Development and Validation of a Low-Cost Seismic Monitoring System for Urban Environments

Thesis Abstract

Urban areas are increasingly vulnerable to seismic hazards, yet traditional seismic monitoring systems remain prohibitively costly and technically complex, limiting widespread deployment and real-time hazard assessment in densely populated environments. This study aims to develop and validate an innovative low-cost seismic monitoring system tailored for urban settings, with the objective of enhancing early warning capabilities, promoting community resilience, and facilitating sustainable urban planning. The specific objectives include designing an affordable seismic sensor array, developing a robust data acquisition and transmission framework, and evaluating the system's performance against established seismic monitoring standards. The research adopts a mixed-methods approach, integrating engineering design principles with empirical validation techniques. A systematic review of existing seismic monitoring technologies informs the development of a customized hardware prototype using off-the-shelf microelectromechanical systems (MEMS) sensors, microcontrollers, and wireless communication modules. The population of the study encompasses urban seismic activities and sensor deployment locations within a major metropolitan city that experiences moderate seismicity. A sample of 50 sensor nodes is strategically distributed across various urban micro-environments, selected through stratified random sampling to ensure representation of diverse structural and geological conditions. Data collection involves continuous seismic recordings over a 12-month period, along with auxiliary data such as ambient noise levels, sensor calibration metrics, and environmental parameters. Data analysis employs a combination of signal processing techniques, including Fast Fourier Transform (FFT) for spectral analysis and wavelet transforms for noise filtering. The system’s detection accuracy, sensitivity, and timing precision are quantified through statistical measures such as receiver operating characteristic (ROC) curves, precision-recall analysis, and regression analysis to compare system outputs with data from established high-cost seismic stations. To validate the system, comparative assessments are conducted using ground-truth data collected from a nearby standard broadband seismometer installed by a national geophysical agency. The study also explores the application of the Theory of Technological Adoption and Resilience Theory to interpret factors influencing system acceptance and operational sustainability in urban environments. Expected findings anticipate that the low-cost seismic monitoring system will demonstrate a detection accuracy exceeding 85%, with a temporal resolution comparable to conventional systems within an error margin of ±0.2 seconds. The sensor array is projected to reliably identify seismic events with magnitudes as low as 3.0 within a 50 km radius, offering timely alerts for urban emergency preparedness. The study expects to identify key design parameters that optimize cost-effectiveness without compromising data quality, and to reveal operational constraints such as environmental noise interference and power management issues. This research significantly contributes to the body of knowledge by pioneering an affordable, scalable seismic monitoring technology suitable for widespread use in resource-constrained urban areas. It advances existing frameworks by integrating sensor miniaturization, wireless communication, and real-time data analytics to foster resilient urban infrastructure. Moreover, the study provides a comprehensive evaluation methodology that can be adapted to different geophysical and socio-economic contexts, thereby influencing policy and technology development in earthquake preparedness. The main conclusion underscores the feasibility of deploying low-cost seismic systems to enhance urban hazard monitoring and emergency response. Recommendations include further refinement of sensor durability, integration with urban infrastructure for enhanced resilience, and the development of a centralized data-sharing platform to maximize the system’s impact. Future research should explore the long-term operational stability of such systems, their integration with early warning networks, and user-centered design enhancements to facilitate community engagement.