Jingang Yi
Rutgers University-New Brunswick, NJ·Engineering
Construction is one of the most dangerous industries in the U.S. Workers face heavy physical strain and serious injury risks.
- Fields
Engineering
Computer Science
Biomedical Engineering
- Topics
construction safety
wearable sensors
soft exoskeletons
- Grants
- 1 known grant, through Sep 2027
What they work on
- Develop machine learning methods for real-time recognition of construction workers' activities and estimation of their body posture, using wearable sensors.
- Design soft exoskeletons through a user-centered process, and integrate them with wearable safety sensing for assistive robot-worker collaboration that reduces musculoskeletal injury risk.
- Use mixed reality to support skill transfer and workplace learning, and evaluate the technology's social and economic impacts through pilot studies and industry deployment.
More about the research
The industry is also short of skilled labor: many workers are aging toward retirement, few young adults are entering the field, and women made up only 4% of the workforce in 2020. Robots are increasingly used on job sites, but research has focused mostly on productivity. Few studies have examined how wearable robotic devices could prevent muscle and joint injuries or make construction work safer and more accessible.
Why it matters
Wearable sensors and soft exoskeletons could help prevent work-related muscle and joint injuries among construction workers, one of the highest-risk groups in the U.S. workforce. By making physically demanding jobs safer and less strenuous, the technology may help keep older workers on the job longer and attract more women and young people. This could ease the industry's labor shortage and improve productivity.
Known grants
From NIH and NSF research grants. Labs often have other funding we can't see.
Closest labs
Carol Menassa
University of Michigan, MI·Engineering
Identify, through participatory design with an embedded cohort of wheelchair users, the factors that determine whether an end-to-end mobility system succeeds for people with physical disabilities.
Omobolanle Ogunseiju
Georgia Institute of Technology, GA·Education Research
Identify the competencies needed to advance sustainable construction with sensing technologies, using a Delphi expert-consensus study and focus groups with industry practitioners, and convert them into formal learning content.
Jee Woong Park
University of Nevada-Las Vegas, NV·Engineering
Develop computer vision AI algorithms that detect workplace hazards in photographs that trainees take on their own construction sites.
The school
Rutgers University-New Brunswick: 57 labs on PI Pages, $837M a year on research, 713 research doctorates a year.
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