Multi-Modal Visual Features Perception Technology for Internet of Vehicles (IoV)

In the realm of the Internet of Vehicles (IoV), this study addresses a fundamental question that causes the emerging trends within the IoV landscape, Previous research in IoV has laid the groundwork but is limited by conventional single-modal methods. This study advances our understanding by incorporating innovative Multi-Modal Visual Features Perception Technology by inputting various images from LiDAR cameras, Radar and processing using ConvolutionalNeural Networks (CNN), alongside single-modal approaches. Through this research, we uncover hidden facets of IoV, promising transformative insights. The implementation of Multi-Modal Visual Features Perception Technology using deep learning, along with single-modal methods, holds the potential to revolutionize vehicular connectivity and shape a more connected and secure future.