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Current Status and Outlook of Intelligent Transport Systems (ITS) Implementation in Korea Current Status and Outlook of Intelligent Transport Systems (ITS) Implementation in Korea ▲ Senior Researcher Yoon Young-min, Construction Test & Certification Department, KICT Prologue Intelligent Transport Systems (ITS), according to Article 2 (Definition) of the National Transport System Efficiency Act, are transportation systems that aim to scientifically advance and automate the operation and management of the transportation system, enhancing both the efficiency and safety of transportation. This is achieved by developing and utilizing advanced transportation technologies, including electronic controls and communication, for vehicles and transport facilities. ITS encompasses a number of service sectors, including traffic management, public transportation, electronic payments, traffic information dissemination, supplementary traffic information provision, intelligent vehicles and roads, and freight transportation. The introduction of ITS is motivated by the growing challenges of traffic congestion and accidents caused by the increasing number of automobiles. Despite continuous efforts to expand existing roads and construct new ones to address these issues, the complexity of diverse traffic environments has created limitations. Consequently, there is a growing emphasis on enhancing efficiency through the advancement of the management and operation methods of existing facilities. Introduction Stage (1993-2004) A representative project that marked the initiation of Intelligent Transport Systems (ITS) in Korea was the Freeway Traffic Management System (FTMS), launched in 1994. This system, equipped with CCTV, roadside display boards, and vehicle detection devices on major highways, was implemented to manage traffic flow. It operates through stages of information collection, processing, and dissemination. In 1997, the city of Gwacheon in Gyeonggi Province was designated as an ITS pilot city, leading the way for urban ITS projects. Concurrently, a pilot project for building ITS was initiated on major national roads. Based on these initiatives, Seoul hosted the 5th ITS World Congress in 1998. In 1999, the "Traffic System Efficiency Act" was made law, laying the groundwork for a national, decade-long ITS master plan. In 2001, the Korea Expressway Corporation built the Electronic Toll Collection System (ETCS) pilot project, introducing the Hi-pass automatic toll collection system. By 2003, ITS Model Cities (Jeonju, Daejeon, Jeju) were selected, focusing on cities with World Cup stadiums, to further advance ITS projects. Growth and Expansion Stage (2005-2012) During this period, substantial ITS projects were launched, building on the groundwork and institutionalization established in the introduction stage. In 2005, starting with the Sadang-Suwon section, the Bus Information System (BIS), which aimed at enhancing the convenience of public transportation, was implemented and expanded in metropolitan cities at the local government level. In 2006, ITS centers were established in five local Construction and Management Administrations (Seoul, Wonju, Daejeon, Iksan, Busan) for collecting and providing traffic information on national roads. In 2007, the nationwide implementation of the Hi-pass system on highways was initiated. In 2009, to strengthen the integration of rapidly evolving information and communications technologies with the transportation system, the "Traffic System Efficiency Act" was entirely revised, leading to the enactment of the "National Integrated Traffic System Efficiency Act." This laid the groundwork for the expansion of ITS construction projects across local governments nationwide. In 2010, 12 years after it was hosted in Seoul in 1998, Busan hosted the 17th ITS World Congress, showcasing Korea's ITS technology on the global stage and securing international competitiveness. Maturity Stage (2013-2022) In the implementation strategy for "ITS Master Plan 2020," which is a roadmap to the successful implementation plan of ITS projects up to 2020, the most significant change compared to the previous plan (2010) lies in its emphasis on services. Specifically, there has been a shift from the post-incident management of congestion and accidents to proactive prevention. Another noteworthy transformation is the transition of the public sector-led traffic information provision service into a collaborative framework encompassing the public and the private sector. The widespread adoption of advanced IT devices such as smartphones based on 4G (LTE) technology by the private sector led to the generation of real-time traffic information for nationwide roads. As a result, the accessibility of traffic information for service users significantly improved, moving beyond traditional sources like road signs, TV, and radio to smartphone apps. In August 2014, the MOLIT devised an ITS innovation plan that separated the roles of the public and private sectors to maximize the efficiency and effectiveness of investments in collecting and providing transportation and traffic information. Based on this, an MOU on collaboration in transportation information provision was signed between the government and private companies. As result, the installation of communication information collection devices, such as vehicle detectors, was reduced on major highways and national roads, while the deployment of safety information collection equipment, such as emergent situation detection systems, was expanded. In 2014, the pilot project for the next-generation Intelligent Transport System (Cooperative ITS or C-ITS), incorporating technologies that included Wave communications technology, GPS, precision maps, and security technology, was commenced on sections of highways and national roads between Daejeon and Sejong. Starting in 2018, demonstration projects were implemented in Seoul, Jeju, Ulsan, Gwangju, and other locations. The primary distinction between conventional ITS and C-ITS lies in their communication methods. While ITS employs a simplex communications approach, collecting information at a control center for processing and dissemination, C-ITS utilizes Vehicle-to-Everything (V2X) communications. This full duplex communications approach involves the real-time exchange of information between vehicles and vehicles (V2V), vehicles and pedestrians (V2P), and vehicles and infrastructure (V2I). This enables the proactive sharing of traffic and safety information, allowing for both a preventive and responsive approach to congestion and accidents. C-ITS has evolved as a key technology for ensuring the stability of future autonomous vehicles through autonomous collaborative driving. Outlook on the Present and Future (2023-2030) In recent years, several local governments have applied a number of advanced information technologies to various ITS projects, including artificial intelligence (AI), big data, the Internet of Things (IoT), edge computing, and digital twin, through the government subsidiary on ITS projects. Notably, the most actively pursued project in the field of ITS solutions is the Smart Intersection Traffic Management System, which monitors intersection congestion levels in real time, dramatically improving public safety and traffic flow, securing the golden hour for emergency patients, and ensuring the safe operation of emergency vehicles. In 2025, Suwon is set to host the ITS Asia-Pacific Conference, which will be followed by Gangneung hosting the ITS World Congress in 2026. These events are expected to have diverse practical impact, which will include vitalizing Korea's ITS industry to lead the global mobility market and enhancing the competitiveness of Korean companies in overseas markets. "ITS Master Plan 2030," which maps the future of ITS up to 2030, envisions the realization of a digital road system supporting eco-friendly advanced mobility services. It sets goals in four areas: safety, efficiency, innovation, and convenience. Over the past 30 years, from 1993 to the present, Korea's ITS has grown consistently, adapting to a rapidly changing road and traffic environment and advancements in IT. However, the ITS environment needs to evolve to adapt to a number of changes: social shifts, including the recent ongoing population decline, aging society and increasing number of single-person households, growing leisure time, sluggish economic growth, climate change, and transition to a carbon-neutral era. ――――――――――――――――― 1. This is an annual general meeting of the ITS International Organization, a union of ITS implementation organizations from each country to exchange information and seek development regarding ITS, and a gathering to discuss the current status and case studies of member countries and exchange information on ITS systems and applications, as well as technical, structural, and institutional issues around ITS implementation. 2. Various services and means of transportation, contributing to the convenient movement of people and objects ――――――――――――――――― Reference • 2022 Roadwork Manual, Ministry of Land, Infrastructure and Transport • ITS Master Plan 2010, 2020, 2030, Ministry of Land, Infrastructure and Transport Construction Test & Certification Department Date2023-12-22 Hit 373
Proposed Analysis Approach for Spillover Effects of Large-Scale Public Projects at the Post-Assessment Stage Proposed Analysis Approach for Spillover Effects of Large-Scale Public Projects at the Post-Assessment Stage ▲ Senior Researcher Cha Yong-woon, Department of Construction Policy Research, Background and Purpose The 2023 SOC budget of the Ministry of Land, Infrastructure and Transport (MOLIT) was KRW 19.9 trillion, a 10% decrease from the previous year. In previous years, the budget had seen continuous increases, from KRW 17.3 trillion in 2017 to KRW 22.1 trillion in 2022 (Korea Policy Briefing 2022). The total budget, including budgets from other ministries and local governments, for 2023, is approximately KRW 25 trillion. Within this, the budget for large-scale government projects, such as roads and railways, is around KRW 15 trillion, with substantial national finances being invested annually. To ensure the appropriate allocation of funds and analyze the performance of such large-scale government projects, a system has been put in place. This system involves a pre-assessment (preliminary feasibility study and feasibility assessment) to examine a project’s economic feasibility, as well as a post-assessment that compares the planned outcomes with the actual execution, and analyzes the effects of the project. However, despite several improvements since its introduction in 2000, the preliminary feasibility study stage (referred to as "Ye-ta") has faced criticism for judging the feasibility of projects based only on economic aspects, without considering policy aspects. To address this concern, policy-related items were added to Ye-ta from 2019 (Inter-Agency Joint Task Force, 2019). Nevertheless, despite the emphasis on the importance of policy considerations in the preliminary feasibility study, there is a limitation in assessing this aspect due to a lack of a specific analysis methodology for policy effect indicators. In practice, elements such as "indirect employment effects" and "improvement in living conditions" among policy considerations have often been recognized as unreliable in actual preliminary feasibility studies, due to inaccurate data and methodology application (Lee, Seung-heon, 2021). Meanwhile, a post-assessment evaluates project performance (cost, schedule, safety, and re-construction) within 60 days after project completion, project efficiency (demand, B/C or Benefit-Cost Ratio, property assessment) within five years, and spillover effects (regional economy, environment, safety, etc.). In this process, the demand and B/C are measured in ways that mostly adhere to the guidelines outlined in the preliminary feasibility study, facilitating a relatively straightforward comparison with the pre-assessment results. On the other hand, although the spillover effect indicators are subdivided into regional economy, environment, safety, etc., it has been pointed out that the lack of specific analysis methods hinders their practical utility (Cha Yong-woon, 2022a). The current post-assessment task manual (Korea Institute of Civil Engineering and Building Technology, 2015) provides very brief information on the analysis methods and application strategies for spillover effects, making it insufficient for effective utilization in new, similar projects, which is the essential purpose of post-assessment. Thus far, the perspective on the performance of large-scale government projects has primarily focused on economic aspects, such as costs and schedules. However, as mentioned earlier, although it was institutionalized due to the emphasis on policy and spillover aspects, there is a lack of specific methods and formalization. In this article, we aim to propose indicators and analytical methodologies for assessing spillover and policy effects in the post-assessment stage of large-scale government projects. We also seek to examine their practical applicability through case studies, and suggest approaches to feeding this information back into the preliminary assessment stage. Proposed Analysis Approach for Policy Effects Currently, the preliminary feasibility study focuses on measurable benefits, and while there are policy effect indicators, there is a lack of systematic analysis. Indicators that are particularly challenging to analyze in the policy aspect of the preliminary feasibility study include "Indirect employment" and "Improvement of living conditions." Acquiring reliable data is essential to quantitatively estimate these effects at the project planning stage. Traditionally, the indicators being utilized are publicly disclosed by analyzing and converting relevant data into monetary terms based on past cases. However, policy effect indicators, such as indirect employment and improvement of living conditions, have limitations when it comes to data collection and analysis based on past cases, unlike economic feasibility analysis indicators. Furthermore, among the post-assessment spillover effect indicators, there are indicators for the local economy, but there is a lack of detailed analysis methods in the post-assessment manual. However, as the local economy indicators are linked to the feasibility study indicators, and the assessment indicators, called spillover effects, are connected to the policy effect indicators, it was considered possible to relate to them accordingly. In particular, the purpose of a post-assessment is to enhance the efficiency of public construction projects by utilizing post-assessment results when pursuing similar projects. Therefore, by linking them with the preliminary feasibility study items and analyzing policy aspects in the post-assessment phase, the utility of post-assessment results can be expected to increase. The existing spillover effect indicators in a post-assessment were employment effects and improvement of living conditions in the preliminary feasibility study (Figure 1). To be more specific, new indicators for employment effects and the quality of employment are introduced. The employment effects are linked with the employment during the project and operation periods outlined in the preliminary feasibility study. The proposed analysis approach includes the application of the Inter-Regional Input-Output (IRIO) Model, an industry-related model in the preliminary feasibility study guidelines, and the analysis matrix for the quality of employment effects. Next, for indicators that are difficult to analyze in the preliminary feasibility study, such as indirect employment effects and improvement of living conditions, a causal inference methodology capable of quantitative analysis was considered. In the planning stage, estimating causal inference is challenging due to data collection limitations. However, in the post-assessment stage, data collection is possible, as the project has concluded. Therefore, the Difference-in-Differences (DID) method was deemed to be suitable. DID involves distinguishing between experimental and control groups before and after a specific event or implementation of a policy or project, and comparing the differences between them. For instance, it is considered that comparing employment effects and improvement of living conditions before and after the construction project allows for an estimation of the causal effects of road construction. Finally, while maintaining environmental and safety indicators, it was intended to utilize post-environmental impact assessments and a traffic accident analysis system. Case Application To review the utility of the proposed new indicators, a road project for which a post-assessment was conducted was selected, and the case was applied. The "Songsan Industrial Complex Access Road" was selected as a case, based on considerations such as data collection feasibility and post-assessment completion. This project, which had a total budget of approximately KRW 150 billion, aimed to expand Provincial Road No. 633 and Country Road No. 5 connecting Dangjin IC and Songsan Industrial Complex. The project is situated in areas connecting Dangjin to Daejeon, Dangjin to Cheonan, and the West Coast Expressway, contributing to the efficient handling of traffic and logistics volume, as well as the dispersion of traffic volume on National Road No. 38, thereby revitalizing the local economy. Due to the constraints of this text, we aim to focus on the results of the DID analysis in this article. Firstly, the impact area was defined by selecting the eups, myuns, and dongs within a 5 km radius of the project route and connecting route (National Road 38) among the 29 eups, myuns, and dongs in Seosan and Dangjin, where the project is located. The remaining 20 eups, myuns, and dongs were defined as the control group. The period variable was represented by a dummy variable, with 1 for the post-opening year of 2020 and 0 for the pre-opening year of 2015. Finally, data for the number of businesses, employees, and total wages for each eup, myun, and dong during the pre-and post-opening periods were collected from the "National Business Survey" for each relevant year. The DID model for analyzing the indirect employment effect of the Songsan Industrial Complex Access Road construction is represented by Equation 1, where the dependent variables are the number of businesses and employees. The results indicate a statistically significant increase of 742 in the average number of businesses in the eups, myuns, and dongs of the impact area (within 5 km) with a p-value of 0.10. While the average number of new jobs created in the eups, myuns, and dongs of the impact area (within 5 km) increased by 1,783, this change was not statistically significant. Additionally, the DID model for analyzing the effect of productivity according to the improvement of living conditions is represented by Equation 2, with the dependent variable Yit as total wages. It showed a statistically significant increase of 54.39 billion won in the average total wages in the eups, myuns, and dongs of the impact area (within 5 km) with a p-value of 0.10. This implies an increase in labor productivity due to the construction of the Songsan Industrial Complex Access Road. In summary, positive spillover effects resulting from the construction of the Songsan Industrial Complex Access Road were confirmed. However, it is deemed necessary to perform additional scrutiny to ensure statistical significance. This involves assessing the adequacy of data according to the analysis period, the validity of the analysis variables selected, and hypotheses related to setting of the impact area. Conclusion and Future Research It is undeniable that the performance management of large-scale national projects has been approached from an economic perspective. However, the recent emphasis on policy outcomes and spillover effects has led to improvements in the system, particularly in analyzing the distribution and effects of national finances from the perspective of national balanced development. While the institutional framework for this shift has been established, there has been a lack of methodology to analyze the actual effects of large-scale national projects on the citizens, who are the actual users, and whether the original objectives of the projects have been properly realized. In this article, with the goal of enhancing the utility of a post-assessment, which is its inherent purpose, we proposed improvements to spillover effect analysis indicators that can be linked with pre-assessment. While the spillover effects in post-assessment were limited to the local economy, we subcategorized these indicators and linked them with the indicators from the preliminary feasibility study. Specifically, to quantitatively analyze indirect employment effects and improvement in living conditions indicators that are challenging to analyze in pre-assessment, we proposed the use of the causal inference methodology, Difference in Differences (DID). To assess the utility of the proposed DID, we performed a case analysis focusing on the Songsan Industrial Complex entrance road construction project, confirming positive spillover effects on the increase in the number of businesses and productivity in the local community. Although the proposed indicators and methodology have not been institutionalized yet, the Construction Project Post-Assessment Center, with which I am affiliated, is conducting additional case applications. It is expected that ongoing research will contribute to the efficient execution of public projects. On the other hand, the cost and schedule performance of large-scale public projects in Korea is very poor. In fact, as shown in Figure 2, the construction cost of large-scale public projects of KRW 50 billion or more in Korea has increased by an average of about 24% since 2000 (including escalation), and the schedule has been delayed by about 51% (Cha Yong-woon 2022b). Even in recent years, the same pattern has been observed in construction projects, and it seems to be a problem that cannot be solved through the introduction of the latest technology. Some factors include project execution for political reasons, long-term continuous construction leading to a contract extension, indirect costs of a contract extension, and finally, human optimism bias. To enhance the efficiency of large-scale public projects funded by taxpayers, efforts to eliminate external influencing factors need to be made by politicians, public officials, and researchers. However, it is worth noting that this pattern is not unique to Korea, as similar patterns can be observed globally (Bent Flyvbjerg et al., 2003). ――――――――――――――――― 1. Data source: 746 construction projects selected by the research team through the construction project information system and various reports ――――――――――――――――― References • Preliminary Feasibility Study System Reform Plan, Jointly Proposed by Relevant ministries (2019) • Ministry of Land, Infrastructure and Transport (2023), “2023 Ministry of Land, Infrastructure and Transport Budget Plan Press release, Korea Policy Briefing • Lee Seung-heon (2021), Research on Policy Effect Application of Government Finance Investment Projects, Research Report of Public Investment Management Center, Korea Development Institute (KDI) • Cha Yong-woon (2022a), Derivation of Revisions to Construction Post-Assessment Implementation Manual Revision, The Korea Academia-Industrial Cooperation Society Spring Conference Papers, pp.1011-1012 • Cha Yong-woon (2022b), Development of Multi-attribute Model for Construction Performance Diagnosis, Korea Institute of Civil Engineering and Building Technology, No-fear Research Report (Research on Advancement of Construction Management Research: KICT 20220150-001) • Korea Institute of Civil Engineering and Building Technology (2015), Construction Post-Assessment Implementation Manual and Utilization Guidelines, Ministry of Land, Infrastructure and Transport • Bent Flyvbjerg, Nils Bruzelius, Werner Bothengatter(2003), Megaprojects and Risk: An Anatomy of Ambition, Cambridge University Press, Cambridge, UK, https://doi.org/10.1017/CBO9781107050891 Department of Construction Policy Research Date2023-12-22 Hit 400
Inundation and Flood Risk Assessment Using Rainfall Radar Technology Inundation and Flood Risk Assessment Using Rainfall Radar Technology ▲ Senior Researcher Kang Na-rae, Department of Hydro Science and Engineering Research, KICT Prologue Recently, heavy rainfall events have become more frequent. In urban areas, heavy rains are characterized by their sudden and localized nature, resulting in a rise in human casualties and property damage. Urban areas have seen a surge in flood damage due to extreme weather events, such as localized torrential rainfalls and typhoons. Various media outlets have pointed to climate change as the cause, and have warned of the potential for more severe damage in the future. Additionally, there is growing concern as the scale of flooding in rivers and streams in the middle and upper reaches, as well as in small rivers, is gradually increasing. Furthermore, flood magnitudes are progressively increasing in the upper reaches and small streams of rivers, beyond the major rivers where flood forecasts are being carried out, leading to heightened concerns. In South Korea, flood forecasting is carried out to reduce flood damage and enable early responses based on meteorological and river conditions. Currently, these forecasts focus primarily on Korea's major rivers, where the significance of flooding is high, and observational data is collected. As such, there is a need to establish a comprehensive nationwide flood forecasting system that covers areas for which monitoring or sufficient measurement data are lacking. These areas include small and medium-sized rivers and other bodies of water, for which flood forecast information cannot currently be provided. This is essential to address the existing information gaps and deliver precise flood forecast information. The water levels of small and medium-sized rivers (and other bodies of water) are prone to experience abrupt changes within a short timeframe. This is because these rivers have the characteristic of experiencing rapid increases in water levels due to the brief time it takes for precipitation from the upstream areas to accumulate in the downstream of the rivers. It is thus crucial to focus on early forecasting of water levels, starting from the initial stages of rainfall before rapid increases occur, and to promptly gather on-site information to facilitate swift evacuations. Furthermore, in urban areas, floods triggered by localized torrential rainfalls occur suddenly and frequently in terms of both time and space, leading to increased risk to human lives and property damage. Ultimately, successful flood management in small and medium-sized rivers and urban areas hinges on how quickly observations can be conducted, and the level of detail of such observations. For this reason, research into the utilization of rainfall radar technology for rainfall and flood prediction and monitoring is actively underway. Risk Prediction Based on Rainfall Radar Rainfall radar can monitor rainfall events in real time over a wide area, and can detect rainfall fields passing through ungauged watersheds, which existing ground rain gauge observation networks cannot provide. Rainfall radar makes it possible to identify areas in which heavy rain is falling by imaging the distribution and movement of rainfall. Although it is possible to roughly identify areas where it is raining with rainfall radar, it doesn't necessarily mean that the information is consistent with whether a disaster has occurred in those areas. Most of the research conducted to date has focused primarily on the amount of rainfall, which is the dynamic factor, at the watershed scale, to assess flood risk. However, to accurately predict flood disasters, it is necessary not only to figure out the amount of rainfall but also to understand in what direction the rain that has fallen changes or escalates the situation due to the surrounding conditions, such as land conditions, land use, slope (static factors), etc. (Figure 1). The Japan Meteorological Agency has introduced a "risk index" system based on rainfall radar to provide comprehensive risk information nationwide that covers all areas, which is highly correlated with disaster occurrences, instead of relying solely on conventional rainfall-centered flood risk prediction. This system doesn't focus only on the amount of rainfall, but also pays attention to how rain that has fallen changes the situation due to potential environmental factors related to disaster occurrence, such as land conditions. It models processes like rainfall infiltration into the ground and river runoff. Through this approach, it quantifies the risk levels for each type of disaster and provides a "risk index" that allows the visual tracking of changes. As a result, the system has significantly improved the precision of forecasts of floods caused by heavy rain, and increased the relevance compared to conventional rainfall-based predictions The purpose of this text is to provide a brief introduction to an index that can precisely predict the risks of flood and inundation in urban and small to medium-sized river watersheds using grid-based observed and forecasted rainfall data generated from the rainfall radar observation network currently under development in Korea. Inundation Risk Index The Inundation Risk Index is an indicator used to assess the increase in flood risk due to heavy rainfall in a short timeframe. It indexes the increase in flooding risk by calculating how much rainfall has been accumulated and retained on the surface of the earth, taking into account the ground cover, geology, and topographic slope. The entire country is divided into a grid with a resolution of 1 km, and two types of tank models are used for each area to quantify the level of risk, considering surface cover conditions, geology, and terrain slope (Figure 2). The Inundation Risk Index primarily targets disasters in the form of inland water flooding in urban areas. However, it can be applied across the entire country, and offers a reasonable degree of precision in practical way because it doesn't require detailed input information about drainage facilities. Flood Risk Index The Flood Risk Index is an indicator used to assess the extent to which flood risk at downstream locations increases due to rainfall in the upstream region of a river. It quantifies this increase in flood risk by calculating the amount of rainfall that enters arbitrary rivers and points within local rivers using a grid with a resolution of 1 km. As depicted in Figure 3, this calculation takes into account the processes through which rainfall in the upstream area either infiltrates the surface or flows underground and eventually contributes to the river's runoff (runoff process). It also considers the subsequent flow of water downstream (run-of-river process). These calculations are based on nationwide river flow patterns, river basins, geography (topography/geology), and land use information. The Flood Risk Index allows for the establishment of a response relationship regarding the occurrence of flood events based on past flood disaster cases spanning several years. It can also provide forecasts for several hours ahead using prediction data, and can be applied to all rivers nationwide, including those where water levels and flow rates are not monitored. Utilization of Inundation and Flood Risk Indices The two indices introduced earlier are highly correlated with disaster response. However, they represent relative risks, and it is not possible to directly assess the likelihood of disaster occurrence using these index values alone. The assessment of the likelihood of disaster occurrence needs to be compared to established "criteria" based on past disaster records. This comparison ultimately influences the criteria when setting them based on past disasters. Therefore, it is believed that using the index values in conjunction with the judgment results based on criteria such as alerts, rather than relying solely on the index values themselves, can provide valuable information. The flood and inundation prediction technology based on rainfall radar introduced herein thus far has allowed for a more precise delineation of flood-prone areas and an expansion of flood information coverage to small river basins and urban areas. Providing flood information for ungauged watersheds is expected to contribute to the safety of local residents. Department of Hydro Science and Engineering Research Date2023-10-11 Hit 484
Recent Trends in Artificial Intelligence Research for Facility Maintenance and Management Recent Trends in Artificial Intelligence Research for Facility Maintenance and Management ▲ Senior Researcher Won Ji-sun, Department of Future & Smart Construction Research, KICT Prologue The global artificial intelligence (AI) market in the construction sector is predicted to grow at an average annual rate of 35%, reaching KRW 2.33 trillion by 2023 (Market Research Future, 2020). At the same time, the Korean AI market is anticipated to reach KRW 1.9 trillion by 2025, with an average annual growth rate of 15.1% for five years from 2021 (IDC Korea, 2022). In recent times, the construction industry has adopted or has been actively considering adopting various AI technologies across the design, construction, and maintenance phases. The adoption of AI technologies has shown positive effects in the construction industry, including shortened construction durations, cost savings, improved safety, and enhanced quality (Lee, 2020). The adoption and utilization of AI technology are recognized as essential strategies, not optional choices, for enhancing corporate competitiveness. At the national level, there is a need for research strategies and direction-setting in the field of AI technology that align with the role of the public sector in securing the competitiveness of AI technology in construction. This article aims to introduce a portion of the research conducted (Won et al., 2022) in the field of future AI technology for facility maintenance, focusing on numerical data and case studies, to help establish research directions and preparations. AI Research Trends Seen Through Numbers Over the past five years (2016-2021), I've analyzed a total of 33 documents, including research papers and reports, related to AI technology development in the field of facilities maintenance and management. During the document collection, basic search keywords, such as "artificial intelligence," "maintenance," "machine learning," "deep learning," and "convolutional neural network," as well as various model names commonly employed in research, were used. I've analyzed research trends based on the 41 collected AI application cases, considering four perspectives: 1. Purpose of utilizing AI, 2. Targeted facilities, 3. Collected raw data, and 4. Types of learning data. Through my analysis of documents from the perspective of utilizing AI, two main types of AI technology usage were identified: direct utilization of AI technology for maintenance works, and utilization of AI in the intermediate stage for data collection and processing for learning purposes. The research areas that directly employ AI in maintenance work were further categorized into Inspection and assessment, Continuous measurement, Repair and reinforcement, and Aging prediction. The research areas in which research is active are as follows, and are listed in order of prominence: Inspection and assessment (62%), Building learning data for AI (17%), Continuous measurement (7%), Repair and reinforcement (7%), and Aging prediction (7%). To summarize, the current status of research regarding the five purposes of utilizing AI is as follows: 1. [Inspection and assessment] AI applications for inspection and assessment primarily focus on damage detection, such as crack detection using facility inspection photos. Local governments and construction corporations are increasingly adopting automated inspection technologies utilizing unmanned vehicles, such as drones and robots, for inspections in hard-to-reach areas. The development of classification models, primarily around concrete crack detection, is the most prevalent trend. Additionally, the technology is being expanded to include other types of damage beyond cracks, as well as techniques for quantifying damage location, size, and area. 2. [Repair and reinforcement] Regarding the application of AI for repair and reinforcement, research is being conducted with the purpose of training AI with repair and reinforcement data to predict maintenance methods and costs, as well as to predict repair timings exceeding the criteria by using time-series accumulated images of visual inspection grids. 3. [Continuous measurement] Regarding the application of AI for continuous measurement, research has primarily been focused on predicting changes in the condition of facilities and detecting real-time defects for immediate response. This research utilizes accelerometer sensor data and IoT sensor data to detect damaged locations or measurement anomalies, with the purpose of managing performance changes and risks. 4. [Aging prediction] In the application of AI for aging prediction, research is being conducted primarily on creating concrete degradation models or estimating remaining service life based on accelerometer data and structural health data, and utilizing this information for preventive maintenance. 5. [Building learning data for AI] In building data for AI learning, research is being conducted during the data collection and preprocessing stages with the purpose of creating learning data that is currently lacking, such as accelerometer data and crack images, or enhancing low-resolution images to high-resolution ones. The target facilities in AI application research, ranked in descending order, have been bridges (58%), concrete structures (22%), road facilities with a focus on road pavement/surfaces (15%), and buildings (5%). In terms of the types of learning data for AI, images (56%) outnumbered text (44%). Among the detailed types of text data derived from collected raw data, it was observed that measurement data obtained from equipment, database data acquired from system databases, and documents such as inspection reports were utilized, in that order. Of the 33 collected documents that specified data collection methods, it was found that 5 (15%) used retained data, 9 (27%) used publicly available data, and 19 (58%) collected data directly through measurements and crawling, among other methods. AI Research Trends Seen Through Cases Through the analysis of 34 previous research cases related to inspection and assessment, repair and reinforcement, continuous measurement, and aging prediction, this study presents the main research status for each specific maintenance and management work type, utilization purposes, data utilized, and representative research cases. Epilogue We have examined trends in AI research in the field of facility maintenance through numbers and cases. In terms of works where AI is applied, the area of inspection and assessment stands out as the most active and technologically mature field within the maintenance domain. It is expected that the adoption of AI will accelerate, particularly for facilities that are difficult to inspect visually and are dangerous to access. Furthermore, as maintenance technology in Korea transitions towards proactive and preventive maintenance systems in response to aging infrastructure and facilities, there is a growing demand for AI research in aging prediction. In terms of data, image-based research is currently the most active, with text-based research acquired through measuring equipment also being quite prevalent. With recent advancements in natural language processing technology, the expansion of text-based research utilizing construction documents such as inspection reports in the future is anticipated. Many documents highlight the limitations of insufficient AI learning data in their research. Given that this significantly impacts the efforts to secure AI performance, it is expected that the establishment of specialized AI learning datasets for the field of maintenance and research on data quality will become increasingly important. Department of Future&Smart Construction Research Date2023-10-11 Hit 398
Development of Digital Image-Based Soil Color Assessment Technologies Development of Digital Image-Based Soil Color Assessment Technologies ▲ Senior Researcher Kwak Tae-young, Department of Geotechnical Engineering Research, KICT Prologue Soil color is widely used as a fundamental indicator for classifying and predicting soil properties, as it is known to be influenced by factors such as mineral composition, organic content, moisture content, and ion concentration, among others. Particularly in the field of agriculture, soil color is utilized as a prominent indicator for classifying soils, and suitable farming practices and crop types are determined based on soil color variations. Additionally, in civil engineering, the color of soil samples collected during soil surveying of a site is recorded in the boring log. This practice is based on the understanding that soils with similar colors in adjacent areas are highly likely to have similar geotechnical properties. Color is typically determined through visual observation. The MUNSELL Soil Color Charts shown in Figure 1 were developed to objectively differentiate observed soil colors based on combinations of hue, value, and chroma. However, the method of determining soil color using MUNSELL Soil Color Charts has the following limitations: ① It is susceptible to the subjectivity of the observer, ② the color of soil samples and the standard color chips can vary depending on environmental conditions like lighting, and ③ the standard color chips are discontinuous, making numerical or statistical analysis challenging. Recently, digital image-based soil color assessment technology has been highlighted as a means of overcoming these limitations. Digital image processing involves a series of computer-based processes to analyze digital images, allowing for rapid and objective soil color determination without the need for observer involvement. Furthermore, since soil color is represented as continuous values in digital image-based systems, it offers the advantage of enabling numerical or statistical analysis. Current Status of Development of Digital Image-Based Soil Color Assessment Technologies Current Status of Development of Digital Image-Based Soil Color Assessment Technologies Variations in Soil Color Due to Changes in Lighting Conditions Figure 2 presents digital images of granitic soils in the Anseong area, captured under lighting conditions simulating natural light. Despite capturing consistently prepared soil samples with the same camera settings, the soil color displayed in the images varied significantly based on the lighting's color temperature and illuminance. Color temperature is a measure of the color of light sources expressed in absolute temperature (K). The lower the color temperature, the redder the light source; the higher the color temperature, the bluer the light source. Illuminance is a measure of the intensity of light received on a specific surface. As illuminance increases, the light source becomes brighter. Soil color exhibited a similar trend to changes in color temperature and illuminance of the lighting. The phenomenon of soil color changing with lighting conditions highlights the clear limitations of previous studies that were not applicable in practical field settings. It is believed that the development of a digital image-based soil color analysis method that can consider irregular lighting conditions would further enhance the universality and applicability of research findings in practical field settings. Development of Digital Image Processing-Based Soil Color Analysis Technology A color system is a method of numerically representing colors, expressing a specific color as a point in a color space. There are various ways to define a color space, depending on the color system used. Some common color systems include RGB, HSV, CIEXYZ, CIExyY, CIELAB, and CIELUV (Billmeyer and Saltzman, 1981). In this study, two color systems, RGB and CIELAB, were utilized for soil color analysis. The RGB color system is the method most widely used in electronic devices such as digital cameras, and represents colors using the three primary colors of light: red (R), green (G), and blue (B). The RGB color system has the advantage of being able to reproduce most colors through a simple combination of the three colors. However, it cannot represent all the colors that the human eye can perceive. To overcome this limitation, the International Commission on Illumination (CIE) proposed the CIELAB color system based on the CIEXYZ color system (CIE, 1978). In the CIELAB color system, colors are expressed as a combination of L*, a*, and b*. L* represents the brightness of the color and ranges from 0 (dark) to 100 (bright). Additionally, a* and b* represent color values, and a* represents which side of red (positive number) and green (negative number) it is closer to, while b* indicates which side of yellow (positive number) and blue (negative number) it is closer to. Color System for Digital Image-Based Soil Color Analysis In an attempt to overcome the limitations of previous researches, the Korea Institute of Civil Engineering and Building Technology (KICT) has developed a digital image processing-based soil color analysis technology that can consider irregular lighting conditions in the field. As shown in Figure 3, a digital image capture studio was established to simulate natural light conditions. Various soil samples, including a single silica-based sand sample and granitic soil collected from four different regions, were photographed under different lighting conditions. Digital image processing was performed on the captured sample images to extract and analyze soil color in various color systems (RGB, CIELAB). In the RGB color system-based soil color analysis, it was observed that as the illuminance of the lighting intensified, the soil color components (R, G, B) also increased. Of the RGB components, green (G), which is known to have the highest correlation with brightness, showed a very high correlation with illuminance. However, red (R) and blue (B) showed relatively lower correlations due to the influence of color temperature. Since soil color represented in the RGB color system is influenced to some extent by both illuminance and color temperature, it was considered challenging to completely exclude (or correct for) the effects of lighting conditions using this system. The analysis of soil color based on the CIELAB color system revealed that L* is influenced only by illuminance, while a* and b* are affected solely by color temperature, and the correlations were high. This is attributed to the fact that L* represents the brightness of the color, while a* and b* are indicators of hue. Based on the analysis of the relationship between L* and illuminance, as well as a* and b* with color temperature within the CIELAB color system, I proposed the following soil color correction equations according to varying lighting conditions. In this context, I and T represent the illuminance and Color temperature received by the soil, respectively. aL and fL denote the slope and intercept of the linear regression equation between the L* value of soil color and Illuminance, while aa and fa represent the slope and intercept of the linear regression equation between the a* value of soil color and color temperature, and ab and fb signify the slope and intercept of the linear regression equation between the b* value of soil color and color temperature. For dry soil, it was confirmed that the slopes (i.e., aL, aa, ab) in Equations (1) to (3) are similar, regardless of the type of sample. Ultimately, the following correction equation was proposed. Through the proposed method, it is possible to correct the soil color of soil samples captured under arbitrary lighting conditions to the desired soil color under specific lighting conditions. More detailed correction procedures are described in Baek et al. (2023). Epilogue The KICT is currently developing a digital image-based soil color analysis technology that can consider irregular lighting conditions in the field. As shown by the results of an analysis of captured images, it appears that the impact of irregular lighting conditions on soil color can be eliminated (or corrected) based on the CIELAB color system. Using the analysis results for dry soil samples, a lighting condition correction equation has been proposed. In addition, currently, analyses are being conducted for soil samples containing water. Once the analysis for water-containing unsaturated soils is completed, it will become possible to acquire soil color quickly and easily from digitally captured soil images in the field, regardless of moisture content, enabling statistical analysis. Department of Geotechnical Engineering Research Date2023-10-11 Hit 370
Firefly Sensor Developed for the Monitoring of Ground Failures Firefly Sensor Developed for the Monitoring of Ground Failures ▲ Department of Geotechnical Engineering Research, KITC - Smart Sensor and System Developed to Detect Symptoms of Ground and Structural Failure - Field-deployable, Fast, and Accurate Technology that Contributes to Public Safety The Korea Institute of Civil Engineering and Building Technology (KICT) has developed a smart detection sensor (Firefly Sensor), which can detect signs of ground and structural failure, along with a real-time remote monitoring system. The technology was developed jointly with Disaster Safety Technology Co., Ltd., KICT's first research affiliated company, and EMTAKE Co., Ltd., a Korean venture company. The developed Firefly Sensor can be easily mounted in various high-risk areas where ground failures are a concern, with a spacing of 1 m to 2 m. In addition, it can detect deviations as small as 0.03° in real-time, surpassing the 0.05° threshold of the slope inclinometer criteria set by the Korea Forest Service for slope collapse. When a sign of collapse is detected, an immediate alert is triggered using LED illumination. The LED alert utilizes high-efficiency optical transmission lens technology, enabling managers and workers on site to visually confirm the alert, even at a distance of 100 m during daylight hours. Site conditions can be simultaneously and remotely monitored from the control room in real time, facilitating additional measures such as sharing the risk situation with related institutions. In addition, the sensor offers easy installation, resulting in more than a 50% cost savings compared to the installation and operation expenses of conventional measurement sensors. It offers the advantage of operating for a full year without battery replacement, thanks to its ultra-low power design. Additionally, the sensor is designed to operate reliably in extreme temperatures ranging from -30°C to 80°C, and is considered especially suitable for regions with distinct seasonal variations. The Firefly Sensor is equipped with an algorithm technology that prevents malfunctions by analyzing and assessing risks based on the installation location. This means that it can be utilized in a range of locations that includes construction and civil engineering sites, aging buildings, cultural heritage and fortress structures, steep slopes, areas prone to landslides, tunnel construction, mines and underground structures, bridges, dams, areas where erosion protection is needed, and more. Currently, the Firefly Sensor is being operated in pilot installations that include Jeju Lava Cave, water treatment and sewage plants in Incheon, cut slopes and mountain slopes along national highways, the KINTEX station section of the GTX-A route, construction sites for apartment complexes in Daejeon and Damyang-gun, and LG chemical factories. It has also been incorporated into the design of the extension project for the 2023 Sin Bonding Line. It is expected that its application in national infrastructure construction projects, including in the demolition of buildings, will increase. This achievement would not have been possible without the support of the Ministry of Science and ICT, specifically as part of the KICT's main project (Regional Cooperation Project) entitled "Development of Jeju-type Ground Subsidence Response System for Road Safety Operation (2020-2022)." Department of Geotechnical Engineering Research Date2023-06-27 Hit 437
Ammonia: From a Forgotten Element in Sewage to a Valuable Resource Ammonia: From a Forgotten Element in Sewage to a Valuable Resource ▲ Department of Environmental Research, KICT - Adsorbent Material Developed for the Selective Recovery of Ammonia from Sewerage - Key Technologies Acquired for the Establishment of a Carbon-Neutral Sewerage Treatment Facility The Korea Institute of Civil Engineering and Building Technology (KICT) has developed an adsorbent material that selectively removes and utilizes ammonia from sewage, which contains a range of pollutants. The ammonia found in wastewater is a prominent contaminant. If left untreated, it can lead to eutrophication (algal bloom) in rivers and generate foul odors in wastewater treatment plants. It also contributes to soil acidification and is a cause of particulate matter generation, compounding environmental concerns. Currently, nitrogen compounds in sewage undergo a process of conversion to ammonia, followed by nitrification and denitrification in wastewater treatment facilities. However, this treatment process poses challenges, as it requires substantial energy and resources. As of 2019, the electricity consumption in domestic wastewater treatment facilities reached 3,650 GWh. This accounts for only 0.7% of the total electricity supply in Korea (520,499 GWh), and yet approximately 30% of this energy is utilized for the removal of nitrogen compounds such as ammonia from the water. Ammonia is a valuable resource used to produce fertilizers and aqueous urea solutions, and also is utilized in a range of industrial activities. While its production continues to increase, Korea still relies fully on imports for its industrial ammonia. As well, the conventional production method of the energy-intensive Haber-Bosch process under high temperature and pressure further contributes to energy consumption. What if we could recover and reuse ammonia, instead of simply removing it? This approach could dramatically reduce the energy consumption involved in wastewater treatment and ammonia production, ultimately leading to a reduction in carbon emissions. Research on ammonia recovery from sewage is being conducted globally. However, due to the odor issue caused by ammonia leakage during the recovery process and the technical limitations of the developed materials, finding commercially viable technologies has been challenging. To address this, the research team from the KICT’s Department of Environmental Research, led by Dr. Kang Sung-won, has achieved a breakthrough in the development of an ammonia adsorbent material that offers simple production processes and enables mass production. Previously, the selective adsorption of ammonia using Copper hexacyanoferrate (CuHCF), a nano-material, had limitations in terms of its practical applicability in wastewater treatment due to difficulties in recovery. The adsorbent developed by Dr. Kang's research team chemically combines CuHCF with ion exchange resin, featuring particles measuring 1-2 mm, which are suitable for wastewater treatment. In addition, this adsorbent shows remarkable ammonia selectivity even under conditions with a range of coexisting contaminants, surpassing the efficiency of other adsorbents. The adsorbed ammonia can be easily separated from wastewater through a simple regeneration process, enabling the recovery of a highly-concentrated ammonia solution. The developed technology is expected to significantly contribute to achieving carbon neutrality by dramatically reducing the greenhouse gases emitted during the ammonia treatment process. This achievement was developed with the support of the Ministry of Science and ICT, as part of the Research on Next Generation Environmental Technology for Carbon Neutrality project (2021 to 2022). The findings have been published in the February issue of the Chemical Engineering Journal, a leading international journal in the field of environmental engineering. Department of Environmental Research Date2023-06-27 Hit 344
Smart Envelope Systems With Integrated Smart Envelope Materials and Facilities to Achieve Zero-Energy Buildings Smart Envelope Systems With Integrated Smart Envelope Materials and Facilities to Achieve Zero-Energy Buildings ▲ Postdoctoral Researcher Lee Hyun-hwa, Department of Building Energy Research, KITC Prologue Following the 2019 UN Climate Action Summit, the policy agenda of achieving carbon neutrality by 2050 began to gain prominence. Europe and the United States have set carbon neutrality targets, while China has declared its commitment to achieving carbon neutrality by 2060. In Korea, the government's 2050 Carbon Neutrality Promotion Strategy includes a roadmap for carbon neutrality in the building sector. In 2023, zero-energy building requirements have been expanded to include public buildings larger than 500 m² and public housing projects with more than 30 units. There also is a growing movement to transform aged buildings, which constitute 74% of the total building stock, into zero-energy buildings through initiatives like Green Remodeling. The gradual enforcement of zero-energy building requirements is underway. This movement is a global trend, and the IEA FTS (International Energy Agency's Faster Transition Scenario) predicts a 75% reduction in greenhouse gas emissions through investments in energy-efficient measures in the building sector. This is expected to create a domestic market worth approximately KRW 80 trillion for new construction and remodeling, while the global market for zero-energy buildings is projected to reach approximately USD 1.3 trillion by 2035. The transition of current architectural technologies toward future technologies is hindered by certain limitations. In particular, there are limitations to the extent to which both passive and active single-element technologies can be advanced, and there has been a decline in construction quality due to joint defects caused by sequential on-site construction. Additionally, existing control systems are inadequate when it comes to responding quickly to environmental changes. As a result, there is a growing need for smart envelope systems that can overcome these limitations by incorporating smart envelope materials and facilities. These systems should address issues such as energy efficiency, comfort, and design, while considering energy, safety, and business feasibility through prefabrication and modular construction methods. This article aims to introduce the current status of technological development for smart envelope systems integrating smart envelope materials and facilities, both at home and abroad. Current Status of Technological Development for IUES of Envelope Materials and Facilities in Other Countries One example is the MVHR-μHP testbed case, which was part of the iNSPiRe project conducted in 2015. The project verified the performance of the building envelope, small-scale heat pumps, and ventilation systems. Ultimately, its advantage lies in its minimization of the space utilization of the machine equipment installation location on the interior side by using an assembled prefabricated envelope and installing it as an integral wall, thereby reducing the air path. The MORE-CONNECT project is a test bed and demonstration project that applies a developed converged envelope in several European countries, including Denmark and Estonia. It is a project in which remodeling was performed linking renewable energy on the wall and roof surface corresponding to the envelope. In the Danish demonstration case, the PV (Photovoltaics) panel and the roof-integrated module is utilized in the remodeling demonstration. As a result, it can be confirmed that the renewable energy and the electrical system are organically connected to the outer wall. The Estonian demonstration is a case study in which a prefabricated factory-manufactured wood frame module system, combined with an envelope material that incorporates various facility technologies and a renewable energy system, was used to remodel an apartment housing complex with a concrete structure. During the remodeling process, changes were made to the high-performance insulation envelope, balcony reconstruction, heating system, and ventilation system. In addition, solar power and solar thermal renewable energy sources were utilized. This is an example of continuous monitoring being conducted through the building's monitoring system. Current Status of Technological Development for IUES of Envelope Materials and Facilities in Korea The Korea Institute of Civil Engineering and Building Technology (KICT) has conducted a research project entitled "Empirical Study on the Development of Smart Cladding and Facility Convergence Technology for Achieving Zero-Energy Buildings and Establishment of a Performance Evaluation System," which was supported by the Korea Institute of Energy Technology Evaluation and Planning (KETEP). In this research, the Incremental Unitary Envelope System (IUES), an exterior material and facility convergence module system, was developed. Its performance was validated through testing in a testbed, and it is now being prepared for implementation in a real-world demonstration site. The IUES, while combining the cooling and heating system with the interior materials of the building, aims to maximize energy efficiency by utilizing various energy sources, such as renewable energy, and implementing AI-based integrated control. The KICT has selectively integrated five core technologies and 26 detailed technologies, including exterior material technology, facility technology, optimal operation technology, integrated quality certification system establishment, and life cycle management system development to make up units. After combining these units into a unified exterior module, it successfully completed the design, prototype, and testbed application of the standard model for the Smart Cladding and Facility Convergence Module System. The Smart Cladding and Facility Convergence Module System offers a number of advantages that include improved on-site safety through mitigating the risks associated with factory production, transportation, and easy installation. It ensures construction quality through prefabrication, and enables cost-effectiveness by shortening the construction period. Department of Building Energy Research Date2023-06-27 Hit 369
Development of Visualization Technology for Building Energy Information Based on IndoorGML Development of Visualization Technology for Building Energy Information Based on IndoorGML ▲ Research Fellow Choi Hyun-sang, Department of Future & Smart Construction Research, KICT Prologue In the representation of indoor spaces used in the construction of indoor spatial information, international standards such as IFC (Industrial Foundation Classes), CityGML (City Geographic Markup Language), and IndoorGML (Indoor Geographic Markup Language) can be applied. There are two ways to construct indoor space data using these standards: the first is a direct construction method using authoring programs, which allows for detailed representation but involves a significant amount of time and cost. The second method involves creating data by converting data that are already standard or are used in practice, which is effective in reducing time and cost. Thus, this study aimed at developing a Revit Plug-In based on BIM to extract core indoor spatial information object from sample models, convert them to IndoorGML and integrate them with data visualization technology to develop the supporting technology for the utilization of indoor spatial information. Theoretical Considerations of IndoorGML IndoorGML is a data model for expressing and exchanging indoor spatial information, which was developed by the Open Geospatial Consortium (OGC), an international standardization organization for spatial information. It is a data standard in GML format based on XML (eXtensible Markup Language) schema. IndoorGML was developed to support the requirements for indoor spatial data services, and is defined based on a cell space model. IndoorGML focuses on the expression of the geometric relationships and topology (topological relationships) information of indoor spaces, rather than the detailed representation of indoor objects such as building components or furniture. In IndoorGML, the smallest and most basic spatial unit that constitutes a building is called a cell space, and a building is considered a series of cell spaces. To represent this cell space model in detail, IndoorGML defines the following four items: Cell Geometry Topological Relationship between Cells Meaning of the Cell Multi-Layer Spatial Model Based on the four definitions mentioned above, IndoorGML can ① represent the characteristics of indoor spaces, and ② provide spatial reference information about the topographic features located within indoor spaces. Figure 1 shows the geometry options provided by IndoorGML. It displays three options for geometric representation in IndoorGML, and the meanings of each option are as follows: Option 1 : (External Reference) Instead of explicitly representing geometry in IndoorGML, it can be expressed solely through external links to objects defined in other datasets, such as CityGML. OOption 2 : (IndoorGML Geometry Information) When including geometric representations for cell spaces in IndoorGML, 3D spaces are represented as GM_Solid, and 2D spaces (walls) are represented as GM_Surface according to the definition in ISO 19107. Openings (e.g. doors, windows, etc.) are also included in this case. OOption 3 : (No Geometry) IndoorGML document does not include geometry information for cell spaces (spaces can be represented solely by Nodes). Geometry Rules for IndoorGML Conversion The geometry rules for the key objects that constitute IndoorGML are based on the modeling rules presented in the SIG3D "Modeling Guide for 3D Objects Part 1: Basics (Rules for Validating GML Geometrics in CityGML)" technical document. Among the regulations in the aforementioned technical document, the implementation rules for representative objects that are most closely related to this study are as follows: gml : LinearRing: The geometry composing the objects that make up the building is comprised of a single polygon boundary, i.e. a LinearRing (Rs) (Figure 2). gml: Polygon: A polygon (S) is represented as a set of planar LinearRings (Rs). gml : MultiSurface: The MultiSurface used to visually represent the surface objects (M) that make up a building is represented as a collection of unstructured polygons (S), i.e., M={S1, S2, Sn}. gml: The geometry of a 3D object is defined as a collection of polygons that are composed of multiple surface objects (Multi-Surface), and errors can occur depending on the composition of the polygons. Table 1 shows examples of correct and incorrect cases when constructing indoor objects. Development of IndoorGML Plug-In Based on Revit Software (1) Design of Revit Data Conversion Process Autodesk's Revit software, which is commonly used to create 3D BIM models, provides a range of 3D modeling features that support accurate input in terms of visualization and geometry, as well as tools to input and manage relationships between constituent objects. In this study, the Room Schedule and Door Schedule functions provided by Revit were used as a basis, and the CellSpace (Node) and Transaction (Edge), which are core objects of IndoorGML, were constructed based on the connection information entered between the spaces during building design. However, if Room/Door Schedule is missing in the initial BIM modeling process or is omitted due to worker error, it must be checked and corrected through a pre-validation process. Figure 3 shows the data conversion process applied in this study. (2) How to Use Revit's Room Objects, and Rules for Handling Virtual Spaces To extract CellSpaces in IndoorGML using Room objects created in Revit, it is necessary to first check whether the Room object has been input into the Revit model. Figure 4 shows that if a Room object has been input, it is displayed on the screen with crosslines, and that even irregular spaces can be configured as Room objects. In the design of typical buildings, only spaces composed of actual structures (walls, columns, floor surfaces, ceiling surfaces, etc.) are represented. However, in IndoorGML, an indoor space information, it is necessary to divide virtual indoor spaces for large spaces such as auditoriums or banquet halls, as well as narrow and long corridors with changing directions. For this purpose, preprocessing of virtual spaces is required before converting to IndoorGML, and setting and modifying rules for processing virtual spaces is necessary. In this study, additional functions were developed based on the features provided by Revit for processing virtual spaces. (3) Main Features and Achievements of Revit SW-based IndoorGML Plug-In In the Revit SW, it is common to create Room and Door Schedules during the BIM modeling process. However, there may be cases in which they are omitted due to human error or spatial constraints, so it is necessary to check them in advance and make corrections as needed. Figure 5 shows a feature provided by Revit that allows the user to check Room Tags and missing information. Then, when converting Revit data to IndoorGML data using the "IndoorGML Exporter" menu, a verification process is also carried out to check for any missing information. Once the verification of the Revit data that serves as the source of IndoorGML is complete, the user can selectively convert only the desired floors or the entire building into a single IndoorGML file. Figures 7 and 8 show examples of the conversion of Main Buildings 1 and 2 of the Korea Institute of Civil Engineering and Building Technology (KICT). (4) Development of IndoorGML-based Building Energy Information Visualization System In this study, we developed a 3D system that can visualize building energy management by assigning representative values for each spatial unit based on measured values by room and location in Main Building 1 of KICT that was investigated through the aforementioned process, as well as values obtained from the survey. Figure 9 shows the process of integrating the results of a user satisfaction survey program for the building, KBOSS, into indoor space units (left), and examples of floor-by-floor visualization (right). Epilogue This study was performed to secure the core technology for integrating and managing detailed energy data for individual building units and occupant satisfaction survey results in a format that is compliant with the international spatial information standards, which is necessary for developing the technology for energy inspections of metropolitan-scale buildings. Through this study, an IndoorGML data authoring tool was developed and applied to store and represent energy-related information investigated for KICT at the minimum space unit (room) level. It is expected that the results can be utilized as a database and operational technology for micro-level building energy inspection information in the future implementation of carbon reduction policies, which are an important part of building energy monitoring and management on a national scale. Department of Future&Smart Construction Research Date2023-02-27 Hit 503
ISO 19650-based BIM Information Management Framework ISO 19650-based BIM Information Management Framework ▲ Senior Researcher Won Ji-sun, Department of Future & Smart Construction Research, KICT Prologue In this "Digitize or Die" era, digital transformation is recognized as an essential strategy for corporate survival, and is accelerating across all industries. The construction industry is responding to paradigm shifts through the spread of smart construction technologies such as Building Information Modeling (BIM) adoption, construction machine automation, and the activation of Off-Site Construction (OSC). In July of this year, the Ministry of Land, Infrastructure and Transport (MOLIT) announced the "S-Construction 2030” plan, which aims to achieve "digitalization and automation of the entire construction process by 2030." It presents three promotional tasks for achieving this goal: digitalization of the construction industry, advancement of the production systems, and promotion of the smart construction industry. Of these, the detailed plan for realizing the digitalization of the construction industry specifies the organization of the BIM system and the phased expansion of projects subject to mandatory BIM application. Other countries, including the UK, Denmark, and Ireland, have also introduced the concept of digitalization into their existing BIM roadmaps and are redesigning them as national digital transformation strategies or digital twin strategies. BIM is now recognized as an essential strategic tool for digital transformation. Upon examination, it is evident that ISO 19650 is being actively adopted. ISO 19650 is a BIM information management framework that standardizes the process and information requirements for BIM information procurement across the life cycle of a construction project, and was established in 2018. This international standard was developed by adding digital information management concepts to the UK’s BIM standards (BS 1192 series), which was previously used as the global standard during the early phases of BIM adoption. The UK, Europe, and Australia have designated the ISO 19650 original text or translation as their national BIM standard, while countries like Singapore, Hong Kong, and Saudi Arabia are revising their national BIM standards to include ISO 19650. Many countries are now mandating ISO 19650 certification as a prerequisite for bidding on public construction projects or offering incentives, and more companies in Korea are obtaining ISO 19650 certification to demonstrate their global-level BIM information management technology and capabilities. There is a growing trend of the active utilization of ISO 19650 as part of a BIM-based digital transformation policy. Moreover, as a company's ISO 19650 certification and compliance capacity has become a measure of competitiveness, it is necessary to consider the introduction of ISO 19650 at the national level in Korea. Thus, we aim to propose strategies and methods for introducing ISO 19650 in Korea. In this study, we adopted an approach that reflects the key concepts of ISO 19650 in accordance with the situation in Korea. Our research involved three steps. First, we investigated the current status of ISO 19650 adoption in other countries, and derived the key components of the BIM information management framework by examining international standard documents. Second, we analyzed the software, platforms, and other support tools that enable ISO 19650 adoption, and selected the main functions that need to be implemented for practical application. Third, based on the key components of ISO 19650 and the main functions of ISO 19650 support tools, we proposed an ISO 19650 utilization model and suggested ways to introduce it in Korea. Stages 2 and 3 can be understood as a process of scanning multiple buildings from an urban/regional perspective based on appropriate indicators (whole-building level identification), while Stages 4 and 5 can be understood as a process of closely examining the scanned buildings in detail from a building component perspective (system level diagnostics). In this study, we would like to introduce the data-centric checkup technique of building energy performance that corresponds to Stages 2 and 3 in this context. Current Status of ISO 19650 Adoption in Other Countries Generally, national BIM roadmaps utilize BIM maturity models to establish phase-specific goals for BIM adoption levels and situations. Many countries have already been utilizing the BIM maturity model defined in the UK BIM roadmap (British Standards Institution B/555), which was announced in 2011, as a global standard. In the BIM maturity model of the UK, Level 0 is set in an environment centered on documents such as 2D drawings and text, Level 1 is set in an environment where 2D drawings and 3D data files are used concurrently, Level 2 is set in a discipline-specific BIM model environment, and Level 3 is set in an integrated web-based BIM environment that centrally manages data through a single model. The UK is actively utilizing ISO 19650 to attain Level 2, and is preparing a digital transformation roadmap for attaining Level 3. Currently, most countries are in the Level 2 adoption or activation phase. Many countries are in the process of adopting ISO 19650, as shown in Table 1. Thus, the adoption of ISO 19650 is recognized as an essential requirement for attaining BIM Level 2. The ISO 19650-1 established in 2018 presents the maturity levels of digital information management in each phase as a concept of "stage." The types of data, such as 2D, 3D, and BIM, covered in the UK BIM maturity model have been changed to concepts such as structured, unstructured, BIM, and server-based BIM, and the concept of Common Data Environment (CDE) has been subdivided into the file- and model-based CDE forms and the big data-based CDE forms. Digital information management maturity for each phase is divided into three information management stages along the horizontal axis, and is composed of four layers (standard, technology, information, industry) that represent the major information management perspectives along the vertical axis. In terms of information management perspectives according to standards, Stage 1 is defined as information management based on existing national standards for handling structured and unstructured data, Stage 2 as information management based on ISO 19650 standards for handling shared BIM models, and Stage 3 as information management based on future standards for handling server-based BIM models and structured/unstructured big data. The current stage is Stage 2, and to achieve the corresponding level, information management based on ISO 19650-1 and 2 is required. Deriving Key Components of BIM Information Management Framework Through Analysis of ISO 19650 To achieve the goals aligned with the BIM maturity level or digital information management maturity level, it is important to specify the national-level BIM standards that must be complied with at each phase. Specifically, there are BIM guidelines, BIM classification systems, contracts related to information procurement and LOD standards, as well as BIM maturity assessment methodologies. The BIM Information Management Framework is a standardized system that supports workflows and data acquisition to generate, utilize, and manage BIM data in an integrated digital construction environment throughout the construction life cycle. BIM standards related to the BIM Information Management Framework include BIM standard classification, building SMART International's IFC, IDM, IFD, and COBie. ISO 19650 covers processes in the digital collaboration system such as subject-specific information requirements, digital model deliverables, workflows, information management plans, CDE, etc. from the perspective of comprehensive use of these open standards. The currently published ISO 19650 series is as follows: ISO 19650-1(2018) : Concepts and Principles for Information Management Using BIM ISO 19650-2(2018) : Information Management Using BIM in the Delivery Stage ISO 19650-3(2020) : Information Management Using BIM in the Operational Stage ISO 19650-4(2022) : Process and Standards for Information Exchange ISO 19650-5(2020) : Security Management During Information Management Using BIM ( 1 ) ISO 19650-1 (2018): Concepts and Principles for Information Management Using BIM ISO 19650-1 contains the concepts and principles of an information management framework for BIM collaboration throughout the construction life cycle. Information management is defined as "the process of supporting the production and management of information over the entire construction asset life cycle." The key components of the BIM information management framework are: ① specification of information requirements, ② planning for information delivery, and ③ delivery of information, which support a collaborative environment to enable the consistent delivery of information that varies by project, stakeholder, and purpose through a coherent process and delivery system. In the project delivery phase and operational phase, an information procurement plan is established based on the information requirements of the participants and contractors. In addition, it has the flow in which deliverables reflecting this, such as PIM (Project Information Models) and AIM (Asset Information Models), are delivered and approved. For effective information management, the setting of responsibilities, authorities, and scope of work is crucial, and pertinent functions should be assigned during the project and asset management period. The responsibility assignment items must be specified in the contract document (e.g., through a Responsibility Matrix) to ensure that a person with “AIM approval competency” is designated for asset management and a person with the information standard, process, and CDE configuration competency of the project is designated for project delivery. ( 2 ) ISO 19650-2 (2018): Information Management Using BIM in the Delivery Stage ISO 19650-2 sets information requirements during the project execution phase, and defines a collaborative environment and process for lead appointed parties and appointed parties to efficiently produce information. The information entities of the project delivery phase are set as the appointing party, lead appointed party, and appointed party. The information management process as well as function and standard requirements for each entity are presented for each project delivery phase. A total of eight information management functions in the project delivery phase are defined, and the detailed information management processes for each entity are specified in each section of Chapter 5 in ISO 19650-2 (5.1 Evaluation and requirements → 5.2 Bid announcement → 5.3 Bidding participation → 5.4 Contracting → 5.5 Resource mobilization → 5.6 Collaborative information production → 5.7 Information model delivery → 5.8 Project completion). In this study, ISO 19650-1 and 2 were analyzed to identify the key components of the framework, including specifications related to information management entities, requirements, processes, deliverables, and roles, and were divided into seven components as shown in Table 2 (1. Information Requirements, 2. Information Delivery, 3. Information Management Entities and Roles, 4. Workflows, 5. Information Procurement Plan, 6. Information Management Level, and 7. CDE). Deriving Key Functions through Analysis of ISO 19650 Practical Application Support Tools To apply the ISO 19650 component concept in practice, it is necessary to identify the actually implemented functions and interfaces. According to a survey of the software, websites, platforms, and other tools that support ISO 19650, it was found that the Plannerly platform from the United States is a representative tool that faithfully incorporates the ISO 19650 concepts. However, there are many tools, like US BEXEL, that only partially support ISO 19650 concepts, such as information delivery and CDE concepts, and open BIM formats such as IFC, BCF, and COBie. ( 1 ) The US: Plannerly Plannerly is a BIM information management platform that provides integrated support for the appointing party (project owner), designing party (AE), lead appointed party (contractor), and the appointed party (subcontractor) to plan, manage, and validate BIM requirements in one place. It is designed to facilitate the easy and efficient use of BIM standards, requirements, processes, and regulations in accordance with ISO 19650, and provides an environment in which all construction stakeholders can collaborate on information and processes without disruption on a single site. Its interface features ISO 19650 templates (OIR, PIR, EIR, AIR, BEP, etc.) based on the UK BIM Framework guidelines and workflows to enable easy and consistent operations. The platform also incorporates the CDE concept to enable the centralized generation, storage, and management of information. It is largely comprised of six modules: Plan, Scope, Contract, Schedule, Track, and Verify. ( 2 ) The US: BEXEL Manager BEXEL Manager is software that supports digital workflows in an open BIM environment according to ISO 19650, and provides a collaborative environment to manage the PIM and AIM information delivery models in a CDE environment. It supports open standard formats such as IFC standards, MVD, BCF, and COBie. Based on an analysis of these two support tools, it was determined that the key factors to consider when introducing them to Korea are whether they support a BIM-based workflow, including BIM contract and requirements management, BIM task performance, BIM data verification, collaboration, information requirements definition, information procurement plan establishment, information management level setting, and open BIM standard formats. The main functions to benchmark are derived in Table 4 based on such analysis results. To create building-level screening indicators, the dataset collected at the building registry level should be matched and integrated (Figure 2, ② Data Preprocessing). However, since publicly collected data is generated for different policy and administrative purposes, there usually is no unique key to link and match the building registry information. Therefore, the location information (latitude and longitude) and address information (street number, dong, ho or suite number) of each data must be processed and linked to match the resolution of the building registry. This task requires string processing technology for non-standardized address and location information, which is quite difficult and requires a substantial budget and time. Approaches to Introduce the ISO 19650-based BIM Information Management Framework to the Republic of Korea The ISO 19650 utilization model is a conceptually defined model that integrates the key components of a digital-based BIM execution workflow and data procurement framework for BIM information management, from a user perspective, to enable unified utilization. The ISO 19650 utilization model was constructed based on the main components of the BIM information management framework derived through the analysis of ISO 19650 and the main functions derived through the analysis of ISO 19650 support tools. The ISO 19650 utilization model consists of six modules, as shown in Figure 4. Module 1 is Standards, which signifies Open BIM standard for exchanging and distributing BIM data and Standards for defining the BIM information management operating system. Module 2 is Requirements, which functions to set information requirements, information management entities and roles, and information procurement plans in project phases such as design and construction and facility operation phases. Module 3 is Workflows, and it is designed to define and manage detailed BIM processes for each project delivery and operational phase. Module 4, Deliverables, defines and manages PIM and AIM data, which are information delivery outputs. Module 5 refers to the CDE environment for collaboration and sharing. Modules 2 and 3 pertain to the process area, while modules 4 and 5 consist of the data area created, shared, and saved according to the process. Modules 2 through 5 need to be operated to achieve a sequential flow. Module 1 is used as a criterion for data creation, and module 6 serves as an interface where the BIM information management entity utilizes modules 1 to 5. The concept of each module can be provided in the form of specifications, such as standards and guidelines, or in the form of platform functions. We propose the following implementation plan and future tasks to apply the ISO 19650 utilization model in practice. First, in order to establish Level 2 of BIM in Korea, it is necessary to customize the major components of ISO 19650 defined in modules 2 through 5 and the open BIM standard defined in module 1 to fit the domestic situation and present it as a national standard. From a regulatory perspective, a strategy is required to gradually expand the mandatory application of ISO 19650 to some public construction companies, and a verification process through pilot projects should be accompanied before making it mandatory. Second, to directly utilize the ISO 19650 utilization model in work, it is necessary to incorporate the workflow of module 3 and develop a BIM project workflow support platform that includes the functions of module 6. For this purpose, it is important to convert document-level specifications into digital specifications and combine clauses and workflow units. In addition, a plan to link ISO 19650's key functions and data with commercial BIM platforms and enterprise ERP systems to operate needs to be prepared to increase the effectiveness of ISO 19650 adoption. Third, with the acceleration of the digital transformation paradigm, proactive future responses are needed, such as revising the BIM roadmap to prepare for the next maturity phase, as well as research on the introduction and stabilization strategy for digital information management maturity Stage 2 and BIM maturity Level 2. Epilogue In the era of digital transformation, the adoption and utilization of ISO 19650 in the global market has become an essential strategy for securing global competitiveness. To proactively respond to these changes domestically, an approach to the adoption of ISO 19650 has been suggested. To implement the core functions that can reflect the main components of ISO 19650 and be applied to practical situations, an ISO 19650 utilization model has been defined, and adoption plans and challenges for implementation in Korea have been proposed. It is anticipated that an adoption plan based on ISO 19650 will be reviewed in devising a national-level BIM information management operation system in the future. Department of Future&Smart Construction Research Date2023-02-27 Hit 811

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