Fires usually occur in homes because of carelessness and changes in environmental conditions. They cause threats to the residential community and may result in human death and property damage. Consequently, house fires must be detected early to prevent these types of threats. The immediate notification of a fire is the most critical issue in domestic fire detection systems. Fire detection systems using wireless sensor networks sometimes do not detect a fire as a consequence of sensor failure. Wireless sensor networks (WSN) consist of tiny, cheap, and low-power sensor devices that have the ability to sense the environment and can provide real-time fire detection with high accuracy. In this paper, we designed and evaluated a wireless sensor network using multiple sensors for early detection of house fires. In addition, we used the Global System for Mobile Communications (GSM) to avoid false alarms. To test the results of our fire detection system, we simulated a fire in a smart home using the Fire Dynamics Simulator and a language program. The simulation results showed that our system is able to detect early fire, even when a sensor is not working, while keeping the energy consumption of the sensors at an acceptable level.

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For flood risk assessment, it is necessary to quantify the uncertainty of spatiotemporal changes in floods by analyzing space and time simultaneously. This study designed and tested a methodology for the designation of evacuation routes that takes into account spatial and temporal inundation and tested the methodology by applying it to a flood-prone area of Seoul, Korea. For flood prediction, the non-linear auto-regressive with exogenous inputs neural network was utilized, and the geographic information system was utilized to classify evacuations by walking hazard level as well as to designate evacuation routes. The results of this study show that the artificial neural network can be used to shorten the flood prediction process. The results demonstrate that adaptability and safety have to be ensured in a flood by planning the evacuation route in a flexible manner based on the occurrence of, and change in, evacuation possibilities according to walking hazard regions.

Emergency exit signs have an important role in the fire safety of buildings. Exit signs help evacuees rapidly escape fire by following the fastest and safest escape routes immediately after the detection of fire. In other words, evacuation can greatly vary according to environmental factors regarding evacuation within the building. In this study, change in the evacuation speed by exit signs and environmental conditions was analyzed through experiments with 138 subjects. Four environmental factors in the experiment are visibility, distance between exit sign and evacuees, spatial configuration, and size and brightness of exit sign. In conclusion, changes in the spatial conditions around exit signs influenced the evacuation speeds of the subjects in poor visibility, and the changes in physical conditions of exit signs exerted more influence when the visibility was relatively better.

Recently, BIM (Building Information Modeling) became mandatory in Korea, and BIM started to be implemented in construction area. It is a design tool for maximizing the efficiency of design, construction, and maintenance throughout the entire lifecycle, but there are not many studies about the demolition wastes (DW) in the demolition stage. This study gathered basic data concerning the development of a database of DW disposed in the demolition stage using BIM-based building material database. For this, a BIM software, ARCHICAD, and construction material categories of the item list system of the PPS (Public Procurement Service) were analyzed to select major building materials. Based on the analysis, the disposal routes were analyzed considering the characteristics of DW. The database of DW was developed by examining the disposal routes of 52 major construction materials selected according to the characteristics of each material during demolition and selecting 7 major DW.