AI, Digital Twins Eyed for Earlier Roadway Fault Detection
Roadway designer Nidhi Sonar said AI and digital twins could help transport agencies spot road deterioration sooner. She noted that 5G, IoT, edge computing and cloud platforms can keep digital models updated. Sonar suggested India start with focused digital-twin projects on key corridors and recurring maintenance issues.
Nidhi Sonar works in roadway design at HDR and holds a master’s in civil engineering from Georgia Tech. Her graduate research examined digital twins and data-driven methods for public safety and urban decision-making. In an interview with TelecomTalk, she described how AI and digital twins might help transport agencies detect road deterioration and infrastructure risks sooner.
Digital twins differ from static 3D models by merging live and historical data to reflect how road infrastructure performs over time. Sonar noted that connected sensors, 5G links, edge processing and cloud services can supply connectivity and processing. She suggested India begin with focused digital-twin projects on critical corridors and recurring maintenance issues.
If adopted, AI-enabled digital twins could affect drivers, maintenance crews, transport agencies and urban planners by helping them spot road deterioration earlier and schedule repairs more predictably. That may reduce unexpected disruptions and improve safety over time. However, fragmented systems, uneven data quality and limited coordination could shape who benefits and how quickly. Smaller agencies or regions with weaker connectivity may see slower gains, while well-monitored corridors could receive more timely attention.