Urban IoT deployments: traffic and congestion, parking, public-space occupancy, street-level environmental sensing and municipal testbeds.
Free CC0 synthetic dataset: 672 rows of UTCI thermal comfort, PM2.5 and NO2 air quality, occupancy and LAeq noise. Crowded Festival.
Large-scale distributed IoT IDS benchmark with traffic captured at individual device interfaces across 78 heterogeneous smart city IoT devices using the Gotham testbed. PCAP and CSV. Published January 2026 on Zenodo. Designed for federated learning and decentralised IDS research.
Open urban sensing dataset from 130 IoT nodes across Chicago measuring temperature, humidity, pressure, light, CO, NO₂, SO₂, ozone, sound, and pedestrian/vehicle traffic. CSV via Chicago Open Data Portal. Used for smart city analytics and urban environment research.
Integrated multi-modal data from smart urban sensor network including vehicle traffic, power consumption, and environmental monitoring.
AirIoT is an open-access dataset for IoT-based air pollution monitoring, featuring real-time sensor readings for PM2.5, PM10, temperature, and humidity from urban deployments.
pNEUMA is a large-scale dataset of naturalistic vehicle trajectories from half a million vehicles in Athens, Greece, collected via a swarm of drones for traffic congestion research.
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.
Multimodal smart city dataset combining IoT sensor data (environmental, traffic, infrastructure) with ground-truth anomaly labels for urban safety applications, anomaly detection, and multi-source data fusion research in smart cities.
Real-world parking occupancy and capacity data from NCP-operated car parks in Birmingham, UK, collected every 30 minutes from October to December 2016 for time-series occupancy prediction.
Collection of real-world smart city IoT datasets from the CityPulse project, including vehicle traffic, parking occupancy, and weather data from Aarhus (Denmark) and other cities.[web:111][web:114][web:116]
City-scale environmental IoT dataset with more than 24 million temperature measurements from SmartSantander sensors deployed across Santander, Spain, including spatial, temporal, and device metadata.[web:113][web:115][web:118]
Two years of continuous IoT-based smart parking lot usage data collected via ThingSpeak platform. Features IR sensors and ESP32 boards monitoring slot availability, occupancy patterns, peak hours, and parking duration for urban parking management optimization.
Large-scale real-time air quality monitoring dataset from Dhaka, Bangladesh with 155,406 records. Captures CO, NO2, SO2, O3, PM2.5, and PM10 using IoT sensors with Arduino integration. Ideal for environmental analytics, pollution prediction, and smart city air quality management.
Comprehensive IoT dataset from educational environments capturing student behavior, classroom utilization, environmental conditions, and attendance patterns. Designed for edge computing analytics, real-time monitoring, and data-driven educational planning.
Multimodal smart city dataset combining environmental sensors (temperature, humidity, gas, vibration, noise, motion) and surveillance images with binary anomaly labels. Designed for edge computing, urban anomaly detection, and real-time city monitoring research.
Comprehensive dataset capturing cybersecurity threats and sustainability metrics in smart city IoT and edge networks, including communication behavior, energy consumption patterns, and attack scenarios.
Simulated traffic data from 30 major cities worldwide (2015-2024). Includes patterns, congestion metrics, time-of-day effects, and weather correlations for traffic management systems.
High-resolution temperature data from dense IoT sensor networks in urban areas for monitoring and analyzing Urban Heat Island (UHI) effects. Integrates data from meteorological offices, environmental authorities, and citizen-generated sensors.
Simulated smart city environment capturing multimodal data from distributed urban sensors and surveillance sources. Includes synchronized environmental and visual data for edge computing and urban anomaly detection research.
Daily sensor measurements from an urban waste water treatment plant for operational efficiency analysis.
Fill-level data from smart trash bins equipped with ultrasonic sensors to optimize garbage truck collection routes.
Readings from solar power inverters paired with local weather station data to predict energy generation efficiency.
Comprehensive traffic accident data collected via police reporting systems and road sensors across the UK, ideal for predictive safety analysis.
Granular energy usage data from smart meters across kitchen, living room, and HVAC systems.