IoV Data Processing Algorithms for Automatic Real-Time Object Detection - Literature Review

With the advent of the Internet of Vehicles (loV)., there is an increasing demand for real-time and accurate object detection algorithms for intelligent transportation systems. This literature review aims to provide a comprehensive analysis of the latest research in loV data processing algorithms for automatic real-time object detection. By analyzing and comparing various state-of-the-art algorithms such as Faster R-CNN., Mask R-CNN., and YOLOv4., the strengths and limitations of each approach are identified. Additionally., the challenges associated with real-world implementation are discussed and provide recommendations for future research directions. This research study highlights the importance of efficient and accurate object detection algorithms in the context of the loV and emphasizes the need for ongoing research in this field.