IoT-Based Precision Livestock Monitoring for Real-Time Detection of Thermal Stress and Metabolic Disorders in Dairy Cows
Keywords:
Internet of Things, stres termal, THI, precision livestock farming, gangguan metabolikAbstract
Climate change and seasonal temperature variations significantly affect the welfare, metabolic health, and productivity of dairy cows, particularly in tropical regions characterized by high temperatures and humidity. Heat stress reduces milk yield, impairs reproduction, and increases the risk of metabolic and infectious diseases. The Internet of Things (IoT) enables real-time monitoring through integrated environmental and behavioral sensors, supporting precision dairy management. This study evaluated an IoT-based multi-sensor system to detect thermal stress and early metabolic health changes in dairy cows on a tropical dairy farm in Indonesia. The system combined a temperature–humidity sensor to calculate the Temperature–Humidity Index (THI) and a smart collar with a three-axis accelerometer to monitor activity and rumination. Data were collected from 50 lactating cows over three months and analyzed using descriptive and correlation analysis. Maximum THI reached 86.4, indicating severe heat stress, and showed a strong negative correlation with milk production (r = −0.88). Behavioral changes, including reduced rumination and activity, were detected up to 36 hours before clinical symptoms. These results confirm that IoT-based monitoring enables early stress detection, improving welfare, productivity, and dairy farm resilience.
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