## 2 Bridge Structural Health Monitoring (SHM) System
### Defining and Identifying the Damage  
Among the traditional methods for identifying the location and extent of damage in the health monitoring system of bridges are visual inspections by expert observers. Although this method has advantages, such as a local and visual visit, human understanding of the damage in place, etc., it also has several disadvantages. Among the disadvantages of visual inspections, we can point out the lack of access or the difficulty of the inspector's access to all points of the bridge. Furthermore, if the internal elements of the bridges are damaged, visual inspection cannot be used to monitor them. In the last few decades, researchers have made a lot of progress on improving the SHM system in the areas of monitoring, control, assessment, and making decisions. One of their most important contributions has been the development of artificial intelligence (AI) systems for this purpose [48; 49]. Bridge damage monitoring and analysis have been greatly aided by technological developments and interdisciplinary efforts over the last several decades. On the other hand, new technologies like the Internet of Things (IoT) have helped SHM technology to grow significantly.  
SHM may be divided into two broad types: diagnostic and prognostic. Diagnostic methods identify flaws, pinpoint their sites, and measure their severity. The ultrasonic method, radiography, penetrant liquid tests, magnetic particles, and eddy currents are all methods that are often used to find defects as diagnostic methods [50]. However, prognostication uses diagnostic data to predict how long a structure will remain functional. This technique allows for online testing of the structure's behavior, allowing for remedial and preventative measures to be implemented in the event of any more defects that are detectable by the sensor in question. Damage is defined as any change to a system that detracts from its ability to perform its intended purpose, either now or in the future. Damage detection is an important part of SHM because figuring out if there is damage, where it is, and how bad it is, can have a big effect on the decisions made about monitoring and managing structural health. A meaningful assessment of damage requires comparison to the condition of the system before the harm occurred. A system is said to be in its \"initial state\" when it has not been modified or damaged in any way relative to its original condition [51]. Many times, a bridge's damage is identified utilizing a hierarchical system. In order to properly identify problems at a higher level in a hierarchical system, it is generally required to have some understanding of the lower levels. Each subsequent level's success may be affected by the prior levels' results in comparison to the one being completed [52; 53; 54]. Damage has been categorized in various novel ways by researchers [52; 53]. The classification system divides damage into five classes as follows:  
**- Level I (Damage detection)**: This level is identified when a damage event occurs.
**- Level II (Damage location)**: This level is detected when damage occurs, and then the location and orientation of the damage are determined.
**- Level III (Damage typification)**: This level is detected when damage occurs, the location and orientation of the damage, and then damage severity is determined, and the kind of damage is estimated.
**- Level IV (Damage extent)**: This level considers the possibilities of limiting or postponing the extent of damage once previous levels have been completed.
**- Level V (Damage prediction)**: After completing the previous four levels, this level assesses the bridge's remaining usable life or its viability status, depending on the situation.