Abstract:
Virtual replicas of infrastructure can be used to run simulations and optimize the construction,
management, and maintenance of such assets throughout their entire lifecycle. These digital
twins (defined as integrated multi-physics, multiscale, and probabilistic simulations of a complex
product) mirror the behavior and environmental responses of its corresponding twin.
Digital reconstruction techniques using optical sensor technologies and mobile sensor platforms
are providing viable, low-cost alternatives to develop digital twins of physical infrastructure.
In previous work, the digital twinning of asphalt pavement surfacings using visual
simultaneous localization and mapping and the initiation of a digital twin of a local road
network were investigated and successfully demonstrated. In this article, the further development
of the concept, incorporating road surface temperatures collected over a 1-month period,
as well as potential inferences based on these data, in the micro- and macro-twinning of a local
road, are discussed. Light detection and ranging, unmanned aerial vehicles, and traffic counting
artificial intelligence allows for quantification of the road geometry and infrastructure utilization
over large areas (macro-twinning), whereas the photogrammetric reconstruction technique
based on a neural network, a proprietary environmental condition sensor (SNOET, or
SNiffing Omgewing / Environmental Tester) and commercial temperature sensors were used
to acquire the surface texture and environmental conditions respectively (micro-twinning), as
well as surface temperatures at four locations and different surfacing materials. The combination
of advanced environmental monitoring data, physical data, and surface temperature data provide management data that can assist in the maintenance of such roads. This article
expands (with the permission of the conference organizers) on a GeoChina 2021 article through
the addition of further temperature data collected on the discussed digital twin, with substantial
additional data analysis and discussion.
