Bridge weigh-in-motion (B-WIM) refers to a specific method that uses an instrumented bridge or culvert to weigh passing vehicles in motion [1]. Such systems use strain transducers, installed at the mid-span of each longitudinal girder or each strip of a bridge slab. They work based on the static assumption principles, proposed by Moses [2]. More than 40 years of development have pushed B-WIM systems not only to use bridges as large scales but also to measure the structure's response to calculate the performance indicators, such as influence lines, lane and/or girder distribution factors, and dynamic amplification factors. In a recent study [3], data from B-WIM strain sensors installed on a multi-span highway viaduct equipped with long-term monitoring were used for the first time for finite element model updating (FEMU). The digital twin concept pulls together several existing mature technologies [4]. The first two key features of a digital twin [5] are already elaborated in [3]. This paper presents how data from the B-WIM system, which is part of the long-term monitoring, could be used to satisfy the 3rd key feature of the digital twin, the ability to monitor and report the structural behaviour and health of a civil engineering asset throughout its entire service life. For this purpose, a framework is presented of how a model updating concept using B-WIM data for the FEMU, presented in [3], could be upgraded to consider random and not only statically pre-weighted calibration vehicles. This would enable monitoring the viaduct's health throughout its service life.