Application of Digital Twin Technology for Smart Pavement Monitoring and Maintenance

Author

A.Poornima, B.Sirisha, K.Rohith, K.Mohith, A.Akhila

Abstract

 The pavement infrastructure is an integral part of transport infrastructure, and maintenance plays a critical role in ensuring that the infrastructure operates properly. The traditional methods of pavement monitoring are primarily based on periodic inspections, which can not accurately detect pavement deterioration in its early stages or provide up-to-the-minute information on pavement condition. A digital twin can be a promising solution with a dynamic digital representation of a physical pavement that can be continuously updated by data retrieved from monitoring systems. This paper proposes a framework for the application of Digital Twin technology in smart pavement monitoring that combines Building Information Modelling (BIM), Internet of Things (IoT) sensors and real-time data analysis. BIM software like Revit can be used to build a three-dimensional model of the pavement, and sensors can be installed to measure key pavement parameters like temperature, strain, moisture and deformation. The data collected can then be imported into the digital twin environment to represent the condition of the physical pavement. This can be used to facilitate continuous condition monitoring, early detection of pavement deterioration, predictive maintenance and enhanced decision making. The proposed framework has the potential to revolutionise the way pavements are managed, moving away from the traditional approach and using data to become a smart, efficient monitoring system.

Keywords

Digital Twin, Smart Pavement, BIM, IoT, Pavement Monitoring, Sensors, Predictive Maintenance.

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References

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