The need for a rapid assessment of the state of critical and conventional civil structures, such as bridges, control centers, airports, and hospitals, among many, has been amply demonstrated during recent natural disasters. Research is underway at Stanford University to develop a state-of-the-art automated damage monitoring system for long term and extreme event monitoring based on both ambient and forced response measurements. Such research requires a multi-disciplinary approach harnessing the talents and expertise of civil, electrical, and mechanical engineering to arrive at a novel hardware and software solution. Recent advances in silicon micro-machining and microprocessor design allow for the economical integration of sensing, processing, and communication components. Coupling these technological advances with parameter identification algorithms allows for the realization of extreme event damage monitoring systems for civil structures. This paper addresses the first steps toward the development of a near real-time damage diagnostic and monitoring system based on structural response to extreme events. Specifically, micro-electro-mechanical- structures (MEMS) and microcontroller embedded systems (MES) are demonstrated to be an effective platform for the measurement and analysis of civil structures. Experimental laboratory tests with small scale model specimens and a preliminary sensor module are used to evaluate hardware and obtain structural response data from input accelerograms. A multi-step analysis procedure employing ordinary least squares (OLS), extended Kalman filtering (EKF), and a substructuring approach is conducted to extract system characteristics of the model. Results from experimental tests and system identification (SI) procedures as well as fundamental system design issues are presented.