Edge-AI Sensor Dataset for Real-Time Fault Prediction in Smart Manufacturing

This dataset presents a multi-sensor, multi-modal dataset collected in a simulated smart manufacturing environment to support research in predictive maintenance and real-time fault detection using AI. It includes time-series data from vibration, temperature, humidity, and pressure sensors, annotated machine states (normal, warning, failure), and control logs from PLC systems. The dataset is ideal for edge-AI model training, digital twin simulations, and industrial AI benchmarking. Supplementary materials such as a data dictionary, README file, and system architecture diagram are included to facilitate adoption and reproducibility.