About

The Urban Intelligence Lab at Michigan Technological University is dedicated to shaping smarter, more responsive urban environments through innovative technology and data-driven insights.

Our team specializes in developing cutting-edge, AI-powered sensing and analytics systems to understand and optimize human interactions within public spaces.

By leveraging advanced computer vision, machine learning, and data visualization techniques, we create intelligent solutions that empower urban planners, communities, and campus administrators to enhance mobility, sustainability, and the livability of social infrastructure.

Through collaborative, multidisciplinary projects, our students and researchers are pioneering the future of smart, connected, and inclusive cities.

Projects

Campus Activity Tracking

This project uses computer vision to detect, track, and map how students move through campus and interact with its infrastructure. By generating data on traffic patterns, gathering spots, and asset usage, the system provides a clearer picture of campus dynamics. These insights directly support the Alternative Energy Enterprise in identifying optimal locations for renewable energy panels, ensuring smarter and more efficient deployment.

Vessel Tracking & Fisheries Monitoring

Working with the Great Lakes Research Center, the team is developing computer vision systems to track and classify vessels traveling through the Portage Canal. This work will expand to monitor fishing activity at remote locations like Stannard Rock, where collecting reliable data has historically been difficult. By producing high-quality usage data, the project strengthens fisheries research and supports collaborative management with tribal and state partners, ultimately benefiting recreational anglers and regional ecosystems alike.

Team

• 

  Gabriel Draughon, Ph.D.

  Advisor • Engineering Fundamentals • Assistant Professor

  Interests: Smart and Connected Cities, Self-efficacy in STEM undergraduates

  LinkedIn

• 

  Anna Tolles

  Student (President) • Data Science (Statistics Minor) • BS '27

  Interests: Data Analysis, Database Management and Design, Statistics Education, Human Factors

  LinkedIn

• 

  Alisa Teige

  Student • Data Science (Statistics Minor) • BS '27

  Interests: Machine Learning for Health and Urban Data, Data Analysis and Visualization, Applied Statistics

  LinkedIn

• 

  Isaac Spratke

  Student • Mechanical Engineering • BS '28

  Interests: Mathematics, AI Ethical Usage and Integration

  LinkedIn

• 

  Petra Gablowski

  Student (Vice President) • Dual Major Aerospace and Mechanical Engineering • BS '29

  Interests: CV model training and evaluation, Autonomous Flight: Propulsion systems and micro jet engines, CAD Modeling: Onshape, SolidWorks

  LinkedIn

• 

  Mary Dowhan

  Student • Computer Science • BS '26

  Interests: Data Analytics, Algorithms, Predictive Modeling

  LinkedIn

• 

  Ben Sabet

  Student • Computer Engineering • BS '28

  Interests: Prosthetics, Computational Biology, Machine learning

  LinkedIn

• 

  Blaze

  Good boy • CS (Chaos and Spunk) • Team Mascot

  Interests: Beach, Sticks, Biting

  LinkedIn

Contact

• Twitter
• Facebook
• Instagram
• GitHub

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