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:

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.