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NSFI-Corps

I-Corps: Translation Potential of Artificial Intelligence-Assisted, Data-Informed Urban Planning

Completed
Institution
University of North Carolina at Charlotte, NC
Principal investigator
Hamed Tabkhi
Funding
$50K
Duration
2025–2026
Open portfolio

Moonbase score

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Abstract

This I-Corps project focuses on the development of a privacy-preserving video analytics platform that transforms existing urban camera infrastructure into a tool for generating actionable insights on public space usage and mobility patterns. The technology analyzes anonymized visual data to measure foot traffic, dwell times, pedestrian flow, and interactions with urban infrastructure in real time. These insights support data-informed urban planning by revealing how people move through and engage with parks, sidewalks, transit hubs, and commercial corridors. Unlike traditional approaches that rely on manual observation or invasive surveillance methods, this solution prioritizes ethical design, converting raw footage into de-identified, abstract representations such as heatmaps. The platform enables municipal agencies, design firms, and economic development organizations to assess the effectiveness of public infrastructure investments and optimize the use of shared spaces. This I-Corps project utilizes experiential learning coupled with a first-hand investigation of the industry ecosystem to assess the translation potential of the technology. This solution is based on the development of an edge-based artificial intelligence system that captures behavioral and mobility trends while excluding facial, demographic, or personally identifiable information. Through direct engagement with urban planners, transportation agencies, business districts, and civil engineering stakeholders, the project investigates market demand, deployment feasibility, and stakeholder needs across multiple sectors. By quantifying the impact of infrastructure changes, such as sidewalk redesigns, street closures, or event staging, this platform provides a scalable and affordable approach to understanding the evolving dynamics of city life. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

Research team

  • Hamed TabkhiPI
  • Philip E OtienoburuCo-PI

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I-CorpsDirectorate for Technology, Innovation, and PartnershipsBig Data Science &Engineeringinfrastructuremobilityparkstranslation potentialurbanagenciesclosuresstreet

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