

Tak gon Kim, CTOWhile traditional data-driven artificial intelligence (AI) relies on statistical approaches and big data processing, digital twins stand out by using real-time data to predict accurate outcomes and optimize complex processes. KOREA DIGITAL TWIN LAB. Inc. (KDT), with its cutting-edge digital twin platform, WAiSER setting new benchmarks in business decision-making.
“Unlike traditional simulation software, WAiSER allows real-time adjustments to models during simulation runs, enabling unparalleled flexibility and responsiveness,” says Tak gon Kim, CTO of KDT.
WAiSER, built on big data, AI, and simulation (BAS) modeling, solves structural difficulties in data and simulation models. It seamlessly integrates continuous time and discrete event components, making it a powerful tool for dynamic systems and an invaluable asset in decision-making processes. WAiSER 1.0, the first version, was developed from the research theories and project experiences of 40 PhDs and 70 master’s students from the Korean Advanced Institute of Science and Technology’s (KAIST) SMS Lab. Building upon this groundwork, KDT developed WAiSER (Core) 2.0, incorporating state-of-the-art IT technology.
In addition, the platform has model composer and synthesizer functions that help clients create new models by modifying specific variables through the composer function. The synthesizer function, along with the standard interface function of HLA/RTI, facilitates model synthesis, enabling prompt decision-making and efficient problem-solving. WAiSER (Core) 2.0 also leverages multi-processing and multi-threading technology for the swift and effective execution of large-scale, intricate models.
While many organizations concentrate on data and shaping, KDT focuses on understanding and improving the behavioral aspect of the three major components of the digital twin—data, shape, and behavior. This is crucial as it enables the digital twin to accurately duplicate the actions and performance of its counterpart, providing valuable insights for optimization and prediction.
WAiSER’s practical applications are nothing short of groundbreaking and are used by prominent clientele, including Korea Telecom, HD Korea Shipbuilding & Offshore Engineering, and the Ministry of National Defense. Initially built for the defense industry, WAiSER has expanded its domains to include smart cities, energy, and manufacturing sectors. For instance, traffic congestion is a serious issue in major South Korean cities, costing the country KRW 70.62 trillion yearly, which is approximately 3.5 percent of its gross domestic product (GDP). The firm addresses this issue by implementing BAS-based digital twins throughout these cities to optimize traffic signals and reduce congestion costs. In the pilot phase, these smart models have improved traffic flow by over 10 percent on average, showcasing the potential to save KRW 7 trillion annually when implemented nationwide.
Another impressive feat of WAiSER is its contribution to a project that provides swift decision-making assistance to minimize flood damage in river basins by predicting the water level in dams and adjusting discharges accordingly. The existing legacy system was time-consuming due to the need for simulations at over 800 points in the dam and river basin. However, implementing WAiSER reduced the simulation time from 46 to 0.2 seconds. The platform not only streamlined the prediction of flood and dam water levels, but it also assisted the government in making quick and efficient decisions using actionable data, ensuring a rapid response to potential flood threats.
Korea Digital Twin Lab Inc.’s WAiSER platform is a testament to digital twins’ transformative power. The platform is a game-changing breakthrough that addresses the limitations of traditional data-driven AI and simulation software, transforming decision-making processes across various industries. Amidst the complexities of the business sector, WAiSER (Core) 2.0 strategically guides and empowers them to make decisions that shape a more efficient future.
While many organizations concentrate on data and shaping, KDT focuses on understanding and improving the behavioral aspect of the three major components of the digital twin—data, shape, and behavior. This is crucial as it enables the digital twin to accurately duplicate the actions and performance of its counterpart, providing valuable insights for optimization and prediction.
WAiSER’s practical applications are nothing short of groundbreaking and are used by prominent clientele, including Korea Telecom, HD Korea Shipbuilding & Offshore Engineering, and the Ministry of National Defense. Initially built for the defense industry, WAiSER has expanded its domains to include smart cities, energy, and manufacturing sectors. For instance, traffic congestion is a serious issue in major South Korean cities, costing the country KRW 70.62 trillion yearly, which is approximately 3.5 percent of its gross domestic product (GDP). The firm addresses this issue by implementing BAS-based digital twins throughout these cities to optimize traffic signals and reduce congestion costs. In the pilot phase, these smart models have improved traffic flow by over 10 percent on average, showcasing the potential to save KRW 7 trillion annually when implemented nationwide.
Unlike traditional simulation software, WAiSER allows real-time adjustments to models during simulation runs, enabling unparalleled flexibility and responsiveness
Korea Digital Twin Lab Inc.’s WAiSER platform is a testament to digital twins’ transformative power. The platform is a game-changing breakthrough that addresses the limitations of traditional data-driven AI and simulation software, transforming decision-making processes across various industries. Amidst the complexities of the business sector, WAiSER (Core) 2.0 strategically guides and empowers them to make decisions that shape a more efficient future.
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Company
KOREA DIGITAL TWIN LAB. Inc. (KDT)
Management
Tak gon Kim, CTO
Description
KOREA DIGITAL TWIN LAB. Inc. is an innovative company that constantly thrives on collecting and analyzing data to help clients make effective decisions, improve productivity, and assist them in overcoming the hurdles of low reliability and difficult validation for accelerating digital transformation.