• Journal of the Korea institute for structural maintenance and inspection
• /
• 제27권6호
• /
• pp.79-85
• /
• 2023

Skid resistance pavement is an accessory to the road and is a facility for the safe driving of cars by increasing the skid resistance of road pavement. In particular, in bad weather conditions such as snow, rain, and black ice, the skid resistance performance of skid resistance pavement greatly affects the safety of road traffic and drivers. However, BPT(British Pendulum Tester) has a test area of only 0.009 m², making it difficult to represent the overall packaging surface. A reliable method of evaluating slip resistance performance is needed for maintaining non-slip packaging. In this study, the conventional BPT test and the skid resistance performance evaluation method of the PFT(Pavement Friction Tester) and µGT(Micro Grip Tester) tests were compared through guidelines and standard investigations and applied to the field skid resistance performance evaluation. In addition, skid resistance pavement with different skid resistance performance was installed at the test-bed and actual road demonstration sites to compare BPN(British Pendulum Number), SN(Skid Number), GN(Grip Number), and to derive correlations for each performance evaluation method. As a result of the experiment, SN and GN showed similar skid resistance performance, and the GN value was derived similar to BPN × 0.01.

• Journal of Internet of Things and Convergence
• /
• 제9권6호
• /
• pp.93-98
• /
• 2023

In paddy rice farming, water management is a critical task. To suppress weed emergence during the early stages of growth, fields are deeply flooded, and after transplantation, the water level is reduced to promote rooting and stimulate stem generation. Later, water is drained to prevent the production of sterile tillers. The adequacy of water supply is influenced by various factors such as field location, irrigation channels, soil conditions, and weather, requiring farmers to frequently check water levels and control the ingress and egress of water. This effort increases if the fields are scattered in remote locations. Automated irrigation systems have been considered to reduce labor and improve productivity. However, the net income from rice production in 2022 was about KRW 320,000/10a on average, making it financially unfeasible to implement high-cost devices or construct new infrastructure. This study focused on developing an IoT-Based irrigation valve that can be easily integrated into existing agricultural infrastructure without additional construction. The research was carried out in three main areas: Firstly, an irrigation valve was designed for quick and easy installation on existing agricultural pipes. Secondly, a power circuit was developed to connect a low-power Cat M1 communication modem with an Arduino Nano board for remote operation. Thirdly, a cloud-based platform was used to set up a server and database environment and create a web interface that users can easily access.

• Korean Journal of Remote Sensing
• /
• 제39권5_2호
• /
• pp.785-798
• /
• 2023

Recently, forest fires have become frequent due to climate change, and the size of forest fires is also increasing. Forest fires in Korea continue to cause more than 100 ha of forest fire damage every year. It was found that 90% of the large-scale wildfires that occurred in Gangwon-do over the past five years were concentrated in the east coast area. The east coast area has a climate vulnerable to forest fires such as dry air and intermediate wind, and forest conditions of coniferous forests. In this regard, studies related to various forest fire analysis, such as predicting the risk of forest fires and calculating the risk of forest fires, are being promoted. There are many studies related to risk analysis for forest areas in consideration of weather and forest-related factors, but studies that have conducted risk analysis for forest-friendly areas are still insufficient. Management of forest adjacent areas is important for the protection of human life and property. Forest-adjacent houses and facilities are greatly threatened by forest fires. Therefore, in this study, a grid-based forest fire-related disaster risk map was created using factors affected by forest-neighboring areas using national branch numbers, and differences in risk ratings were compared for forest areas and areas adjacent to forests based on Gangneung forest fire cases.

• Journal of Korean Society of Rural Planning
• /
• 제30권1호
• /
• pp.15-31
• /
• 2024

The study primarily aims to examine the characteristics of the transition from natural landscape to modern agricultural landscape on the Daesan plain in Dong-myeon, Changwon-si, in the lower reaches of the Nakdong River. The periods covered in the transition include the late Joseon Dynasty, the early Japanese colonial period, and the late Japanese colonial period. The study concluded the following: It was found that the Daesan Plain used to function as a hydrophilic landscape before it formed into a rural landscape. This is characterized by the various water resources in the Plain, primarily by the Nakdong River, with its back marsh tributaries, the Junam Reservoir and Jucheon. To achieve its recent form, the Daesan Plain was subjected to human trial and error. Through installation of irrigation facilities such as embankments and sluices, the irregularly-shaped wetlands were transformed into large-scale farmlands while the same irrigation facilities underwent constant renovation to permanently stabilize the rural landscape. These processes of transformation were similarly a product of typical colonial expropriation. During the Japanese colonial period, Japanese capitalists initiated the construction of private farms which led to the national land development policy by the Governor-General of Korea. These landscape changes are indicative of resource capitalism depicted by the expansion of agricultural production value by the application of resource capital to undeveloped natural space for economic viability. As a result, the hierarchical structure was magnified resulting to the exacerbation of community and economic structural imbalances which presents an alternative yet related perspective to the evolution of landscapes during the Japanese colonial period. In addition, considering Daesan Plain's vulnerability to changing weather conditions, natural processes have also been a factor to its landscape transformation. Such occurrences endanger the sustainability of the area as when floods inundate cultivated lands and render them unstable, endangering residents, as well as the harvests. In conclusion, the Daesan Plain originally took the form of a hydrophilic landscape and started significantly evolving into a rural landscape since the Japanese colonial period. Human-induced land development and geophysical processes significantly impacted this transformation which also exemplifies the several ways of how undeveloped natural landscapes turn into mechanized and capitalized rural landscapes by colonial resource capitalism and development policies.

• Economic and Environmental Geology
• /
• 제57권2호
• /
• pp.107-117
• /
• 2024

The objective of this study is to estimate riverbed fluctuations and the volume of aggregate extraction attributable to climate change. Rainfall-runoff modeling, utilizing the SWAT model based on climate change scenarios, as well as long-term riverbed fluctuation modeling, employing the HEC-RAS model, were conducted for the Nonsan River basin. The analysis of rainfall-runoff and sediment transport under the SSP5-8.5 scenario for the early part of the future indicates that differences in annual precipitation may exceed 600 mm, resulting in a corresponding variation in the basin's sediment discharge by more than 30,000 tons per year. Additionally, long-term riverbed fluctuation modeling of the lower reaches of the Nonsan Stream has identified a potential aggregate extraction area. It is estimated that aggregate extraction could be feasible within a 2.455 km stretch upstream, approximately 4.6 to 6.9 km from the confluence with the Geum River. These findings suggest that the risk of climate crises, such as extreme rainfall or droughts, could increase due to abnormal weather conditions, and the increase in variability could affect long-term aggregate extraction. Therefore, it is considered important to take into account the impact of climate change in future long-term aggregate extraction planning and policy formulation.

• Atmosphere
• /
• 제34권2호
• /
• pp.123-138
• /
• 2024

Using 18 multi-model-based a Shared Socioeconomic Pathway (SSP) and Representative Concentration Pathways (RCP) climate change scenarios, future changes in temperature and warmth index on the Korean Peninsula in the 21st century (2011~2100) were analyzed. In the analysis of the current climate (1981~2010), the ensemble averaged model results were found to reproduce the observed average values and spatial patterns of temperature and warmth index similarly well. In the future climate projections, temperature and warmth index are expected to rise in the 21st century compared to the current climate. They go further into the future and the higher carbon scenario (SSP5-8.5), the larger the increase. In the 21st century, in the low-carbon scenario (SSP1-2.6), temperature and warmth index are expected to rise by about 2.5℃ and 24.6%, respectively, compared to the present, while in the high-carbon scenario, they are expected to rise by about 6.2℃ and 63.9%, respectively. It was analyzed that reducing carbon emissions could contribute to reducing the increase in temperature and warmth index. The increase in the warmth index due to climate change can be positively analyzed to indicate that the effective heat required for plant growth on the Korean Peninsula will be stably secured. However, it is necessary to comprehensively consider negative aspects such as changes in growth conditions during the plant growth period, increase in extreme weather such as abnormally high temperatures, and decrease in plant diversity. This study can be used as basic scientific information for adapting to climate change and preparing response measures.

• Journal of Korea Society of Industrial Information Systems
• /
• 제29권4호
• /
• pp.1-11
• /
• 2024

Bridges crack and become damaged due to age and external factors such as earthquakes, lack of maintenance, and weather conditions. With the number of aging bridge on the rise, lack of maintenance can lead to a decrease in safety, resulting in structural defects and collapse. To prevent these problems and reduce maintenance costs, a system that can monitor the condition of bridge and respond quickly is needed. To this end, existing research has proposed artificial intelligence model that use sensor data to identify the location and extent of cracks. However, existing research does not use data from actual bridge to determine the performance of the model, but rather creates the shape of the bridge through simulation to acquire data and use it for training, which does not reflect the actual bridge environment. In this paper, we propose a bridge safety determination edge AI model that detects bridge abnormalities based on artificial intelligence by utilizing acceleration data from bridge occurring in the field. To this end, we newly defined filtering rules for extracting valid data from acceleration data and constructed a model to apply them. We also evaluated the performance of the proposed bridge safety determination edge AI model based on data collected in the field. The results showed that the F1-Score was up to 0.9565, confirming that it is possible to determine safety using data from real bridge, and that rules that generate similar data patterns to real impact data perform better.

• Journal of the Society of Disaster Information
• /
• 제20권3호
• /
• pp.484-499
• /
• 2024

Purpose: Recently, due to the aging of safety facilities in national industrial complexes, there has been an increase in the frequency and scale of safety accidents, highlighting the need for a shift toward a prevention-centered disaster management paradigm and the establishment of a digital safety network. In response, this study aims to provide an information system that supports more rapid and precise decision-making during disasters by utilizing digital twin-based integrated control technology to predict the spread of hazardous substances, trace the origin of accidents, and offer safe evacuation routes. Method: We considered various simulation results, such as surface diffusion, upper-level diffusion, and combined diffusion, based on the actual characteristics of hazardous substances and weather conditions, addressing the limitations of previous studies. Additionally, we designed an integrated management system to minimize the limitations of spatiotemporal monitoring by utilizing an IoT sensor-based backtracking model to predict leakage points of hazardous substances in spatiotemporal blind spots. Results: We selected two pilot companies in the Gumi Industrial Complex and installed IoT sensors. Then, we operated a living lab by establishing an integrated management system that provides services such as prediction of hazardous substance dispersion, traceback, AI-based leakage prediction, and evacuation information guidance, all based on digital twin technology within the industrial complex. Conclusion: Taking into account the limitations of previous research, we used digital twin-based AI analysis to predict hazardous chemical leaks, detect leakage accidents, and forecast three-dimensional compound dispersion and traceback diffusion.

• Journal of Korean Society of Coastal and Ocean Engineers
• /
• 제36권5호
• /
• pp.185-198
• /
• 2024

Tidal power is a technology that generates electricity by utilizing tidal current energy, and in recent years, with the advancement of technology, it has reached the stage of real sea performance test. However, in the case of Korea, there is a lack of construction experience and equipment, and work in fast flows such as the Uldolmok region involves various risk factors. In order to establish measures to reduce these risk factors, Korea's Occupational Safety and Health Act recommends performing a risk assessment to identify and manage risk factors that may occur during work in advance. Risk assessment is a process aimed at identifying and evaluating potential risk factors that may arise during work, with the goal of minimizing losses caused by accidents. Therefore, in this study, a risk assessment was conducted to identify risk factors that may occur during offshore O&M work of the 1 MW tidal current energy converter and to ensure the safety of workers and the environment. A total of 60 risk factors were identified, including marine and weather conditions, equipment and personnel, and work environments, and a qualitative risk assessment was conducted three times based on the judgment of several field experts.

• Journal of the Korea Society of Computer and Information
• /
• 제29권10호
• /
• pp.69-75
• /
• 2024

Noise caused by adverse weather conditions in data collected during autonomous driving can lead to object recognition errors, potentially resulting in critical accidents. While this risk is widely acknowledged, there is a lack of research that quantitatively and systematically analyzes it. Therefore, this study aims to examine and quantify the extent to which noise affects object detection in autonomous driving environments. To this end, we utilized the YOLO v5 model trained on unprocessed datasets. The test data were divided into noise ratios of 0% (Original), 20%, 40%, 60%, and 80%, and the detection results were evaluated by constructing a Confusion Matrix. Experimental results show that as the noise ratio increases, the True Positive (TP) rate decreases, and the F1-score also significantly drops across all noise levels, specifically from 0.69 to 0.47, 0.29, 0.18, and 0.14. These findings are expected to contribute to enhancing the stability of autonomous driving technology. Future research will focus on collecting real datasets that include naturally occurring noise and developing more effective noise removal techniques.