Sensor-Assisted Livestock Monitoring for Enhancing Animal Welfare and Environmental Sustainability
DOI::
https://doi.org/10.70102/AEJ.2025.17.3.19کلمات کلیدی:
Non-invasive sensors, Ammonia management, Machine learning, LightGBM, Behavioral monitoring, Physiological stress indicators, Resource-use efficiency.چکیده
On-going and objective monitoring of the behaviour of livestock, their physiology and the living conditions are vital in improving the welfare of animals and reducing the environmental impacts of contemporary production systems. This paper has examined how environmental and animal-based sensors that pool lentic system (in dairy cattle housing) could be applied to monitor thermal comfort, livestock behaviours, and resource-use efficiency. The values of environmental factors such as temperature, humidity, air movement, ammonia concentration, and light intensity were measured continuously with major animal behaviours such as feeding period, rest period, locomotors exercise period, respiration rate and skin surface temperature. Interviewed sensor data on thermal discomfort and signs of impaired welfare and labelling of critical thresholds was done using integrated sensor data. The results showed that environmental load has a strong association with observable behaviours of animals and physiological stress indicators. Early warning of heat stress and poor ventilation allowed corrective management practises so as to enhance the comfort of the animals, mitigate the waste of water, and prevent poor feed ratios. Also, the system of monitoring helped to reduce the ammonia level and achieve more effective energy consumption during cooling and ventilation. In general, the analysis shows sensor-based livestock surveillance, without high-level automation and robotization, is an effective, scalable, sustainability-friendly approach to enhancing welfare outcomes and ensuring livestock management to become environmentally responsible in light of increasingly diverse climatic conditions.