9 3-D printing, which is an automated production process with layer-by-layer control, has been gaining rapid development in recent years. The technology has been adopted in the manufacturing industry for decades and has recently been introduced in the construction industry to print houses and villas. The technology can bring significant benefits to the construction industry in terms of increased customization, reduced construction time, reduced manpower and construction cost. A few isolated products and projects have been preliminarily tested using the 3-D printing technology. However, it should be noted that such tests and developments on the use of 3-D printing in the construction industry are very fragmented at the time of the study. It is therefore necessary for the building and construction industry to understand the technology, its historical applications and challenges for better utilization in the future. A systematic review shows that 3-D printing technology, after years of evolution, can be used to print large-scale architectural models and buildings. However, the potential of the technology is limited by the lack of large-scale implementation, the development of building information modelling, the requirements of mass customization and the life cycle cost of the printed projects. It is therefore expected that future studies should be conducted on these areas to consolidate the stability and expand the applicability of 3-D printing in the construction industry.
In the construction process, real-time quality control and early defects detection are still the most significant approach to reducing project schedule and cost overrun. Current approaches for quality control on construction sites are time-consuming and ineffective since they only provide data at specific locations and times to represent the work in place, which limit a quality manager's abilities to easily identify and manage defects. The purpose of this paper is to develop an integrated system of Building Information Modelling (BIM) and Light Detection and Ranging (LiDAR) to come up with real-time onsite quality information collecting and processing for construction quality control. Three major research activities were carried out systematically, namely, literature review and investigation, system development and system evaluation. The proposed BIM and LiDAR-based construction quality control system were discussed in five sections: LiDAR-based real-time tracking system, BIM-based real-time checking system, quality control system, point cloud coordinate transformation system, and data processing system. Then, the system prototype was developed for demonstrating the functions of flight path control and real-time construction quality deviation analysis. Finally, three case studies or pilot projects were selected to evaluate the developed system. The results show that the system is able to efficiently identify potential construction defects and support real-time quality control.
Because the existing approaches for diagnosing sensor networks lead to low precision and high complexity, a new fault detection mechanism based on support vector regression and neighbor coordination is proposed in this work. According to the redundant information about meteorological elements collected by a multisensor, a fault prediction model is built using a support vector regression algorithm, and it achieves residual sequences. Then, the node status is identified by mutual testing among reliable neighbor nodes. Simulations show that when the sensor fault probability in wireless sensor networks is 40%, the detection accuracy of the proposed algorithm is over 87%, and the false alarm ratio is below 7%. The detection accuracy is increased by up to 13%, in contrast to other algorithms. This algorithm not only reduces the communication to sensor nodes but also has a high detection accuracy and a low false alarm ratio. The proposed algorithm is suitable for fault detection in meteorological sensor networks with low node densities and high failure ratios.
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