• Journal of Advanced Information Technology and Convergence
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• v.10 no.1
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• pp.99-109
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• 2020

As environmental pollution has become severe due to the rapid increase in pollutant generation in the air, measurement, collection, and analysis of atmospheric environment information plays an important role. However, it is difficult to measure the high-resolution and real-time atmospheric environment of the cities and tourist spots with high population mobility only by measuring equipment of stationary measuring stations. Therefore, this paper proposes a portable atmospheric environment measurement system for real-time measurement and monitoring of atmospheric environment information. The proposed system is a portable client with a low-power wireless communication method. It is possible to reliably transmit and receive the measured data through a multi-threaded server to monitor the trend of pollutants in the air in real-time.

• Journal of the Economic Geographical Society of Korea
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• v.18 no.1
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• pp.87-102
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• 2015

This study attempts to introduce the methodology for accounting real-time population distribution in the urban areas. For the purpose, we utilize the media user's time-space information from the media users' media diaries in the media panel survey databases. We analyze the space-time population rate for each activity space related with everyday urban lifes. Seoul has been selected as a case study area, since space-time information are relatively rich there, and thus the comparisons are available. The space-time population rates have been verified by the comparative analysis with the T-card results. We propose a real time population measurement method by combination of the space-time population rate with geographical data. The real time population of each activity space at each dong in Seoul has been calculated by multiplying the space-time population rates to the numbers of employer of three categories of activity spaces(residential, working, and commercial). By utilizing GIS, we visualize the results of two time points (3AM and 3PM) and then analyze the spacio-temporal characteristics of real time population distribution in Seoul. The Day time population distribution pattern shows strong relationships with the distribution of business and commercial activities, while the night time population distribution pattern can be explained by resident population distribution almost perfectly.

• Journal of IKEEE
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• v.16 no.1
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• pp.7-14
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• 2012

In this paper, a reception rate of terrestrial digital TV broadcasting service is analyzed and a novel method which can estimate the broadcasting coverage rate more objectively and reliably than the existing method is proposed. Previous method measures the reception rate by means of electric field intensity measurement or subjective video quality assessment. Because of limited measuring points, it inherently has measurement error and cannot consider the viewer's receiving conditions in real-time. In order to consider the viewer's population and receiving environment, morphology which characterizes the viewer's receiving environment is extracted using household census data of National Statistical Office and the land cover map of Ministry of Environment. Using the extracted geographical morphology, the reception rate of terrestrial digital TV broadcasting service is calculated with Spectrum Management Intelligence System (SMIs). Proposed method can calculate the reception rate more objectively and reliably than the existing methods because it fully considers the viewer's receiving environments in real-time.

• International Journal of Advanced Culture Technology
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• v.10 no.4
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• pp.511-517
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• 2022

Recently, due to rapid climate change, the population of honey bees has decreased, posing a great threat to the existence of the Earth's ecosystem. In particular, the colony collapse phenomenon in which bees disappeared nationwide in early 2022 had devastating consequences for beekeepers. In order to solve the problems of beekeeping due to climate change, it is urgent to develop a system that can monitor the situation inside the hive through various IoT sensors. This paper develops a system that can measure the activity of bees inside the hive and uses it to measure the number of times of entry and exit of the hive. The data measured by the developed system can be monitored in real time on a smartphone through the cloud server. The system developed in this paper can monitor the ecology of bees according to climate change and measure internal and external bee activities. Using this method, it is possible to check in advance for the colony collapse phenomenon in which bees disappeared in early 2022. This is very meaningful in that it presents an alternative that can identify the cause of the problem through early detection.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.2
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• pp.103-110
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• 2012

The population growth along with the urbanization, has caused more problems in many public areas, such as subway airport terminals, hospital, etc. Many surveillance systems have been installed in the public areas, but not all of those can be monitored in real-time, because the operators that observe the monitors are very small compared with the number of the monitors. For example, the observer can miss some crucial accidents or detect after considerable delays. Thus, intelligent surveillance system for preventing the accidents are needed, such as Intelligent Surveillance Systems. in this paper, we propose a new crowd density estimation method which aims at estimating moving crowd using images from surveillance cameras situated in outdoor locations. The moving crowd is estimated from the area where using optical flow. The edge information is also used as feature to measure the crowd density, so we improve the accuracy of estimation of crowd density. A multilayer neural network is designed to classify crowd density into 5 classes. Finally the proposed method is experimented with PETS 2009 images.

• Journal of Drive and Control
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• v.21 no.2
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• pp.53-64
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• 2024

Global population growth has resulted in an increased demand for food production. Simultaneously, aging rural communities have led to a decrease in the workforce, thereby increasing the demand for automation in agriculture. Drones are particularly useful for unmanned pest control fields. However, the current method of uniform spraying leads to environmental damage due to overuse of pesticides and drift by wind. To address this issue, it is necessary to enhance spraying performance through precise performance evaluation. Therefore, as a foundational study aimed at optimizing drone-based pest control technologies, this research evaluated water-sensitive paper (WSP) via density map estimation using convolutional neural networks (CNN) with a encoder-decoder structure. To achieve more accurate estimation, this study implemented multi-task learning, incorporating an additional classifier for image segmentation alongside the density map estimation classifier. The proposed model in this study resulted in a R-squared (R²) of 0.976 for coverage area in the evaluation data set, demonstrating satisfactory performance in evaluating WSP at various density levels. Further research is needed to improve the accuracy of spray result estimations and develop a real-time assessment technology in the field.

• Journal of Korea Water Resources Association
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• v.31 no.6
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• pp.821-832
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• 1998

This study investigates the prediction of daily water supply, which is a necessary for the efficient management of water distribution system. Fuzzy neuron, namely artificial intelligence, is a neural network into which fuzzy information is inputted and then processed. In this study, daily water supply was predicted through an adaptive learning method by which a membership function and fuzzy rules were adapted for daily water supply prediction. This study was investigated methods for predicting water supply based on data about the amount of water supplied to the city of Kwangju. For variables choice, four analyses of input data were conducted: correlation analysis, autocorrelation analysis, partial autocorrelation analysis, and cross-correlation analysis. Input variables were (a) the amount of water supplied (b) the mean temperature, and (c)the population of the area supplied with water. Variables were combined in an integrated model. Data of the amount of daily water supply only was modelled and its validity was verified in the case that the meteorological office of weather forecast is not always reliable. Proposed models include accidental cases such as a suspension of water supply. The maximum error rate between the estimation of the model and the actual measurement was 18.35% and the average error was lower than 2.36%. The model is expected to be a real-time estimation of the operational control of water works and water/drain pipes.

• Journal of Korean Society for Atmospheric Environment
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• v.32 no.2
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• pp.216-232
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• 2016

In present, the Seoul City is undergoing traffic congestion problems caused by rapid urbanization and population growth. Thus the City government has reorganized the mass transportation system since 2004 and the subway has become a very important means for public transit. Since the subway system is typically a closed environment, the indoor air quality issues have often raised by the public. Especially since a huge amount of PM (particulate matter) is emitted from ground tunnels passing through the subway train, it is now necessary to assess the characteristics and behaviors of fine PM inside the tunnel. In this study, the concentration patterns of $PM_1$, $PM_{2.5}$, and $PM_{10}$ in the Seoul subway line-2 were analyzed by real-time measurement during winter (Jan 13, 2015) and summer (Aug 7, 2015). The line-2 consisting of 51 stations is the most busy circular line in Seoul having the railway of 60.2 km length. The the one-day average $PM_{10}$ concentrations were $148{\mu}g/m^3$ in winter and $66.3{\mu}g/m^3$ in summer and $PM_{2.5}$ concentrations were $118{\mu}g/m^3$ and $58.5{\mu}g/m^3$, respectively. The $PM_{2.5}/PM_{10}$ ratio in the underground tunnel was lower than the outdoor ratio and also the ratio in summer is higher than in winter. Further the study examined structural types of underground subsections to explain the patterns of elevated PM concentrations in the line-2. The subsections showing high PM concentration have longer track, shorter curvature radius, and farther from the outdoor stations. We also estimated the outdoor PM concentrations near each station by a spatial statistical analysis using the $PM_{10}$ data obtained from the 40 Seoul Monitoring Sites, and further we calculated $PM_{2.5}/PM_{10}$ and $PM_1/PM_{10}$ mass ratios near the outdoor subway stations by using our observed outdoor $PM_1$, $PM_{2.5}$, and $PM_{10}$ data. Finally, we could develop pollution maps for outdoor $PM_1$ and $PM_{2.5}$ near the line-2 by using the kriging method in spatial analysis. This methodology may help to utilize existing $PM_{10}$ database when managing and control fine particle problems in Korea.