The invention relates to the technical field of Internet of Vehicles target detection, in particular to an Internet of Vehicles multi-scene target detection
system and method based on an RISC-V architecture, and the method comprises the steps: S1, obtaining image data, storing the image data in a DMA cache region preset on an RISC-V hardware calculation module, and setting the DMA cache region to be of a fixed size; s2, mapping the image data in the DMA cache region to an
address space of a process on an RISC-V hardware calculation module by utilizing an
mmap mechanism; s3, preprocessing the image data by using an RVV instruction; s4, after target detection
model parameters are loaded for the first time, caching the preprocessed image data into a heterogeneous
shared memory by using a
cache consistency protocol supported by an RISC-V hardware calculation module, performing model reasoning, and obtaining
perception information; s5, performing post-
processing on the model reasoning result through a self-defined post-
processing function, and obtaining display information; and the real-
time frame rate of target detection, the overall performance of the
system and the memory access efficiency are improved.