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Good practice Imported

Array of Things — Chicago's Open-Source Urban Sensor Network

United States of America · Chicago · See the United States of America profile · See the Chicago profile

Evidence: Descriptive / self-reported Top 39% 71/100 · Ask Evidence Copilot about this practice

Argonne National Lab, the University of Chicago and Chicago built the open-source 'Array of Things' sensor network (2016-) for street-level environmental and traffic data. Peer-reviewed papers document the platform; policy-impact evidence is thinner than the engineering evidence.

115
Air-quality sensors deployed on bus shelters (Project Eclipse) (2021-22)
Array of Things — Chicago's Open-Source Urban Sensor Network

Details

Maturity
Scaling
Promoter
Argonne National Laboratory / University of Chicago (with City of Chicago, NSF funding)
Period
2016-present
Keywords
urban sensing, environmental monitoring, open-source hardware, smart-city data

Context

Argonne National Laboratory and the University of Chicago's Urban Center for Computation and Data, funded by the National Science Foundation, began deploying the Array of Things (AoT) sensor network across Chicago in 2016. Described in its own project materials as a 'fitness tracker for the city,' each node measures air quality, noise, heat, light and pedestrian/vehicle counts street by street.

Activities

The platform's design and early results were documented in a peer-reviewed ACM conference paper ('Array of Things: a scientific research instrument in the public way,' 2017) and in Argonne/Department of Energy technical reports. These sources describe extensive community engagement with Chicago neighbourhood organisations before installation, treated as essential rather than optional since community rejection could have stalled deployment entirely. The underlying open-source edge-computing platform, Waggle, was expanded in 2021-22 into 'Project Eclipse,' a joint deployment with the City of Chicago, Microsoft Research's Urban Innovation team and outdoor-advertising firm JCDecaux that placed air-quality sensors on 115 Chicago bus shelters.

Results

MIT Technology Review (2022) reports that the Waggle platform has since been adopted in research deployments beyond Chicago.

Conclusions

The evidence found is strongest on engineering performance and data quality, and weaker on downstream policy impact: none of the sources reviewed independently demonstrate that the sensor data measurably changed a city policy outcome, and no quantified equity results for specific underserved neighbourhoods were found.

Implementation
Indicative cost
Medium (€50k–€500k) — Funded by National Science Foundation research grants and Argonne National Laboratory; the 2021-22 Project Eclipse expansion was a joint deployment with the City of Chicago, Microsoft Research and JCDecaux placing sensors on 115 bus shelters.
Time to results
Long (> 3 years) — Deployment began 2016; the underlying Waggle platform was documented in a 2017 peer-reviewed paper and expanded into Project Eclipse in 2021-22.
Staffing & skills
Argonne National Laboratory research/engineering team, University of Chicago Urban Center for Computation and Data researchers, Chicago neighbourhood community liaisons

Conditions for success

  • NSF grant funding sustaining hardware R&D and deployment
  • Extensive community engagement with neighbourhood organisations treated as essential before installation, since rejection could have stalled deployment
  • Open-source edge-computing platform (Waggle) enabling reuse beyond the original network

Common failure modes

  • No independent study reviewed demonstrates the sensor data measurably changed a city policy outcome
  • No quantified equity results for specific underserved neighbourhoods were found
  • Funded through research grants (NSF, Argonne) rather than a dedicated city operating budget

Where it fits

Governance type
national-lab/university research partnership with city government
Scale
citywide sensor network, expanding to multi-site (Project Eclipse)
Income level
high-income

Commonly funded by

National / regional programmes

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Data sources

Where this practice's information was retrieved from, and when.

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