**1. Introduction**

Infrastructure monitoring is one of the most significant applications of cities [1]. This is likely due to the fact that smooth functioning of cities is a vital need by providing safe and efficient infrastructure. Eventually, complex, large, and expensive engineering assets, i.e., high-rise buildings, long-span bridges, dams, oil platforms, wind turbines, offshore structures, roadways, and rail tracks are designed to last long [2, 3]. For example, bridges are normally built to have a lifespan of 50 years

[4]. However, many of them are near to or have already exceeded their design life. For example, according to ASCE 2021 infrastructure report card, 42% of all bridges across the United States are at least 50 years old, and they are considered structurally deficient; they are in poor condition and in need of repair. Besides, these assets are damage-prone during their service life. This is due to the fact that different external loads induced by environmental effects, overloading, blast loads, wind excitations, floods, earthquakes, and other natural disasters can disturb the serviceability and integrity of these structures.

Structural and materials design is a highly iterative process for the optimal design of infrastructures. Even the simplest structures and materials are composed of multiple elementary structural components which can lead to various optimal designs [5]. Likewise, maintaining the health condition of infrastructures is also an engineering optimization problem. This is because it is not easy to find an exact solution [6]. For instance, evolutionary techniques have been applied as a part of the procedure of achieving the exact solution. Therefore, several metaheuristic algorithms such as genetic algorithm, particle swarm optimization, ant colony optimization, and imperial competitive algorithm have been developed to solve a variety of engineering optimization problems in a transdisciplinary field of engineering, so-called structural health monitoring (SHM). Bridge monitoring and optimization are significant areas of SHM and soft computing, respectively.

SHM and soft computing techniques as powerful tools can be significantly used to mitigate the aforesaid concerns by planning scheduled maintenance, control, and management of infrastructures. Based on the above explanations, this chapter aims to introduce the optimized SHM-based soft computing techniques of bridge structures through artificial intelligence and machine learning algorithms in order to illustrate the performance of advanced bridge monitoring approaches which are required to maintain the health condition of infrastructures as well as to protect human lives.

## **2. Bridge as an iconic infrastructure**

Civil engineering is an ancient profession and one of the most noble in the world. Many structures are monuments to civilization and last for centuries, becoming pilgrim and tourist attractions. Many of these huge monumental structures, being one-off in nature, have warranted large realization times. Some of them have taken centuries to build. The above structural attributes, being passed down from generation to generation, necessarily had certain design processes, motivations, and contexts for posterity to appreciate and admire in terms of form, esthetics, and sustenance [7]. Peter Rice [8], one of the most original and influential engineers of the twentieth century was certain that if the method of manufacturing was true to the project's nature, it would result in a structure capable of producing the emotional response intended by the designer. In the editorial headline "Winning the Emotional Argument," New Civil Engineer editor Mark Hansford commented in 2017: "civil engineering professionals now, more than ever, need to engagingly present the broader benefits of their infrastructure projects, highlighting the direct impacts they are having on society" [9].

Aside from the implicit recognition that successful infrastructure projects now employ a vast range of complementary disciplines—including engineering, planning, architecture, landscape design, ecology, and many others, and are no longer simply

*DOI: http://dx.doi.org/10.5772/intechopen.104905 Introduction to Monitoring of Bridge Infrastructure Using Soft Computing Techniques*

#### **Figure 1.**

*Evolution of bridge design: Influence of materials on esthetics and structural design. Roman aqueduct in Spain, 50 A.D. [5]. Ponte Vecchio bridge in Italy, 1345 [13]. Büyükçekmece bridge in Turkey, 1567 [14]. Khaju bridge in Iran, 1650 [15]. Pulteney bridge in UK, 1769 [12]. Maria Pia bridge in Portugal, 1877 [5]. London Tower bridge in UK, 1894 [14]. Chengyang bridge in China, 1912 [16]. Salginatobel bridge in Switzerland, 1930 [17]. Sydney Harbour bridge in Australia, 1932 [14]. Golden Gate bridge in USA, 1937 [5]. Coronado Girder bridge in USA, 1967 [5]. Magdeburg Water bridge in Germany, 2003 [18]. Seri Wawasan bridge in Malaysia, 2003 [12]. Helix bridge in Singapore, 2004 [14]. Millau Viaduct bridge in France, 2004 [19]. Shenyang Sanhao bridge in China, 2008 [7]. Rewa Rewa bridge in New Zealand, 2010 [20] Lower Hatea Crossing in New Zealand, 2011 [10]. Rzeszów circular footbridge in Poland, 2012 [21].*

"heavy engineering," it seems self-evident that the bigger the project, the greater the need to demonstrate the benefits to society. It is understood that value must be added—beyond the base metrics of people movement—in terms of lasting social, economic, and environmental benefits [10].

A report by Beade-Pereda [11] stated that bridges link previously separate geographic areas, defying gravity and transforming the landscape. They bind communities, acting as connectors of people, inviting interaction and integration. Bridges are a paradigmatic case of human transformation of nature, symbols of union, progress, and often innovation. Bridges across physical, cultural, and spiritual barriers, frequently becoming landmarks or even icons. They are much more than a piece of infrastructure and the design of such emotional, prominent, and long-lasting constructions should go beyond their main function as structures that link areas, and should always aspire to improve the quality of the built world. At International Association for Bridge and Structural Engineering (IABSE) "Future of Design" event in London on September 8, 2016, Professor Enzo Siviero, named "The Bridge-man" said: "I always say if a bridge was a woman I could marry it!". This hilarious example shows the connection between bridges, emotions, culture, and people [12].

Structural and material design is a highly iterative process for the optimal design of infrastructures. Even the simplest structures and materials are composed of multiple elementary structural components, which can lead to various optimal designs [5]. The evolution in bridge design offers an example of this influence between structural components, materials, and boundary conditions on the design (see **Figure 1**). As can be observed from this figure, the designers have integrated esthetics into the design. Another side of this evolution is dramatic changes in the lighting of bridges in the last decades, which have gained insight into the visual and emotional effects [22].
