The invention provides an AI
video monitoring platform based on an RISC-V framework. The AI
video monitoring platform comprises eight levels of frameworks including an equipment
perception layer, an
edge computing layer, a
data access layer, a
data processing layer, a data storage layer, an
algorithm engine layer, a platform
application layer and an industry
application layer. The invention belongs to the technical field of monitoring platforms, particularly relates to an AI
video monitoring platform of an RISC-V architecture, and aims to at least solve the problems that traditional security depends on manual screen
staring and inspection, abnormal
event recognition lags behind and the missing report rate is high, and the existing
system is high in
authorization cost, insufficient in edge scene energy efficiency ratio and poor in adaptability. The risks that the
data transmission delay is high, real-time early warning cannot be supported and privacy leakage exists in original video
cloud storage due to a front end-cloud framework are avoided; the method avoids the phenomena that different brand devices and platform protocols are not uniform, the compatibility is poor, the deployment and maintenance cost is high, and the expansion capability is weak, and overcomes the defects that a
general algorithm is insufficient in precision, lacks an industry exclusive
algorithm, and cannot cover the multi-scene safety protection requirement.