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Artificially Smart and Trustworthy Cities
October 26, 2022 @ 6:00 pm - 7:00 pm CDT
For the past decade, ‘smart city’ projects have emphasized measurement, data analytics, and modeling—all of which are critical to new ways to optimize cities and more importantly, new applications to make cities “better” for their inhabitants.
In Chicago, what began in 2012 as an ambitious urban measurement initiative (The Array of Things, or “AoT”) almost immediately evolved to emphasize new types of measurements that typically require human observers. This drove an ambitious computing architecture embracing edge computing and AI to create a generative platform to support the design and development of “software-defined sensors.”
Why? Because scientists, policymakers, and residents alike were asking for data that cannot be easily measured with electronic sensors. For instance, going beyond counting vehicles to understanding their flows, the mix of vehicle types, or factors influencing safety. This requires not only cameras but also sophisticated AI to analyze images and video.
By supporting such platforms, we can begin to explore how software-defined sensors might provide measurements to improve our understanding of cities across a range of dimensions, from social sciences to traffic safety to environmental sciences. At the same time, introduction of these technologies also requires building and maintaining trust with residents. Catlett will discuss Argonne’s software-defined sensing platform along with lessons learned working with residents and organizations in the City of Chicago, in context of the expanded vision of the team’s current project, SAGE, also funded by the National Science Foundation.
This is a joint webinar between IEEE Computer Society Chicago and ACM Chicago.
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