높아진 생활수준과 주 5일 근무의 정착으로 여가시간이 증가했고, 이에 따라 물을 이용한 공간 에 대한 관심도 크게 증가하였다. 하지만 급격한 양적 성장이 이루어짐에 따라 물놀이 공간은 대부분 획일화된 시설물과 배치로 조성되어 있으며, 다양한 행태에 대한 지원 또한 미흡한 실정이다. 이에 본 연구에서는 빅데이터를 활용한 실증 데이터를 바탕으로 물놀이 공간 및 시설 물의 이용행태를 분석하고자 하였다. 그 결과, 각 물놀이 시설물이 서로 다른 놀이를 지원하며, 각각 유발되는 놀이의 형태나 이용행태가 상이하다는 결론을 도출하였다. 이에 본 연구는 앞으 로 물놀이 공간 조성 시, 물리적 환경과 이용자 간의 관계를 고려하여 설계할 수 있도록 기본자 료를 제시하고자 하였다.

본 연구는 COVID-19 이후 큰 타격을 입은 관광산업 중 하나인 워터파크를 대상지로 선정하여 COVID-19가 워터파크 이용에 있어 어떠한 인식의 변화를 야기했으며 또한 행태변화에 어떠한 영향을 미쳤는지를 살펴보고자 빅데이터 분석 연구를 실시하였다. 이를 위해 텍스톰(TEXTOM)을 활용하여 COVID-19 이전(2015-2019)과 이후(2020-2021)시기를 나누어 데이터를 수집하였고 빈도분석과 TF-IDF, N-GRAM, 그리고 감성분석을 진행하였다. 분석 결과 주목할 만한 점은 우선, COVID-19 이후 워터파크 이용에 제한이 있었음에도 불구하고 이전 시기보다 데이터 양이 늘어났다는 점이다. 이를 통해 사람들의 워터파크에 대한 관심은 이전에 비해 줄어들지 않았다는 것을 확인할 수 있었다. 또한 분석 결과 COVID-19 이전에는 전국 각지의 워터파크에 대한 정보에 관심이 많았지만 이에 반해 COVID-19 이후에는 확실히 마스크, 방역 등 COVID-19의 영향이 짙은 정보에 대한 관심이 늘어났음을 확인하였다. 또한 행태의 변화로 인하여 사람들은 COVID-19의 영향으로 가격이 비싸더라도 타인과 거리두기가 가능한 프라이빗한 공간이나, 외부공간 그리고 자연 속 공간을 선호한다는 것을 알 수 있었다. 이를 통해 워터파크는 변화된 사람들의 기대에 맞춘 설계의 새로운 방향을 고민해볼 필요가 있고 또한 전염병 예방을 위한 워터파크의 새로운 동선 설계를 고민하는 것도 앞으로의 워터파크 관광에 있어 중요한 요소이다. 마찬가지로 기존의 워터파크에서는 무엇보다 전염병 예방에 대한 안전수칙을 강화할 필요가 있고 또한 운영 관리의 측면에서도 이용객 수의 제한 등 내부 공간의 밀도를 낮춰 워터파크가 안전하다는 인식을 심어줄 필요가 있다. 이러한 분석 결과를 통해 앞으로 워터파크의 운영 방안이나 설계의 기준을 뒷받침할 수 있는 기초자료가 될 수 있을 것이라 기대한다.

This study derived the unit of industrial water usage reflecting the latest industry trends. Available for establishing plans such as the master plan for water supply system and analyzed changes in the basic unit by a comparison with the current basic unit values. This study analyzed 4,038 samples with a sampling error of less than 1.5 % at the 95 % confidence level after removing outliers according to a log-normal distribution. As a result, the unit of industrial water usage per site area in the whole manufacturing industry was 7.11 m3/1,000m2/d. The ten industrial categories (C10, C13, C20, C21, C22, C25, C27, C30, C32, C33) showed a similar unit value compared to before, and the four industrials categories (C11, C17, C22, C31) showed a more unit value than before. With regard to the nine industrial categories (C14, C15, C16, C18, C19, C24, C26, C28, C29), the unit value decreased. Cases that companies examined before were the same as the companies examined in this study were analyzed. The result that the changes in the unit industrial water usage were reasonable was obtained. However, in some industrial categories (C17, C14, C24, C29), the unit value was changed by a small number of companies with large-scale water use or unit value of sampling had a large deviation. It was considered necessary to survey them periodically. The unit of industrial water usage derived by the survey in this study reflects the current industrial trends in 2016. Water use in manufacturing companies has continuously changed by the development of manufacturing technologies and simplification of manufacturing processes. In order to deal with this, it is considered necessary to survey the usage of industrial water periodically from a long-term perspective.

Recently, advanced metering infrastructure (AMI) has been recognized as a core technology of smart water grid, and the relevant market is growing constantly. In this study, we developed all-in-one smart water meter of the AMI system, which was installed on the test-bed to verify both effectiveness and field applicability in office building water usage. Developed 15 mm-diameter smart water meter is a magneto-resistive digital meter, and measures flow rate and water quality parameters (temperature, conductivity) simultaneously. As a result of the water usage analysis by installing six smart water meters on various purposes in office building water usage, the water usage in shower room showed the highest values as the 1,870 L/day and 26.6 liter per capita day (LPCD). But, the water usage in laboratory was irregular, depending on the many variables. From the analysis of the water usage based on day of the week, the water usage on Monday showed the highest value, and tended to decrease toward the weekend. According to the PCA results and multivariate statistical approaches, the shower room (Group 3) and 2 floor man’s restroom sink (Group 1-3) have been classified as a separate group, and the others did not show a significant difference in both water use and water quality aspects. From the analysis of water usage measured in this study, the leak or water quality accident did not occur. Consequently, all-in-one smart water meter developed in this study can measure flow rate and water quality parameters (temperature, conductivity) simultaneously with effective field applicability in office building water usage.

요즘 IoT (Internet of things)에 대한 기술개발은 사업 전반에 걸쳐 이루어지고 있으며, 이에 따른 Big Data 분석으로 다양한 제품과 서비스가 만들어 지고 있다. 정수기를 사용함에 있어 과연 소비자는 어떠한 형태로 사용하고 있을까? 또한 정수기를 구성하고 있는 부품들은 어떻게 동작하고 있을까? 이러한 사항들을 측정하고 실사용 데이터를 수집 분석하기 위해 패널을 구축했고 가정집과 다중이용시설에 대해 각각 1년간 측정 분석하여 정수기 사용 패턴을 모니터링 하였다. 본 연구는 사용자의 사용하는 시간대와 장소, 온도와 습도, 사용자 특성 (자녀연령, 직업, 연령대, 수입) 등에 따라 나타나는 패턴을 분석하였다.

Aging water pipe networks hinder efficient management of important water service indices such as revenue water and leakage ratio due to pipe breakage and malfunctioning of pipe appurtenance. In order to control leakage in water pipe networks, various methods such as the minimum night flow analysis and sound waves method have been used. However, the accuracy and efficiency of detecting water leak by these methods need to be improved due to the increase of water consumption at night. In this study the Principal Component Analysis (PCA) technique was applied to the night water flow data of 426 days collected from a water distribution system in the interval of one hour. Based on the PCA technique, computational algorithms were developed to narrow the time windows for efficient execution of leak detection job. The algorithms were programmed on computer using the MATLAB. The presented techniques are expected to contribute to the efficient management of water pipe networks by providing more effective time windows for the detection of the anomaly of pipe network such as leak or abnormal demand.

The estimation of groundwater usage in Jeju island is important to understand hydrologic cycle system and to plan management of water resource because large amounts of groundwater have been used for agricultural and domestic purpose. The model has been developed to estimate agricultural groundwater usage for garlic at uplands and citrus at orchards raising outdoors using the soil water balance model from FAO 56, respectively. The total amount of water supplied for the crop evapotranspiration and the multipurpose function such as sprout promotion can be simulated by the model. However, due to the discrepancy of water use in initial stage between calculated and observed, the model was calibrated and verified using actual groundwater usage monitoring data for 3.5 years (2011.6 to 2014.12) at three uplands for garlic and three orchards for citrus. Consequently, it would be concluded that the model simulated efficiently actual water usage in that root mean square (RMS) and normalized RMS of the validation stage were less than 8.99 mm and 2.43%, respectively, in two different conditions.

In this experiment, the high early strength cement containing massive C3S quantity was used to enhance the early strength of cement mortar using admixtures which can accelerate C3S hydration reaction in the condition of room temperature. The measuring items are zero flow, setting times, compressive strength and analysis of MIP & SEM

This study is to analyze the characteristics of golf course water usage using groundwater and rainwater data obtained from 17 golf courses in Jeju Island during 2007～2009. The groundwater usages were 246,275 ㎥/year, 213,062 ㎥/year, 155,235 ㎥/year, and 126,666 ㎥/year in the west, south, east, and north regions, respectively. Monthly rate of the amount of groundwater usage to the amount of permission was 29.5%. The rainfall usages were 386,591 ㎥/year, 326,464 ㎥/year, 251,248 ㎥/year, and 232,061 ㎥/year in the south, west, east, and north regions, respectively. Monthly rate of rainwater usage to the amount of water retention of golf courses was 19.6%. The average annual water usage in the 17 golf courses was 499,377 ㎥/year. From the average usage, it was found that the rainwater usage (305,126 ㎥/year) was 1.6 times higher than that of groundwater (194,251 ㎥/year). That means the annual average rainwater usage to the entire water usage was 61.1%, which was above the criteria of 40%.