Prof. Dongsoo Har’s research focuses on optimization of communication system operation and transportation system development with embedded artificial intelligence. In detail, his current research areas contain multimedia communication system design and implementation in ITS, communication system/network for autonomous vehicles, wireless sensor network design and implementation for ITS, high-efficiency digital system design for power grid, self-improving artificial intelligence technology, and development of deep neural networks.
Ongoing Research:
Artificial intelligence and its application
AI is the intelligence exhibited by machines or software, which is the subfield of computer science. Also, AI is becoming a popular field in computer science as it has improved the human life in many areas. Application areas of AI have a huge impact on different fields of human life as expert system is widely used these days to solve the complex problems in many areas as science, engineering, business, medicine, weather forecasting. The objective of this research is to increase the quality and efficiency of applications by using AI technology. In our laboratory, AI soccer system using reinforcement learning is being studied. In the ITS, the research about accident area prediction system and feature learning employing deep learning is also being performed, and the architecture of deep neural network is being studied. Finally, the weather forecasting method is also being studied for the prediction of renewable power production.
Energy cloud
The energy cloud represents a digital transformation that reconstructs power grid as a network connecting homes and businesses with a clean energy sources and services, utilizing data to help customers to customize their energy use in whatever manner suits their needs. Emerging technologies, such as cloud computing, Internet of Things, and big data, is highly utilized to achieve the energy cloud assisting the management of data and information related to energy system flow. This leads to the improvement of flexibility, solution scalability, optimization of energy use, and electric device management. The objective of this study is to present the system of power grid and develop various optimization methods considering the basic elements and requirements of the energy cloud. In our laboratory, communication network/system, optimal scheduling and management methods, distribution system design for smart grid, and weather forecasting methods are being studied for the energy cloud.