A Study on a Wearable Smart Airbag Using Machine Learning Algorithm 


Vol. 35,  No. 2, pp. 94-99, Apr.  2020
10.14346/JKOSOS.2020.35.2.94


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  Abstract

Bikers can be subjected to injuries from unexpected accidents even if they wear basic helmets. A properly designed airbag can efficiently protect the critical areas of the human body. This study introduces a wearable smart airbag system using machine learning techniques to protect human neck and shoulders. When a bicycle accident happens, a microprocessor analyzes the biker’s motion data to recognize if it is a critical accident by comparing with accident classification models. These models are trained by a variety of possible accidents through machine learning techniques, like k-means and SVM methods. When the microprocessor decides it is a critical accident, it issues an actuation signal for the gas inflater to inflate the airbag. A protype of the wearable smart airbag with the machine learning techniques is developed and its performance is tested using a human dummy mounted on a moving cart.

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  Cite this article

[IEEE Style]

김현식, 백원철, 백운경, "A Study on a Wearable Smart Airbag Using Machine Learning Algorithm," Journal of the Korean Society of Safety, vol. 35, no. 2, pp. 94-99, 2020. DOI: 10.14346/JKOSOS.2020.35.2.94.

[ACM Style]

김현식, 백원철, and 백운경. 2020. A Study on a Wearable Smart Airbag Using Machine Learning Algorithm. Journal of the Korean Society of Safety, 35, 2, (2020), 94-99. DOI: 10.14346/JKOSOS.2020.35.2.94.

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