A new method to road traffic monitoring using artificial systems

Unmanned aerial vehicles (UAVs) are used in this research to demonstrate a method to traffic monitoring based on auto-mated UAV situation management. Analysis of current techniques of on-board automated detection of abnormal traffic conditions and emergency using artificial vision systems (AVS) is part of the investigation, which also involves preliminary categorization of these events, including the allocation of crises and disasters. A variety of UAV controls are discussed in light of the current scenario. Based on Neyman-Pearson criteria and Bayes, the traffic scenario recognition approach presented in the study is used to identify traffic conditions. In addition, the study examines the current methods for detecting moving and stationary vehicles as well, Image segmentation and machine learning technologies, such as Deep Learning, are used to recognize cars in this paper. Traffic scenarios may be described using solutions to vehicle tracking and velocity detection difficulties.