IoT-Integrated Predictive Maintenance Dataset

This dataset provides time-series sensor readings from multiple industrial machines operating on a production line. Designed to support predictive maintenance research, it captures operational parameters that indicate machine health and potential failure modes. Features include machine ID, timestamp, temperature readings (motor, bearing, ambient), vibration levels (X, Y, Z axes), pressure readings, current draw, RPM, acoustic emissions, and failure labels. The dataset includes both normal operating conditions and labeled failure events, enabling supervised learning for remaining useful life (RUL) estimation and failure prediction models.