Wearable Technology for Ride Safety Evaluation
Developing a set of wearables to record g-force exerted on a ride participant exposed to 8 degrees of freedom
Status:
Published
Categories:
Development, Data Analysis, Research
Technology:
Python, Jupyter Notebook
Links:
TEAM:
- Alex Ferworn Supervisor, Computer Science
- Kathryn Woodcock Supervisor, Human Factors & Themed Entertainment Specialist
- In association with N-CART Labs, Thrill Labs Ryerson University
Overview
Overview
- Designed and developed a wearable architecture catered for ride safety evaluation - analyzing g-force, acceleration, and impact of a ride participant.
- Conducted research on existing/similar solutions, sensor systems and industry standards on human-factors, safety and ergonomics (ASTM and TSSA).
- Iteratively developed low-fidelity mockups into wearable prototypes considering sensor displacement, enhancing comfort, and ensuring technical sustainability in high-impact environments.
- Collected 40 runs on a Zip Line, cleaned and reformatted the data set based on industry requirements to analyze the rider’s movement, g-force and speed. Created data visualization models to assess results with stakeholders.
- TSSA Graduate Research Scholarship Recipient 2018.
Publications
Solution
Results
Learnings
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