Huawei Elevator Predictive Maintenance Dataset — IoT Door Sensors [453.9 kB]
Catalog Summary
"Anonymized elevator-door IoT sensor time series from Huawei Munich Research Center. ZIP format, 453.9 kB, sampled at 4 Hz for predictive maintenance of elevator doors."
Catalog Notes
Overview
This public anonymized predictive-maintenance dataset was released by Huawei Munich Research Center for elevator-door maintenance research.
The dataset contains time-series readings from IoT sensors around an elevator car door, including door ball-bearing, humidity, and vibration-related signals.
Measurements were sampled at 4 Hz during high-peak and evening elevator usage between 16:30 and 23:30.
Column Schema
| Column | Description |
|---|---|
| timestamp | Time index for the sampled time-series observation. |
| door_ball_bearing_sensor | Electromechanical signal associated with the elevator door ball-bearing system. |
| humidity | Ambient humidity measurement around the elevator door environment. |
| vibration | Physics/vibration measurement used to monitor door mechanical condition. |
| usage_window | Operational context for high-peak and evening elevator usage. |
Key Statistics
- Total Records: Time-series data sampled at 4 Hz; exact row count not stated on Zenodo
- Features: IoT door-bearing, humidity, and vibration sensor signals
- File Format: ZIP archive
- File Size: 453.9 kB
- Time Period: Usage window between 16:30 and 23:30; published 2020
Use Cases
- Elevator-door predictive maintenance
- Streaming anomaly detection from IoT sensors
- Condition monitoring of electromechanical door subsystems
Source & Attribution
Created by Cristian Axenie and Stefano Bortoli at Huawei Munich Research Center. Published on Zenodo with DOI 10.5281/zenodo.3653909.
View Data Structure
To explore column names, data types, and sample rows, visit the official dataset page on Zenodo.
Preview on ZenodoCite This Dataset
Axenie, C., & Bortoli, S. (2020). Predictive maintenance dataset. [Dataset]. Zenodo. https://doi.org/10.5281/zenodo.3653909
Source metadata: Zenodo (2020) · DOI: 10.5281/zenodo.3653909
Indexed by IoTDataset.com on Jun 06, 2026
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