Korea Advanced Institute of Science and Technology · 工学
Professor Seongju Chang's research lab specializes in sustainable building technologies and energy-efficient systems, with a strong focus on optimizing energy consumption in commercial and campus buildings through advanced data analytics, simulation, and innovative building-integrated technologies. The lab investigates smart lighting controls, daylight harvesting, green façades, and semi-transparent photovoltaic windows to enhance indoor environmental quality while reducing energy demand. It also explores novel optical fiber systems for high-capacity communication, demonstrating interdisciplinary research at the intersection of building science, energy systems, and photonics. The lab emphasizes data-driven approaches such as data cube modeling and association rule mining to analyze large-scale building energy datasets for actionable insights.
Figures are computed from collected data and may differ slightly.
The quadrature sampling technique as a means of detecting the envelope of RF waveform in the baseband is well known. If this technique is applied to a focused ultrasound imaging system using an array transducer, whether it is a synthetic or nonsynthetic focusing system, unwanted phase terms appear in the expressions of the inphase and quadrature components of the baseband signal when an appropriate delay time is introduced to each channel signal for the purpose of focusing. The expressions of th
Significant amounts of energy are consumed in the commercial building sector, resulting in various adverse environmental issues. To reduce energy consumption and improve energy efficiency in commercial buildings, it is necessary to develop effective methods for analyzing building energy use. In this study, we propose a data cube model combined with association rule mining for more flexible and detailed analysis of building energy consumption profiles using the Commercial Buildings Energy Consump
We experimentally demonstrate transmission over a novel multicore fiber with 9 cores arranged in 3 groups of 3 cores, where strong coupling occurs within the groups and weak couplings between groups. We transmitted over 2500 km in a single group at a time and 715 km when all 9 cores are used. Low-loss 3D waveguides are used as couplers.
The energy consumption behaviour in campus buildings are less well understood than other non-domestic buildings. Energy simulation analysis is a beneficial method in measuring building energy consumption as well as investigating different energy management strategies for the existing buildings. This research has been established through investigating the heating and cooling load reduction potential of green wall as an energy saving measure for three different activity buildings (i.e., research,
This paper argues that analytical approaches (i.e., simulation) and inductive learning methods (i.e., neural networks) can cooperate to facilitate a daylight responsive lighting control strategy. Multiple hybrid controllers are designed to meet four control goals: enriching the informational repertoire of systems control operations for lighting (by inclusion of performance indicators for glare and solar gain), reducing the number of sensing units necessary for capturing the states of building’s
Semi-transparent photovoltaic (STPV) windows, one of the building façade elements, can generate electricity and provide a certain amount of daylight for occupants. Nevertheless, expensive cost and unsatisfying indoor daylight performance in the room are common problems with STPV windows. This study investigates the thermal, daylight, energy, and life-cycle cost performance of STPV windows by considering varied window-to-wall ratios, building orientations, and STPV module types. The electricity b
Ubi-floor is designed as an interactive floor system which allows user to interact with a floor based smart environment. Concerning context aware floor system, previous researches typically dealt with simple ideas of using gate pattern recognition supported by piezoelectric sensing devices or personal identification mediated by body weight estimation that cannot fully support position dependent context-awareness not to mention interactive interfaces based on it. This paper describes the design a
Many countries are concerned about high particulate matter (PM) concentrations caused by rapid industrial development, which can harm both human health and the environment. To manage PM, the prediction of PM concentrations based on historical data is actively being conducted. Existing technologies for predicting PM mostly assess the model performance for the prediction of existing PM concentrations; however, PM must be forecast in advance, before it becomes highly concentrated and causes damage
This paper proposes and develops a residential energy and resource consumption estimation model in the context of multi-family residential housing in Korea using a multi-layer perceptron (MLP) neural network. Eight indicators are introduced which affect the energy and water resource usage characteristics of Korean residential complexes. The proposed model precisely estimated the electricity, gas energy and water consumption for each examined residential complex. In terms of validation, the resul
Unlike in the past, as the scale of buildings expands from a single building to a group of buildings, it is necessary to respond to the demand for energy consumption for the entire community. This study attempted to improve the electricity consumption prediction performance of single buildings by reflecting the inherent occupant behaviour patterns embedded in the shared electricity consumption data of single buildings. The proposed method utilized electricity consumption data for all other 7 tar
ROHINI is a humanoid type flower robot that mediates interactions between occupants and various devices and equipments embedded in a smart home environment. Traditional interfaces such as remote controllers, switches or buttons at home lack of intuitive and natural interactions needed to provide a highly sophisticated monitoring and control of various smart home operations. ROHINI, a rose-like anthropomorphic robot is equipped with biometric sensing system(voice recognition), flower bud and stem
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