The Design of a Smart Livestock Monitoring System
DOI:
https://doi.org/10.70356/jafotik.v3i2.83Keywords:
Smart Farming, Livestock Monitoring, IoT SystemAbstract
The livestock industry faces challenges in maintaining animal health, productivity, and welfare due to reliance on manual observation and delayed detection of health issues. This study aims to design a smart livestock monitoring system that leverages modern technologies to support farmers with timely, data-driven decision-making. The proposed system integrates sensor-based data collection, wireless communication, and a centralized platform for processing and visualization. Through this approach, key parameters such as animal health, activity patterns, and environmental conditions are monitored in real time. The results demonstrate that the system minimizes manual workload, reduces the risk of unnoticed illnesses, and enhances overall resource utilization. The main contribution of this study is the development of an affordable, scalable, and user-friendly system that empowers farmers, including those in small- and medium-scale operations, to adopt digital solutions for sustainable livestock management.
Downloads
References
S. Alhajj Ali et al., “A review on the role of living labs in advancing sustainable practices in rural areas: Insights from agriculture, forestry, and agroforestry systems,” Ital. J. Agron., vol. 20, no. 2, p. 100033, 2025, doi: https://doi.org/10.1016/j.ijagro.2025.100033.
Z. Anam, H. Islam, T. Islam, and A. B. M. M. Bari, “Green Technologies and Sustainability A Fermatean fuzzy approach to analyze the drivers of digital transformation in the agricultural production sector : A pathway to sustainability for emerging economies,” Green Technol. Sustain., vol. 3, no. 3, p. 100197, 2025, doi: https://doi.org/10.1016/j.grets.2025.100197.
M. Uzoamaka, I. Adediji, O. Ibrahim, and F. Gboyega, “e-Prime - Advances in Electrical Engineering , Electronics and Energy Synergizing hybrid renewable energy systems and sustainable agriculture for rural development in Nigeria,” e-Prime - Adv. Electr. Eng. Electron. Energy, vol. 7, no. January, p. 100492, 2024, doi: https://doi.org/10.1016/j.prime.2024.100492.
P. Lidder, A. Cattaneo, and M. Chaya, “Innovation and technology for achieving resilient and inclusive rural transformation,” Glob. Food Sec., vol. 44, no. December 2024, p. 100827, 2025, doi: https://doi.org/10.1016/j.gfs.2025.100827.
N. N. Aruwajoye and R. Coetzee, “Transitioning from linear to circular systems offers sustainable solutions for smallholder agriculture in the Global South,” Environ. Challenges, p. 101300, 2025, doi: https://doi.org/10.1016/j.envc.2025.101300.
V. Choudhary, P. Guha, G. Pau, and S. Mishra, “Environmental and Sustainability Indicators An overview of smart agriculture using internet of things ( IoT ) and web services,” Environ. Sustain. Indic., vol. 26, no. April 2024, p. 100607, 2025, doi: https://doi.org/10.1016/j.indic.2025.100607.
A. Morchid, Z. Oughannou, R. El, H. Qjidaa, M. Ouazzani, and H. M. Khalid, “Results in Engineering Integrated internet of things ( IoT ) solutions for early fire detection in smart agriculture,” Results Eng., vol. 24, no. November, p. 103392, 2024, doi: https://doi.org/10.1016/j.rineng.2024.103392.
N. N. Thilakarathne, M. Saifullah, A. Bakar, E. Abas, and H. Yassin, “Heliyon Internet of things enabled smart agriculture : Current status , latest advancements , challenges and countermeasures,” Heliyon, vol. 11, no. 3, p. e42136, 2025, doi: https://doi.org/10.1016/j.heliyon.2025.e42136.
S. Murgod, T. Kabbur, B. Matte, V. Mujumdar, and M. Meenaxi, “ScienceDirect IoT-Driven Smart Farming with Machine Learning for Sustainable Food Systems,” Procedia Comput. Sci., vol. 260, pp. 552–560, 2025, doi: https://doi.org/10.1016/j.procs.2025.03.233.
A. Chourlias and J. Violos, “Internet of Things Virtual sensors for smart farming : An IoT- and AI-enabled approach,” Internet of Things, vol. 32, no. March, p. 101611, 2025, doi: https://doi.org/10.1016/j.iot.2025.101611.
R. Afroz et al., “Environmental Technology & Innovation Assessments and application of low-cost sensors to study indoor air quality in layer facilities,” Environ. Technol. Innov., vol. 36, no. June, p. 103773, 2024, doi: https://doi.org/10.1016/j.eti.2024.103773.
J. Medina-garcía, C. Boente, J. A. G, D. Campa, J. D. De Rosa, and A. S, “Designing a low-cost wireless sensor network for particulate matter monitoring : Implementation , calibration , and field-test,” vol. 15, no. June, 2024, doi: https://doi.org/10.1016/j.apr.2024.102208.
R. Macagga et al., “Smart Agricultural Technology A new , low-cost ground-based NDVI sensor for manual and automated crop monitoring,” Smart Agric. Technol., vol. 11, no. March, p. 100892, 2025, doi: https://doi.org/10.1016/j.atech.2025.100892.
S. Malik, J. Singh, A. Umar, A. A. Ibrahim, and S. Baskoutas, “Journal of Photochemistry & Photobiology , A : Chemistry Smartphone-integrated paper sensor strips for rapid and on-site detection of heavy metal ions in environmental water samples,” J. Photochem. Photobiol. A Chem., vol. 471, no. August 2025, p. 116675, 2026, doi: https://doi.org/10.1016/j.jphotochem.2025.116675.
L. Deso, H. Adugna, M. Jayakumar, and M. Rangaraju, “Results in Engineering Nanobiomaterials-enabled sensors for heavy metal detection and remediation in wastewater systems : advances in synthesis , characterization , and environmental applications,” Results Eng., vol. 27, no. April, p. 105694, 2025, doi: https://doi.org/10.1016/j.rineng.2025.105694.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 Ananda Ade Firdaus
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
