This paper presents an overview of recent research in structural health monitoring (SHM) of bridge engineering infrastructure in Ireland aimed at promoting net zero carbon civil engineering infrastructure. Scour-induced failure of masonry arch bridges is a common cause of bridge collapse, especially during extreme flood events. Over recent years there have been significant numbers of documented scour induced failures of this bridge stock across Europe and the USA. An overview of the development of a new fibre optic scour sensor (FOSS) for measuring scour events from pressurised flow and neural network to predict scour at bridges based on the structural response of scale structural experiments, experiencing flume derived scour, to loading. This research is particularly focused on the FlexiArchTM , a Queen’s University Belfast patented flexible unreinforced pre-cast concrete arch bridge system, and ArchIMEDES, incorporates a computer vision deformation monitoring tool which is used to capture the structural response (deflections and hinge formation) of the bridge and provides the neural network with raw data on which it makes remote, real-time informed predictions of prevalent scour. In the past two decades, the application of instrumented vehicles for the SHM of bridge structures has attracted interest due to the low emissions and high efficiency of the sensors. Recent advances in intelligent vehicles is accelerating the exploration and application of drive-by monitoring for bridge infrastructure assessment, and in terms of data, for informed decision making by asset owners. However, the removal of undesired vehicle components in the sensor signals from vehicle measurements, under live loading, remains one of the key challenges in drive-by monitoring. To realise the practical implementation of the concept of drive-by monitoring towards net zero emission infrastructure, recent research proposes novel vehicle transfer functions. Additionally, traditional structural health monitoring has tended to examine each bridge structure individually and this limits the ability to apply data from one bridge structure to inform on the condition of another. To overcome this limitation, Population-Based Structural Health Monitoring (PBSHM) aims to group similar structures together to form a ‘population’ so that data from one or more structures can be used to make an inference about the condition of the structure of interest.