IoT Sensor Telemetry from a Simulated Smart Factory Over Six Months

5,003 rows of synthetic high-frequency telemetry from a simulated smart factory. The full dataset contains 50,006 rows across three tables, generated by mindweave to model three CNC lines, a finishing cell, and a predictive-maintenance program. Data was last updated on the platform in April 2026.

Use Cases

• Training predictive maintenance algorithms based on sensor readings and maintenance alerts.
• Simulating factory operations and shift patterns for digital twin development.
• Analyzing time-series patterns in temperature, humidity, pressure, and vibration from rolling 5-minute samples.
• Benchmarking anomaly detection models on synthetic industrial sensor data.

Strengths

• Contains 5,003 rows in the free sample, with a full version of 50,006 rows.
• Data spans a simulated six-month operational period with realistic shift patterns.
• Covers multiple sensor types (temperature, humidity, pressure, vibration) and machine states.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Data is synthetic, which may limit real-world applicability and require validation.
• Description metadata is limited; actual data quality requires manual inspection after download.

Provenance

Source

mindweave on Hugging Face.

Collection Method

Synthetically generated to simulate a smart factory environment.

Time Range

Covers a simulated six-month operational period.

Freshness

Last updated 2026-04-12 04:06:01; freshness should be verified.

Geography

Spatial coverage is not specified; likely a simulated factory.