Predictions of Undesirable behaviors while driving using Support Vector Machine

Conference proceedings article


ผู้เขียน/บรรณาธิการ


กลุ่มสาขาการวิจัยเชิงกลยุทธ์


รายละเอียดสำหรับงานพิมพ์

รายชื่อผู้แต่งNattawut Phramorathat, Piyasawat Navaratana Na Ayudhya, Tirasak Sapaklom, Ekkachai Mujjalinvimut and Jakkrit Kunthong

ปีที่เผยแพร่ (ค.ศ.)2023

URLhttps://ieeexplore.ieee.org/document/10296763/


ดูบนเว็บไซต์ของสำนักพิมพ์


บทคัดย่อ

Automobile vehicles today are not only used for transportation or solely for driving to the desired destination, but can also be used for leisure. Distraction driving often result in can results in driver distractions causing road accidents. According to research studies for detecting driver distractions, which discovered weaknesses in both the comfort and privacy of drivers. In this research, full and half bridge loadcells are installed on the seat and backrest, total of 9 points to detect weight changes when changing the posture of driver. The sensor signals are analyzed using Support Vector Machine (SVM), which is Machine Learning deployed to identify 13 different poses. Measurement data taken from 20 people were analyzed with Support Vector Machine, which revealed the highest prediction certainty of 99.89 percent


คำสำคัญ

ไม่พบข้อมูลที่เกี่ยวข้อง


อัพเดทล่าสุด 2023-22-12 ถึง 23:05