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IMAD-DS: Industrial Multi-Sensor Anomaly Detection Dataset

IoT Sensors
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Abstract

"IMAD-DS captures multi-rate, multi-sensor signals from scaled industrial machines, including a robotic arm and a brushless motor, for anomaly detection research."

Description

Overview

Designed to reflect domain shifts in real industrial environments, this dataset includes normal and abnormal operating conditions under varying settings.

Technical Details

Includes analog microphone data (16 kHz), 3-axis accelerometer (6.7 kHz), and 3-axis gyroscope readings.

Collection Setup

Collected using the STEVAL-STWINBX1 IoT Sensor Industrial Node on scaled industrial equipment.

Recommended Research Tasks

Vibration analysis, acoustic anomaly detection, and sensor fusion for industrial monitoring.

Access & License

Available on Zenodo for open research. Access Dataset

View Data Structure

To explore column names, data types, and sample rows, visit the official dataset page on Kaggle.

Preview on Kaggle

Cite This Dataset 

Augusti, F., Albertini, D., Esmer, K., Sannino, R., & Bernardini, A. (2024). IMAD-DS: Industrial Multi-Sensor Anomaly Detection Dataset. [Dataset]. {Zenodo. https://doi.org/10.5281/zenodo.12665499

Source: {Zenodo (2024) · DOI: 10.5281/zenodo.12665499

Indexed by IoTDataset.com on Feb 05, 2026

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Related Topics & Keywords

#IoT sensors #industrial IoT #anomaly detection #robotic arm #accelerometer #gyroscope #vibration analysis #acoustics

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