Advancing integration strategies on application areas for seismic monitoring sensor systems in civil engineering buildings

The selection of sensor systems for structural health monitoring (SHM) often relies on empirical practices, lacking methods to optimize multi-sensor combinations for both technical and economic performance. This study proposes a novel Function–Structure–Economy (FSE) framework, developed using design science principles. The framework was validated through a case study of a three-story frame-shear wall structure, employing quantitative analysis of functional coverage and cost-effectiveness. Four sensor combinations were evaluated by quantifying coverage of key parameters (displacement, settlement, vibration, strain, cracks). For the economic dimension, the trimmed mean method was applied to sensor market data to exclude outliers and establish robust cost inputs. Results identify an optimal suite (MEMS accelerometers + FBG sensors + Tilt sensors), achieving 80% functional coverage at a 25% lower unit cost than alternatives. For controlled comparison, this study presents multiple case studies and employs case analysis to compare the proposed Function–Structure–Economy (FSE) framework with traditional empirical methods in the same real-world scenarios. As a new principle framework, it provides the missing link between sensor technology, structural engineering, and value-based investment, thereby advancing the intelligent and scalable deployment of seismic monitoring systems.