2019). Invited review: Trends in dairy cattle welfare: What does the future hold? Journal of Dairy Science, 102(3), 2725-2741. https://doi.org/10.3168/jds.2018-15719
Costa, A., Silva, S., & Machado, R. (2020). IoT-based livestock monitoring using RFID and WSN. Computers and Electronics in Agriculture, 171, 105309. https://doi.org/10.1016/j.compag.2020.105309
Delgado, J. A., Short, N. M., Roberts, D. P., & Vandenberg, B. (2019). Big data analysis in agriculture: Improving livestock monitoring and management. Agricultural Systems, 176, 102635. https://doi.org/10.1016/j.agsy.2019.102635
Makin, C., & Wulf, M. (2021). Use of accelerometers in cattle health and reproductive management: A review. Livestock Science, 250, 104582. https://doi.org/10.1016/j.livsci.2021.104582
Poppe, M., Veerkamp, R. F., van Pelt, M. L., & Mulder, H. A. (2021). Artificial intelligence for prediction of animal breeding and genetics. Animal Genetics, 52(6), 693-705. https://doi.org/10.1111/age.13084
Sullivan, J. L., Mickley, R., & Tait, R. G. (2020). The application of machine learning in livestock management. Livestock Science, 232, 103917. https://doi.org/10.1016/j.livsci.2020.103917
Thompson, J. M., & Schulte, B. A. (2020). Wearable technology for real-time monitoring of dairy cow health. Biosystems Engineering, 198, 156-165. https://doi.org/10.1016/j.biosystemseng.2020.08.008
Vázquez-Diosdado, J. A., Bishop, C. M., & Burrell, P. C. (2019). Application of machine learning to cattle behaviour analysis using data from tri-axial accelerometers. Computers and Electronics in Agriculture, 162, 868-880. https://doi.org/10.1016/j.compag.2019.05.046
Nugraha, P., Maskur, C. A., & Ervandi, M. (2024). Faktor–Faktor Yang Memengaruhi Produksi Susu Sapi Perah. JSTT (Jurnal Sains Ternak Tropis), 2(1), 1-11.
https://dx.doi.org/10.31314/jstt.2.1.1-11.2024
Setyorini, D. A., Rochmi, S. E., Suprayogi, T. W., & Lamid, M. (2020). Kualitas dan kuantitas produksi susu sapi di Kemitraan PT. Greenfields Indonesia ditinjau dari ketinggian tempat. Jurnal Sain Peternakan Indonesia, 15(4), 426-433.
https://doi.org/10.31186/jspi.id.15.4.426-433
Saputra, J. S., & Siswanto, S. (2020). Prototype Sistem Monitoring Suhu Dan Kelembaban Pada Kandang Ayam Broiler Berbasis Internet of Things. PROSISKO: Jurnal Pengembangan Riset dan Observasi Sistem Komputer, 7(1).s
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