This two-volume book set contains over 400 papers reporting research on the hardware, software, and data outputs of structural health monitoring. While offering investigations into how sensors, networks, and signaling systems are used in dozens of civil and military applications, a special feature of this book is its exploration of how structural health is being enhanced by new ways of handling data, in real time and in batches. It demonstrates how machine-learning and stochastic methods add value to SHM data by taking into account changing environments and conditional events. It offers new insights on interactions between SHM data and big data for improving the safety and integrity of monitored structures. At the same time, information is presented on how SHM sensing interfaces with smart and functional materials operating in dynamic systems. A large number of SHM applications are explained, including additive manufacturing, advanced composites, actuators, bolts, corrosion, machinery, nuclear plants, phone towers, piping, robots, tainter gates, underground infrastructure, and many more. Chapters in the book are edited presentations from a September 2017 Workshop at Stanford University sponsored by the U.S. Air Force Office of Scientific Research, the Office of Naval Research, Boeing, Airbus/Testia, and Embraer.