The invention provides a collapsed
rockfall accurate identification and monitoring method and device based on AI and
machine vision, and relates to the technical field of
geological disaster monitoring, and the method comprises the steps: collecting the multi-
modal visual data and environmental parameters of a collapse hidden danger region through a cooperative
collection system; performing recognition, contour extraction and
spatial parameter calculation on the multi-
modal visual data through the recognition and positioning model to obtain a contour sequence, a volume sequence, a spatial coordinate sequence and a spatial attitude sequence of the collapsed
rockfall; on the basis of the space coordinate sequence, the space attitude sequence and the multi-
modal visual data, predicting the movement track and the speed sequence of the collapsed
rockfall through a mixed
time sequence AI model; inputting the environment parameters, the contour sequence, the volume sequence, the motion trail and the speed sequence into a
kinetic energy calculation model, and calculating to obtain the
impact energy of the collapsed rockfall; according to the contour sequence, the volume sequence, the motion trail, the speed sequence and the
impact energy of the collapsed rockfall, the collapsed rockfall
risk level is obtained through calculation.