• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1865-1869
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• 2004

A new model for the propagation prediction for mobile communication network inside building is presented in this paper. The model is based on the determination of the dominant paths between the transmitter and the receiver. The field strength is predicted with adaptive neuro - fuzzy inference systems (ANFIS), trained with measurements. The advantage of the ANFIS with hybrid least squares and gradient descent algorithms is fast convergence compared with original neural network. The K-means algorithm for selection of training patterns is also used. Comparison of our predicted results to measurements indicate that improvements in accuracy over conventional empirical model are achieved.

• Journal of the Korea Society for Simulation
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• v.25 no.1
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• pp.53-61
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• 2016

This paper introduces 'EgresSIM', which is microscopic evacuation simulation software. EgresSIM developed in this paper is a three-dimensional (3D) pedestrian evacuation simulator based on the improved model advanced from the floor field model(FFM), a microscopic pedestrian model. This software can simulate large size buildings that consist of a number of floors, stairs, rooms, and exit doors. Moreover, this software can arrange several hundreds or thousands of pedestrians in indoor space and check their movements through the 3D viewer in real time, as well as produce detailed results about evacuation situations such as which paths are employed by individual pedestrians, how long does it takes to evacuate, and how many evacuees are gathered at each of the exit doors. Building data needed in the simulation are constructed as XML files according to pre-defined indoor data models and information of simulation results is also created as XML log files. A moving pattern of pedestrians can be represented in many ways by adjusting the sensitivity parameters of two walk models supported by EgresSIM. Thus, evacuation simulation can be done based on many assumptions of situations such as movement to the nearest exit door or blackout after outage.

• Journal of Sensor Science and Technology
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• v.17 no.3
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• pp.168-177
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• 2008

An indoor environmental monitoring system using IEEE 802.15.4 based wireless sensor network is proposed to monitor the amount of pollutant entering to the room from outside and also the amount of pollutant that is generated in indoor by the building materials itself or human activities. Small-size, low-power wireless sensor node and low power electrochemical sensor board is designed to measure the condition of indoor environment in buildings such as home, offices, commercial premises and schools. In this paper, two query models, the broadcasting query protocol and flooding query protocol, were designed and programmed as a query-based routing protocol in wireless sensor network for an environment monitoring system. The flooding query routing protocol in environment monitoring is very effective as a power saving routing protocol and reliable data transmission between sensor nodes.

• KIEAE Journal
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• v.7 no.5
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• pp.53-58
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• 2007

In order to predict the indoor air pollutant, the VOCs emission rate is used through small chamber in the design process. However, the small chamber method has limitations as the convective mass transfer coefficient, the most important factor when predicting VOCs contamination of indoor air, is different between the small chamber result and the measured data in the actual building. Furthermore, the existing studies which analyzed mass transfer coefficient in the small chamber were directed on the small chambers developed at the time and FLEC(Field and Laboratory Emission Cell), thus, are different from the current small chamber which has been changed with improvements. The purpose of this study is to determine the emission rate of pollutant in multi-layered building materials, and predict the indoor pollutant concentration through the CFD(Computational of Fluid Dynamics) and CRIAQ2 based on the mass transfer coefficient on singled-layered building material by using the current small chamber widely used in Korea. Futhermore, this study used the new convective mass transfer coefficient(hm') which indicates the existing convective mass transfer coefficient(hm) including VOC partition coefficient(k). Also, formaldehyde was selected as target pollutant.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.264-266
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• 2022

In order to apply the RNN model to the radio fingerprint-based indoor path generation technology, the data set must be continuous and sequential. However, Wi-Fi radio fingerprint data is not suitable as RNN data because continuity is not guaranteed as characteristic information about a specific location at the time of collection. Therefore, continuity information of sequential positions should be given. For this purpose, clustering is possible through classification of each region based on signal data. At this time, the continuity information between the clusters does not contain information on whether actual movement is possible due to the limitation of radio signals. Therefore, correlation information on whether movement between adjacent clusters is possible is required. In this paper, a deep learning network, a recurrent neural network (RNN) model, is used to predict the path of a moving object, and it reduces errors that may occur when predicting the path of an object by generating continuous location information for path generation in an indoor environment. We propose a method of giving correlation between clustering for generating an improved moving path that can avoid erroneous path prediction that cannot move on the predicted path.

• Journal of Environmental Health Sciences
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• v.45 no.1
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• pp.1-8
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• 2019

Objectives: The purpose of this study was to estimate the ventilation rate of residential homes in Korea through tracer gas methods using indoor and outdoor concentrations of carbon dioxide ($CO_2$) and $CO_2$ generation rates from breathing. Methods: In this study, we calculated the number of occupants in a home by time through data on the average number of people per household from the Korean National Statistical Office and also measured the amount of $CO_2$ generation by breathing to estimate the indoor $CO_2$ generation rate. To estimate the ventilation rate, several factors such as the $CO_2$ generation rate and average volume of residential house provided by the Korean National Statistical Office, indoor $CO_2$ concentrations measured by sensors, and outdoor $CO_2$ concentrations provided by the Korea Meteorological Administration, were applied to a mass balance model for residential indoor environments. Results: The average number of people were 2.53 per household and Koreans spend 61.0% of their day at home. The $CO_2$ generation rate from breathing was $13.9{\pm}5.3L/h$ during sleep and $15.1{\pm}5.7L/h$ in a sedentary state. Indoor and outdoor $CO_2$ concentrations were 849 ppm and 407 ppm, respectively. The ventilation rate in Korean residential houses calculated by the mass balance model were $42.1m^3/h$ and 0.71 air change per hour. Conclusions: The estimated ventilation rate tended to increase with an increase in the number of occupants. Since sensor devices were used to collect data, sustainable data could be collected to estimate the ventilation rate of Korean residential homes, which enables further studies such as on changes in the ventilation rate by season resulting from the activities of occupants. The results of this study could be used as a basis for exposure and risk assessment modeling.

• Spatial Information Research
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• v.21 no.3
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• pp.89-101
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• 2013

Recently, importance of indoor space is on the rise, as larger and more complex buildings are taking place due to development of building technology. Accordingly, range of the target area of spatial information service is rapidly expanding from outdoor space to indoor space. Various demands for indoor spatial information are expected to be created in the future through development of high technologies such as IT Mobile and convergence with various area. Thus this research takes a look at available methods for building indoor spatial information and then builds high accuracy three-dimensional indoor spatial information using indoor high accuracy laser survey and 3D vector process technique. The accuracy of built 3D indoor model is evaluated by overlap analysis method refer to a digital map, and the result showed that it could guarantee its positional accuracy within 0.04m on the x-axis, 0.06m on the y-axis. This result could be used as a fundamental data for building indoor spatial data and for integrated use of indoor and outdoor spatial information.

• The Journal of Korea Robotics Society
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• v.3 no.3
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• pp.194-202
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• 2008

This paper describes a new method for indoor environment mapping and localization with stereo camera. For environmental modeling, we directly use the depth and color information in image pixels as visual features. Furthermore, only the depth and color information at horizontal centerline in image is used, where optical axis passes through. The usefulness of this method is that we can easily build a measure between modeling and sensing data only on the horizontal centerline. That is because vertical working volume between model and sensing data can be changed according to robot motion. Therefore, we can build a map about indoor environment as compact and efficient representation. Also, based on such nodes and sensing data, we suggest a method for estimating mobile robot positioning with random sampling stochastic algorithm. With basic real experiments, we show that the proposed method can be an effective visual navigation algorithm.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.11
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• pp.310-318
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• 2018

Recently, the importance of big data analysis is increasing as a large amount of data is generated by various devices connected to the Internet with the advent of Internet of Things (IoT). Especially, it is necessary to analyze various large-scale IoT streaming sensor data generated in real time and provide various services through new meaningful prediction. This paper proposes a real-time indoor PM10 concentration prediction LSTM model based on streaming data generated from IoT sensor using AWS. We also construct a real-time indoor PM10 concentration prediction service based on the proposed model. Data used in the paper is streaming data collected from the PM10 IoT sensor for 24 hours. This time series data is converted into sequence data consisting of 30 consecutive values from time series data for use as input data of LSTM. The LSTM model is learned through a sliding window process of moving to the immediately adjacent dataset. In order to improve the performance of the model, incremental learning method is applied to the streaming data collected every 24 hours. The linear regression and recurrent neural networks (RNN) models are compared to evaluate the performance of LSTM model. Experimental results show that the proposed LSTM prediction model has 700% improvement over linear regression and 140% improvement over RNN model for its performance level.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.1
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• pp.1-10
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• 2024

The radio propagation characteristics of the 6, 10, and 17 GHz frequency bands in multiple paths in an indoor lobby environment were analyzed. The line-of-sight (LOS) and non-LOS (NLOS) paths were measured from a distance of 2-16 m (0.5 m intervals) from the transmitting to the receiving antenna positions. For basic transmission losses, three parameters were compared using the floating intercept path loss model corresponding to the path. For a root mean square delay spread, the measurement results were compared for cumulative probabilities of 10, 50, and 90%. Propagation loss and propagation delay occurred in all measured frequencies owing to the existence of pillars and an unusual lobby structure. Thus, a measurement scenario for an indoor lobby environment and the provision of standard measurement data was proposed. The results may facilitate research on the radio propagation characteristics of 5G and millimeter-wave bands in indoor lobby environments with various structures.