International Journal of Physics, Chemistry, Mathematics and Biology

An AI-driven framework called The Smart Zoo is presented to enhance the welfare of captive animals through continuous, non-invasive monitoring. Multimodal sensors, video analytics, and machine-learning models work together to assess health conditions, behavioural patterns, and environmental parameters in real time. This approach overcomes long-standing challenges of manual observations, irregular data collection, and species-specific behavioural complexity. Early trials indicate that AI-assisted monitoring improves early disease detection, supports evidence-based husbandry decisions, and strengthens emergency response. Key considerations such as data accuracy, algorithmic reliability, and ethical handling of telemetry data are also discussed. Overall, the Smart Zoo model demonstrates a scalable and structured pathway for transforming traditional zoo management into an intelligent, welfare-centric, and scientifically informed system that can support long-term conservation goals.