Non-contact detection technology for individual characteristics of motorcycle riding operation using electrostatic induction
Abstrak
In this study, the ultra-sensitive electrostatic induction current detection technology is used to detect the motion of getting on and off the motorcycle under non-contact conditions as an example of daily activities. The detected waveforms are wavelet-transformed to obtain scalograms. Comparing these obtained scalograms, it is shown that the scalogram patterns of the same subjects are almost reproducible and that the scalogram patterns are different among the subjects. Therefore, individual identification by deep learning is carried out using these scalograms. Consequently, it is shown that personal identification is possible with an accuracy of 92.7% using the movement of riding a motorcycle.
Topik & Kata Kunci
Penulis (1)
Koichi Kurita
Akses Cepat
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- 2021
- Sumber Database
- DOAJ
- DOI
- 10.1016/j.measen.2021.100118
- Akses
- Open Access ✓