The invention provides a pension service supervision method and
system based on an image recognition AI model
algorithm. The method comprises the following steps: aiming at
respiratory arrest,
pressure sores and limb stiffness risks in a bedridden old-age care scene, firstly, establishing a physiological
abnormality library containing parameters such as a
respiratory rate threshold value and a body pressure critical value; a physical sign monitoring device is deployed to collect body pressure hot area distribution data of the bedridden person in real time,
breathing interval abnormity,
heartbeat attenuation and body pressure exceeding areas are analyzed through an AI model, and a retention
risk index is generated. And when the
monitoring data exceeds an abnormal
library threshold value, triggering multi-
modal early warning information, fusing
risk area positioning, abnormal duration and
temperature gradient change, outputting a multi-
modal early warning report combining images and texts, and guiding the
nursing personnel to perform targeted intervention. According to the technical scheme provided by the invention, real-time monitoring and multi-mode risk early warning of health hidden dangers in
bed are realized, the occurrence rate of complications such as
respiratory arrest and
pressure sores is reduced, and the precision and response efficiency of
nursing for the aged are improved.