The Internet-of-things (IoT) and blockchain are growing realities of modern society, and both are rapidly transforming civilization, either separately or in combination. However, the leverage of both technologies for structural health monitoring (SHM) to enable transparent information sharing among involved parties and autonomous decision making has not yet been achieved. Therefore, this study combines IoT with blockchain-based smart contracts for SHM of underground structures to define a novel, efficient, scalable, and secure distributed network for enhancing operational safety. In this blockchain-IoT network, the characteristics of locally centralized and globally decentralized distribution have been activated by dividing them into core and edge networks. This division enhances the efficiency and scalability of the system. The proposed system was effective in simulation for autonomous monitoring and control of structures. After proper design, the decentralized blockchain networks may effectively be deployed for transparent and efficient information sharing, smart contracts-based autonomous decision making, and data security in SHM.

The purpose of this study is to analyze the results of construction accidents occurred from 2011 to 2015 in Korea. The annual reports from the Ministry of Employment and Labor, Korea (MOEL), and the annual reports from the Statistics Korea were used for the analysis in this study. The gender, age, company size and accident types were chosen as a category to analyze the trend of various occupational accidents. In order to analyze the characteristics of construction accidents, incidence rates (IRs) and mortality rates (MRs) were calculated. Further, T-tests and ANOVA analysis were performed to discover the relationships among IRs, MRs, and chosen categories. Male workers’ IRs and MRs were significantly higher than those of female workers. Construction workers over 40 years of age suffered the most from occupational injuries. In terms of company size, as company size increases, both IRs and MRs tended to decrease. Occupational injuries caused by falls were higher than other accident types each year. This paper will be able to provide information on occupational accidents for establishing strategies to reduce the accident rate in construction sectors of Korea.

Construction is a hazardous industry in which accidents occur frequently. Occupational accidents at construction sites are a serious public health issue in Korea. Construction site conditions often create dangerous situations by requiring workers and heavy equipment to work in close proximity to each other. In 2015, approximately 11% (46) of the 437 occupational fatalities in the construction industry in Korea resulted from workers colliding with objects or equipment. In this paper, we present a proximity warning system developed to address this issue and enhance safety at construction sites. The proposed technology functions in real time to alert workers and equipment operators of hazardous proximity situations. Also, when the radio frequency identification (RFID) sensor detects an approaching worker, the main board instantly shuts down the excavator for the prevention of accident. This system contains an RFID tag, RFID reader, alarm device, camera, a display device (the Around View Monitor), and excavator control technology. A field test demonstrated successful performance of the proposed system. It is widely applicable in small construction fields alongside excavators and other equipment because this system does not require additional communication infrastructure, such as servers.

A proximity warning system to detect the presence of a worker/workers and to warn heavy equipment operators is highly needed to prevent collision accidents at construction sites. In this paper, we developed a robust construction safety system (RCSS), which can activate warning devices and automatically halt heavy equipment, simultaneously, to prevent possible collision accidents. The proximity detection of this proposed system mainly relies on ultra-wideband (UWB) sensing technologies, which enable instantaneous and simultaneous alarms on (a) a worker’s personal safety (personal protection unit (PPU)) device and (b) hazard area device (zone alert unit (ZAU)). This system also communicates with electronic control sensors (ECSs) installed on the heavy equipment to stop its maneuvering. Moreover, the RCSS has been interfaced with a global positioning system communication unit (GCU) to acquire real-time information of construction site resources and warning events. This enables effective management of construction site resources using an online user interface. The performance and effectiveness of the RCSS have been validated at laboratory scale as well as at real field (construction site and steel factory). Conclusively, the RCSS can significantly enhance construction site safety by pro-actively preventing collision of a worker/workers with heavy equipment.

Bridges are exposed to various kinds of external loads, including vehicle and hurricanes, during their life cycle. These loads cause structural damage, which may lead to bridge collapse. To ensure bridge safety, it is essential to periodically inspect the physical and functional conditions of bridges. The displacement responses of a bridge have significance in determining the structural behaviors and assessing their safety. In recent years, many researchers have been studying bridge displacement measurements using image processing technologies. Image-processing-based displacement measurements using a computer analysis system can quickly assess bridge conditions and, thus, can be used to enhance the reliability of bridges with high accuracy. This paper presents a method based on multiple-image processing bridge displacement measurements that includes enhanced robustness to image rotation. This study applies template matching and a homography matrix to measure the displacement that works well regardless of the angle between the smartphone camera and the target.