# An Integral Fuzzy Model to Evaluate Slab and Beam Bridges with a Preventive Approach
## 2 State of the Art
### Research Gaps  
By analyzing the state of the art presented in Sections 2.1 and 2.2, we can highlight several limitations and gaps in the traditional methods and works that innovate through fuzzy logic.  
The assessment in traditional methods focuses on corrective measures, prioritizing the detection of deterioration in its advanced stages [3; 16; 17]. While this is not necessarily a shortcoming, it represents a disadvantage in terms of maintenance costs, since the greater the damage to the bridge, the greater the budget required for its repair. Furthermore, these assessments do not reveal the internal processes used to determine the importance of the factors considered when assigning ratings. As a result, although the decision-maker knows the bridge's final rating, they are unaware of the factors that influenced its assessment, making it difficult to provide appropriate care. In addition, the assignment of ratings is based on binary logic, i.e., the damage either exists completely or does not exist at all. This approach limits the inspector to assigning a single rating to the element's condition, even if that rating does not accurately reflect its actual state. This limitation has been one of the primary reasons why fuzzy logic has been incorporated into the assessment work [11; 12; 19] as it enables the simultaneous determination of conditions that may belong to different levels of deterioration.  
Although the use of fuzzy logic has managed to overcome existing restrictions in traditional methods, caused by the use of binary logic, some deficiencies that both methods share persist. One of the main deficiencies is the lack of a comprehensive assessment of bridges. Both traditional and fuzzy logic methods focus on specific bridge elements, without considering all the primary and secondary elements that influence the overall performance of the structure. This partial assessment reveals a significant deficiency in establishing relationships between the various components, making it challenging to determine the relevance of each identified defect to the overall condition of the bridge. As a result, maintenance actions are usually carried out exclusively on the main components [5; 16; 17], which can lead to more advanced deterioration in the secondary elements and ultimately affect the long-term safety of the bridge. Furthermore, there is a lack of works and manuals that present recommendations on periodic, preventive, and corrective maintenance of bridges. As a result, even when the condition of the bridge is known, it is difficult for professionals to determine the most appropriate type of maintenance to restore its functionality.  
To address these challenges, our work focuses on the development of a fuzzy logic-based model to determine the condition of bridges in the road network and the urgency of their intervention. This proposal considers both the primary and secondary components that influence the bridge's performance, evaluating the importance of each individual element within the relationships that exist between them. In this way, the model avoids underestimating the impact that the condition of each component can have on the overall performance of the structure. Our proposal for the assessment process is carried out with a preventative approach, which is beneficial for maintaining the long-term safety and functionality of bridges. By considering a preventive approach, ours helps reduce the costs and disruptions associated with major repairs as it enables the timely detection and addressing of deterioration before it worsens in severity. In addition, we aim to help professionals to more accurately assess the condition of bridges and make informed decisions about necessary maintenance actions and optimal timing, an aspect that has been poorly addressed in the existing literature.