<![CDATA[This study presents a Tinkercad-based virtual prototyping approach for monitoring suspension vibration in smart vehicle systems. The objective was to develop a low-cost yet systematic framework that integrates Arduino simulation, vibration indices analysis, and real-time visualization. The methodology included modeling road excitations (smooth, moderate, rough, bump) using signal generators, applying moving-average filtering, and computing vibration indices such as root mean square (RMS), peak-to-peak (P2P), crest factor (CF), and zero-crossing rate (ZCR). Circuit prototyping and coding were carried out entirely in Tinkercad, and vibration data were collected through the Arduino Serial Monitor for analysis. The results demonstrated that vibration indices varied consistently across road conditions. RMS values increased from 0.82 (smooth) to 1.52 (bump), while P2P rose from 1.50 to 2.80. Similarly, CF escalated from 1.20 to 1.78, reflecting higher peak loads, whereas ZCR remained stable at ~6.25 except for the bump mode where oscillations decreased. These findings validate that the Tinkercad platform can capture dynamic vibration trends aligned with theoretical expectations and literature benchmarks. The study contributes to advancing virtual prototyping as an accessible tool for vibration diagnostics in automotive suspensions. Future research could extend this framework toward hybrid monitoring systems that integrate energy harvesting and self-powered vibration sensing, enhancing applications in smart and green vehicles.]]>
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