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디아이랩 주식회사 Photovoltaic

Company Name 디아이랩 주식회사 CEO 명광민
Business Type Information and Communication,R&D Main Business Photovoltaic, Buildings
Tel. 02-364-2388 Fax. --
E-mail km.myung@dilab.kr Website dilab.kr
Address 47, Kyonggidae-ro, Seodaemun-gu, Seoul, 03752, Korea

Company Information

  • Business Information DI Lab provides a weather and climate intelligent platform service to respond to climate change based on its expertise in the weather and climate, artificial intelligence (AI) technology and data analysis know-how. The representative solution is 'DI CAST', an artificial intelligence-based anomaly detection and prediction solution. Our main solution is 'DI CAST', an artificial intelligence-based anomaly detection and prediction solution. Our services include 'Modoo Solar', which provides a service for predicting solar power generation and facility abnormality detection, and 'Modoo Air', which optimally manages air quality in indoor workspaces such as factories and food kitchens. Recently, we are developing ‘deep learning-based nowcasting and flood risk detection’ technology for target points to minimize damage caused by heavy rains. Under the mission of “a company that solves problems through data and makes a healthy society,” DI Lab is focusing on reducing risks caused by climate change, which is a global issue.
  • Technology One of DI Lab's representative solutions, "DI CAST," is a weather and climate AI solution that provides anomaly detection capabilities by analyzing sensor data such as fine dust, temperature and humidity, solar radiation, solar power generation, noise, and vibration through temporal and spatial distribution. It detects abnormal data, removes error data, and provides notifications in case of dangerous situations. It refines and fuses data from weather and environmental observations, satellites, and numerical models to build learning data, providing accurate and precise prediction data for target locations. During the process, it selects the optimal model for prediction factors and objectives, optimizes the model through past data learning, and maintains the best performance through continuous model updates.