UTA’s New Wheelchair-Mounted Smart Tech Gathers Real-World Data to Guide Inclusive Building Design

Backed by a National Science Foundation grant, the project’s key innovation is WHEELCOM—a device that captures wheelchair movement data to help engineers design smarter, more inclusive buildings.

Traversing a university campus—or anywhere for that matter—can be a challenge for disabled people in a wheelchair. Now an assistant professor of civil engineering at the University of Texas at Arlington is seeking ways to make their lives easier.

June Young Park has received a grant from the National Science Foundation to lead a research project that could significantly improve how wheelchair users navigate and access buildings, UTA said.

“While the Americans with Disabilities Act has led to important progress, our buildings and public spaces are still largely designed with ambulatory individuals in mind,” Park said in a statement. “We want to explore how wheelchair users experience thermal stress, air quality, and physical exertion in ways that are often overlooked by current design standards.”

The project is part of the NSF’s Smart and Connected Communities program and brings together an interdisciplinary team of experts in psychology, kinesiology, social work, computer science, and disability studies, UTA said. The team’s goal is to better understand how wheelchair users perceive and interact with building environments—moving beyond standard accessibility guidelines and toward a more user-centered design, the university said.

According to the organization Disability Rights Texas, more than 3.5 million people in the state have a disability. Typically, UTA has more than 450 disabled students enrolled during each fall and spring semester with a diverse range of disabilities, including mobility impairments, visual impairments, learning disabilities, and more.

‘Making technology more accessible and less intrusive’

UTA said that an important innovation of the project is WHEELCOM, a new device that attaches to a wheelchair—not the user—and collects data on motion, kinetic energy, and other factors.

By applying machine learning, researchers said they aim to better understand how building design affects comfort and exertion for wheelchair users—insights that could directly inform smarter design decisions.

“Previous studies relied on placing multiple sensors on the individual, which can be fatiguing,” Park said. “By focusing on the wheelchair itself, we’re making the technology more accessible and less intrusive.”

UTA said the project is expected to begin local testing with the university community as early as fall 2025, and Park says the project’s long-term goal is to provide architects and engineers with better tools for designing in an era of smart technologies.

“This research is about expanding our vision on what a human-centered built environment can be,” Park said. “With the tools we now have—machine learning, sensing technology, and collaborative expertise—it’s time to rethink how we design buildings that truly serve everyone.”


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