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Zenodo

A Multi-Year Urban Streetlight Imagery Dataset for Visual Monitoring and Drift Detection

Smart City
Feb 07, 2026
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Abstract

"A longitudinal visual dataset of urban streetlight scenes captured daily over several years including 2025, accompanied by structured metadata for smart city monitoring, drift detection, and anomaly analysis. Includes over 526,000 images with timestamps and GPS metadata, enabling vision-based model training in urban environments."

Description

Overview

This large visual dataset supports urban monitoring, anomaly detection and spatio-temporal drift detection using imagery from streetlight cameras deployed across ® Bristol, UK.

Dataset Contents

  • Data modality: Images + CSV metadata
  • Scale: 526,000+ images
  • File formats: JPEG, CSV
  • Metadata: Timestamps, GPS

Collection Methodology
  • Environment: Urban deployment
  • Duration: Multi-year coverage
  • Devices/Sensors: Fixed cameras
  • Sampling rate: Hourly

Labels and Targets
  • Labeling: Not labeled (vision analytics)
  • Ground truth: Timestamped images

Recommended Use Cases
  • Vision model training
  • Anomaly and drift detection
  • Urban monitoring research

Limitations and Considerations
  • Large storage and compute requirements

Access and Licensing

This dataset is available at official repository page. Licensed under CC BY 4.0.

📊 View Data Structure

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

Preview on Zenodo

Cite This Dataset

Li, P., Mavromatis, I., Sahadevan, A., Farnham, T., & Aijaz, A. (2025). A Multi-Year Urban Streetlight Imagery Dataset for Visual Monitoring and Drift Detection. [Dataset]. Zenodo. https://doi.org/10.5281/zenodo.17781192

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Original source: Zenodo (2025). Visit official page for more details.

Indexed by IoTDataset.com on Feb 07, 2026

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