Abstract

As demand for bicycles increases, bicycle-related accidents are on the rise. There are many items such as helmets and racing suits for bicycles, but many people do not wear helmets even if they are the most basic safety protection. To protect the rider from accidents, technology is needed to measure the rider’s motion condition in real time, determine whether an accident has occurred, and cope with the accident. This paper describes an artificial intelligence airbag. The artificial intelligence airbag is a system that measures real-time motion conditions of a bicycle rider using a six-axis sensor and judges accidents with artificial intelligence to prevent neck injuries. The MPU 6050 is used to understand changes in the rider’s movement in normal and accident conditions. The angle is determined by using the measured data and artificial intelligence to determine whether an accident happened or not by analyzing acceleration and angle. In this paper, similar methods of artificial intelligence (NN, PNN, CNN, PNN-CNN) to are compared to the orthogonal convolutional neural network (O-CNN) method in terms of the performance of judgment accuracy for accident situations. The artificial neural networks were applied to the airbag system and verified the reliability and judgment in advance.

Highlights

  • Personal means of transportation, such as kick scooters and Segways, have been gaining popularity

  • This paper describes an artificial intelligence airbag for bicycles

  • ImTTrpralaienimninienggtdindagatatAaacracerideneneeetdeSedidteudtaottiotornatriaanninadrCatirofitliclfeiiacctliiainnlgtienDltleaigtllaeignecne.ceT.raTirnaiinngindgatdaaotan ochnacrhaactrearcitsetricisotifcascoFcfoealrechrcaeytlpieoornathtaieontnidcaaanlndagcaucnildagerunlvaterslovimceilutoylcaidttiyeopdneesn,pdtehninedgsiniotgunaoatnioraindrsiedore’fsra’smfmrootoniottinaolnwiwmereperaecaatc,cacuumrmeuaurlalaitmeted-d ptthahrcroto,uuagghlhesfsetevivmeerrpaaallcaatc,cccaiidndedennatterexixgppheetrriiimmmepenantctststwtooettrrraeaiinansasarurttmiififecicdiai.allTinihnteetelslleilgingesenoncrceea. t.tached to the back of the mannequin measured the mannequin’s motion every 50 ms, and data were stored on t3h.e1.SIDmpclaermde.nWtinhgenAccocildleencttinSgitudaattiaon, tahneddCaotlalescatimngplDedataat 50 ms cycle were saved as a CSV

Read more

Summary

Introduction

Personal means of transportation, such as kick scooters and Segways, have been gaining popularity. To protect the rider from accidents, technology is needed to measure the rider’s motion condition in real time, determine whether an accident has occurred, and cope with the accident. The studies on human behavioral recognition technology mainly use acceleration and angular speed sensors, and vision techniques using images and sound are mainly used. In [14], motion is detected through an artificial neural network by measuring the movement of a human leg. In [15], a real-time safety monitoring vision system using four image sensors is presented, and behaviors are inferred by fusion with CNN and CSS-PI modules. The artificial intelligence airbag is a system that measures real-time motion conditions of a bicycle rider using a six-axis sensor and judges accidents with artificial intelligence to prevent neck injuries.

Safety Airbag System Design
Sensing Part Design
Drive Part Design
Data Collection and Analysis
Implementing Accident Situation and Collecting Data
Findings
ANN Comparison and Substantiation
Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.