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International Conference

Modeling and Calibrating Digital Twin of Automatic Garbage Collection System in Sejong City
categorize
Agent Modeling
Author
Tae Sub Yun, Minsang Park, and Il-Chul Moon
Year
2023
Conference Name
Annual Modeling and Simulation Conference (ANNSIM 2023)
Presentation Date
May 23-26
City
Ontario
Country
Canada
File
Modeling_and_Calibrating_Digital_Twin_of_Automatic_Garbage_Collection_System_in_Sejong_City 1.pdf (6.5M) 22회 다운로드 DATE : 2024-01-16 15:18:11

Tae Sub Yun, Minsang Park, and Il-Chul Moon, Modeling and Calibrating Digital Twin of Automatic Garbage Collection System in Sejong City, Annual Modeling and Simulation Conference (ANNSIM 2023), Ontario, Canada, May 23-26, 2023 


Abstract

In recent years, developing a digital twin for a complex system has been a key research effort in the modeling and simulation (M&S) community. This paper presents one of the digital twin systems for an urban garbage collection system, located in Sejong City, South Korea. This garbage collection system requires constant maintenance and management, and particularly, a rapid collection of distributed garbage is required for urban sanitation and the population’s satisfaction. However, the current status-quo is following a routine garbage collection schedule, so the system management becomes rigid. Therefore, we develop a digital twin model to experiment with the garbage collection mechanism and speed to provide a simulator for further study on its operation. Our digital twin model is designed by following the DEVS formalism and calibrated by a large-scale of real-world datasets. This paper delivers the practice of designing, experimenting, and calibrating this urban system. 


@inproceedings{yun2023modeling, 

title={Modeling and Calibrating Digital Twin of Automatic Garbage Collection System in Sejong City}, 

author={Yun, Tae-Sub and Park, Minsang and Moon, Il-Chul}, 

booktitle={2023 Annual Modeling and Simulation Conference (ANNSIM)}, 

pages={572--583}, 

year={2023}, 

organization={IEEE} 

} 


Source Website:

https://ieeexplore.ieee.org/document/10155383