Smart buildings, as dynamic ecosystems, integrate cross-dependent sensors to enhance structural serviceability, optimize efficiency, and improve safety. This research employs a custom-designed sensor prototype to explore the feasibility of developing an automated system for evaluating building sensitivity to traffic-induced vibrations. The methodology involves collecting acceleration data from a full-scale structure subjected to traffic vibrations, processing it through an automated algorithm, and categorizing buildings qualitatively based on vibration levels and human perception, as defined by the Vibration Dose Value (VDV) method in the BS 6472-1 standard. Comparative analyses reveal the method’s sensitivity to signal duration and amplitude variations, highlighting its potential for integration into real-time smart monitoring systems.