Our research pioneers an AI-driven digital twin framework to revolutionize veterinary emergency care by enabling real-time, low-latency coordination between ambulances, veterinary experts, and robotic surgical systems. Addressing critical challenges such as network failures, sensor inaccuracies, and unpredictable case dynamics, we integrate edge computing, AI/ML, and tactile internet protocols to optimize decision-making in life-threatening situations. This system allows veterinarians to remotely monitor, guide, and perform robotic-assisted surgeries while dynamically managing anesthesia and patient stabilization. By leveraging synthetic and real-time veterinary datasets, our approach enhances predictive treatment strategies, ensuring precision, reliability, and rapid response in mobile healthcare settings. Ultimately, our interdisciplinary research transforms emergency veterinary interventions, pushing the boundaries of AI, digital twins, and real-time analytics to save animal lives in critical scenarios.
