Structural health monitoring (SHM) is of great significance for post-earthquake damage assessment. Smartphone-based monitoring techniques provide the possibility to perform crowdsensing for all buildings in urban regions after an earthquake. However, this idea still faces many difficulties and is hard to realize. Fortunately, the development of game engines provides the opportunity for simulating this kind of experiment. The main objective of this study was to use Unity to simulate the whole process when a city is struck by an earthquake that consists of one main shock and one aftershock. During the emergency response, the citizens and the “city brain” in Unity, named Ground Eye, cooperate to finish the task of taking refuge and collecting data for regional damage assessment. Some basic assumptions were made first. Then the city model was established in Unity, and the behaviors of the citizens were directed by the behavior tree artificial intelligence (AI). OpenSees was utilized to determine the monitoring demand and simulate the monitoring results. A GUI was built to exhibit the data during the whole process. The results show that the evacuation and monitoring plan is feasible. The simulation framework presented in this paper can be used in other SHM application scenarios.

The life-cycle inspection of civil infrastructure can guide decisions on structural safety and reliability. This paper proposes a strategy for smartphone-based public participation in the life-cycle inspection of civil infrastructure (SPIC). The SPIC strategy consists of three parts: participants, Urban Brain, and Global View. Next, the feasibility of this strategy is verified by simulation experiments implemented in Unity3D. Civil infrastructure inspection modes include routine inspection, focus inspection, and emergency inspection. The activation and transition of the three inspection modes are tested. Test results show that routine inspection with public participation could timely identify pre-set damaged civil infrastructures. All abnormal civil infrastructures are observed by the Urban Brain. The focus inspection mode is activated when an abnormal civil infrastructure is detected, and the focus inspection provides a detailed and professional assessment of the abnormal civil infrastructure. Then, the inspection of all civil infrastructures in emergency inspection mode is completed in the test. Furthermore, this paper carries out a factor sensitivity analysis of this strategy. The proposed strategy establishes the mechanism for the assign-accept-feedback inspection task. In addition, the simulation performed in Unity3D is one of the next alternatives for large-scale urban disaster prevention and mitigation experiments in the real world. The SPIC strategy can effectively enhance the disaster prevention and mitigation capabilities of civil infrastructure.

Micro-image strain sensing (MISS) is an innovative technology to measure strain within a measurement range of ±8300 microstrains. It has been proved to be effective and satisfy all requirements in the field of structural health monitoring. However, there is still room for improvement and extend the range of measurement. In this paper, an improved method is proposed to increase the measurement range of strain and displacement. Moreover, various tests were conducted to verify the efficiency of the improved method. The results showed that the modified method is efficient and accurate and can be readily used to extend the measurement range of both strain and displacement. This research will likely help stimulate the development of multifunctional sensors to obtain abundant useful information about structures in the field of structural health monitoring. It will allow measuring strain and displacement, which require different levels of accuracy, using one unified sensor.