Array of Things Chicago — Urban IoT Sensor Network [130 Nodes, Multi-Modal]
Catalog Summary
"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."
Catalog Notes
Overview
The Array of Things (AoT) is a large-scale urban IoT sensing project jointly developed by the Urban Center for Computation and Data of the Computation Institute — a joint initiative of Argonne National Laboratory and the University of Chicago — in collaboration with the City of Chicago. As of January 2020, approximately 130 sensor nodes were installed at street level across Chicago neighborhoods.
Each node is a modular, open-source sensor box collecting real-time, location-stamped measurements across a broad range of environmental, atmospheric, and urban activity indicators. The project is designed as a "fitness tracker" for the city, providing researchers, urban planners, and citizens with open data to analyze and improve urban livability, infrastructure, and sustainability.
All data collected is publicly available through the City of Chicago Open Data Portal in CSV format, organized by node location, sensor type, and timestamp. The sensor suite covers climate variables (temperature, barometric pressure, relative humidity), air quality (CO, NO₂, SO₂, ozone), electromagnetic spectrum, acoustic levels, and mobility indicators (pedestrian and vehicle traffic counts).
Column Schema
| Column | Description |
|---|---|
| timestamp | Date and time of the sensor reading (UTC). |
| node_id | Unique identifier for the Array of Things sensor node. |
| subsystem | Sensor subsystem name (e.g., metsense, chemsense, alphasense). |
| sensor | Specific sensor within the subsystem. |
| parameter | Measured parameter (e.g., temperature, co, pedestrians). |
| value_raw | Raw sensor reading value. |
| value_hrf | Human-readable formatted value with units applied. |
| lat / lon | GPS coordinates of the node installation location. |
Key Statistics
- Nodes Deployed: ~130 street-level IoT nodes (as of 2020)
- Sensor Modalities: 20+ environmental, air quality, acoustic, and mobility parameters
- File Format: CSV (via Chicago Open Data Portal API and bulk download)
- Data Access: Real-time and historical via Socrata Open Data API
- Coverage: City of Chicago neighborhoods and key intersections
- Time Period: 2018–2020 (primary deployment)
Use Cases
- Urban environment monitoring and smart city analytics
- Air quality and microclimate mapping across city neighborhoods
- Pedestrian and vehicle traffic pattern analysis at street level
- IoT sensor network deployment research and geospatial data fusion
Source & Attribution
The Array of Things project is led by Charlie Catlett at Argonne National Laboratory and the University of Chicago, funded in part by the National Science Foundation. Data is published openly by the City of Chicago and is permanently accessible through the Chicago Open Data Portal.
View Data Structure
To explore column names, data types, and sample rows, visit the official dataset page on Government.
Preview on GovernmentCite This Dataset
Catlett, C., & others (2018). Array of Things: A Scientific Research Instrument in the Public Way. [Dataset]. City of Chicago Open Data Portal / Argonne National Laboratory. https://data.cityofchicago.org/Environment-Sustainable-Development/Array-of-Things-Locations/6rq2-yx28
Source metadata: City of Chicago Open Data Portal / Argonne National Laboratory (2018)
Indexed by IoTDataset.com on Apr 17, 2026
Review the Source Record
Confirm the licence, version, access conditions, file format, and provenance at the source before use.