AI-Enhanced Digital Infrastructure Monitoring for Smart Transportation Systems: A Review

Abstract

Smart transport is a rapidly becoming a crucial part of modern urban transport, and is being facilitated by digital infrastructure in order to make it safer, more efficient and sustainable. However, the more complicated these systems are the more demanding are the needs in more sophisticated monitoring solutions. The Artificial Intelligence (AI) is a new solution in terms of improving the monitoring of the digital infrastructure through the real-time analysis of the data, supportive maintenance, anomaly detection and adaptive traffic control. Below is a review of literature and uses of AI in smart transportation systems monitoring. It examines the input of machine learning/computer vision and AI systems to the IoT to make decisions in advance, reduce downtimes, and improve passenger safety. The traffic flows optimization, structural health analysis of transport infrastructure, predicting vehicles maintenance, and the security of the transportation network are the most important ones. The evaluation compares and contemplates the advantages of AI-infused surveillance which ought to be enhanced in terms of efficiencies of operation, cost-saving, and sustainability. Other potential issues such as problem of scalability, interoperability, ethical concerns and data dependency on high quality are also critically outlined. The topic on discussion has research gaps, and the aspect of the future has been also touched upon in the paper; all this is connected with the concept of the simulation of stronger systems, enhanced with the assistance of edge AI, federated learning and digital twins. It appears that the findings imply that AI mediated surveillance is not a new technology, but rather a type of planning that will lead to intelligent, safe and sustainable transport systems.