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MDBR: Mobile Driving Behavior Recognition Using Smartphone Sensors

  • Dang-Nhac Lu
  • Thi-Thu-Trang Ngo
  • Hong-Quang Le
  • Thi-Thu-Hien Tran
  • Manh-Hai Nguyen
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10449)

Abstract

The driving behavior is interested approach in human life service provider, special using various smartphone sensors. We proposed an efficient framework for recognizing driving behavior using smartphone sensors. It names Mobile Driving Behavior Recognition Systems (MDBRS). The system implement while users put and change their smartphones dynamic due to their trips. The synchronous Practice Swarm Optimization (PSO) is used to auto select suitable features extracted from sensor data. The online user activity is predict by classification algorithms via only accelerometer signal. Hence, the system recognizes online behavior base on training data set by Artificial Neural Network (ANN). It auto predicts abnormal behavior from seven activity such as stop, moving, acceleration, deceleration, turn left, turn right and U-turn. MDBRS experiment on walking, bicycle, motorbike, bus and car and announce safety or unsafe behavior by abnormal behaviors predicted. The system also allowing update data training set by user confirmation from feedback module and achieve higher results with 86.71% accuracy.

Keywords

Activity recognition Online behavior recognition Detecting behavior PSO algorithm 

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Dang-Nhac Lu
    • 1
  • Thi-Thu-Trang Ngo
    • 2
  • Hong-Quang Le
    • 3
  • Thi-Thu-Hien Tran
    • 3
  • Manh-Hai Nguyen
    • 4
  1. 1.University of Engineering and Technology, Vietnam National University in HanoiHanoiVietnam
  2. 2.Posts and Telecommunications Institute of TechnologyHanoiVietnam
  3. 3.Academy of Journalism and CommunicationHanoiVietnam
  4. 4.HoChiMinh National Academy of PoliticsHanoiVietnam

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