Real-Time Vibration Monitoring: Continuously analyzes 3- accelerometer data to detect deviations from normal operational patterns. Fast Training: Requires only a short sample of normal vibration data to establish a reliable detection baseline, enabling rapid deployment. Threshold-Based Anomaly Detection: Uses Euclidean distance metrics to compare live data against learned templates, ensuring precise abnormality recognition without complex AI models. Low-Power Embedded Hardware: Runs efficiently on XIAO S3, making it ideal for battery-powered or resource-constrained applications. Plug-and-Play Hardware Setup: Composed of XIAO and Grove ecosystem modules, easily attachable to machines, motors, or moving components for seamless vibration tracking. Edge Detection without Cloud Dependency: he inference runs locally-no internet or cloud service required (event output can be sent via the internet though). SenseCraft AI Integration: Visualize vibration data, configure system alerts, and quickly fine-tune thresholds with the friendly SenseCraft AI web UIs. Color: Black Material: PCB Package Contents: 1*Vibration Anomaly Detection Kit Only the above package content, other products are not included. Note: Light reflection and different displays may cause the color of the item in the picture a little different from the real thing. The measurement allowed error is +/- 1-3cm.