Real-time Automated Traffic Management Scheme Using Blockchain Based on Unmanned Aerial Vehicles

Abstract

The drones or Unmanned Aerial Vehicles (UAVs), will be crucial for addressing issues in airspace and developing traffic management. This paper’s goal will provide a review of recent research, which focuses on the development of the system based on four requirements: accuracy of position, system quality, power consumption, and user interface. Additionally, upgrades in computer vision algorithms will be implemented to capture specific information from UAVs that have captured video and images, facilitating communication with other research endeavors. On enhancing traffic flow prediction and analysis methods, addressing the challenges posed by increased numbers of UAVs (multiUAVs) and how to overcome roundabouts and obstacles, in conjunction with their consequences. This paper will summarize all methods used in mining data and leveraging it to identify the most suitable way to reduce accidents and enhance monitoring. We focused on the YOLO (You Only Look Once) algorithm and compared all versions. It was observed that the eighth version is considered the best, and students can benefit from it in projects related to computer vision. Then, the YOLO output can be passed to the Queuing theory for time control, specifically for side applications.