Earticle

초록

영어

Approximately 40% of underground water and sewage pipes in Korea are more than 20 years old. Consequently, potential accidents related to water drainage systems are to be expected. In this study, using a special machine learning method that employs various available data, we developed a system that receives and analyzes data in smart pipes called the "digital twin-based smart pipe integrated management system" (DTMS-IM). This system presents an integrated approach for the efficient operation and monitoring of water pipes, allowing the innovative operation of groundwater pipes through smart decision-making. We trained the model using these data. This well-trained model has become able to predict the aging level of pipes. Similar artificial intelligence prediction models, widely used in various industrial applications, are also discussed.

목차

Abstract
I. INTRODUCTION
II. DTMS-IM
III. A SPECIAL MACHINE LEARNING PREDICTION-BASED MODEL FOR DTMS-IM
IV. CONCLUSION
REFERENCES

저자

• Phil-Doo Hong [ Department of Data Convergence Software Korea Polytechnic Bundang, Korea ]
• YuDoo Kim [ Department of Data Convergence Software Korea Polytechnic Bundang, Korea ] Corresponding Author

참고문헌