Livestock are integral to global food security, contributing meat, milk, and eggs as vital protein sources while supporting millions of livelihoods and sustaining agricultural economies. However, conventional livestock management faces persistent challenges, including disease outbreaks, inefficient health monitoring, and unsustainable resource utilization. The convergence of Artificial Intelligence (AI), Internet of Things (IoT), Computer Vision (CV), and advanced Sensor Technologies is revolutionizing livestock farming through intelligent, real-time, and non-invasive monitoring systems. Smart ear tags and biosensors continuously capture physiological and behavioral data, while AI-driven analytics enable early disease detection, stress assessment, and productivity optimization. These innovations empower farmers with predictive insights for proactive decision-making, improving animal welfare and minimizing economic losses. Despite immense potential, technological adoption remains constrained by high costs, limited connectivity in rural areas, and interoperability issues among IoT devices. Developing scalable, affordable, and integrated AI-sensor frameworks can overcome these barriers and transform traditional livestock farming into a data-driven, sustainable enterprise. Such precision livestock management not only enhances productivity and resource efficiency but also supports global efforts toward resilient, ethical, and technologically advanced food systems. In this review, we discuss the diverse applications of AI, sensor, and computer vision technologies in livestock management, emphasizing their potential to advance precision farming, sustainability, and global food system resilience.

To Cite This Article: Pandey B, Sonkusale L and Mishra AK, 2026. Smart solutions for livestock management and health monitoring. Pak Vet J, 46(2): 256-271. http://dx.doi.org/10.29261/pakvetj/2026.020