The application relates to the technical field of
animal monitoring, and provides a wild animal
epidemic disease monitoring and prevention and control method and
system based on
artificial intelligence, wherein the
system collects data such as video streams,
body surface temperatures, air
pathogen concentrations, sound characteristics and VOCs spectrum graphs of wild animals in real time through multiple
modal sensor nodes, carries out real-time
inference through a wildness AI model in an
edge computing unit, evaluates the health status and
epidemic disease risks of the animals, combines a multi-source risk
knowledge graph and a graph neural network, dynamically adjusts an epidemic situation
occurrence probability threshold value of the
system, generates accurate prevention and control instructions such as
risk area division, isolation early warning and material allocation schemes, after the
epidemic disease risks are confirmed, the system sends early warning information to a prevention and control center through various communication links, and continuously optimizes the prevention and control strategy through
reinforcement learning. The method realizes the intelligentization and precision of wild animal epidemic
disease prevention and control, can respond to complex
ecological environment changes in real time, and significantly improves the prevention and control efficiency and accuracy.