## 1 Introduction
Enhanced construction flexibility can be achieved by the varied forms of cement-based materials available on the market, and the associated technologies in reinforced and prestressed concrete make it an adaptable solution suitable for the highly challenging types of bridges and other ancillary structures, such as bridge support structures, abutments, and piers [15,16]. Several methods have been developed to assess the structural health and conditions of in-service civil infrastructure, which include visual inspections based on expert and skilled personnel who gather and analyse data [17,18]. However, these methods can be highly time-consuming, dangerous, and expensive [19]. Monitoring using technological solutions is required to enhance safety and reduce maintenance and inspection costs. Yet, the spatial resolution of the captured data can be compromised or might depend on the sensors. The method of utilising fixed sensors is widely used and prevalent, but access to these sensors after installation can be highly challenging [18,20]. In cases where only periodic monitoring is needed, contact sensors can incur significant costs as ample time will be invested, while sensor systems require maintenance. Conventional image processing tools depend on boundary detection methods, viz., template matching and Sobel edge/morphological detector for feature extraction from images and are highly susceptible to environment-related elements like shade, light, distortion, and occlusion. SHM techniques are customised to accommodate the specific attributes and possible failure mechanisms of different structural materials, such as concrete, steel, and composites. SHM in concrete constructions emphasises identifying defects, including cracks, delaminations, and voids. Methods such as infrared thermography and ground penetrating radar are frequently utilised for this objective. Recent improvements have offered methods that integrate optimised Grey-Level Co-occurrence Matrix (GLCM) studies with other techniques to improve the detection of structural faults in concrete [21]. Steel constructions, however, are vulnerable to issues such as corrosion and fatigue-related fractures. Non-Destructive Testing (NDT) procedures, including ultrasonic testing and acoustic emission monitoring, are extensively employed to monitor these concerns. SHM must consider the complications resulting from the interaction of diverse materials in composite constructions [22]. SHM is a broad umbrella that includes processes and presents reliable data on any structure's current condition. The appropriate bridge monitoring and deterioration diagnosis require essential tools related to bridges: their functional state and structural integrity. A series of measurement sensors can be applied under SHM to detect the deterioration of structures and bridges over a given time, and particular studies of bridge monitoring have been vast and varied [23]. When talking in terms of sensors, the hardware and software elements of SHM should be considered. The sensors and related instruments constitute the hardware, and damage detection and modelling techniques for damage identification are included in the software elements of SHM [24]. Table 1 gives a list of the variety of techniques that are incorporated in SHM. Bridges are affected either by man-made or natural elements that cause deterioration with time [28]. Most bridges are expected to remain in service for long timespans; thus, any damage can propagate with time and eventually cause catastrophic failure. This makes it mandatory to have regular inspections of the bridges to determine the structural stability, potential hazards, and progression of defects over time [28]. A SHM system is used to diagnose damage, identify the spread of damage, and determine the health status of any bridge; however, either assumption or development of the bridge's pre-damage state is mandatory for damage understanding [29].