Safety Air Bag System for Motorcycle Using Parallel Neural Networks

• Published in: Journal of electrical engineering & technology Vol. 14; no. 5; pp. 2191 - 2203
• Main Authors: Jo, So-Hyeon, Woo, Joo, Jeong, Jae-Hoon, Byun, Gi-Sig
• Format: Journal Article
• Language: English
• Published: Singapore Springer Singapore 01.09.2019; 대한전기학회
• Subjects: Electrical Engineering; Electrical Machines and Networks; Electronics and Microelectronics; Engineering; Instrumentation; Original Article; Power Electronics; 전기공학; IMU; MPU; Machine learning; Motorcycle safety; Air bag; Neural network; Artificial intelligence
• ISSN: 1975-0102; 2093-7423
• DOI: 10.1007/s42835-019-00229-3

Due to the development of leisure sports industry and the increase in delivery demand, the demand for two-wheeled vehicles such as the motorcycle is increasing every year; moreover, the motorcycle accident rate is increasing. The motorcyclist’s body is exposed to the outside, and in cases of accidents, the head and the neck are particularly vulnerable. This paper proposes a study about an air bag equipped with Artificial Intelligence to protect the driver’s neck spine from motorcycle accidents. Through the six-axis sensor, it receives the driver’s motor condition data about the acceleration and angular velocity data and measures real time speed and angle; combines them with algorithms that can judge accidents through Artificial Intelligence learning to activate airbags in real time. Data were collected and learned by dividing the types of accidents; for Artificial Intelligence learning, the general Neural Network method was not used however, a mix of parallel Neural Network with an existing Neural Network were used instead. The Artificial Intelligence learning method proposed in this paper has been found to have more improved accuracy, stability and learning time compared to the existing Neural Network.