Publication Type:

Journal Article

Source:

Journal of Advanced Research in Dynamical and Control Systems, Institute of Advanced Scientific Research, Inc., Volume 10, Number 9 Special Issue, p.892-898 (2018)

URL:

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85050687373&partnerID=40&md5=d7b71dee22e3f1bfa39e362eeb22d78a

Abstract:

<p>The main objective of this paper is to study the feasibility of using moving QR (Quick Response) code as medium of communication between Infrastructures to Vehicle (I2V) communication. Highly automated vehicles in general connected with the internet to get the real time data to make appropriate decisions. At present, RF technology (WiFi / 4G / 5G / DSRC) is commonly used for the wireless connectivity for the highly automated vehicles. There is a potential chance exists that increase in RF networks will lead to a congested communication channel. It also might cause health hazards to humans especially for children, animals and birds in the near future. Fail operational is a mandatory requirement in highly automated vehicles. So in order to maintain the fail operational it is needed to have alternate or redundant connection other than RF connectivity. This paper proposes a low cost alternate method/technology to establish wireless communication between Infrastructures to Vehicle (I2V) Communication. In this proposed method visible light is used as a medium for transmission; Optical Sensor (camera) is used as a receiver. Moving QR is used for encoding the data. Data rate improvement is discussed by employing Deep Neural Network (DNN). © 2018, Institute of Advanced Scientific Research, Inc. All rights reserved.</p>

Notes:

cited By 0

Cite this Research Publication

V. U. Kumar and Dr. Senthil Kumar T., “Deep learning for I2V communication using moving QR code”, Journal of Advanced Research in Dynamical and Control Systems, vol. 10, pp. 892-898, 2018.