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Industrial IoT Dataset (Synthetic) for Predictive Maintenance

Industrial IoT
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Abstract

"The Industrial IoT Dataset (Synthetic) provides a large-scale simulation of sensor readings and operational metrics from machines deployed in a smart factory environment. It focuses on predictive maintenance and anomaly detection."

Description

Overview

A factory sensor simulator dataset created for predictive maintenance and machine learning tasks in Industry 5.0 contexts.

Technical Details

Contains records for 500,000 simulated machines, capturing time-dependent sensor data and equipment status variables.

Collection Setup

Data generation via a simulation pipeline emulating different operational modes and failure dynamics across a virtual fleet.

Recommended Research Tasks

Fault detection, remaining useful life (RUL) estimation, and condition-based maintenance policy design.

Access & License

Available on Kaggle for industrial analytics 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 

Canozensoy, C. (2025). Industrial IoT Dataset (Synthetic) for Predictive Maintenance. [Dataset]. Kaggle. https://www.kaggle.com/datasets/canozensoy/industrial-iot-dataset-synthetic

Source: Kaggle (2025)

Indexed by IoTDataset.com on Feb 05, 2026

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Related Topics & Keywords

#industrial IoT #predictive maintenance #anomaly detection #smart factory #Industry 5.0 #machine sensors #factory analytics

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