Artificial intelligence, digital twins and connected sensing technologies are creating new possibilities for managing roads and transportation networks. Instead of depending exclusively on periodic inspections and reactive repairs, transportation agencies could combine real-time and historical data to monitor roadway conditions, identify deterioration patterns and prioritise maintenance more effectively.

In an exclusive interaction with TelecomTalk, Nidhi Sonar, a roadway designer at HDR, explains how AI-powered digital twins could support infrastructure monitoring, predictive maintenance and urban decision-making. She also discusses the role of 5G, IoT, edge computing and cloud connectivity, the challenges created by fragmented data and the relevance of these technologies for India.

Sonar holds a master’s degree in Civil Engineering from the Georgia Institute of Technology, where her research focused on using digital twins and data-driven approaches to improve public safety and urban decision-making. At HDR, she works on roadway design and major transportation projects, including progressive design-build and emergency infrastructure projects.

Sonar previously explored how AI, digital twins and connectivity can shape the future of smart transportation in an expert article for TelecomTalk.

A 3D model is essentially a digital representation of what an asset looks like. A digital twin goes a step further by representing how that asset is actually behaving over time.

What makes it a true digital twin is the continuous connection between the physical and digital environments. Data from sensors, inspections, traffic systems, weather conditions, maintenance records and other sources can continuously update the digital representation. Ideally, the information also flows the other way, where insights from the twin help inform decisions in the physical world.

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