In this paper, an IoT-based indoor air quality monitoring platform, consisting of an air quality-sensing device called “Smart-Air” and a web server, is demonstrated. This platform relies on an IoT and a cloud computing technology to monitor indoor air quality in anywhere and anytime. Smart-Air has been developed based on the IoT technology to efficiently monitor the air quality and transmit the data to a web server via LTE in real time. The device is composed of a microcontroller, pollutant detection sensors, and LTE modem. In the research, the device was designed to measure a concentration of aerosol, VOC, CO, CO₂, and temperature-humidity to monitor the air quality. Then, the device was successfully tested for reliability by following the prescribed procedure from the Ministry of Environment, Korea. Also, cloud computing has been integrated into a web server for analyzing the data from the device to classify and visualize indoor air quality according to the standards from the Ministry. An application was developed to help in monitoring the air quality. Thus, approved personnel can monitor the air quality at any time and from anywhere, via either the web server or the application. The web server stores all data in the cloud to provide resources for further analysis of indoor air quality. In addition, the platform has been successfully implemented in Hanyang University of Korea to demonstrate its feasibility.

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.

This study deals with (a) the development of a prototype 3D printer for concrete structures having a bed size of 1 × 1 × 1 m for a laboratory testing and (b) laboratory testing of cementitious materials with different design mixes to find their suitability and efficacy for the developed 3D printer. In this printer, a program with the concept of computer numerical controlled milling was adopted to control the nozzle motion using an easy graphic user interface program. The experiment was carried out to test mechanical control and proper material properties of the printer. Thus, the optimum values of water-cement ratio of cementitious materials for the 3D concrete printer were determined by experimental trials. Also, the adequate viscosity of the material for layering and dispensing is determined by a slump-flow test. The suitable size of sands for the dispensing system was found through the trials. However, shrinkage cracks occurred during the hardening process for the paste and mortar that polyvinyl alcohol fibers are added to prevent the cracking and build an improved quality 3D printed structure. After suitable and efficient mix ratio is found, compressive strength is measured for the mechanical property. The experiments demonstrated possibility of printing concrete structure using the 3D printer.

The implementation of wireless sensor networks (WSNs) for monitoring the complex, dynamic, and harsh environment of underground coal mines (UCMs) is sought around the world to enhance safety. However, previously developed smart systems are limited to monitoring or, in a few cases, can report events. Therefore, this study introduces a reliable, efficient, and cost-effective internet of things (IoT) system for air quality monitoring with newly added features of assessment and pollutant prediction. This system is comprised of sensor modules, communication protocols, and a base station, running Azure Machine Learning (AML) Studio over it. Arduino-based sensor modules with eight different parameters were installed at separate locations of an operational UCM. Based on the sensed data, the proposed system assesses mine air quality in terms of the mine environment index (MEI). Principal component analysis (PCA) identified CH₄, CO, SO₂, and H₂S as the most influencing gases significantly affecting mine air quality. The results of PCA were fed into the ANN model in AML studio, which enabled the prediction of MEI. An optimum number of neurons were determined for both actual input and PCA-based input parameters. The results showed a better performance of the PCA-based ANN for MEI prediction, with R² and RMSE values of 0.6654 and 0.2104, respectively. Therefore, the proposed Arduino and AML-based system enhances mine environmental safety by quickly assessing and predicting mine air quality.

The nano scale of particles can result in dramatically improved or different properties from conventional grain-size materials of the same chemical composition. Therefore, it is practical to add nano-silica in particle form with 99.9% of SiO₂ in nano scale to improve the characteristics of cement mortar. The compressive strengths of cement mortar were evaluated at various water-cementitious ratio. Five different water-cementitious ratios were used including, 0.23, 0.25, 0.32, 0.35, and 0.48 and four contents of nano-SiO₂ particles, 3%, 6%, 9%, and 12% by weight of cement. The compressive strength of cement mortar with the addition of silica fume were also evaluated at w/cm ratio of 0.48 to compare with mortar containing nano-SiO₂ particles and three contents of silica fume were: 5%, 10% and 15% by weight of cement. The experimental results show that the compressive strengths of mortars with nano-SiO₂ particles were all higher than those of mortars containing silica fume at 7 and 28 days. It was demonstrated that the nano-particles were more valuable in enhancing strength than silica fume. This paper also analyzed some available examinations to monitor the hydration progress continuously, such as SEM observation, residual quantity test for Ca(OH)₂ and the rate of heat evolution. The results of the examinations indicate that the SiO₂ in nano scale behave not only as a filler to improve the microstructure, but also as an activator to promote pozzolanic reactions.

This study evaluates the mechanical performance of Reinforced Concrete Filled Fiber Reinforced Tube (RCFFT) through compressive and flexural tests for the purpose of applying RCFFT as strut members for a Prestressed Concrete (PSC) Box Girder bridge. Firstly, the compressive behavior of Concrete Filled Fiber Reinforced Plastic Tube (CFFT) and RCFFT members was investigated to examine their confinement effects. Secondly, based on the experimental results, an equation for estimating the ultimate compressive strengths of CFFT and RCFFT was proposed. In addition, the degree of improvement on the flexural performance due to the reinforcement by Fiber Reinforced Plastic (FRP) was analyzed from flexural tests on CFFT and RCFFT. It could be confirmed from the result of this research that the structural performance of RCFFT members were improved. Furthermore, the result of this study might be utilized in the design of the RCFFT strut members of a real PC BOX Girder bridge.