Synthetic Greenhouse IoT Telemetry at 10-Minute Resolution

10-minute resolution data from multiple sensors and irrigation systems. The dataset is synthetic and designed for time-series machine learning and IoT applications. Its source, author, and exact size are unknown.

Use Cases

• Forecasting greenhouse environmental conditions based on multi-sensor telemetry.
• Detecting anomalies in sensor readings or irrigation system behavior.
• Simulating and testing IoT data pipelines using synthetic time-series data.
• Training models for predictive maintenance of agricultural IoT equipment.

Strengths

• Data is provided at a consistent 10-minute temporal resolution.
• The description indicates it contains multi-sensor and irrigation system data.

Limitations

• Row count, file size, and column definitions are unknown, limiting suitability assessment.
• Description metadata is limited; actual data quality requires manual inspection after download.
• Last update date is unknown; freshness unverified.

Provenance

Source

Kaggle

Collection Method

Synthetic generation