Protecting civil infrastructure from natural and man-made hazards is vital. Understanding the impact of these hazards helps allocate resources efficiently. Researchers have recently proposed static and dynamic computational models for community resilience analyses to evaluate a community's ability to recover after a disruptive event. Yet, these frameworks still need to adequately address community interdependencies and consider the impact of decision-making in modeling. This paper presents a state-of-the-art review of computational methods to model community resilience, focusing on the last ten years. It addresses critical terminology, community interdependencies, and current resilience guides within community resilience comprehension and discusses static and dynamic computational models, including probabilistic modeling in uncertain environments, rating models for community resilience assessment, 2 optimization-based modeling for resilient community design, game theory, agent-based, and probabilistic dynamical modeling. This paper presents key findings of promising research for future directions in the community resilience field.

Structural Health Monitoring (SHM) is essential to identifying problems that may cause human and material losses produced by disastrous and unexpected structural failures. The dynamic characterization of civil structures adopting SHM systems provides, at a particular moment, accurate information about the current structural response. When considering a proper SHM strategy and affordable economic investment for the maintenance required by structures, it is possible to safeguard the original structural parameters and avoid potential failures. However, traditional SHM systems are not desirable due to the large economic investments involved and demand for exhausting fieldwork. This research presents the design, implementation, and validation of a low-cost SHM system composed of a Wireless Sensor Network (WSN) and a base station in order to identify dynamic properties from the measured structural response. A set of small- and full-scale experimental tests were conducted to validate the WSN system using a wired traditional SHM system. Vibration data recorded through the low-cost SHM system were processed and compared to determine the natural frequencies, mode shapes, and damping properties of different structures by computing modal identification techniques, frequency analysis, and logarithmic decrement. The obtained dynamic characterization results from small- and full-scale experimental testing conclude that the low-cost SHM system can reliably identify the dynamic properties of the tested structures. This proposal provides an inexpensive, functional, and innovative alternative for SHM regarding traditional monitoring systems.