Identification of Anomalies in Traffic Flows Using Artificial Intelligence in Real Time

Transportation accessibility is fundamental to the development of all areas of human activity and has a direct impact on the quality of life of the population, including access to education, healthcare, and economic development. However, the existing urban transportation systems have been unable to adequately cope with the rapid increase in the number of vehicles, leading to traffic congestion, accidents, delays, and harmful emissions. The implementation of Intelligent Transportation Systems (ITS) helps to address these issues, although not completely. The use of advanced technologies such as artificial intelligence, machine learning, and deep learning opens up new possibilities for improving the efficiency and quality of ITS. This paper presents a real-time anomaly detection system for transportation flows using street surveillance cameras. The high accuracy of location identification and immediate notification of detected anomalies enable road services to promptly address emerging issues.