Enhancing Dairy Farming: An Analysis of IoT, Sensors, and GPS-based Technologies for Disease Detection and Health Monitoring

Advancements in smart farming technologies have enabled significant improvements in dairy health management, with a particular focus on the early detection and management of diseases such as mastitis, a leading cause of reduced productivity and economic losses in dairy farming. This literature review explores the application of Internet of Things (IoT) devices, sensors, and GPS technologies in modern dairy systems. Wearable sensors monitor physiological parameters such as body temperature, milk conductivity, and rumination patterns to enable the early detection of mastitis, reducing the reliance on manual diagnosis and minimizing treatment delays. Additionally, environmental and behavioral data collected through GPS tracking provide insights into grazing patterns, activity levels, and deviations in movement, which are often early indicators of health issues. IoT frameworks integrate these datasets into centralized platforms, enabling real-time health alerts and predictive diagnostics. Despite their potential, challenges such as sensor accuracy, data integration, and scalability persist. This review highlights the transformative role of these technologies in improving herd productivity, mitigating economic losses from diseases like mastitis, and paving the way for sustainable, precision dairy farming practices.