Exploring IoT Approaches to Cattle Disease Detection‐Review on Advancements and Challenges

ABSTRACT Traditional cattle health monitoring methods rely heavily on manual observation and periodic veterinary inspections, which are often time‐consuming, labour‐intensive and ineffective for the early detection of diseases. Delayed diagnosis of conditions such as mastitis, bovine respiratory disease, ketosis, lameness and heat stress can lead to reduced productivity, increased economic losses and compromised animal welfare. The advent of the Internet of Things (IoT) is transforming livestock health management, offering innovative solutions for disease detection and monitoring in cattle. This review explores the latest developments in IoT‐based systems designed to promote animal welfare, enhance farm productivity and support the economic sustainability of cattle farming. IoT technologies enable real‐time data acquisition, continuous monitoring and early disease diagnosis through wearable sensors, environmental monitoring devices and automated health tracking systems. These tools can detect subtle physiological and behavioural changes associated with conditions such as mastitis, bovine respiratory disease, ketosis, acidosis, lameness and heat stress. Case studies demonstrate the effectiveness of IoT in reducing dependence on manual inspections and controlling disease spread. The review also examines key challenges, including sensor accuracy, data management, scalability and privacy concerns, alongside the need for robust data analytics frameworks. Emphasis is placed on interdisciplinary collaboration among veterinary science, data science and agricultural engineering. The integration of artificial intelligence and machine learning is discussed for enhancing predictive capabilities, while blockchain is considered for ensuring data integrity. Overall, IoT emerges as a pivotal technology in advancing a sustainable and health‐focused future for cattle disease management.