본 논문에서는 건설 현장 관리의 과제를 다루고 IoT 기술 활용을 위한 기술 적용에 대해 정리하였다. 도로 포장 장비의 유휴 시간을 모니터링하는 IoT 장치를 설계 및 구현하여 효율적인 장비 관리 시스템을 개발하는 것을 목표한다. 또한, 본 연구에서는 통신방식 선 정, 사용자 친화적인 플랫폼 설계, 데이터 수집 및 분석을 위한 진동센서 기반 IoT 디바이스 개발을 통한 실시간 관리에 중점을 두고 있다. 플랫폼을 통해 공사현황을 실시간으로 모니터링하고 장비 유휴시간을 관리해 효율성을 높일 수 있으며, IoT 디바이스는 90% 이 상의 데이터 정확도를 보장한다. 현장 테스트를 통해 장비 사용 추적 효과가 확인되어 보다 효율적인 건설 관리에 기여하고자 한다.

PURPOSES : This study aimed to perform real-time on-site construction volume management by using Internet of things (IoT) technology consisting of 3D scanning, image acquisition, wireless communication systems, and mobile apps for new and maintenance construction of concrete bridge deck overlays. METHODS : LiDAR was used to scan the overlay before and after construction to check the overlay volume. An enhanced inductively coupled plasma (ICP) method was applied to merge the LiDAR data scanned from multiple locations to reduce noise, and an anisotropic filter was applied for efficient three-dimensional shape modeling of the merged LiDAR data. The construction volume counter of the mobile mixer was directly photographed using an IP camera, and the data were transmitted to a central server via the LTE network. The video images were transmitted to the central server and optical character recognition (OCR) was used to recognize the counter number and store it. The system was built such that the stored information could be checked in real time in the field or at the office. RESULTS : As a result of using LiDAR to check the amount of overlay construction, the error from the planned amount was 0.6%. By photographing the counter of the mobile mixer using an IP camera and identifying the number on the counter using OCR to check the quantity, the results showed that there was a 2% difference from the planned quantity. CONCLUSIONS : Although the method for checking the amount of construction on site using LiDAR remains limited, it has the advantage of storing and managing the geometric information of the site more accurately. Through the IoT-based on-site production management system, we were able to identify the amount of concrete used in real time with relative accuracy.

The objective of this study is to analyze the indoor air quality of multi-use facilities using an IoT-based monitoring and control system. Thise study aims to identify effective management strategies and propose policy improvements. This research focused on 50 multi-use facilities, including daycare centers, medical centers, and libraries. Data on PM10, PM2.5, CO2, temperature, and humidity were collected 24 hours a day from June 2019 to April 2020. The analysis included variations in indoor air quality by season, hour, and day of the week (including both weekdays and weekends). Additionally, ways to utilize IoT monitoring systems using big data were propsed. The reliability analysis of the IoT monitoring network showed an accuracy of 81.0% for PM10 and 76.1% for PM2.5. Indoor air quality varied significantly by season, with higher particulate matter levels in winter and spring, and slightly higher levels on weekends compared to weekdays. There was a positive correlation found between outdoor and indoor pollutant levels. Indoor air quality management in multi-use facilities requires season-specific strategies, particularly during the winter and spring. Furhtermore, enhanced management is necessary during weekends due to higher pollutant levels.

Due to climate change and the rise in international transportation, there is an emerging potential for outbreaks of mosquito-borne diseases such as malaria, dengue, and chikungunya. Consequently, the rapid detection of vector mosquito species, including those in the Aedes, Anopheles, and Culex genera, is crucial for effective vector control. Currently, mosquito population monitoring is manually conducted by experts, consuming significant time and labor, especially during peak seasons where it can take at least seven days. To address this challenge, we introduce an automated mosquito monitoring system designed for wild environments. Our method is threefold: It includes an imaging trap device for the automatic collection of mosquito data, the training of deep-learning models for mosquito identification, and an integrated management system to oversee multiple trap devices situated in various locations. Using the well-known Faster-RCNN detector with a ResNet50 backbone, we’ve achieved mAP (@IoU=0.50) of up to 81.63% in detecting Aedes albopictus, Anopheles spp., and Culex pipiens. As we continue our research, our goal is to gather more data from diverse regions. This not only aims to improve our model’s ability to detect different species but also to enhance environmental monitoring capabilities by incorporating gas sensors.

This study developed an IoT-based agricultural well control system and demonstrated it through a control system in the current state of domestic open-field smart farms where systematic management is insufficient due to the difficulty of collecting accurate data such as agricultural water intake and usage. As a result, it was possible to derive the optimal control system test results according to the watering conditions for each schedule by conducting automatic control focusing on periods when there is no precipitation. This means that irrigation can be carried out smoothly during the time when irrigation is needed to improve crop quality and secure farm income, and as a result, it is possible to systematically manage and operate among demonstration farms connected to irrigation, resulting in a shortage of agricultural water and a resolution of supply imbalances.

본 논문에서는 대규모 실시간 매칭의 생존 게임에서 플레이를 위한 유저들의 소셜 관계에 대해 연구한다. 특 히 “사전 팀 구성”을 통한 자의적인 팀 구성이 어떤 방식으로 유저들을 연결하는 지 연구하고자 한다. 다수 의 사람 간 집단 역학에서 나타나는 특성이나 패턴에 대한 조사를 중심으로 하였으며, 개인의 특성은 보조적 인 수단으로만 사용된다. 이번 연구에서는 게임을 플레이하는 유저들의 익명화 된 대규모 데이터를 활용하며 이에 대한 간소화된 집계 방법을 제안한다. 데이터 세트에는 사전 팀 구성에 관한 11,259만 줄의 속성이 포 함되어 있으며, 데이터에서 우리는 250만개의 노드와 1,182만개의 무방향 에지가 있는 협업 네트워크를 구성 하여 대규모 게임 내 협동 네트워크를 만듭니다. 연결 정도, 경로 길이, 클러스터링 및 소속 하위 컴포넌트의 크기 등 네트워크에 관한 수치를 통해 게임내 소셜 활동에 대한 이해를 높이고자 한다. 본 논문에서는 다음 의 두가지 특성을 중심으로 결론을 제시한다. 첫째, 네트워크 내에는 대규모로 연결된 2개(전체의 44% 및 2%)와 나머지의 파편화된 하위 컴포넌트로 구성 되어있다. 이 대규모 컴포넌트 중 작은 쪽은 한국 유저로만 구성되어 있다. 둘째, 컴포넌트 크기 별 평균 연결 거리와 군집화 계수, k-core를 확인함으로써 기타 다른 네 트워크 대비 이웃 간 연결이 강하면서 전체적으로는 비교적 멀리 떨어져 있음을 확인한다.

본 연구는 네트워크 이상 감지 및 예측을 위해 벡터 자기회귀(VAR) 모델의 사용을 비교 분석한다. VAR 모 델에 대한 간략한 개요를 제공하고 네트워크 이상 체크로 사용 가능한 두 가지 버전을 검토하며 두 종류의 VAR 모델을 통한 경험적인 평가를 제시한다. VAR-Filtered moving-common-AR 모델이 단일 노드 이상 감지 성능에서 우수하며, VAR-Adaptive Learning 버전은 몇 개의 노드 간 이상을 효과적으로 식별하는 데 특히 효 과적이며 두 가지 주요VAR 모델의 전반적인 성능 차이에 대한 근본적인 이유도 분석한다. 각 기술의 장단점 을 개요로 제공하고 성능 향상을 위한 제안도 제시하고자 한다.

PURPOSES : The number of snowfall and the amount of snowfall are gradually increasing, and due to the characteristics of Seoul, which has a lot of traffic, it is difficult to respond quickly with a snow removal method that relies on snow removal vehicles. Therefore, it is necessary to develop an IoT based eco-friendly snow removal system that can respond to unexpected heavy snow in winter. In this study, the low temperature operation and snow removal performance of the IoT road condition snow removal detector and the snow removal system using CNT and PCM are evaluated in the climatic environment chamber. METHODS : To make artificial snow, it consists of an climatic environment chamber that can simulate a low temperature environment and equipment that can supply compressed air and cold water. Depending on the usage characteristics of the climatic environment chamber, use an air-water type snow maker. In order to make artificial snow, wet temperature, which takes into account the actual air temperature and the amount of moisture in the air, acts as the most important variable and is suitable for making snow, below –1.5 ℃. The lower the water temperature, the easier it is to freeze, so the water source was continuously supplied at 0 ℃ to 4 ℃. One of the two different pipes is connected to the water tank to supply water, and the other pipe is connected to the compressor to supply high-pressure air. Water is dispersed by compressed air in the form of many small droplets. The sprayed microscopic water particles freeze quickly in the low temperature environmental climatic chamber air and naturally fall to the floor, forming snow. Based on the KS C IEC 60068-2-1 cold resistance test standard, an integrated environmental test procedure was prepared to apply to IoT-based snow removal systems and performance evaluation was performed accordingly. The IoT based eco-friendly snow removal system is needed to in winter, so visual check and inspect the operation at the climatic chamber before setting up it to the actual site. In addition, grid type equipment was manufactured for consistent and reliable snow removal performance evaluation under controlled environmental conditions. RESULTS : The IoT-based eco-friendly snow removal system normally carried out the task of acquiring data and images without damaging the appearance or freezing in a low temperature environment. It showed clear snow removal performance in areas where PCM and CNT heating technology were applied to the concrete slab. This experiment shows that normal snow removal tasks can be carried out in low temperature environments in winter. CONCLUSIONS : The integrated environmental test procedures and grid type evaluation equipment are applied to low temperature operation and snow removal performance evaluation of snow removal systems. In the climatic environment chamber, where low temperature environments can be simulated, artificial snow is created regardless of the season to derive quantitative experimental results on snow removal performance. PCM and CNT heating technology showed high snow removal performance. The system is expected to be applied to road site situations to preemptively respond to unexpected heavy snow in winter.

PURPOSES : The purpose of this study was to improve the performance of concrete pavements by decreasing measurement deviations using an Internet of Things (IoT)-based air content measurement device. METHODS : We calculated the properties of concrete which varied according to the air content. For a low measurement deviation, the concrete pavement performed according to the design standard. To confirm the difference in the performance of the concrete pavement for various air contents, we verified the change in the relative dynamic modulus according to the number of freeze–thaw cycles for each value of the air content. In addition, we analyzed the number of durability cracks according to the freeze–thaw cycles in the field. RESULTS : We confirmed that IoT-based measurement equipment improved the performance of pavements without changing their mixing designs or specifications. We confirmed that the performance of concrete pavements changed even with variations in air content within the range of quality standards. Using IoT-based air content management, we confirmed the reduction in concrete pavement durability cracks without changing the mixing design. CONCLUSIONS : We confirmed that IoT-based air-content management improved pavement performance. The feasibility of extending this concept to manage other concrete properties such as the chloride content should be acknowledged. Future research will require laboratory tests to understand the variation in concrete properties with varying air contents and to consider diverse load conditions.

Since the impact of COVID-19, the tourism and hospitality (T&H) practitioners have become increasingly aware of the crucial role of technology. The metaverse, which combines multiple emerging technologies, has become a hot topic that can take customers' experience in T&H to the next level. Previous research has already indicated that industrial practitioners should begin to consider business transformation to face the era of the metaverse. The metaverse is a continuum from the digital worlds to the physical worlds, with the convergence of physical and virtual worlds in the middle. Digital worlds include mirror worlds that simulate and reflect the real world and the virtual native, an innovative digital world. The digital twin has been mentioned as being created for destinations, hotels, and resorts, relying on the internet of things (IoT) as a crucial component of metaverse technology. However, previous studies have rarely explored the role of the IoT in the metaverse, particularly for T&H customers' metaverse experience. Therefore, this study aims to explore the role of the IoT in customers' metaverse experience in T&H and provide a clear picture for industrial practitioners to take steps into the metaverse. Exploratory research was adopted, including document analysis, literature review, and in-depth interviews with twelve international metaverse-related company experts. Moreover, this research adopted the thematic analysis technique to analyze the data; the theoretical bases include the Task-Technology Fit (TTF) and the components of metaverse as the lens and framework to develop this research. The findings uncovered three scenes of T&H metaverse experiences, including mirror scenes (that reflect the physical and real world in the digital worlds), convergent scenes (that combine the digital and real worlds), and virtual native scenes (that mainly create a whole new virtual scene but still connect to the real world). All of these scenes require IoT to connect the physical world and digital at different levels. Such as, mirror scenes strongly need digital twin techniques through IoT to enhance the authenticity and synchronicity of digital hotels or attractions to immerse guests. Under a convergent scene, connecting via IoT devices to display visitors' paths in the attractions simultaneously or a message board with IoT functionality for users’ social interactions simultaneously. In a virtual native museum, even though users stay in a whole new virtual world, IoT techniques can transfer users from the real world to the virtual world and make them feel physically present. The results provide practical implementations to integrate the IoT into T&H, increasing customers' metaverse experience and enhancing the creative and innovative aspects of the T&H experience.

PURPOSES : The purpose of this study was to improve the performance of concrete pavements by measuring the unit-water content with an Internet-of-Things (IoT)-based unit-water content measurement device at an increased precision compared with that of existing measuring equipment. METHODS : We calculated the properties of concrete that varied according to variations in the unit-water content. To confirm the change in the performance of concrete pavements, we compared and analyzed the fatigue cracking rate and international roughness index of concrete pavements at the 20-year point of public use according to the changes in properties using the Korea Pavement Research Program(KPRP). RESULTS : We confirmed that IoT-based measurement equipment can improve the performance of pavements without changing their mixing designs or specifications. We confirmed that the performance of the concrete pavements changed significantly, even with unit-water content variations within the range of quality standards. According to IoT-based unit-water content management, we confirmed that the performance of the concrete pavement (fatigue cracking rate and international roughness index) improved without changing the mixing design. CONCLUSIONS : We confirmed that by using IoT-based unit-water content management, pavement performance can be improved. It is necessary to consider whether the application of this concept to other concrete property management items, such as the chloride content, is possible. Considering the changes in concrete properties according to the unit-water content based on laboratory tests and considerations of various load conditions will be necessary for future research.