Smart City EV Charging Network Spatiotemporal Telemetry Dataset

This dataset originates from a smart city electric vehicle (EV) charging infrastructure deployed in Helsinki, Finland, where a large-scale urban charging network supports municipal services, public transportation systems, and healthcare fleets, including those associated with Helsinki University Hospital. The collected data capture integrated cyber–physical interactions among charging stations (CS), connected EVs, and drone-assisted monitoring platforms operating across geographically distributed urban zones. The telemetry includes detailed network traffic statistics, protocol-level communication behaviors, infrastructure utilization metrics, and UAV-based spatiotemporal observations, enabling comprehensive characterization of both normal system operation and adversarial network conditions. The dataset spans from March 3, 2023, to April 3, 2025, with measurements recorded at 10-minute intervals, reflecting realistic monitoring resolutions used in operational smart transportation systems. Each observation corresponds to a CS–EV interaction enriched with temporal context and environmental sensing, allowing the modeling of dynamic communication patterns and infrastructure load variations. The data inherently exhibit real-world properties such as class imbalance, heavy-tailed feature distributions, and temporal variability caused by fluctuating charging demand and network dynamics. To ensure privacy and operational confidentiality, all records were anonymized and preprocessed prior to analysis while preserving chronological continuity and system-level dependencies. This real-world dataset provides a reliable foundation for evaluating spatiotemporal learning frameworks in detecting distributed DDoS attacks and capturing coordinated anomalies across smart city EV charging ecosystems.