Development of a Cognitive Digital Twin for Pavement Infrastructure Health Monitoring

A road network is the key foundation of any nation’s critical infrastructure. Pavements represent one longest-living structures, having a post-construction life 20–40 years. Currently, most attempts at maintaining and repairing these structures are performed in reactive traditional fashion. Recent advances technology research have proposed implementation costly measures time-intensive techniques. This presents novel automated approach to develop cognitive twin pavement structure by implementing advanced modelling machine learning techniques from unmanned aerial vehicle (e.g., drone) acquired data. The established how initially developed subsequently capable detecting current damage on structure. method also compared evaluating condition as well more employing specialized diagnosis vehicle. study demonstrated an efficiency enhancement