RESEARCH AND DEVELOPMENT

AI Technology Research for River and Sabo Infrastructure Management

Optimized dam operation using AI

Dam operation must take into consideration the balance of flood control (preventing or mitigating disasters) and water utilization (use of stored water for power generation etc.). Operational methods in this regard generally use rainfall estimations to predict future river flow rates, then release water accordingly.
 

However, rainfall estimation accuracy is imperfect, and predictions can be significantly off the mark. Trusting in such predictions when operating a dam is dangerous as doing so can trigger disasters downstream or result in a lack of stored water for power generation. This research aims to develop AI technology that minimizes losses by taking estimated rainfall precision into consideration.

Dam anomaly detection

All structures eventually deteriorate. Infrastructure is no exception. To ascertain whether structures are sound, a variety of data is collected from many types of infrastructure. Development of ICT in recent years has resulted in the collection of significantly more data, leading to an increase in accuracy. However, in many cases, the data is checked visually by a person to ascertain soundness and identify anomalies.
 

This research uses collected data to develop AI technology that is capable of completely and quantitatively detecting anomalies that were previously only detectable via a visual inspection or according to worker experience. The technology is expected to be applied not only to dams, but various other infrastructure areas to streamline maintenance tasks.

Automatic identification of Sabo facility deformation

Conventionally, a visual inspection of Sabo facilities was required to identify deformations and assess soundness. However, such facilities are found in steep mountainous areas, making comprehensive, objective identification of deformations, and assessment of overall soundness difficult in terms of safety and efficiency.
 

On the other hand, development of AI image analysis and UAV imaging related technologies has continued to progress in recent years. When considering the massive amount of inspection data being collected, it is important to appropriately combine these technologies to effectively promote maintenance via digital transformation (DX).
 

This research focuses on developing AI technology capable of automatically identifying deformations in Sabo facilities. Continuous research in this area should enable more efficient inspections at such facilities through consideration of methods that have been incorporated into the erosion control facility inspection.