# AIoT Monitoring Technology for Optimal Fill Dam Installation and Operation
## 2 Literature Review  
Approximately 616 dam facilities are present in Korea, of which 45% are more than 30 years old. Among them, 62% are expected to deteriorate in 10 years [4]. Deteriorated agricultural fill dams are vulnerable to collapse. Moreover, the safety of agricultural fill dams in excellent condition can rapidly deteriorate due to heavy rainfall exceeding the design frequency because of climate change. Although safety management of fill dam facilities is increasingly being considered, it continues to be dependent on conventional approaches based on simple measurements or visual inspection. Damage continues to occur annually in countries where technologies for the safety management of dams have not been established. Dam safety management is essential for the following reasons. (a) Dam failures or safety issues can lead to potential loss of life. Therefore, ensuring the safe operation and proper management of dams is crucial to minimize such risks and guarantee human safety. (b) Dam failures can result in significant damage to the surrounding areas, including homes, farmlands, and infrastructure. Maintaining the structural integrity of dams through safe operations contributes to the protection of nearby properties. (c) Dams primarily serve the purposes of storing water and controlling water resources. Safe dam operations aid in efficient water resource management and help in preparing for natural disasters, such as droughs or floods. (d) Some dams contribute to energy generation through hydropower. Dam safety is essential to ensure continuous and reliable energy supply to meet the power demand of a nation or region. (e) Dam operations can affect the surrounding environment. Safeguarding dams through proper safety management contributes to the protection and preservation of the local ecosystems. (f) Safe dams contribute to the stability and development of local communities. Ensuring a secure water supply and protecting the properties of local residents contributes to the economic and social development of the region. Therefore, research on dam safety is continuously being published. [PERSON] et al. [5] used GPS to monitor the deformation of an old fill dam structure (length: 680 m and width: 5 m) constructed in 1949. A static GPS observation technique was applied for the monitoring. The coordinate values were obtained by repeatedly observing the deformation of the fill dam structure at a certain time interval. A comparison of these values showed that large deformations occurred at specific monitoring points. [PERSON] et al. [6] developed an automatic visual monitoring system that can acquire real-time digital photographic images, create three-dimensional (3D) coordinates for the surface displacement of a dam, and automatically interpret the vector extraction process. This system can be used in situations where real-time measurements cannot be performed. Figure 2: KE 2/20 REC dam failure case [3]. (a) KE 2/20 REC dam failure; (b) Erosion after broken culvert segment. It can especially address the challenge of applying softcopy photogrammetry, a real-time measurement method that uses photographic images; the method cannot be easily applied owing to the time-consuming interpretation process. The field applicability of the developed system was examined through outdoor testing, and the system showed relatively high precision. In recent years, various techniques, such as advanced photogrammetry, digital twin, GNSS, deep learning algorithms, and numerical methods [7; 8; 9; 10], have been reported. [PERSON] [11] constructed a 3D model for the Malpasset Dam located in southern France by introducing short-range photogrammetry and observed the dam failure geometry using the model. The 3D model was created by obtaining 158 images from the site and was used for collapse simulation analyses and geological surveys. [PERSON] et al. [12] developed an HMI solution to improve dam safety monitoring, thus enabling the transmission of the collected measurement data.