Earticle

본 연구는 한국 건설산업의 고질적인 병폐인 불법하도급 문제를 해결하기 위해 기존의 수기 및 서류 중심 단속 체계가 가진 한계점을 분석하고, 국가 행정정보와 인공지능(AI) 기술을 결합한 지능형 감시체계의 설계 방향을 제안하였다. 현재 우리나라의 불법하도급 단속은 연간 17만 건이 넘는 방대한 공사 물량에 비해 전담 인력은 10여 명에 불과하여 물리적인 감시 사각지대가 발생할 수밖에 없는 심각한 구조적 제약에 직면해 있다. 이러한 자원의 부족은 위장계약이나 다단계 재하도급과 같이 정교화된 위법 행위를 실시간으로 포착하는 것을 어렵게 만든다. 이러한 문제들을 해결하기 위해 본 연구는 국세청의 전자세금계산서, 고용노동부의 고용 및 4대 보험 자료, 그리고 건설기계 등록정보 등 여러 기관에 산재한 행정정보를 통합하는 AI 기반 감시 모형을 제시하였다. 다차원적인 데이터 세트에 대한 실시간 교차검증을 통해 AI는 계약 서류와 실제 현장 투입 주체(근로자 및 장비) 간의 불일 치나 비정상적인 자금 흐름과 같은 이상 징후를 자동으로 식별할 수 있다. 본 연구는 ‘위장계약’, ‘이면계약’, ‘다단계 재하도급’에 대한 구체적인 탐지 시나리오를 상세화함으로써 기술적 구현을 위한 실질적인 윤곽을 수립하였다. 나아가 본 연구는 AI 감시시스템의 조속한 구축, 범정부 차원의 정보공유 플랫폼 마련, 민간 공사 하도급 계약등록 의무화, 그리고 특별사법경찰권 도입을 통한 단속 권한 강화 등을 포함하는 종합적인 정책 패키지를 제안하였다. 본 연구는 기술적 혁신, 제도적 개선, 행정적 효율성을 통합함으로써 단속의 정확도를 높이고 건설 관리의 공정성과 안전성을 확보하기 위한 전략적 대안을 제공한다는 점에서 학술적·정책적으로 중요한 의의를 지닌다.

This study analyzes the limitations of existing manual and document-based enforcement systems to address the chronic issue of illegal subcontracting in the Korean construction industry. It proposes an intelligent monitoring framework that integrates national administrative data with Artificial Intelligence (AI) technology. Currently, enforcement faces severe structural constraints; with over 170,000 annual construction projects but only about 10 dedicated personnel, vast monitoring blind spots are inevitable. This lack of resources makes it difficult to detect sophisticated illegalities such as disguised contracts or multi-level subcontracts in real time. To solve these problems, this research proposes an AI-driven monitoring model that integrates fragmented administrative data—including tax invoices from the National Tax Service, employment and four major insurance data from the Ministry of Employment and Labor, and machinery registration information. By performing real-time cross-verification of these multi- dimensional datasets, the AI can automatically identify anomalies, such as discrepancies between contract documents and actual on-site entities (laborers and equipment) or irregular financial patterns. The study establishes a concrete technical outline by detailing specific detection scenarios for "sham contracts," "back-door contracts," and "multi-level subcontracting". Furthermore, the study recommends a comprehensive policy package: the rapid deployment of an AI monitoring system, the legalization of a government-wide data-sharing platform, mandatory subcontract registration for private projects, and the strengthening of enforcement through special judicial police powers. This research holds significant academic and policy value as it provides a strategic framework to enhance enforcement accuracy, promote fairness, and ensure safety in construction management by integrating technology, institutional reform, and administrative efficiency.

A data acquisition and monitoring system was developed for an automated system of a smart fish farm. The fish farm is located in Jang Hang, South Korea, and was designed as circulation filtration system. Information of every aquaculture pool was automatically measured by pH sensors, dissolved oxygen sensors, and water temperature sensors and the data were stored in the database in a remoted server. Modbus protocol was used for gathering the data which were further used to optimize the pool water quality to predict the rate of growth and death of fish, and to deliver food automatically as planned by the fish farmer. By using JSON protocol, the collected data was delivered to the user's PC and mobile phone for analysis and easy monitoring. The developed monitoring system allowed the fish farmers to improve fish productivity and maximize profits.

An emergency monitoring system for the elderly, which uses acceleration data measured with an accelerometer, angular velocity data measured with a gyroscope, and heart rate measured with an electrocardiogram, is proposed. The proposed fall detection algorithm uses multiple parameter combinations in which all parameters, calculated using tri-axial accelerations and bi-axial angular velocities, are above a certain threshold within a time period. Further, we propose an emergency detection algorithm that monitors the movements of the fallen elderly person, after a fall is detected. The results show that the proposed algorithms can distinguish various types of falls from activities of daily living with 100% sensitivity and 98.75% specificity. In addition, when falls are detected, the emergency detection rate is 100%. This suggests that the presented fall and emergency detection method provides an effective automatic fall detection and emergency alarm system. The proposed algorithms are simple enough to be implemented into an embedded system such as 8051-based microcontroller with 128 kbyte ROM.

Recently, security researches have been processed on the method to cover a broader range of hacking attacks at the low level in the perspective of hardware. This system security applies not only to individuals' computer systems but also to cloud environments. "Cloud" concerns operations on the web. Therefore it is exposed to a lot of risks and the security of its spaces where data is stored is vulnerable. Accordingly, in order to reduce threat factors to security, the TCG proposed a highly reliable platform based on a semiconductor-chip, the TPM. However, there have been no technologies up to date that enables a real-time visual monitoring of the security status of a PC that is operated based on the TPM. And the TPB has provided the function in a visual method to monitor system status and resources only for the system behavior of a single host. Therefore, this paper will propose a m-TMS (Mobile Trusted Monitoring System) that monitors the trusted state of a computing environment in which a TPM chip-based TPB is mounted and the current status of its system resources in a mobile device environment resulting from the development of network service technology. The m-TMS is provided to users so that system resources of CPU, RAM, and process, which are the monitoring objects in a computer system, may be monitored. Moreover, converting and detouring single entities like a PC or target addresses, which are attack pattern methods that pose a threat to the computer system security, are combined. The branch instruction trace function is monitored using a BiT Profiling tool through which processes attacked or those suspected of being attacked may be traced, thereby enabling users to actively respond.

Nowadays, emotion detection based on the physiological changes of the body is a major concern. Anger is one of the most destructive emotional states and needs continuous monitoring for a healthy lifestyle. In this study, we developed and implemented a wearable anger-monitoring system, which analyses various physiological changes during the state of anger in humans and notifies the monitoring unit using a global system for mobile communication. This is unique as it detects the human mood swing and realizes it on hardware. The developed low-cost noninvasive wrist band can be used all-day and anywhere for detecting anger.

This paper embodies the agent based cinder monitoring system which supports PDA{Personal Digital Assistant). Monitoring system automatically manages data by using data managing agents such as a state managing agent, a location managing agent, a badness managing agent, a circumstances managing agent, etc, and uses a massive data processing agent to manage massive data. The development of agent based data monitoring system for the stable cinder reuse will be an epoch-making method to develop the process mechanized or manual-labored that widely spreads into the real-time automated process.

This paper embodies the agent based cinder monitoring system which supports PDA(Personal Digital Assistant). Monitoring system automatically manages data by using data managing agents such as a state managing agent, a location managing agent, a badness managing agent, a circumstances managing agent, etc, and uses a massive data processing agent to manage massive data. The development of agent based data monitoring system for the stable cinder reuse will be an epoch-making method to develop the process mechanized or manual-labored that widely spreads into the real-time automated process.

A smart dust monitoring system is useful for obtaining information on rough terrain that is difficult for humans to access. One of ways to deploy sensors to gather information in smart dust environment is to use an aircraft in the Amazon rainforest to scatter an enormous amount of small and cheap sensors (or smart dust devices), or to use an unmanned spacecraft to throw the sensors on the moon's surface. However, scattering an enormous amount of smart dust devices creates the difficulty of managing such devices as they can be scattered into inaccessible areas, and also causes problems such as bottlenecks, device failure, and high/low density of devices. Of the various problems that may occur in the smart dust environment, this paper is focused on solving the bottleneck problem. To address this, we propose and construct a three-layered hierarchical smart dust monitoring system that includes relay dust devices (RDDs). An RDD is a smart dust device with relatively higher computing/communicating power than a normal smart dust device. RDDs play a crucial role in reducing traffic load for the system. To validate the proposed system, we use climate data obtained from authorized portals to compare the system with other systems (i.e., non-hierarchical system and simple hierarchical system). Through this comparison, we determined that the transmission processing time is reduced by 49%-50% compared to other systems, and the maximum number of connectable devices can be increased by 16-32 times without compromising the system's operations.

Sensors, equipment, ICT facilities and their corresponding software have a relatively short lifetime relative to that of constructional structure, so these devices have to be continuously fixed or exchanged during maintenance and management. Furthermore, software or analysis tools should be periodically upgraded according to advances in ICT and analysis technology. Conventional monitoring systems have serious problems in that it is difficult for site engineers to modify or upgrade hardware and analysis algorithms. Moreover, we depend on the original system developer when we want to modify or upgrade inner program structures. In this paper, we propose a novel design for integrated maintenance and management of a monitoring system by applying the mobile cloud concept. The system is intended for use in disaster prevention of constructional structures, including bridges, tunnels, and in traditional buildings in a local heritage village, we analyze the status of these structures over a long term or a short-term period as well as in disaster situations. Data are collected over a mobile cloud and future expectations are analyzed according to probabilistic and statistical techniques. We implement our integrated monitoring system to solve the existing problems mentioned above. The final goal of this study is to design and implement a monitoring system for more than 10,000 structures spread within Korea. Furthermore, we can specifically apply the monitoring system presented here to a bridge made from timber in Asan Oeam Village and a traditional house in Andong Hahoe Village to monitor for possible disasters. The entire system design and implementation can be developed on the LinkSaaS platform and the monitoring services can also be implemented on the platform. We prove that the proposed system has good performance by performing a TTA authentication test, web accommodation test, and operation test using emulated data.

In this paper, we propose a integrated real-time monitoring system for recycling agriculture resourcing based on USN. We design and implement the monitoring system so that we can integrate the quality control of farmyard and liquid manures, barn environment monitoring, and positioning information control into a total management system performing recycling of excrement and manure. Selection of sensors and sensor-node construction and requirements, structure of wire/wireless communication networks, and design of monitoring program are also presented. As a result of operating our system, we can get over various drawbacks of conventional separated system and promote the proper circulation of excrement up to the farmyard. We confirm that these advanced effects arise from the effective management of the total system integrating quality control of farmyard/liquid manure, barn/farmhouse information, and vehicle moving monitoring information etc. Moreover, this monitoring system is able to exchange real-time information throughout communication networks so that we can construct a convenient information environment for agricultural community by converging IT technology with farm and stockbreeding industries. Finally we present some results of processing using our monitoring system. Sensing data and their graphs are processed in real-time, positioning information on the v-world map offers various moving paths of vehicles, and statistical analysis shows all the procedure from excrement occurrence to recycling and resourcing.

Mobile computers can process large amounts of data at high speeds, and it is feasible and easy to implement a remote monitoring system utilizing mobile computers. Because of their portability and convenience, these computers have been employed in various research areas to develop such monitoring systems. Existing monitoring system is a bit difficult to real time monitoring the scattered offshore facilities. So this paper compensate the existing system by using mobile computers such as a tablet PC-based monitoring system. Also, the scattered offshore facilities can be monitored in real-time through the tablet PC. The developed monitoring system is a fully Internet-based monitoring platform that enables one to monitor and control remote oceanic applications at any time and any place where it is possible to access the Internet. It can be applied to many oceanic applications as well as the unmanned systems and remote monitoring systems on land.

Working in a hazardous environment can decrease work efficiency and cause a variety of occupational diseases. To prevent occupational accidents and build a refreshing and pleasant work environment, therefore, it is necessary to develop an application system through which a worker's safety can be monitored on a realtime basis and provide related services. Recently, smartphones have become very popular across the nation, with over 10 million users. As a result, a variety of application services have been developed and provided in diverse sectors. This study proposes a system structure to develop application services which monitor work environment using smartphones and examines its applicability through the implementation of server and client interfaces.

Objective: This study aimed to evaluate the validity of a depth camera-based system for monitoring physical function, assessing its feasibility for accurately monitoring activities of daily living. Design: A cross-sectional study. Methods: Twenty-three participants were enlisted to perform fifteen activities of daily living within a living laboratory designed to simulate a home environment. Activities were monitored using a depth camera system capable of classifying actions into standing, sitting, and lying down, with a conventional video camera employed for activity recording. The duration of each activity, as measured by the system, was compared to direct observations made by a physical therapist which were analyzed using a motion analysis software. The association between these two measurement approaches was assessed through correlation analysis, coefficient of determination, intraclass correlation coefficient (ICC), and Bland-Altman plots. Results: Our findings indicated that standing activities exhibited the highest correlation (r=0.847) between the system measurements and physical therapist observations, followed by sitting (r=0.817) and lying down (r=0.734), which demonstrated lower correlations. However, the ICC and Bland-Altman plots revealed notable variances between the two measurement methods, particularly for activities involving lying down. Conclusions: In this study, the depth camera-based physical monitoring system showed promise feasibility in distinguishing standing, sitting, and lying down activities at home environments. However, the current study also underlined some necessities of enhancements in capturing lying down activities.

The exceptional development of electronic device technology, the miniaturization of mobile devices, and the development of telecommunication technology has made it possible to monitor human biometric data anywhere and anytime by using different types of wearable or embedded sensors. In daily life, mobile devices can collect wireless body area network (WBAN) data, and the co-collected location data is also important for disease analysis. In order to efficiently analyze WBAN data, including location information and support medical analysis services, we propose a geohash-based spatial index method for a location-aware WBAN data monitoring system on the NoSQL database system, which uses an R-tree-based global tree to organize the real-time location data of a patient and a B-tree-based local tree to manage historical data. This type of spatial index method is a support cloud-based location-aware WBAN data monitoring system. In order to evaluate the proposed method, we built a system that can support a JavaScript Object Notation (JSON) and Binary JSON (BSON) document data on mobile gateway devices. The proposed spatial index method can efficiently process location-based queries for medical signal monitoring. In order to evaluate our index method, we simulated a small system on MongoDB with our proposed index method, which is a document-based NoSQL database system, and evaluated its performance.

This study aims to investigate termite infestation routes in areas concentrated with urban hanoks and establish preemptive measures to effectively prevent them. To achieve this goal, this study employed a structured observational protocol using Colony Elimination System Monitoring (CESM), prompting five instances of systematic monitoring activities from January 2020 to April 2021. As a result, this study observed actual termite activities only in Gahoe-dong ②, which suggests that local conditions, such as soil moisture, organic residues, and shaded environments, influence termites' ecological preferences. Findings also confirmed that the proximity between hanoks and preexisting damage were also crucial factors to the horizontal termite spread. CESM maintained stable performance during the entire operation and predicted termite existence with 80% accuracy through logistic regression analysis, demonstrating its effectiveness as a long-term monitoring tool. However, this study has limitations in failing to include important environmental variables, such as relative humidity, soil moisture, and rainfall, which suggests a more advanced variable design in future research. Lastly, this research proposed three practical methods for the effective use of CESM: (1) priority of application for areas densely concentrated with hanoks; (2) setting the priority of installation based on damage history; and (3) establishing a monitoring system linked to public platforms. Furthermore, discussions also took place on the possibility of expanding into a predictive pest control system utilizing IoT and AI.

The remote monitoring and warning system for dangerous chemicals is designed with the concept of the Cyber-Physical System (CPS) in this paper. The real-time perception, dynamic control, and information service of major hazards chemicals are realized in this CPS system. The CPS system architecture, the physical layer and the applacation layer, are designed in this paper. The terminal node is mainly composed of the field collectors which complete the data acquisition of sensors and video in the physical layers, and the use of application layer makes CPS system safer and more reliable to monitor the hazardous chemicals. The cloud application layer completes the risk identification and the prediction of the major hazard sources. The early intelligent warning of the major dangerous chemicals is realized and the security risk images are given in the cloud application layer. With the CPS technology, the remote network of hazardous chemicals has been completed, and a major hazard monitoring and accident warning online system is formed. Through the experiment of the terminal node, it can be proved that the terminal node can complete the mass data collection and classify. With this experiment it can be obtained the CPS system is safe and effective. In order to verify feasible, the multi-risk warning based on CPS is simulated, and results show that the system solves the problem of hazardous chemicals enterprises safety management.

The lane departure avoidance systems have been considered promising to assist human drivers in AVCS (Advanced Vehicle Control System). In this paper, a lane departure monitoring and control system is developed and evaluated in the hardware-in-the-loop simulations. This system consists of lane sensing, lane departure monitoring and active steering control subsystems. The road image is obtained based on a vision sensor and the lane parameters are estimated using image processing and Kalman Filter technique. The active steering controller for avoiding the lane departure is designed based on the lane departure metric. The proposed lane departure avoidance system is realized in a steering HILS (hardware-in-the-loop simulation) tool and its performance is evaluated with a driver in the loop.

A piezoelectric sensor-based health monitoring technique using a two-step support vector machine (SVM) classifier is developed for railroad track damage identification. A built-in active sensing system composed of two PZT patches was investigated in conjunction with both impedance and guided wave propagation methods to detect two kinds of damage in a railroad track (hole-damage 0.5cm in diameter at the web section and transverse cut damage 7.5cm in length and 0.5cm in depth at the head section). Two damage-sensitive features were separately extracted from each method: a) feature I: root mean square deviations (RMSD) of impedance signatures, and b) feature II: sum of square of wavelet coefficients for maximum energy mode of guided waves. By defining damage indices from these two damage-sensitive features, a two-dimensional damage feature (2-D DF) space was made. In order to enhance the damage identification capability of the current active sensing system, a two-step SVM classifier was applied to the 2-D DF space. As a result, optimal separable hyper-planes (OSH) were successfully established by the two-step SVM classifier: Damage detection was accomplished by the first step-SVM, and damage classification was carried out by the second step-SVM. Finally, the applicability of the proposed two-step SVM classifier has been verified by thirty test patterns prepared in advance from the intact state and two damage states.

In this paper, to prevent accidents of school vehicles used by students, which have emerged as a continuous social problem, a boarding and leaving notification system using Bluetooth beacons is proposed. The platform structure uses Bluetooth, a smartphone, and an application, and provides real-time message reception between parents and teachers. It is not simply a system with Bluetooth capability alone, but also an IcT technology that is closely related to real life using two-way communication. The purpose is to provide user-friendly ICT technology as an integrated system for more practical effects. Two-way exchange of information between parents and teachers using cloud servers is made possible. By using this Bluetooth beacon notification system, safety accidents in student vehicles are reduced, which brings confidence from traffic accidents to schoolchildren of parents and teachers. Therefore, it is expected that parents and teachers are expected to improve their mental stability and quality of life from traffic accidents.