"Industrial Sensor Time-Series with Operational Event Labels for Digital Twin Research"

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Authors: Safayat Bin Hakim
Cited by: 0

Abstract

"This dataset provides multivariate industrial sensor time series for digital twin research, featuring temperature, vibration, pressure, operational hours, efficiency index, system state, and performance score. Each sequence includes labeled operational events such as threshold violations, maintenance patterns, state transitions, and interaction deviations. The data support anomaly detection, adaptive control, explainable reasoning, and reinforcement learning studies. It is suitable for benchmarking neuro-symbolic and human-interpretable digital twin methods in industrial environments worldwide."

Fields of Study & Subjects

Digital Transformation in Industry Fault Detection and Control Systems Time Series Analysis and Forecasting

Publication details

Journal / source
IEEE DataPort
Publication date
18 January 2026
Document type
Dataset